Annual epidemiological commentary: Gram-negative ......Annual epidemiological commentary....

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Annual epidemiological commentary: Gram-negative bacteraemia, MRSA bacteraemia, MSSA bacteraemia and C. difficile infections, up to and including financial year April 2018 to March 2019 11 July 2019

Annual epidemiological commentary. Gram-negative bacteraemia, MRSA bacteraemia, MSSA bacteraemia and C.

difficile infections up to and including financial year April 2018 to March 2019

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About Public Health England

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Prepared by: Dimple Chudasama, Simon Thelwall, Olisaeloka Nsonwu, Graeme Rooney,

Sobia Wasti, Russell Hope

For queries relating to this document, please contact: [email protected]

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Published July 2019

PHE publications

gateway number: GW-518

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Contents

About Public Health England ........................................................................................................... 2

Executive summary ......................................................................................................................... 6

Bacteraemia caused by Gram-negative organisms ......................................................................... 8

E. coli bacteraemia ...................................................................................................................... 8

Total reports ............................................................................................................................. 8

Age and sex distribution ........................................................................................................... 9

Seasonal trends in E. coli ....................................................................................................... 14

Source of E. coli bacteraemia ................................................................................................ 15

Geographic distribution of E. coli bacteraemia ....................................................................... 16

Klebsiella spp. bacteraemia ....................................................................................................... 19

Total reports ........................................................................................................................... 19

Distribution of Klebsiella species ............................................................................................ 19

Age and sex distribution ......................................................................................................... 20

Seasonal trends in Klebsiella spp. ......................................................................................... 21

Source of Klebsiella spp. bacteraemia ................................................................................... 22

Geographic distribution of Klebsiella spp. bacteraemia.......................................................... 23

Pseudomonas aeruginosa bacteraemia .................................................................................... 25

Total reports ........................................................................................................................... 25


Seasonal trends in P. aeruginosa .......................................................................................... 27

Source of P. aeruginosa bacteraemia .................................................................................... 28

Geographic distribution of P. aeruginosa bacteraemia .......................................................... 30

Discussion ................................................................................................................................. 31

Epidemiological analysis of Staphylococcus aureus bacteraemia ................................................. 34

Meticillin-resistant Staphylococcus aureus bacteraemia ........................................................... 34

Total reports ........................................................................................................................... 34

Trust-assigned reports ........................................................................................................... 36


Source of MRSA bacteraemia ................................................................................................ 41

Geographic distribution of MRSA bacteraemia ...................................................................... 42

Discussion .............................................................................................................................. 43



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Meticillin-susceptible Staphylococcus aureus bacteraemia ....................................................... 46

Total reports ........................................................................................................................... 46

Hospital-onset reports ............................................................................................................ 47


Source of MSSA bacteraemia ................................................................................................ 51

Geographic distribution of MSSA bacteraemia ...................................................................... 51

Discussion .............................................................................................................................. 53

Epidemiological analysis of Clostridioides difficile Infection .......................................................... 55

Hospital-onset reports ............................................................................................................ 56

Prior trust exposure ................................................................................................................ 56

Seasonal trends in CDI .......................................................................................................... 58


Trends in age and sex............................................................................................................ 60

Geographic distribution of CDI ............................................................................................... 62

Discussion .............................................................................................................................. 63

Appendix ....................................................................................................................................... 66

Background to the mandatory surveillance of MRSA and MSSA bacteraemia .......................... 66

Mandatory surveillance of C. difficile infection ........................................................................... 67

Mandatory surveillance of Gram-negative bacteraemia ............................................................ 67

E. coli bacteraemia................................................................................................................. 67

Klebsiella and P. aeruginosa bacteraemia ............................................................................. 67

A note on terminology ................................................................................................................ 68

Use of mandatory surveillance statistics .................................................................................... 68

Data included in the 2018/19 Annual Epidemiological Commentary (AEC) ............................... 68

E. coli bacteraemia................................................................................................................. 69

Klebsiella spp. bacteraemia ................................................................................................... 69

P. aeruginosa bacteraemia .................................................................................................... 69

MRSA bacteraemia ................................................................................................................ 70

MSSA bacteraemia ................................................................................................................ 70

C. difficile infections ............................................................................................................... 70

Commentary .......................................................................................................................... 70

Alternative presentations of the annual data .......................................................................... 71

Glossary ........................................................................................................................................ 72



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Methods ..................................................................................................................................... 74

Inclusion criteria for reporting to the surveillance system ....................................................... 74

Methods of reporting data on the HCAI Data Capture System (DCS) .................................... 75

Deadline for entering data ...................................................................................................... 75

CCG attribution process ......................................................................................................... 76

Overview of CCG attribution .................................................................................................. 76

Algorithms for apportioning cases .......................................................................................... 76

Assignment of MRSA cases through the Post Infection Review ............................................ 78

Analysis of data ......................................................................................................................... 80

Time to onset calculations ...................................................................................................... 80

Denominator data .................................................................................................................. 81

Rate calculations .................................................................................................................... 82

Healthcare associated infections in Wales, Scotland and Northern Ireland ............................... 83

References .................................................................................................................................... 85



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Executive summary

Overall rates of MRSA bacteraemia and C. difficile infection have continued to see year on

year reductions. These declines in MRSA bacteraemia and CDI rate, were in both the

community and hospital settings, testament to the success of the interventions introduced

to combat these infections. In contrast, the E. coli and MSSA rates have increased, with

the most prominent rises seen in the community-onset cases. MSSA showed a small

increase in hospital-onset cases but for E. coli this has been relatively static.

Therefore, over time the community-onset component has accounted for an increasing

proportion of cases, this is even true for the MRSA and CDI, as although rates have

reduced in both settings the reduction was steeper in the hospital setting. This highlights

the need to increase efforts to prevent cases in the community. Nevertheless, hospital-

onset infections remain important, representing thousands of cases a year.

While many of the infections were community-onset it is estimated that a large proportion

(up to 50% in the case of E. coli) have had recent healthcare interactions. Therefore, in

order to reduce infection rates further, control efforts in the hospital setting must be

maintained or strengthened, while increasing focus on interventions in the community and

the interface between hospital and community infection control teams improved.

The highest rates across all the pathogens was among those eighty-five and older

especially in males. However, there was a substantial number of cases (~80%) in the

younger age groups, and therefore prevention strategies should be focused across all

patient ages groups if we wish to minimise preventable infections and see a significant

reduction in cases.

Highlights

Rates of Escherichia coli bacteraemia have continued to rise, in 2018/19 the rate had

increased to 77.7 cases per 100,000 population (from 73.7 per 100,000 in the previous

year). The smallest annual increase in E. coli bacteraemia, since the mandatory

surveillance started in 2011, occurred between 2016/17 and 2017/18, of 2.5%. The

increase in the latest financial year (2018/19) was approximately 5%, similar to that

observed in previous years.



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After E. coli, Klebsiella and Pseudomonas spp. are the most common causative organisms

in Gram-negative bacteraemia but have substantially lower rates of bacteraemia than E.

coli. Rates of Klebsiella spp. increased, from 17.5 in 2017/18 to 19.1 in 2018/19. Rates of

Pseudomonas aeruginosa bacteraemia declined slightly, from 7.7 in 2017/18 to 7.5 in

2018/19. Urinary tract infection (UTI) remained the most important primary focus of E. coli,

Klebsiella spp. and Pseudomonas aeruginosa bacteraemia, causing 49.1%, 33.5% and

29.7% of cases respectively.

Rates of Meticillin-Sensitive Staphylococcus aureus (MSSA) bacteraemia continued to

increase moderately from 2011/12 when the surveillance was introduced. The rate

increased from 21.5 cases per 100,000 population in 2017/18 to 21.7 per 100,000

population in 2018/19.

In contrast those of MSSA, rates of Meticillin-Resistant Staphylococcus aureus (MRSA)

bacteraemia and Clostridioides difficile infection (CDI) have remained low in comparison to

rates at their peak, at 1.5 and 22.1 per 100,000 population, respectively in 2018/19.

The high rates of Gram-negative bacteraemia’s and diverse nature of the underlying

causes of these infections compared to MRSA and CDI present a significant challenge to

achieving the ambition to halve healthcare-associated Gram-negative bacteraemia by

2023/2024: HM Government 2018

This report constitutes a full and descriptive analysis of the data from the mandatory

surveillance of bacteraemia and CDI programmes in England. Detailed information on

each pathogen can be found in the individual sections of the report.



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Bacteraemia caused by Gram-negative

organisms

E. coli bacteraemia

Total reports

A total of 43,242 cases of E. coli bacteraemia were reported by NHS Trusts in England

between 1 April 2018 and 31 March 2019. Of the 43,242 E. coli cases, 7,632 (17.6%) were

hospital-onset (Table 1). The total number of cases reported in 2018/19 is an increase of

5.2% from 2017/18 (n = 41,091), and an increase of 33.8% from 2012/13 (n = 32,309).

Figure 1 shows the trends in the rates of E. coli cases from 2012/13 to 2018/19. The rate

of E. coli cases per 100,000 population has risen from 60.4 in 2012/13 to 77.7 in 2018/19.

Table 1: E. coli counts and rates by financial year, England: 2012/13 to 2018/19

Financial year

Mid-year population estimate*

All reported

cases

Rate (all reported cases

per 100,000 population)

Total bed days**

Hospital-onset cases

Rate (Hospital-onset cases per

100,000 bed days)

2012/13 53,475,358 32,309 60.4 34,439,455 7,552 21.9 2013/14 53,976,973 34,286 63.5 34,327,781 7,558 22.0 2014/15 54,432,437 35,816 65.8 34,797,208 7,380 21.2 2015/16 55,018,884 38,309 69.6 34,576,351 7,742 22.4 2016/17 55,240,933 40,647 73.6 34,976,071 7,878 22.5 2017/18 55,619,430 41,091 73.9 34,749,047 7,680 22.1 2018/19 55,619,430 43,242 77.7 34,525,599 7,632 22.1 * Mid-year population estimates for 2018/19 were not available at time of publication and so population data for 2017/18

were used as a proxy. ** Bed day data population data were not available for quarter 4 of FY 2018/19 (January to March 2019). As a result, the 2018/19 bed day data is an aggregate of quarter 1, 2 and 3 of 2018/19 and quarter 4 of 2017/18.



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Figure 1: Trends in the rate of E. coli bacteraemia in England, 2012/13 to 2018/19

* Mid-year population estimates for 2018/19 were not available at time of publication and so population data for 2017/18

were used as a proxy.

** Bed day data population data were not available for quarter 4 of FY 2018/19 (January to March 2019). As a result, the

2018/19 bed day data is an aggregate of quarter 1, 2 and 3 of 2018/19 and quarter 4 of 2017/18.

Age and sex distribution

For all age and sex analyses, cases in which the sex was missing or given as unknown

were excluded. In 2012/13, the sex was unknown for 815 cases (2.5%), while in 2018/19,

the sex was unknown for 24 cases (0.1%).

Figure 2 compares the age and sex structure of E. coli bacteraemia cases in England

between 2012/13 and 2018/19. For both years, E. coli bacteraemia rates were highest

among patients ≥ 85 years of age. In 2012/13, the rate among males was 718.2 cases per

100,000 population and 482.1 among females. In 2018/19, the rate among males was

922.8 per 100,000 population and 623.3 among females. , however it must be noted that

the population for ≥ 85 is much lower than the other age groups, particularly for males. It

should also be noted that the ≥ 85 years group accounts for 22.9% of all E. coli



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bacteraemia’s, whereas the rest is made up by the other age groups, with the 75-84 year

olds with the highest proportion of E. coli bacteraemias at 27.9% and the 1-14 age group

with the lowest of 0.5%.

Figure 2: Age and sex structure of E. coli rates per 100,000 population, England*



In general, the rates of E. coli bacteraemia are greater among males than among females,

and particularly so among older age groups. However, there is a notable exception to this.

In young adulthood (15-44) the rate of E. coli bacteraemia is considerably higher among

females (24.4 per 100,000 population) than among males (7.7 per 100,000 population),

giving a male-to-female rate ratio of 3 (95% CI: 2.9-3.4).



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Although the rates of E. coli bacteraemias have increased over time, the percentage gap

in rates between sexes within an age group have not changed appreciably (Table 2 & 3).

To compare disease incidence between two groups, one can calculate the ratio of rates

between the two groups to produce a rate ratio. The rate ratio for E. coli between male and

females in 2012/13 was 0.9 (95% CI: 0.9-1). In comparison, the rate ratio in 2018/19 was 1

(95% CI: 0.9-1).

Table 2: E. coli counts and rates by age group and sex, England: 2012/13

Age group (years) Population n cases Rate, per 100,000

Male Female Male Female Male Female

<1 353,705.1 336,393.0 306 195 86.5 58.0 1-14 4,503,696.0 4,294,577.8 81 136 1.8 3.2 15-44 10,724,195.2 10,658,627.9 712 2,087 6.6 19.6 45-64 6,669,558.9 6,835,423.2 2,944 2,878 44.1 42.1 65-74 2,347,921.0 2,530,753.9 3,520 2,889 149.9 114.2 75-84 1,320,659.4 1,677,572.3 4,577 4,311 346.6 257.0 ≥ 85 408,947.6 813,326.7 2,937 3,921 718.2 482.1

Table 3: E. coli counts and rates by age group and sex, England: 2018/19



<1 335,035 318,432 420 283 125.4 88.9 1-14 4,813,341 4,581,557 110 119 2.3 2.6 15-44 10,749,133 10,572,163 829 2,578 7.7 24.4 45-64 7,014,072 7,205,186 3,934 3,905 56.1 54.2 65-74 2,646,091 2,849,090 4,930 4,170 186.3 146.4 75-84 1,435,728 1,747,546 6,236 5,816 434.3 332.8 ≥ 85 487,653 864,403 4,500 5,388 922.8 623.3



Figure 3 shows the trends in rate of E. coli bacteraemia by age group and by sex. For both

sexes the rate of E. coli bacteraemia has increased most dramatically amongst the ≥ 85

age group. However, there have also been increases in rate in the <1 age group.



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Figure 3: Trend in age and sex structure of E. coli cases and rate per 100,000

population, England, 2012/13 to 2018/19

*2018/19 population data were not available at time of preparation and 2017/18 population data were used in place.

Percentage changes in the age & sex-specific rates of E. coli bacteraemia relative to the

first year of surveillance are shown in Figure 4. Except for females between the ages of 1-

14, rates of E. coli bacteraemia have increased since the start of surveillance.



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The proportionally largest increases in rate are observed in those less than 1 years old for

both males and females.

In contrast to the females, rates among males 1-14 years old have shown increases in rate

almost as great as the <1s.

Figure 4: Change in age- and sex-specific rates since 2011/12



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Seasonal trends in E. coli

Seasonality trend analysis, seen in Figure 5, show a clear seasonality for E. coli

bacteraemia, with the highest percentages reported in the July to September quarter (Q2).

This appears to be the same for both hospital-onset and community-onset cases, however

it is more consistent in community-onset cases. More variable is seen in hospital-onset

cases compared to community-onset, particularly from 2014/15 to 2018/119.

Figure 5: Trends in the seasonality of E. coli bacteraemia, 2011/12 to 2018/19



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Source of E. coli bacteraemia

The provision of data on the most likely primary focus of E. coli infection information is

voluntary. In 2012/13 a total of 27,610 (85.5%) of records had entries for the source of

bacteraemia. By 2018/19 a total of 27,747 (64.2%) had entries for the most likely primary

focus of the bacteraemia (Table 4).

Urinary tract infection (UTI) has consistently been the most frequent primary focus for E.

coli bacteraemia cases. In 2012/13, 48.9% of cases had a most likely primary focus of UTI,

by 2018/19 it was 49.1%. Conversely, the percentage of records for which the primary

focus was reported as unknown has decreased from 20.2% in 2012/13 to 14.3% in

2018/19.

Table 4: E. coli bacteraemia counts and rates by primary focus of bacteraemia,

England: 2018/19

Financial

year GI * n (%) HB** n (%) UTI n (%) Respiratory tract n (%)

Other*** n (%)

Unknown n (%) Total n (%)

2012/13 1,782 (6.5) 3,756 (13.6) 13,501 (48.9) 1,050 (3.8) 1,936 (7.0) 5,585 (20.2) 27,610 (100.0) 2013/14 1,711 (6.0) 3,855 (13.6) 13,393 (47.3) 1,016 (3.6) 1,873 (6.6) 6,452 (22.8) 28,300 (100.0) 2014/15 1,640 (5.7) 3,818 (13.3) 13,087 (45.6) 1,099 (3.8) 1,851 (6.4) 7,233 (25.2) 28,728 (100.0) 2015/16 1,491 (5.6) 3,556 (13.4) 12,219 (46.2) 1,068 (4.0) 1,703 (6.4) 6,408 (24.2) 26,445 (100.0) 2016/17 1,237 (5.4) 3,277 (14.4) 10,724 (47.2) 1,027 (4.5) 1,553 (6.8) 4,907 (21.6) 22,725 (100.0) 2017/18 1,718 (6.7) 4,034 (15.8) 12,564 (49.1) 1,575 (6.1) 1,756 (6.9) 3,963 (15.5) 25,610 (100.0) 2018/19 1,934 (7.0) 4,604 (16.6) 13,633 (49.1) 1,674 (6.0) 1,929 (7.0) 3,973 (14.3) 27,747 (100.0)

* Gastrointestinal not including hepatobilary

** Hepatobilary

****Other” includes the following options in the HCAI DCS; bone and joint, central nervous system, genital tract

(including prostate), indwelling intravascular device, other, respiratory tract, skin/soft tissue, no clinical signs of bacteraemia.

When the analysis of the most likely primary focus is restricted to cases where date of

admission was available, some differences in distribution are noted (Figure 6). The most

common primary focus is UTIs, accounting for just under half of all cases with an

admission date.

The primary focus of E. coli bacteraemia also varies according to time to onset. UTI were

the primary focus for over half (51.1%) of patients where the time to onset was < 2 days

from admission. In contrast, in cases where the time to onset was two to six days from

admission, only 33.2% of cases had a primary focus that was UTI.



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Figure 6: Distribution of primary focus E. coli bacteraemia, by time to onset,

England 2018/19

Geographic distribution of E. coli bacteraemia

Some geographical variation in rates of E. coli is noted (Figure 7). Areas with high rates

tended to be towards the North of England (NHS England North (Cumbria and North East)

Q74: 104.7 E. coli bacteraemia per 100,000 population, NHS England North (Cheshire and

Merseyside) Q75: 91.4 and NHS England Midlands and East (North Midlands) Q76: 89.9).

In contrast, lower rates were observed in the south of England, with the lowest rate in

2018/19 occurring in NHS England London (Q71) with a rate of 64.6 bacteraemia per

100,000 population.



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Figure 7: Geographic distribution of E. coli rates per 100,000 population, England

2018/19*



Table 5 gives NHS local office-specific rates. All local offices have experienced increases

in E. coli incidence over time. The largest increase in incidence was observed in NHS

England South West (South West South) Q85, which saw the incidence rise from 57.2 per

100,000 population in 2012/13 to 88.9 in 2018/19. However, between 2017/18 and

2018/19, drops in rate were observed for two local offices: Q88 NHS England South East

(Kent, Surrey and Sussex) from 77.2 to 75.1 and Q87 NHS England South East

(Hampshire, Isle of Wight and Thames Valley) from 71.1 to 70.2 bacteraemia per 100,000

population.



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Table 5: E. coli rates by NHS local office, England per 100,000 population: 2012/13 to

2018/19*

Code NHS local office

20

12

/13

20

13

/14

20

14

/15

20

15

/16

20

16

/17

20

17

/18

20

18

/19

Q78 NHS England Midlands and East (Central Midlands) 56.0 58.8 61.6 64.7 65.3 66.0 67.5 Q79 NHS England Midlands and East (East) 52.1 55.5 57.6 62.5 68.4 69.1 72.3 Q76 NHS England Midlands and East (North Midlands) 72.5 79.3 82.6 83.1 86.4 81.5 89.9 Q77 NHS England Midlands and East (West Midlands) 60.7 62.5 66.3 67.3 68.6 67.6 74.9 Q75 NHS England North (Cheshire and Merseyside) 71.9 86.2 76.7 81.4 89.1 91.4 91.4 Q72 NHS England North (Yorkshire and Humber) 71.5 73.6 76.1 80.1 84.9 82.4 89.0 Q83 NHS England North (Greater Manchester) 66.0 66.5 63.4 68.7 72.6 70.3 79.0 Q74 NHS England North (Cumbria and North East) 77.0 74.0 82.9 88.1 92.5 96.6 104.7 Q84 NHS England North (Lancashire and South Cumbria) 67.2 70.4 74.9 78.4 82.5 85.5 87.3 Q87 NHS England South East (Hampshire, Isle of Wight and

Thames Valley) 48.8 51.8 56.6 60.0 65.8 71.1 70.2

Q88 NHS England South East (Kent, Surrey and Sussex) 57.7 62.0 62.3 68.2 75.9 77.2 75.1 Q86 NHS England South West (South West North) 50.6 52.4 57.5 59.1 58.4 57.0 65.1 Q85 NHS England South West (South West South) 57.2 60.2 66.6 72.6 79.6 81.1 88.9 Q71 NHS England London 53.2 55.7 56.6 60.9 63.0 62.6 64.6 National 60.4 63.5 65.8 69.6 73.6 73.8 77.7

* 2018/19 population data were not available at time of preparation and 2017/18 population data were used in place.



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Klebsiella spp. bacteraemia

Total reports

A total of 10,638 cases of Klebsiella spp. bacteraemia were reported by NHS Trusts in

England between 1 April 2018 and 31 March 2019. Of the 10,638 Klebsiella spp. cases,

3,182 (29.9%) were hospital-onset (Table 6).

Table 6: Klebsiella spp. bacteraemia counts and rates by financial year, England:

2018/19

Financial year

Mid-year population estimate

All reported

cases



Total bed days**



100,000 bed days)

2017/18 55,619,430 9,744 17.5 34,749,047 2,902 8.4 2018/19 55,619,430 10,638 19.1 34,525,599 3,182 9.2

* Mid-year population estimates for 2018/19 were not available at time of publication and so population data for 2017/18were

used as a proxy. * Bed day data population data were not available for quarter 4 of FY 2018/19 (January to March 2019). As a result, the 2018/19 bed day data is an aggregate of quarter 1, 2 and 3 of 2018/19 and quarter 4 of 2017/18.

Distribution of Klebsiella species

Klebsiella pneumoniae was the most frequently reported Klebsiella species. Species

distribution was similar between hospital-onset cases and community-onset cases (Table 7).

Table 7: Counts and percentages of Klebisella species, England 2018/19

Species All cases Hospital-onset

cases Community-onset

cases

K. pneumoniae 7,850 (73.8%) 2,279 (71.6%) 5,571 (74.7%) K. oxytoca 1,743 (16.4%) 532 (16.7%) 1,211 (16.2%) K. aerogenes 131 (1.2%) 64 (2.0%) 67 (0.9%) Other named species 396 (3.7%) 142 (4.5%) 254 (3.4%) Not speciated 518 (4.9%) 165 (5.2%) 353 (4.7%)



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Rates of Klebseilla spp. bacteraemia were higher among males than among females. This

was particularly true among age groups greater than 65 years old (Figure 8). A further

breakdown of age distribution can be seen in Table 8. The rate ratio between males and

females in the ≥ 85 age group was 3.1 (95% CI: 2.8-3.3).

Figure 8: Age and sex structure of Klebsiella spp. rates per 100,000 population,

England




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Table 8: Klebsiella spp. counts and rates by age group and sex, England: 2018/19



<1 335,035 318,432 109 84 32.5 26.4 1-14 4,813,341 4,581,557 92 48 1.9 1.0 15-44 10,749,133 10,572,163 372 425 3.5 4.0 45-64 7,014,072 7,205,186 1,391 950 19.8 13.2 65-74 2,646,091 2,849,090 1,624 920 61.4 32.3 75-84 1,435,728 1,747,546 1,798 894 125.2 51.2 ≥ 85 487,653 864,403 1,219 708 250.0 81.9

Seasonal trends in Klebsiella spp.

Seasonality analysis of Klebsiella spp. bacteraemia (Figure 9), show a higher percentage

of cases in the quarter July to September (Q2), similar to that seen in E. coli bacteremia. In

contrast to E. coli bacteraemia, where there is little difference the proportional seasonal

shifts in hospital-onset cases, for the Klebseilla spp. infections the effect was more

pronounced.

Figure 9: Trends in the seasonality of Klebsiella spp. bacteraemia, 2017/18 to

2018/19



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Source of Klebsiella spp. bacteraemia

The most frequent primary focus of Klebsiella spp. bacteraemia was UTI, constituting

33.5% of cases with a reported primary focus of infection. The primary focus of infection

was not reported in 46.8% of cases (Table 9).

Table 9: Klebsiella spp. bacteraemia counts and rates by primary focus of

bacteraemia, England: 2018/19

Financial

year UTI GI* HB** Respiratory

tract Others Unknown Total

n % n % n % n % n % n %

2017/18 1677 32.9 374 7.3 1031 20.2 469 9.2 601 11.8 944 18.5 5096 2018/19 1893 33.5 483 8.5 1083 19.1 559 9.9 747 13.2 891 15.8 5656

* Gastrointestinal not including hepatobilary ** Hepatobilary ****Other” includes the following options HCAI DCS; bone and joint, central nervous system, genital tract (including prostate), indwelling intravascular device, other, respiratory tract, skin/soft tissue, no clinical signs of bacteraemia.

Amongst patients with an admission date and a time to onset of less than 2 days, UTI

forms a major primary focus of bacteraemia (37.8%). However, in case with an onset ≥ 7

days after admission, this declined to 20.1%



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Figure 10: Distribution of primary focus of Klebsiella spp. bacteraemia, by time to

onset, England 2018/19

Geographic distribution of Klebsiella spp. bacteraemia

Generally, rates of Klebsiella spp. bacteraemia were higher in the North of England than in

the South. (Figure 11). However, with the exceptions of: Q83 NHS England North (Greater

Manchester) had a rate of 18.7 cases per 100,000 population and Q84 NHS England

North (Lancashire and South Cumbria) had a rate of 19.5, both showing slightly lower

rates. Also, two southerly offices showing higher rates, Q85 NHS England South West

(South West South) and Q88 NHS England South East (Kent, Surrey and Sussex) with a

rate of 21.3 and 20.2, respectively (Table 10).



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Figure 11: Geographic distribution of Klebsiella spp. Rates per 100,000 population,

England 2018/19*

* Figure 9: Geographic distribution of Klebsiella spp. rates per 100,000 population, England 2018/19

Table 10: Klebsiella spp. rates by NHS local office, England: 2018/19

Code NHS local office 2017/18 2018/19

Q76 NHS England Midlands and East (North Midlands) 19.6 21.0 Q77 NHS England Midlands and East (West Midlands) 14.9 16.5 Q78 NHS England Midlands and East (Central Midlands) 16.1 17.7 Q79 NHS England Midlands and East (East) 16.4 17.7 Q72 NHS England North (Yorkshire and Humber) 17.8 20.5 Q74 NHS England North (Cumbria and North East) 24.3 25.6 Q75 NHS England North (Cheshire and Merseyside) 20.1 21.9 Q83 NHS England North (Greater Manchester) 16.8 18.7 Q84 NHS England North (Lancashire and South Cumbria) 18.6 19.5 Q87 NHS England South East (Hampshire, Isle of Wight and Thames Valley) 15.6 16.8 Q88 NHS England South East (Kent, Surrey and Sussex) 19.4 20.2 Q85 NHS England South West (South West South) 18.0 21.3 Q86 NHS England South West (South West North) 15.1 16.4 Q71 NHS England London 16.6 17.9 National 17.5 19.1




25

Pseudomonas aeruginosa bacteraemia

Total reports

A total of 4,185 cases of P. aeruginosa bacteraemia were reported by NHS Trusts in

England between 1 April 2018 and 31 March 2019. Of the 4,185 P. aeruginosa cases,

1,517 (36.2%) were hospital-onset (Table 11).

Table 11: P. aeruginosa bacteraemia counts and rates by financial year, England:

2018/19

Financial

year Mid-year

population estimate*

All reported cases



Total bed days**



100,000 bed days)

2017/18 55,619,430 4,299 7.7 34,749,047 1,624 4.7 2018/19 55,619,430 4,185 7.5 34,525,599 1,517 4.4

* Mid-year population estimates for 2018/19 were not available at time of publication and so population data for 2017/18 were used as a proxy. ** Bed day data population data were not available for quarter 4 of FY 2018/19 (January to March 2019). As a result, the 2018/19 bed day data is an aggregate of quarter 1, 2 and 3 of 2018/19 and quarter 4 of 2017/18.


The age and sex distribution of P. aeruginosa bacteraemia were higher among older

people and particularly among older men Figure 12.



26

Figure 12: Age and sex structure of P. aeruginosa rates per 100,000 population,

England 2018/19*


The rate ratio between men and women in the ≥ 85 age group was 3.4 (95% CI: 2.9-3.9). A further breakdown of age distribution can be seen in Table 12



27

Table 12: P. aeruginosa counts and rates by age group and sex, England: 2018/19

Age group (years) Population* n cases Rate, per 100,000 Male Female Male Female Male Female

<1 335,035 318,432 34 25 10.1 7.9 1-14 4,813,341 4,581,557 65 55 1.4 1.2 15-44 10,749,133 10,572,163 183 153 1.7 1.4 45-64 7,014,072 7,205,186 525 370 7.5 5.1 65-74 2,646,091 2,849,090 631 354 23.8 12.4 75-84 1,435,728 1,747,546 724 327 50.4 18.7 ≥ 85 487,653 864,403 483 254 99.0 29.4

*2018/19 population data were not available at time of preparation and 2017/18 population data were used in place

Seasonal trends in P. aeruginosa

Seasonality analysis of P. aeruginosa bacteraemia (Figure 13), show a higher percentage

of cases in the quarter July to September (Q2) for community-onset cases in 2017/18,

whereas although an increase is seen around the same time in hospital-onset cases, a

peak is seen in the October - December 2017 (Q3) month. However, there is a shift in the

2018/19, where both peaks for hospital-onset and community-onset are seen in Q2,

similarly to the trend seen in E. coli and Klebsiella spp. bacteraemia.



28

Figure 13: Trends in the seasonality of P. aeruginosa bacteraemia, 2017/18 to

2018/19

Source of P. aeruginosa bacteraemia

The most frequent primary focus of bacteraemia for P. aeruginosa was UTI, constituting

29.7% of cases with a reported primary focus of infection (Table 13). However, the primary

focus was not reported for half (49.6%) of the cases.

Table 13: P. aeruginosa counts and rates by primary focus of bacteraemia, England:

2018/19

Financial year

GI* HB** UTI Respiratory tract

Others Unknown Total

n % n % n % n % n % n %

2017/18 125 6 102 5 637 30 300 14 491 23 471 22 2,126 2018/19 152 7 100 5 626 30 275 13 545 26 413 20 2,111

Among patients with an available admission date, those with a time to onset of less than 2

days, UTI was the most commonly reported primary focus of P. aeruginosa bacteraemia

(34.0%). However, for patients where the time to onset was ≥ 7 days from admission, the

percentage of infections with a UTI primary focus declined to 22.6% (Figure 14).



29

Figure 14: Distribution of primary focus of P. aeruginosa bacteraemia by time to

onset, England 2018/19



30

Geographic distribution of P. aeruginosa bacteraemia

Figure 15: Geographic distribution of P. aeruginosa rates per 100,000 population,

England 2018/19*


Figure 15 and Table 14 gives NHS local office-specific rates. Broadly speaking there is no

north-south divide in the rates of P. aeruginosa, unlike that observed for the other Gram-

negative bacteraemias. The highest rate was observed in Q88 NHS England South East

(Kent, Surrey and Sussex) (9.7 cases per 100,000 population) and Q76 NHS England

Midlands and East (North Midlands) (8.3 cases per 100,000 population) (Table 14).



31

Table 14: P. aeruginosa bacteraemia rates by NHS local office, England: 2018/19*

Code NHS local office 2017/18 2018/19

Q76 NHS England Midlands and East (North Midlands) 8.9 8.3 Q77 NHS England Midlands and East (West Midlands) 7.0 7.6 Q78 NHS England Midlands and East (Central Midlands) 7.1 7.6 Q79 NHS England Midlands and East (East) 7.4 7.6 Q72 NHS England North (Yorkshire and Humber) 7.4 7.1 Q74 NHS England North (Cumbria and North East) 8.0 8.0 Q75 NHS England North (Cheshire and Merseyside) 8.4 7.2 Q83 NHS England North (Greater Manchester) 5.8 4.8 Q84 NHS England North (Lancashire and South Cumbria) 6.7 6.3 Q87 NHS England South East (Hampshire, Isle of Wight and Thames Valley) 8.2 7.5 Q88 NHS England South East (Kent, Surrey and Sussex) 9.0 9.7 Q85 NHS England South West (South West South) 7.0 5.7 Q86 NHS England South West (South West North) 7.8 6.2 Q71 NHS England London 8.1 8.2 National 7.7 7.5


Discussion

This report provides the first two years of data for the expanded Gram-negative

surveillance and is the second annual commentary in which onset status has been

reported for E. coli bacteraemia. Data on bacteraemia caused by E. coli, Klebsiella spp.

and P. aeruginosa showed both similarities and differences in the epidemiology of these

infections.

E. coli bacteraemia had the highest rate of all the bacteraemias caused by Gram-negative

organisms, causing 77.7 cases per 100,000 population in 2018/19. Klebsiella spp. and P.

aeruginosa bacteraemias had much lower rates of infection (19.1 and 7.5 respectively).

Differences were also observed in the proportion of cases that were hospital-onset (E. coli

- 18%, Klebsiella spp. - 30% and P. aeruginosa - 36%).

While the UTIs remains a major source of bacteraemia for all Gram-negative infections (E.

coli - 49%, Klebsiella spp. - 33% and P. aeruginosa – 30%), the respiratory tract is the

focus for 13% of P. aeruginosa infections but only 6% in E. coli and 10% in Klebsiella spp.

infections.

The collection of information on primary focus of bacteraemia changed in April 2018/19

with the introduction of mandatory surveillance of Klebsiella spp. and P. aeruginosa. For

this reason, the data on primary focus of infection for E. coli bacteraemia presented in this



32

report may not match those in previous reports. Despite the differences in epidemiology

noted above, there are similarities in the age and sex distribution of all three bacteraemias.

Rates of infection are higher among older age groups (65-74, 75-84 and ≥ 85) and those

under one year old for all Gram-negative bacteraemias. Despite this similarity, the rate of

bacteraemia caused by either Klebsiella spp. or P. aeruginosa is much greater among

men than among women. This contrasts with rates of bacteraemia caused by E. coli where

the rate of bacteraemia is similar between men and women. It should, however, be noted

that rates of E. coli bacteraemia are still higher among males than females for most age

groups.

Seasonality trends appeared similar across all three bacteraemias, particularly in regard to

the highest infection rates being seen in Q2 of the financial year. Community-onset cases

in general, appeared to see the larget and most consistent seasonal shifts in the

proportion of infections. However, seasonal changes were still clearly evident in the

hospital-onset cases especially in P. aeruginosa.

Rates of E. coli and Klebsiella spp. showed substantial inter-regional variation and similar

geographic distributions in England with higher rates in the North of England and generally

lower rates in the South of England. In contrast, rates of P. aeruginosa bacteraemia are

more evenly spread across England, except for relatively higher rates in the South East of

England. Interestingly, for all infections, the Manchester region has lower rates of infection

compared to its surrounding areas.

Long term trends are available for E. coli and reveal increasing rates of incidence since the

first full financial year of mandatory surveillance in 2012/13.

The rate of increase in counts of E. coli bacteraemia has been consistent between

2012/13 and 2016/17, averaging 5% per year. However, between 2016/17 and 2017/18,

the count of cases only increased by 1%, the first time it had been that low in the 6 years

of the mandatory surveillance of E. coli bacteraemia. However, between 2017/18 and

2018/19 the annual increase in counts of cases rate returned to 5%. Despite the increase

in all-case incidence, the incidence of hospital-onset cases has remained approximately

stable, suggesting that much of the increase in incidence is occurring in community-onset

cases. However, as community-onset cases include patients with recent hospital

admissions and other healthcare interactions, increases of cases within this category

should not be seen as coterminous with non-healthcare related infection. For E. coli

bacteraemia approximately half of the community-onset cases will be healthcare-

associated (E. coli bacteraemia sentinel surveillance group 2017, NHSI 2017).



33

Examination of the trends in the age group show increases in incidence rate among the

older age groups (65-74 and ≥ 85) for males and females but also among the under ones.

Although the highest rates of E. coli bacteraemia occur in the ≥ 85 population, the

proportionally greatest increases have occurred among the <1 age groups. The generally

uniform increase in rate across the age groups suggest that there is no particular change

in the age related risk factor that is driving the increase in E. coli bacteraemia. The

exception to this is the constantly low rate of E. coli bacteraemia among males and

females in the 1-14 age group. It is not clear why rates have reduced and remained the

lowest amongst this group.

As described above, rates of E. coli bacteraemia have been rising for several years. The

number of Gram-negative bacteraemias far exceeds those caused by S. aureus

bacteraemias. In 2017/18, a total of 5,865 people died within 30 days of having E. coli

bacteraemia. For these reasons, the Secretary of State for Health introduced an ambition

to reduce healthcare-associated Gram-negative bacteraemia by March 2021(NHSI 2017,

HM Government 2018) which has now been extended to March 2024. The reduction in

rates of C. difficile infection and MRSA bacteraemia show what is possible with targeted

interventions. However, there are important differences in the epidemiology of E. coli

bacteraemia and that of MRSA bacteraemia and CDI which means that the type of

interventions introduced to control MRSA bacteraemia and CDI may not be effective in

controlling E. coli bacteraemia.

For both CDI and MRSA bacteraemia at their peak, cases were more likely to occur in the

hospital setting. This means that the patient’s environment could be more carefully

controlled and healthcare interventions readily improved. With many of the cases of E. coli

being community-onset, altering clinical practice to reduce infection rates is likely to be

harder than it was for MRSA and CDI. Urinary tract infections were found to be the main

source of Gram-negative bacteraemia cases and thus should be targeted by infection

prevention control programs if substantial reductions are to be achieved. If urinary tract

infections can be reduced or where they do occur detected and resolved quickly then a

concomitant reduction in bacteraemias should follow (P. Wilson 2019).



34

Epidemiological analysis of Staphylococcus

aureus bacteraemia

A total of 12,878 Staphylococcus aureus bacteraemia cases were reported to PHE in

2018/19 through both the methicillin-resistant S. aureus (MRSA) bacteraemia and

meticillin-susceptible S. aureus (MSSA) bacteraemia surveillance schemes. This

represents a 0.6% increase in the numbers of bacteraemia caused by S. aureus from

2017/18 (n = 12,797) and a 30.3% increase from 2011/12 (n = 9,883) when MSSA

reporting was made mandatory.

In 2018/19, 6.3% (n = 805) of S. aureus bacteraemia reports were caused by MRSA. This

is a 44.6% decrease from 2011/12, in which 11.3% (n = 1,116) of reports were caused by

MRSA and a 5.8% decrease from 2017/18 in which 6.6% (n = 849) of reports were caused

by MRSA. At its peak MRSA bacteraemias accounted for approximately 40% of all S.

aureus bacteraemia cases in England (Johnson AP 2005).

The following sections will describe the epidemiology of MRSA and MSSA in England

separately.

Meticillin-resistant Staphylococcus aureus bacteraemia

Total reports

A total of 805 cases of MRSA bacteraemia were reported by NHS acute trusts in England

between 1 April 2018 and 31 March 2019. This is a decrease of 5.2% from 2017/18 (n =

849), and a decrease of 81.9% from 2007/08 (n = 4,451). Figure 16 shows the trends in

rates of MRSA cases for all cases and hospital-onset cases from 2007/08 to 2018/19. The

rate of all MRSA cases per 100,000 population, per year has fallen from 8.6 in 2007/08 to

1.4 in 2018/19.



35

Figure 16: Trends in the all case and hospital-onset rate of MRSA bacteraemia in

England 2007/08-2018/19


Although the MRSA all-case rate for the most recent year (1.4 per 100,000 population) is

less than the rate in 2007/08 (8.6 per 100,000 population), it has remained approximately

stable for the past four years (Figure 16).

Of the 805 total cases reported in FY 2018/19, 271 were hospital-onset (0.8 per 100,000

bed days), remaining steady from 2017/18 (Table 15).



36

Table 15: MRSA counts and rates by financial year, England: 2007/08 to 2018/19

Financial year


All reported

cases

Rate (all reported cases per 100,000

population) Total bed

days



100,000 bed days)

2007/08 51,594,959 4,451 8.6 37,320,817 2008/09 51,803,017 2,935 5.7 37,700,812 1,606 4.3 2009/10 52,306,371 1,898 3.6 37,326,212 1,004 2.7 2010/11 52,757,040 1,481 2.8 35,094,388 688 2.0 2011/12 53,312,604 1,116 2.1 34,502,306 473 1.4 2012/13 53,475,358 924 1.7 34,439,455 398 1.2 2013/14 53,976,973 862 1.6 34,327,781 364 1.1 2014/15 54,432,437 800 1.5 34,797,208 285 0.8 2015/16 55,018,884 823 1.5 34,576,351 298 0.9 2016/17 55,240,933 825 1.5 34,976,071 315 0.9 2017/18 55,619,430 849 1.5 34,749,047 276 0.8 2018/19 55,619,430 805 1.4 34,525,599 271 0.8



Trust-assigned reports

Prior to the introduction of the PIR process, cases were reported according to groups in

the apportioning algorithm, categorising cases by their time to onset in relation to patient

on the date of admission, patient location and the date of the specimen. Since only four

years of PIR data are available, of which the first year’s categorisation differed to the most

recent three, this report will also present cases grouped according to the apportioning

algorithm. Detailed data on the number of cases by PIR assignment group can be found in

Table 16.

The PIR data show a consistent decline in the rates of Clinical Commissioning Group

(CCG)-assigned cases from 0.8 cases per 100,000 population in 2013/14 to 0.4 cases per

100,000 population in 2017/18. In contrast, rates of trust-assigned MRSA bacteraemias fell

from 1.2 cases per 100,000 bed days in 2013/14 to 0.9 in 2014/15, after which trust-

assigned rates remained steady at 0.8 in 2017/18. The rate of Third Party assigned cases

has increased from 0.2 per 100,000 population to 0.6 per 100,000 population. Some of the

decline in rates of CCG-assigned cases and trust-assigned cases will be due to the

introduction of Third Party assignment, which resulted in some cases that would have

been otherwise assigned to either an acute trust or CCG, being assigned to the new

category.



37

Table 16: MRSA counts and rates by PIR assignment, England: 2013/14 to 2018/19


CCG assigned Trust-assigned Third Party

Financial year

cases rate* Total bed

days cases rate** cases rate*

2013/14 53,976,973 450 0.8 34,327,781 412 1.2 2014/15 54,432,437 370 0.7 34,797,208 315 0.9 115 0.2 2015/16 55,018,884 280 0.5 34,576,351 298 0.9 245 0.4 2016/17 55,240,933 214 0.4 34,976,071 316 0.9 295 0.5 2017/18 55,619,430 224 0.4 34,749,047 293 0.8 332 0.6

* Rates for CCG and Third-party cases are given per 100,000 population. ** Rates for trust-assigned cases are given per 100,000 bed days.



were excluded. In 2007/08, 52 cases (1.2%) gave the sex as unknown. In 2018/19, 0

cases (0%) gave the sex as unknown.

Figure 17, compares the age and sex structure of MRSA bacteraemia cases in England

between 2007/08 and 2018/19. For all ages and sexes there has been a considerable

decline in rates. Despite the decline in rates, the age and sex structure has remained

consistent. For both years, MRSA bacteraemia rates were highest among patients ≥ 85

years of age. In 2007/08, the rate among males was 147.4 per 100,000 population and

44.2 among females. In 2018/19, the rate among males was 22.1 per 100,000 population

and 7.2 among females.



38

Figure 17: Age and sex specific rates of MRSA rates per 100,000 population,

England

* Mid-year population estimates for 2018/19 were not available at time of publication and so population data for 2017/18 were used as a proxy.

In general, the rates of MRSA bacteraemia are greater among males than among females,

and particularly so among older age groups. Although the rates of MRSA bacteraemia

have declined over time, the proportional difference in rates between sexes within an age

group have not changed appreciably. The rate ratio for males and females in ≥ 85 age

group is 3.3 (95% CI: 2.9-3.8) in 2007/08. In comparison, the rate ratio in 2018/19 was 3.1

(95% CI: 2.3-4.2) (Table 17 & 18).



39

Table 17: MRSA counts and rates by age group and sex, England: 2007/08

Age group (years) Population n count Rate, per 100,000


<1 333,164.7 317,035.9 31 28 9.3 8.8 1-14 4,369,016.7 4,166,420.1 22 14 0.5 0.3 15-44 10,728,560.1 10,721,325.4 252 149 2.3 1.4 45-64 6,322,972.5 6,463,536.8 594 306 9.4 4.7 65-74 2,011,279.4 2,205,682.2 583 269 29.0 12.2 75-84 1,208,494.0 1,655,252.5 884 436 73.1 26.3 ≥ 85 337,199.9 755,018.8 497 334 147.4 44.2



Table 18: MRSA counts and rates by age group and sex, England: 2018/19

Age group (years) Population n count Rate, per 100,000


<1 335,035 318,432 7 7 2.1 2.2 1-14 4,813,341 4,581,557 10 10 0.2 0.2 15-44 10,749,133 10,572,163 59 60 0.5 0.6 45-64 7,014,072 7,205,186 124 52 1.8 0.7 65-74 2,646,091 2,849,090 95 42 3.6 1.5 75-84 1,435,728 1,747,546 112 57 7.8 3.3 ≥ 85 487,653 864,403 108 62 22.1 7.2



Trends in the age- and sex-specific rates of MRSA bacteraemia are shown in Figure 18.

Rates of MRSA bacteraemia have fallen across all age and sex groups since the start of

the surveillance in 2007/08. Despite this, some fluctuations in rate are seen for both sexes

in the < 1 age group in which rates increased in 2015/16 and 2016/17 (from 1.5 per

100,000 population in females in 2013/14 to 2.2 in 2016/17 and from 2.3 in males in

2013/14 to 5.0 in 2016/17). Rates have also increased in males ≥ 85 from 21.1 in 2016/17

to 22.1 in 2018/19.



40

Figure 18: Trend in age- and sex-specific rates of MRSA bacteraemia per 100,000





41

Source of MRSA bacteraemia

The HCAI Data Capture System provides acute trust users the opportunity to add

information regarding the likely source of bacteraemia. Source of bacteraemia refers to the

likely cause of the bacteraemia, such as an intravenous catheter, rather than an organ

where the infection first arose as in primary focus for Gram-negative bacteraemia. The

provision of this information is voluntary for each of the bacteraemia collections (MRSA,

MSSA, and Gram-negative bacteraemias) and has declined over time for MRSA.

In 2007/08 a total of 2,414 (54.2%) of MRSA records had entries (including “Unknown”) for

the source of bacteraemia. By 2018/19 a total of 287 (35.7%) MRSA records had entries

for the source of bacteraemia.

There have been large declines in the percentage of MRSA cases in which the source of

bacteraemia was a catheter or line. In 2007/08, catheters or lines were the source of

25.6% of cases. By 2018/19, this had declined to 12.9% of cases. In contrast, the

percentage of cases caused by skin and soft tissue infections has increased from 16.4% in

2007/08 to 33.4% in 2018/19. Between 2007/08 and 2014/15, the percentage of cases for

which the source of bacteraemia was pneumonia increased from 6.6% to 11.2%. Between

2014/15 and2017/18, the percentage of cases for which pneumonia was the source

fluctuated between 15.4% and12.3%. Trends in sources of bacteraemia are shown in

Table 19.

Table 19: MRSA counts and proportion by source of bacteraemia, England: 2018/19

Financial

year Catheters & lines* n (%)

SSTI n (%)

Pneumonia n (%) Other** n (%)

Unknown n (%)

Total n (%)

2007/08 617 (25.6) 395 (16.4) 160 (6.6) 705 (29.2) 537 (22.2) 2,414 (100.0) 2008/09 346 (22.5) 276 (17.9) 113 (7.3) 552 (35.8) 254 (16.5) 1,541 (100.0) 2009/10 178 (19.5) 191 (20.9) 63 (6.9) 328 (35.8) 155 (16.9) 915 (100.0) 2010/11 118 (17.5) 146 (21.6) 47 (7.0) 251 (37.1) 114 (16.9) 676 (100.0) 2011/12 71 (14.7) 98 (20.3) 41 (8.5) 177 (36.7) 95 (19.7) 482 (100.0) 2012/13 72 (18.3) 74 (18.8) 34 (8.6) 128 (32.5) 86 (21.8) 394 (100.0) 2013/14 39 (13.3) 57 (19.4) 33 (11.2) 100 (34.0) 65 (22.1) 294 (100.0) 2014/15 30 (11.9) 53 (20.9) 39 (15.4) 64 (25.3) 67 (26.5) 253 (100.0) 2015/16 38 (15.5) 56 (22.9) 25 (10.2) 89 (36.3) 37 (15.1) 245 (100.0) 2016/17 51 (20.0) 80 (31.4) 21 (8.2) 88 (34.5) 15 (5.9) 255 (100.0) 2017/18 50 (15.4) 101 (31.1) 40 (12.3) 118 (36.3) 16 (4.9) 325 (100.0) 2018/19 37 (12.9) 96 (33.4) 30 (10.5) 114 (39.7) 10 (3.5) 287 (100.0)

“Catheters and lines” includes the following options from the HCAI DCS question: dialysis lines, central venous catheter (CVC) associated, peripheral venous catheter (PVC) associated and intravenous (IV) lines. “*Other includes the following options HCAI DCS: endocarditis, osteomyelitis, other, prosthetic joint, surgical site infection (SSI), septic arthritis, urinary tract infection (UTI) and ventilator-associated pneumonia.



42

Geographic distribution of MRSA bacteraemia

Some geographical variation in rates of MRSA is noted (Figure 19). The local office with

the highest rate of MRSA in 2018/19 was Q86 NHS England South West (South West

North): 2.8 cases per 100,000. The local offices with the lowest rates were Q84 NHS

England North (Lancashire and South Cumbria) and Q76 NHS England Midlands and East

(North Midlands) 0.9 cases per 100,000.

Figure 19: MRSA rates by NHS local office, England: 2018/19


Table 20 gives NHS local office-specific rates. MRSA bacteraemia rates for all local offices

have declined between 2009/10 and 2018/19. However, increases in rates have been

observed for some local offices in recent years. The three regions with the largest

increases since 2016/17 are Q86 NHS England South West (South West North) , Q79

NHS England Midlands and East (East)andQ85 NHS England South West (Soyth West

South) .



43

Table 20: MRSA rates by NHS local office, England: 2018/19*


20

09

/10

20

10

/11

20

11

/12

20

12

/13

20

13

/14

20

14

/15

20

15

/16

20

16

/17

20

17

/18

20

18

/19

Q76 NHS England Midlands and East (North Midlands)

4.2 2.6 1.7 1.2 1.0 1.5 1.2 1.2 1.1 0.9

Q77 NHS England Midlands and East (West Midlands)

2.5 2.6 1.6 1.7 1.1 1.6 1.2 1.1 0.7 1.0

Q78 NHS England Midlands and East (Central Midlands)

2.4 2.4 1.7 0.9 1.1 1.3 1.1 1.1 1.1 1.1

Q79 NHS England Midlands and East (East) 3.1 1.9 1.8 1.4 1.2 1.2 1.5 1.7 1.8 2.0 Q72 NHS England North (Yorkshire and Humber) 4.2 3.4 2.5 2.0 1.9 1.3 1.3 1.5 1.6 1.5 Q74 NHS England North (Cumbria and North East) 3.1 2.4 1.3 1.9 1.2 1.6 1.5 1.6 1.4 1.0 Q75 NHS England North (Cheshire and Merseyside) 4.6 3.5 2.7 2.6 2.2 1.6 1.8 1.8 1.7 1.6 Q83 NHS England North (Greater Manchester) 4.6 3.5 2.4 2.3 1.9 1.5 1.9 2.1 1.6 1.9 Q84 NHS England North (Lancashire and South

Cumbria) 3.5 2.8 1.9 1.5 1.4 1.4 1.7 1.4 1.1 0.9

Q87 NHS England South East (Hampshire, Isle Of Wight and Thames Valley)

2.7 2.0 1.8 1.1 1.5 1.2 1.5 1.1 1.4 1.2

Q88 NHS England South East (Kent, Surrey and Sussex)

3.9 3.0 2.5 1.8 1.9 1.4 1.4 1.6 1.8 1.6

Q85 NHS England South West (South West South) 2.6 2.1 1.6 1.3 1.0 1.0 1.2 0.9 1.2 1.2 Q86 NHS England South West (South West North) 4.2 2.0 2.1 2.2 1.7 2.3 2.3 2.5 2.7 2.8 Q71 NHS England London 4.6 3.7 2.7 2.2 2.3 1.8 1.8 1.7 1.9 1.6 National 3.6 2.8 2.1 1.7 1.6 1.5 1.5 1.5 1.5 1.4


Discussion

MRSA bacteraemia rates have declined year on year from 2007/8 to 2014/15, however in

2015/6 the rate increased slightly but remained the same in 2016/17. In 2018/19 the rate

has decreased for all cases, and hospital-onset cases.

Over time, numerous interventions aimed at reducing the incidence of MRSA bacteraemia

and other infections have been introduced. These include the DoH policy document

‘Winning Ways’, published in 2003 (Department of Health 2003b); The ‘CleanYourHands’

campaign launched by the National Patient Safety Agency in 2014 (Stone et al. 2012); the

‘Saving Lives’ programme launched by the DoH in 2005 which included the ambition to

halve MRSA rates by 2008 (Department of Health 2005); the 2006 Health Act which

introduced a code of practice to provide guidance on reducing HCAI including MRSA

(Department of Health 2006); and the Health and Social Care Act, 2008 which requires the

code of practice to be regularly updated (Department of Health 2008).



44

Thus, the epidemiology of MRSA has changed since its peak, with the greatest proportion

of cases now being community-onset. This switch in setting is most likely due to the

majority of MRSA bacteraemia interventions being targeted to the acute care setting and

thus largest reductions in MRSA bacteraemias were seen in hospital-onset cases. The

duration of stay of hospital patients is also on the decline. In 2001, the average length of

stay for a hospitalised patient in the UK was 7.4 days, this decreased to 5.9 days in 2013

(Organisation of Economic Co-operation and Development 2018). The reduced hospital

stay lessens the risk of acquiring a hospital-acquired infection. A declining length of stay

could also mean patients may acquire an MRSA infection in an acute care setting and yet

not display symptoms until they have returned to the community. Such cases would then

be readmitted, at which point the time-to-onset would be less than 2 days, according to the

definitions used here. It is also possible that early detection of MRSA bacteraemia is

improving with advances in diagnostics as well as general improvement in clinical

awareness of sepsis (Sepsis Trust, 2013).

The PIR process was introduced in April 2013 to aid the zero-tolerance policy for MRSA

bacteraemia (NHS England 2014b). Since then, rates of CCG-associated cases have

fallen each year. Trust-assigned rates fell between 2013/14 and 2014/15 but then

remained stable between 2014/15 and 2017/18. The PIR process has now been made a

local-only process and will not be reported further in these reports.

The percentage of MRSA bacteraemia where the likely source of infection was a catheter

or a line, has shown steady decrease between 2007/8 and 2014/15, with a sudden sharp

rise between 2015/16 to 2017/18, and subsequently returned to levels seen prior to

2015/16. Declines in the proportion of MRSA bacteraemia where the most likely source of

infection is a catheter or line have been noted previously and may be due to greater

clinical awareness of the importance of this route of infection and the introduction of care

bundles aimed at reducing infections in intra-vascular lines and selective decolonization of

patients with MRSA carriage.

The percentage where the primary focus is something other than catheters or intravenous

lines have fluctuated considerably over time. The percentage of infections whose likely

source is skin or soft tissue infection does appear to have increased over time, from 16.4%

in 2007/8 to 33.4% in 2018/19. However, in 2018/19 approximately 35.7% of records had

information on the likely source of bacteraemia and therefore, interpretation of these data

should be approached cautiously.

Considered together, the stabilisation in the rate of trust-assigned cases and the increase

in the percentage of infections due to catheters and lines since 2014/15 highlight the need



45

for continued vigilance and continued efforts on infection prevention initiatives to reduce

hospital-onset cases further. In addition, to maintain good practice in an acute trust setting,

interventions are required in the community setting, considering the majority of MRSA

cases are now community-onset. The geographical distribution of MRSA bacteraemia

across England does not show any obvious pattern. Highest rates are observed in the

South West of England, and lowest rates in the West Midlands. Elsewhere, the rates of

MRSA bacteraemia are relatively evenly distributed across the country.



46

Meticillin-susceptible Staphylococcus aureus bacteraemia

Total reports

A total of 12,073 cases of MSSA bacteraemia were reported by NHS acute trusts in

England between 1 April 2018 and 31 March 2019. This is broadly similar to 2017/18 (n =

11,948), and an increase of 37.7% from 2011/12 (n = 8,767). Figure 20 shows the trends

in rates of MSSA cases for all cases and hospital-onset cases from 2011/12 to 2018/19.

The rate of all MSSA cases per 100,000 population, per year has risen from 16.4 in

2011/12 to 21.7 in 2018/19.

Figure 20: Trends in the rate of MSSA bacteraemia in England

*Mid-year population estimates for 2018/19 were not available at time of publication and so population data for 2017/18 were used as a proxy. ** Bed day data population data were not available for quarter 4 of FY 2018/19 (January to March 2019). As a result, the 2018/19 bed day data is an aggregate of quarter 1, 2 and 3 of 2018/19 and quarter 4 of 2017/18.



47

Hospital-onset reports

Of the 12,073 total cases reported in FY 2018/19, 3,322 were hospital-onset (9.6 per

100,000 bed days). Similar to all-reported MSSA cases, the incidence rate for hospital-

onset MSSA cases has increased steadily (from 7.8 in 2012/13 to 9.6 in 2018/19, a

change of 22.7%). Despite the increase in hospital-onset rates, the percentage of cases

that were hospital-onset has declined from 32.6% in 2011/12 to 27.5% in 2018/19 (Table

21).

Table 21: MSSA counts and rates by financial year, England: 2011/12 to 2018/19

Financial year


All reported

cases


population) Total bed

days



100,000 bed days)

2011/12 53,312,604 8,767 16.4 34,502,306 2,854 8.3 2012/13 53,475,358 8,812 16.5 34,439,455 2,700 7.8 2013/14 53,976,973 9,290 17.2 34,327,781 2,696 7.9 2014/15 54,432,437 9,862 18.1 34,797,208 2,807 8.1 2015/16 55,018,884 10,608 19.3 34,576,351 2,921 8.4 2016/17 55,240,933 11,497 20.8 34,976,071 3,098 8.9 2017/18 55,619,430 11,948 21.5 34,749,047 3,152 9.1 2018/19 55,619,430 12,073 21.7 34,525,599 3,322 9.6



were excluded. In 2011/12, 265 cases (3%) gave the sex as unknown. In 2018/19, 7 cases

(0.1%) gave the sex as unknown.

Figure 21 compares the age and sex structure of MSSA bacteraemia cases in England

between 2011/12 and 2018/19. For both years, MSSA bacteraemia rates were highest

among patients ≥85 years of age. In 2011/12, the rate among males was 134.5 per

100,000 population and 65.6 among females. In 2018/19, the rate among males was 186

per 100,000 population and 77.7 among females. The rate of MSSA bacteraemia is also

particularly high among <1s (186 per 100,000 population and 77.7 in 2018/19).



48

Figure 21: Age and sex structure of MSSA rates per 100,000 population, England


In general, the rates of MSSA bacteraemia are greater among males than among females,

and particularly so among older age groups. As the rates of MSSA bacteraemia have

increased over time, the rate ratio between sexes has increased somewhat. The rate ratio

for MSSA between males and females 85 years and over in 2011/12 is 2.0 (95% CI: 1.8-

2.3) compared with 2.4 (95% CI: 2.2-2.6) in 2018/19. Rates are also much higher in <1

age group, much more than what is seen with MRSA in this age group. Age group data is

tabulated in Table 22 and 23.



49

Table 22: MSSA counts and rates by age group and sex, England: 2011/12

Age group (years)

Population* n cases Rate, per 100,000


<1 350,817.8 333,993.3 251 189 71.5 56.6 1-14 4,476,176.1 4,269,121.6 283 174 6.3 4.1 15-44 10,799,091.6 10,738,537.1 849 482 7.9 4.5 45-64 6,678,566.3 6,837,399.2 1,409 731 21.1 10.7 65-74 2,241,803.6 2,422,555.7 947 516 42.2 21.3 75-84 1,295,415.4 1,666,592.1 964 646 74.4 38.8 ≥ 85 394,885.2 807,649.1 531 530 134.5 65.6

Table 23: MSSA counts and rates by age group and sex, England: 2018/19

Age group (years)

Population* n cases Rate, per 100,000


<1 335,035 318,432 213 139 63.6 43.7 1-14 4,813,341 4,581,557 306 225 6.4 4.9 15-44 10,749,133 10,572,163 1,300 814 12.1 7.7 45-64 7,014,072 7,205,186 2,117 1,039 30.2 14.4 65-74 2,646,091 2,849,090 1,499 687 56.6 24.1 75-84 1,435,728 1,747,546 1,358 790 94.6 45.2 ≥ 85 487,653 864,403 907 672 186.0 77.7


Rates of MSSA bacteraemia among older males have increased substantially since

2013/14. In 2013/14 the rate of MSSA bacteraemia was 136.6 among those ≥ 85. By

2018/19, this rate was 186.0 (Figure 22 below). Interestingly, rates appear to have

reduced in the <1 age group, and have increased in all the populations >14, when

comparing the 2007/08 figures to 2018/19.



50

Figure 22: Trend in age and sex structure of MSSA cases and rate per 100,000


* *Mid-year population estimates for 2018/19 were not available at time of publication and so population data for 2017/18 were used as a proxy.



51

Source of MSSA bacteraemia

In 2011/12 a total of 3,305 (37.7%) records had entries for the source of bacteraemia. By

2018/19 a total of 3,724 (30.8%) had entries for the source of bacteraemia.

The percentage of cases caused by skin and soft tissue infections has increased from

20.3% in 2011/12 to 27.6% in 2018/19. The percentage of infections caused by

pneumonia has also risen substantially from 6% in 2011/12 to 12.1% in 2018/19. There

have been fluctuations in the percentage of MSSA cases in which the source of

bacteraemia was from either a catheter or line. In 2011/12, catheters or lines were the

source of 17.1% of cases. By 2018/19, this had declined to 15.4% of cases.

The percentage of cases for which the source of infection was unknown has decreased

from 23.6% in 2011/12 to 2.1% in 2018/19. Trends in sources of bacteraemia are shown in

Table 24.

Table 24: MSSA counts and rates by source of bacteraemia, England: 2018/19

Financial

year Catheters & lines* n (%) SSTI n (%)

Pneumonia n (%)

Other** n (%)

Unknown n (%) Total n (%)

2011/12 565 (17.1) 670 (20.3) 197 (6.0) 1093 (33.1) 780 (23.6) 3,305 (100.0) 2012/13 492 (15.1) 699 (21.4) 232 (7.1) 1088 (33.3) 755 (23.1) 3,266 (100.0) 2013/14 435 (13.4) 684 (21.1) 218 (6.7) 1124 (34.7) 775 (23.9) 3,236 (100.0) 2014/15 445 (13.1) 706 (20.8) 305 (9.0) 1087 (32.0) 855 (25.2) 3,398 (100.0) 2015/16 493 (15.3) 769 (23.9) 306 (9.5) 1169 (36.3) 487 (15.1) 3,224 (100.0) 2016/17 499 (15.7) 871 (27.4) 365 (11.5) 1279 (40.2) 169 (5.3) 3,183 (100.0) 2017/18 516 (14.6) 1003 (28.4) 445 (12.6) 1440 (40.8) 125 (3.5) 3,529 (100.0) 2018/19 575 (15.4) 1028 (27.6) 450 (12.1) 1594 (42.8) 77 (2.1) 3,724 (100.0)

“Catheters and lines” includes the following options from the HCAI DCS question: dialysis lines, central venous catheter (CVC) associated, peripheral venous catheter (PVC) associated and intravenous (IV) lines. “^Other includes the following options HCAI DCS: endocarditis, osteomyelitis, other, prosthetic joint, surgical site infection (SSI), septic arthritis, urinary tract infection (UTI) and ventilator-associated pneumonia.

Geographic distribution of MSSA bacteraemia

Some geographical variation in rates of MSSA is noted (Figure 23). The local offices with

the highest rates of MSSA were in the north of England Q75 NHS England North

(Cheshire and Merseyside): 30.4, followed by both Q84 NHS England North (Cumbria and

North East) and Q81 NHS England North (Lancashire and South Cumbria): both reporting

28 MSSA bacteraemia per 100,000 population. However, there is one local office that

bucks the trend of higher rates in the north: Q85 NHS England South West (South West

South) had a rate of 25.8 per 100,000 population (Figure 23).



52

The local office with the lowest rate in 2018/19 was Q71 NHS England London with a rate

of 16.6 cases per 100,000 population.

Figure 23: Geographic distribution of MSSA rates per 100,000 population, England

2018/19


Table 25 gives NHS local office-specific rates. For most local offices, rates of MSSA

bacteraemia followed the national trend; one of increasing incidence over time. The

exception of Q83 NHS England North (Greater Manchester) and Q84 NHS England

(Lancashire and South Cumbria) showing a slight decrease on last year’s rates.

The largest increase in incidence was observed in Q74 NHS England North (Cumbria and

North East) which saw the incidence rise from 17.3 cases per 100,000 population in

2011/12 to 28 in 2018/19. Q75 NHS England North (Cheshire and Merseyside) also saw a

large increase in incidence from 20.7 cases per 100,000 population in 2011/12 to 30.4 in



53

2018/19. In contrast, two regions (NHS England North (Cumbria and North East) and NHS

England London) close to stable rates of MSSA over time.

Table 25: MSSA rates by NHS local office per 100,000 population, England: 2011/12

to 2018/19*


2011

/12

2012

/13

2013

/14

2014

/15

2015

/16

2016

/17

2017

/18

2018

/19

Q76 NHS England Midlands and East (North Midlands)

17.9 19.5 19.1 21.6 23.4 24.7 24.3 24.4

Q77 NHS England Midlands and East (West Midlands)

17.2 16.6 17.6 17.3 16.4 18.6 20.0 20.2

Q78 NHS England Midlands and East (Central Midlands)

15.4 14.6 13.4 15.8 16.7 18.4 18.9 18.1

Q79 NHS England Midlands and East (East) 14.0 13.2 13.9 14.7 17.6 17.9 18.8 18.9 Q72 NHS England North (Yorkshire and Humber) 20.7 19.3 20.3 20.4 23.2 24.1 23.5 25.4 Q74 NHS England North (Cumbria and North East) 17.3 17.6 20.1 19.6 25.0 26.2 26.6 28.0 Q75 NHS England North (Cheshire and Merseyside) 20.7 20.2 21.1 24.7 24.3 28.4 27.6 30.4 Q83 NHS England North (Greater Manchester) 16.2 18.3 19.3 17.2 20.5 21.3 24.9 23.9 Q84 NHS England North (Lancashire and South

Cumbria) 17.6 20.5 20.4 22.8 24.8 23.7 26.5 24.3

Q87 NHS England South East (Hampshire, Isle Of Wight and Thames Valley)

13.7 13.7 15.2 17.6 17.2 19.3 19.4 19.8

Q88 NHS England South East (Kent, Surrey and Sussex)

14.1 14.8 15.4 17.3 17.9 20.4 21.2 20.8

Q85 NHS England South West (South West South) 18.6 16.8 20.1 21.9 22.9 25.1 27.4 25.8 Q86 NHS England South West (South West North) 16.3 15.6 16.3 17.6 17.1 19.8 17.8 20.9 Q71 NHS England London 14.6 15.5 15.6 15.0 14.9 16.0 17.1 16.6 National 16.4 16.5 17.2 18.1 19.3 20.8 21.5 21.7 * Mid-year population estimates for 2018/19 were not available at time of publication and so population data for 2017/18 were used as a proxy.

Discussion

Mandatory surveillance of MSSA bacteraemia was introduced in January 2011. In the first

year, MSSA bacteraemia rates were stable (2011/12 to 2012/13), before increasing each

subsequent year. In contrast, hospital-onset rates fell slightly in the first year of the

mandatory surveillance programme being introduced; beyond this rates have been

increasing slightly year on year.

Age and sex structure of MSSA bacteraemia show rates increase with age group, with the

highest rate seen in the 85 and over age group, furthermore males also show higher rates

of MSSA bacteraemia compared to females. However, rates of MSSA bacteraemia are

also seen to be very high in the youngest age group, <1 years old, compared to young



54

patients (1-14 years old) and adults (15 to 74 years old). This contrasts with MRSA

bacteraemia in which rates among the <1 age group are close to the rates in the 1-14 age

group.

Research using data gathered by the mandatory surveillance found that cases arising in

very young patients were most likely attributable to healthcare-associated infections, rather

than community-associated infections and were related to intravascular devices

(Abernethy et al. 2017). Despite the increase in MSSA bacteraemia rates over the years,

little change has been observed in rates between males and females, with the rate in men

85 years or greater being 2.4 times greater in 2018/19 than amongst women of the same

age, 186.0 and 77.7 cases per 100,000 population, respectively.

Levels of completion of the likely source of infection for MSSA have declined over time. In

2017/18, only 30.8% of records had a source of infection information available, a slight

increase on 29.3% from last year. There has been a gradual increase over the years in the

percentage of cases where the source has been either, skin or soft tissue or pneumonia,

however a slight decrease has been observed for both in 2018/19, which is also mirrored

in MRSA bacteraemias. However it must be noted that likely source is not a mandatory

field in the DCS.

Geographically there appears to be no trends or similarities in rates of infections between

MRSA and MSSA. With a couple of exceptions MSSA appears to be most prevalent in the

north. This contrasts with the geographic distribution of MRSA in which no particular North-

South distribution was observed.

The epidemiology of MRSA and MSSA bacteraemia also show differences in mortality.

The 30-day mortality in 2017/18 was reported as 25.9% for MRSA and 19.5% for MSSA

(PHE 2018).

As rates of MRSA continue to fall steadily, we see the MSSA bacteraemia rates have

slowly increased, in both hospital- and community-onset cases. The increase in MSSA

cases appears to be driven by the increases in community-onset cases. In 2018/19, 72.5%

of all reported MSSA bacteraemias were community-onset, reasons for this are unclear.

This indicates that the focus for interventions needs to placed on community-onset MSSA

cases.



55

Epidemiological analysis of Clostridioides

difficile Infection

A total of 12,275 cases of Clostridioides difficile infection were reported by NHS trusts in

England between 1 April 2018 and 31 March 2019. This is a small decrease of 7.7% from

2017/18 (n = 13,299) and a decrease of 77.9% from 2007/08 (n = 55,498). Figure 24

shows the trends in rates of CDI cases for all cases and hospital-onset cases from

2007/08 to 2018/19. The rate of all CDI cases per 100,000 population, per year has fallen

from 107.6 in 2007/08 to 22.1 in 2018/19.

Figure 24: Trends in the rate of C. difficile infection in England

* Mid-year population estimates for 2018/19 were not available at time of publication and so population data for 2017/18 were used as a proxy. ** bed day data were not available for quarter 4 of FY 2018/19 (January to March, 2019). As a result, the 2018/19 bed day data is an aggregate of quarters 1, 2 and 3 of 2018/19 and quarter 4 of 2017/18.



56

Hospital-onset reports

Of the 12,275 total cases reported in FY 2018/19, 4,201 were hospital-onset (12.2 per

100,000 bed-days). It should be noted that CDI cases are considered hospital-onset if they

occur ≥ 4 days after admission to an acute trust, where day of admission is day 1. This is

in contrast to ≥ 3 days for bacteraemia cases. The incidence rate for hospital-onset CDI

cases mirrors the trends in incidence for all cases, with declining rates from 2007/08 to

2013/14 which then remained approximately stable to 2017/18. The rate of hospital-onset

CDI cases decreased slightly from 13.6 in 2017/18 to 12.2 in 2018/19, a change of 10.8%

(Table 26).

Table 26: CDI counts and rates by financial year, England: 2007/08 to 2018/19

Financial year


All reported

cases


population) Total bed-

days



100,000 bed-days)

2007/08 51,594,959 55,498 107.6 37,320,817 33,434 89.6 2008/09 51,803,017 36,095 69.7 37,700,812 19,927 52.9 2009/10 52,306,371 25,604 49.0 37,326,212 13,220 35.4 2010/11 52,757,040 21,707 41.1 35,094,388 10,417 29.7 2011/12 53,312,604 18,022 33.8 34,502,306 7,689 22.3 2012/13 53,475,358 14,694 27.5 34,439,455 5,980 17.4 2013/14 53,976,973 13,362 24.8 34,327,781 5,034 14.7 2014/15 54,432,437 14,193 26.1 34,797,208 5,233 15.0 2015/16 55,018,884 14,143 25.7 34,576,351 5,162 14.9 2016/17 55,240,933 12,847 23.3 34,976,071 4,622 13.2 2017/18 55,619,430 13,299 23.9 34,749,047 4,740 13.6 2018/19 55,619,430 12,275 22.1 34,525,599 4,201 12.2


Prior trust exposure

In April 2017, the mandatory surveillance captured information on whether a patient with

CDI had been previously admitted to the reporting trust in the past 84 days. These data

have previously been reported as monthly counts in the monthly tables produced by the

mandatory surveillance team but have not previously been published as annual rates.



57

With the prior trust exposure, cases are split into the following groups:

Hospital-onset, healthcare associated (HOHA) - Cases where the date of onset is two or

more days after the date of admission, where date of admission is day zero and the

patient was admitted to an NHS acute trust at time of specimen.

Community-onset, healthcare associated (COHA) - Cases which are not HOHA but have

previously been discharged from the reporting organisation within the 28 days prior to

specimen date.

Community-onset, indeterminate association (COIA) - Cases which are not HOHA but

have previously been discharged from the reporting organisation but have been

discharged from the reporting organization between 28 and 84 days prior to specimen

date.

Community-onset, community associated (COCA) - Cases which are not HOHA and have

not previously been discharged from the reporting organisation within the past 84 days.

Cases for which “Don’t know” was recorded against the prior trust exposure status are

grouped into “Unknown” and cases for which no information about the prior trust exposure

was entered are grouped into “No information”. Both of these groups are included in the

community-onset group as they are known not to be HOHA cases (Table 27).

Table 27: Prior healthcare exposure of CDI cases by financial year, England: 2017/18

to 2018/19*

Financial year

Total bed-days

HOHA

COHA COIA COCA Unknown* No

information** Total cases Count Rate

2017/18 34,749,047 5,465 15.7 1,890 1,064 2,857 262 1,761 13,299 2018/19 34,525,599 4,871 14.1 2,271 1,330 3,467 331 5 12,275 *The record indicates that it is unknown whether the patient was admitted to the reporting organisation in the past three months. **No information was entered for the prior trust exposure. HOHA – Hospital-onset, healthcare associated COHA - Community-onset, healthcare associated COIA - Community-onset, indeterminate association COCA – Community-onset, community associated

The count of HOHA dropped from 5,465 in 2017/18 to 4,871 in 2018/19. In contrast, each

of the community-onset categories increased in counts of cases between 2017/18 and

2018/19. The count of cases for which no prior trust information was provided, dropped

from 1,761 in 2017/18 to 5 in 2018/19



58

Seasonal trends in CDI

Data from previous Annual Epidemiological Commentaries have indicated a shift in the

seasonality of hospital-onset CDI. In 2010/11, 28.8% of hospital-onset cases were

reported in the first quarter of the financial year, with declining percentages reported in the

subsequent quarters of the financial year (Figure 25). hospital-onset cases in 2011/12

showed a similar distribution. However, in 2014/15, hospital-onset cases were more evenly

distributed throughout the year. Cases reported in the first quarter of the year made up

23.0% of cases and cases reported in the fourth quarter of the year made up 26.1%. From

2015/16 onwards, the second quarter of the year (July-September) saw the greatest

proportion of cases reported (between 26% and 29% of cases each year).

In contrast, community-onset cases have always shown a peak in the second quarter of

the financial year, with this quarter forming 28% to 29% of cases for the financial year.

Figure 25: CDI counts by financial year and quarter, England 2010/11 to 2018/19



59



were excluded. In 2007/08, the sex was reported as unknown for 667 cases (1.2%). In

2018/19, the sex was reported as unknown for 22 cases (0.2%).

Figure 26 compares the age and sex structure of CDI cases in England between 2007/08

and 2018/19. For both years, CDI rates were highest among patients ≥ 85 years of age. In

2007/08, the rate among men was 1,504.7 per 100,000 population and 1,490.2 among

females. In 2018/19, the rate among males was 215.7 per 100,000 population and 221

among fenales.

Figure 26: Age and sex structure of CDI rates per 100,000 population, England


Table 28 and 29 show the comparison of the sex structure of CDI rates reveals very little

gap in rates between men and women. The rate ratio between men and women ≥85 years

old is 1.0 (95% CI: 0.9-1.1).



60

Table 28: CDI counts and rates by age group and sex, England: 2007/08

Age group (years)

Population n cases Rate, per 100,000


2-14 4,046,149.6 3,858,142.2 178 157 4.4 4.1 15-44 10,728,560.1 10,721,325.4 1,251 1,539 11.7 14.4 45-64 6,322,972.5 6,463,536.8 3,479 3,333 55.0 51.6 65-74 2,011,279.4 2,205,682.2 4,970 4,904 247.1 222.3 75-84 1,208,494.0 1,655,252.5 7,974 10,721 659.8 647.7 ≥ 85 337,199.9 755,018.8 5,074 11,251 1,504.7 1,490.2

Table 29: CDI counts and rates by age group and sex, England: 2018/19

Age group (years)

Population n cases Rate, per 100,000


2-14 4,467,295 4,252,796 162 128 3.6 3.0 15-44 10,749,133 10,572,163 400 672 3.7 6.4 45-64 7,014,072 7,205,186 903 1,118 12.9 15.5 65-74 2,646,091 2,849,090 1,149 1,370 43.4 48.1 75-84 1,435,728 1,747,546 1,424 1,965 99.2 112.4 ≥ 85 487,653 864,403 1,052 1,910 215.7 221.0


Trends in age and sex

Although CDI rates are greatest among the elderly, as a percentage of cases reported to

the mandatory surveillance, there has been an increase among younger age groups, and

a concomitant decline in the percentage of cases that are from older age groups. In

2007/08, among females, the percentage of cases that occurred among those ≥85 years

old was 35.3%. In 2018/19, this had declined to 26.7%. Trends in the percentage of cases

among females between 75 and 84 years old has also declined over the same time period.

In 2007/08, among females, the percentage of cases that occurred among those between

75 and 84 years old was 33.6%. In 2018/19, this had declined to 27.4%.

In contrast, the percentage of cases that occurred among females between 65-74 years

old was 15.4% in 2007/08 and 19.1% in 2018/19. Younger age groups have also seen

increases in the percentage of cases which they form.



61

The increase in percentage of cases among younger age groups has not been seen in

males. In 2007/08, 22.1% of cases among males occurred in the ≥85 age group. In

2018/19, this was 20.7%. A small increase has been observed among the 15-44 age

group in males from 5.5% in 2007/08 to 7.9% in 2018/19.

It is important to note that this only reflects percentages of cases and that, because of the

age and sex structure of the population of England, the incidence rate by age and sex can

be very different.

Figure 27: Trend in age and sex structure of CDI cases ant rate per 100,000





62

Geographic distribution of CDI

The geographical distribution of CDI incidence in England shows a north-south divide

(Figure 28). The local offices with the highest rates of CDI are in the north of England Q74

NHS England North (Cumbria and North East): 29.2 CDI per 100,000 population, Q75

NHS England North (Cheshire and Merseyside): 29.7 and Q84 NHS England North

(Lancashire and South Cumbria): 28.9). In contrast, the local office with the lowest rate in

2018/19 was Q71 NHS England London with a rate of 15.2 cases per 100,000 population.

Figure 28: Geographic distribution of CDI rates per 100,000 population, England

2018/19


Table 30 gives NHS local office-specific rates. All local offices showed declining trends in

the rate of CDI since 2009/10. The greatest declines occurred in Q74 NHS England North



63

(Cumbria and North East) and Q75 NHS England North (Cheshire and Merseyside). For

Q74 NHS England North (Cumbria and North East) the rate of CDI was 74.6 for 2009/10

and 29.2 for 2018/19. For Q74 NHS England North (Cheshire and Merseyside) the rate of

CDI was 74.2 for 2009/10 and 29.7 for 2018/19.

Table 30: CDI rates by NHS local office, England: 2011/12 to 2018/19*


20

11

/12

20

12

/13

20

13

/14

20

14

/15

20

15

/16

20

16

/17

20

17

/18

20

18

/19

Q76 NHS England Midlands and East (North Midlands) 50.8 45.3 32.3 31.4 28.5 30.7 30.5 25.0 Q77 NHS England Midlands and East (West Midlands) 55.5 47.9 45.9 30.0 26.8 25.8 25.6 24.9 Q78 NHS England Midlands and East (Central Midlands) 45.9 35.1 26.2 24.1 22.8 23.1 22.6 20.1 Q79 NHS England Midlands and East (East) 40.6 31.1 24.0 22.5 20.4 26.0 24.8 22.8 Q72 NHS England North (Yorkshire and Humber) 46.2 43.5 39.8 31.8 29.6 28.7 28.1 26.7 Q74 NHS England North (Cumbria and North East) 74.6 46.4 37.9 35.0 28.0 32.4 34.1 27.4 Q75 NHS England North (Cheshire and Merseyside) 74.2 55.9 39.0 30.8 28.6 31.5 31.0 29.4 Q83 NHS England North (Greater Manchester) 67.0 58.3 42.9 35.5 29.4 30.9 29.5 28.3 Q84 NHS England North (Lancashire and South Cumbria) 58.9 46.2 35.3 30.5 28.0 33.9 34.7 25.1 Q87 NHS England South East (Hampshire, Isle Of Wight

and Thames Valley) 45.5 39.5 34.5 24.3 21.7 21.1 21.0 20.2

Q88 NHS England South East (Kent, Surrey and Sussex) 42.4 38.6 28.4 25.8 23.8 23.1 23.1 24.5 Q85 NHS England South West (South West South) 43.8 43.5 43.2 27.5 25.0 28.7 29.3 23.5 Q86 NHS England South West (South West North) 53.0 41.4 37.1 33.1 31.6 27.9 28.3 25.2 Q71 NHS England London 33.5 31.1 25.5 20.1 17.9 19.9 18.7 16.5 National 49.0 41.1 33.8 27.5 24.8 26.1 25.7 23.3


Discussion

Between 2007/08 and 2012/13 rates of CDI fell rapidly. Since 2012/13 rates have

continued to decline, but much less rapidly. The rapid decline in the rate of all cases of

CDI has been mirrored in hospital-onset cases. However, the decline in community-onset

cases has not been so rapid and community-onset cases now constitute 66% of cases,

where as in 2011/12 it only accounted for 57.3% . Many of the interventions aimed at the

reduction of CDI rates were targeted at the hospital setting, which likely explains the

greater reduction in hospital-onset cases compared to community-onset cases. However,

the division of cases into hospital-onset and community-onset cases ignores the effect of

any prior admissions to hospital which could increase the risk of CDI. For this reason, and

to better align surveillance in England with that performed by ECDC and CDC, information

on prior trust exposure was introduced in April 2017.

The prior trust exposure classification groups cases according to whether the patient has

previously been admitted to the reporting trust in the past three months (84 days). Since



64

the prior trust exposure classification of cases has only been running for two years, it is

hard to make comments about whether observed differences between years represent

long-term trends. Hospital-onset, healthcare-associated cases formed the largest group by

the new apportioning method, but showed a considerable decline from 5,465 cases in

2017/18 to 4,871 cases in 2018/19. In contrast, the counts of cases for community-onset

groups have each increased, at least partly because of a change in the provision of

information on prior trust exposure. The proportion of cases which lack any information on

prior trust exposure declined from 13% in 2017/18 to <0.1% in 2018/19, probably as a

result of making the questions around prior trust exposure mandatory.

Although the prior trust exposure only records admission to the reporting organisation,

analysis by the mandatory surveillance team using data from the Hospital Episodes

Statistics estimates that this captures over 80% of all hospital interactions.

Rates of CDI are highest among older age groups; those ≥ 75 years of age. Recent

research has shown that over time, elderly individuals are getting frailer and experiencing

polypharmacy (Melzer et al. 2015). A frailer population, receiving greater levels of

medication would suggest that greater levels of healthcare interaction were being

experienced by this age group. Despite this, rates of CDI have decreased considerably

among the oldest age group. The reason for this difference is likely to be due to the care

bundle introduced by the DHSC which recommended the use of personal protective

equipment, cohort nursing and environmental decontamination which were geared towards

preventing HCAI in acute care settings and not community settings. (Department of Health

2007).

The decline in rates has done little to affect the age- and sex-specific rates of CDI. Those

patients 85 years or older are the most frequently affected and there is little difference in

the rates between the sexes. This marks a difference in epidemiology between CDI and

bacteraemia in which rates are higher among males than females in almost all age groups.

The shift in seasonality is intriguing and currently lacks an explanation. Between 2010/11

and 2013/14, most hospital-onset and allsi community cases occurred in the April-to-June

quarter of the financial year. From 2016/17 onwards, the quarter with the greatest number

of cases was the July-to-September quarter.

In contrast to the geographic distribution of both MSSA and E. coli bacteraemia, which

both show a weak north-south divide in rates, there is a clear north-south split in the

distribution of CDI with higher rates in the north of England than in the south. Previous

work by this group has indicated an association between higher levels of deprivation and



65

higher rates of CDI, the same is true for E. coli and MSSA, although the strongest

association was seen in E. coli.

The decline in rates of CDI is difficult to explain fully, in terms of which interventions had

the largest effect, in part because the interventions were not applied in isolation. A number

of the interventions aimed at reducing MRSA rates were also aimed at reducing CDI (the

‘CleanYourHands’ and Saving Lives campaigns). It is perhaps not surprising, then, that the

trends in rates of CDI mirror those of MRSA. In addition, targets to reduce CDI cases were

introduced in 2008. These aimed to reduce the number of cases reported annually to 30%

of the 2007/08 count by 2010/11 (Department of Health 2008). Failure to achieve targets

was associated with financial penalties. Financial sanctions against acute trusts for

exceeding expected numbers of CDI were reduced in 2014/15 from £50,000 to £10,000

per case (NHS England 2014a), in addition, only those cases deemed to be associated

with a lapse in care are now subject to the financial sanctions. This was introduced in

recognition of the fact that some cases can occur even if best practice is followed.In

addition to the objectives and the ‘CleanYourHands’ and Saving Lives campaigns,

guidance was issued aiming to reduce clindamycin, cephalosporin or fluoroquinolone

prescribing, which had been shown to promote the spread of epidemic strains of C. difficile

(Department of Health and Health Protection Agency 2008). The resulting reduction in

prescribing of fluoroquinolones and cephalosporins has been associated with a significant

decline in the incidence of CDI, in regional analysis (Dingle et al. 2017).

The epidemiology of CDI is changing from a mostly hospital-onset infection to a

community-onset one, along with this change of setting the distribution of strains causing

CDI in England has changed over time. A C. difficile ribotype (ribotype 027) associated

with the high numbers of CDI cases in the early 2000s is no longer as prevalent.(Wilcox et

al. 2012) This particular ribotype is associated with poorer patient outcomes, reductions in

fataity rate from 26.3% of cases in 2007/08 to 15.2% in 2017/18, may be in part due to the

reduction in prevalence seen in ribotype 027 (Inns et al. 2013).



66

Appendix

Background to the mandatory surveillance of MRSA and MSSA bacteraemia

During the 1990s, voluntary surveillance of antibiotic resistance by microbiology

laboratories across England, Wales and Scotland saw increasing reports of MRSA

(Johnson, Pearson, and Duckworth 2005). In response to the concerns about the rising

number of reports of MRSA, the Department of Health and Social Care (DHSC) made

surveillance of MRSA bacteraemia mandatory from April 2001 (Department of Health

2003a).

Public Health England (PHE) has managed the mandatory surveillance on behalf of the

DHSC since the inception of the surveillance. The surveillance initially captured aggregate

counts of bacteraemia due to S. aureus and the number of those that were MRSA. The

results were reported every six months.

The frequency of data collection was increased to every quarter in 2004 and then monthly

in 2005. Enhanced surveillance of MRSA bacteraemia was introduced in October 2005,

allowing reporting of individual cases, rather than aggregated counts for a time period.

This had the advantage of providing information about the date of onset of bacteraemia,

relative to the date of admission and the department or specialty in which the patient was

being treated (Department of Health 2005).

In 2011, the surveillance was further expanded to include enhanced surveillance of MSSA

bacteraemia which had not shown the same decline in incidence that MRSA had.

Between 2013 and 2014, the outcome of a PIR could only assign a case to either a clinical

commissioning group (CCG) or an NHS acute trust. However, it was acknowledged that

this did not sufficiently recognise the complexity of some MRSA cases and from 1 April

2014, cases could be assigned to a third party. Third party cases include patients who may

be resident in England but have received care from some third party (i.e. neither the

reporting organisation nor the commissioning CCG), cases in patients not resident in

England or intractable cases (NHS England 2014b). The PIR process was halted in April

2018 when it became a local-only process (NHSI 2018).

Current surveillance of MRSA and MSSA bacteraemia allows reporting of cases through a

web-based data capture system (DCS) which provides the means to capture clinical

information on the patient and the infection, the likely source of infection and previous



67

healthcare interactions. The DCS also provides dynamic, on-demand reporting to acute

trusts, CCGs and other organisations allowing those involved in the care of patients to

investigate trends at a local level.

Mandatory surveillance of C. difficile infection

Voluntary surveillance of CDI by microbiology laboratories identified a steady increase in

the number of reports between 1990 and 2001. From 2002, this increase accelerated

rapidly (Department of Health 2007). In 2004, quarterly surveillance of CDI in patients

aged 65 years or above was made mandatory (Department of Health and Health

Protection Agency, 2005). This involved reporting aggregate numbers of cases to PHE on

the behalf of the DHSC. From 2007, the surveillance was expanded to include all patients

two or more years old and was extended to enhanced surveillance to capture patient-level

information (Department of Health 2018). Since 2007, rates of CDI have declined

dramatically.

In April 2017, prior healthcare exposure questions were introduced to the CDI mandatory

surveillance programme, to determine onset status of cases. This involved further

classification of cases in to the following onset statuses, hospital-onset healthcare

associated, community-onset healthcare associated, community-onset indeterminate

associated and community-onset community associated. Thus allowing the CDI

surveillance to be more comparable with international definitions.

Mandatory surveillance of Gram-negative bacteraemia

E. coli bacteraemia

Since the mid-2000s onwards, E. coli has been the most common pathogen causing

bacteraemia in England and has seen year-on-year increases. Given this sustained

increasing trend in the number of E. coli bacteraemia reports made through the voluntary

service, the DoH made reporting of E. coli bacteraemia mandatory in June 2011

(Department of Health 2011).

Klebsiella and P. aeruginosa bacteraemia

From April 2017, it became mandatory for acute trusts to report bacteraemias caused by

any species of Klebsiella bacteria and P. aeruginosa. This was introduced to support the



68

UK Government’s ambition to reduce Healthcare-associated Gram-negative bacteraemias

by 50% by 2023/24.

A note on terminology

In financial year 2018/19, mandatory surveillance stopped using the term Trust-

apportioned and started using the terms hospital-onset and community-onset instead. This

change was introduced due to the need to increase awareness of cases that occur in the

community. The algorithm for the separation of cases into hospital-onset/trust-apportioned

and those that are not has not changed. Clostridium difficile taxonomy classification has

been changed to Clostridiodes difficile.

Use of mandatory surveillance statistics

The data presented in this commentary, and in the accompanying data files and

infographics serve several purposes. First, they provide information to clinicians in trusts

about rates of bacteraemia and CDI in their organisation, helping to improve care and

infection control at their trust. Second, they provide information on the epidemiology of

these infections to clinicians, healthcare researchers and other interested parties,

identifying the likely sources of infection. Third, the information at CCG level allows

commissioners of care to understand healthcare-associated infection rates in their

community. Fourth, the national picture provides information to the DHSC, NHS England

and NHS Improvement regarding the infection rates across the country, and how these are

changing over time, while also providing information about where new interventions could

be targeted. Fifth, they are utilised by NHS Choices to assist in providing information to the

general public about healthcare-associated infection rates in their area and in facilities

where they might receive care.

Further information on data purpose, relevance and associated user-need can be found in

the Mandatory Health Care Associated Infection Surveillance Data Quality Statement.

Data included in the 2018/19 Annual Epidemiological Commentary (AEC)

Counts and rates of MRSA, MSSA, Gram-negative bacteraemias and CDI included in this

report are those with dates of specimens found to be positive within the period 1 April 2007

to 31 March 2019. This report includes data, extracted from the Healthcare Associated

Infections (HCAI) DCS on 17 April 2019, from 148 NHS acute trusts, 196 clinical

commissioning groups (CCGs), 14 specialised commissioning hubs and mapped to 14

https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/514147/Mandatory_HCAI_surveillance_data_quality_statement.pdf

https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/514147/Mandatory_HCAI_surveillance_data_quality_statement.pdf



69

NHS local offices. Data is published in line with organisational arrangements on the HCAI

DCS as of 31 March 2019. Data by acute trust and CCG is presented on an annual and

quarterly basis. Epidemiological commentaries are presented on an annual basis. Data

tables included in the Annual Epidemiological Commentary can also be found in

OpenDocument Spreadsheets (.ods) format on the Annual Epidemiological Commentary

web page.

This is the sixth annual publication to include MRSA bacteraemia data by PIR assignment

- FY 2013/14 to FY 2017/18. Since the PIR process became a local process at the start of

FY 2018/19, future reports will not contain the PIR data.

This publication forms part of the range of National Statistics outputs routinely published

by PHE. Epidemiological analyses included in this report are on an annual (financial year)

basis. Further epidemiological analyses by quarter can be found in our quarterly

epidemiological commentaries.

Data is also reported monthly for MRSA, MSSA, E. coli, Klebsiella spp., P. aeruginosa

bacteraemia and CDI.

We are always striving to ensure that routine outputs meet user need as much as possible.

If you have any suggestions for changes and/or additions please email

[email protected]. Hyperlinks are highlighted in red.

E. coli bacteraemia

Table 1: Financial year counts and rates of E. coli bacteraemia aggregated cases and by

onset status (2012/13 to 2018/19).

Klebsiella spp. bacteraemia

Table 2: Financial year counts and rates of Klebsiella spp. bacteraemia aggregated cases

and by onset status (2017/18 to 2018/19).

P. aeruginosa bacteraemia

Table 3: Financial year counts and rates of P. aeruginosa bacteraemia aggregated cases

and by onset status (2017/18 to 2018/19).

https://www.gov.uk/government/statistics/mrsa-mssa-and-e-coli-bacteraemia-and-c-difficile-infection-annual-epidemiological-commentary

https://www.gov.uk/government/statistics/mrsa-mssa-and-e-coli-bacteraemia-and-c-difficile-infection-quarterly-epidemiological-commentary

https://www.gov.uk/government/statistics/mrsa-mssa-and-e-coli-bacteraemia-and-c-difficile-infection-quarterly-epidemiological-commentary

https://www.gov.uk/government/collections/staphylococcus-aureus-guidance-data-and-analysis

https://www.gov.uk/government/collections/staphylococcus-aureus-guidance-data-and-analysis

https://www.gov.uk/government/collections/escherichia-coli-e-coli-guidance-data-and-analysis

https://www.gov.uk/guidance/klebsiella-species#epidemiology

https://www.gov.uk/government/collections/pseudomonas-aeruginosa-guidance-data-and-analysis#epidemiology

https://www.gov.uk/government/collections/clostridium-difficile-guidance-data-and-analysis

mailto:[email protected]



70

MRSA bacteraemia

Table 4: Financial year counts and rates of MRSA bacteraemia aggregated cases

(2007/08 to 2018/19) and by onset status (2008/09 to 2018/19).

MSSA bacteraemia

Table 5: Financial year counts and rates of MSSA bacteraemia aggregated cases

(2011/12 to 2018/19) and by onset status (2011/12 to 2018/19).

C. difficile infections

Table 6: Financial year counts and rates of C. difficile infections bacteraemia aggregated

cases, by onset status (2007/08 to 2018/19), and by prior healthcare exposure (2017/18 to

2018/19).

Commentary

This document contains national and regional level (NHS England local office)

epidemiological commentaries for Gram-negative bacteraemias, MRSA and MSSA

bacteraemias and C. difficile infections. Mandatory surveillance data series included in this

report start from FY 2007/08 or the earliest full quarter of data collection.

For local office analyses presented in this report, CCGs and their attributed cases are

linked to the local offices of which they are part.1

However, CCGs only came into existence on 1 April 2013. In 2015, NHS regions were

reorganised from nine regions and 27 area teams into four regions and 14 local offices.

Analyses looking at time trends use retrospective attribution of cases to CCGs and local

offices. These may become less accurate the older the data is and; therefore, these have

only been performed back to FY 2009/10 reports. The temporal data before 2013/14

contained in this report with regards to CCGs and local offices has only been provided as

an indication of the trend over time for a given CCG/local office and thus, should be

treated with caution.

______________________ 1 Local offices can also be mapped via NHS acute trusts, based upon the local offices within which an NHS trust is

located, which is how the local offices included in tables 1-6 (to which this document is a supplementary commentary)

are derived.



71

Alternative presentations of the annual data

Data included in this report is also available on https://fingertips.phe.org.uk/ ; this is a user-

friendly application that enables access to local data. It is ideal for both healthcare

professional and the general public alike. Fingertips enables access to these data in a

succinct format. Much of the mandatory surveillance data is available in graphical format,

facilitating easy understanding of key trends and geographical differences.

Please note that there is a one month delay between the publication of our statistics on

gov.uk and the publication of the same data on fingertips. For example, data published on

gov.uk at the start of April 2019 would be available on Fingertips in May 2019.

https://fingertips.phe.org.uk/



72

Glossary

Average: Scientifically speaking, this is a measure of location. It is a way of describing

data and helps to distribute any inequalities in the data across the whole series. There are

three main mathematical measures which can be used to calculate an “average” value; the

mean, mode and median. Each of these methods has their own strengths and

weaknesses.

Bacteraemia: The presence of bacteria in blood

Bias: Is the systematic deviation of either results and/or inferences from the real situation.

Confidence interval (CI): Confidence intervals indicate the likely range in which an

estimated parameter (such as a mean or rate) is likely to fall. For most scientific studies, it

is impractical or impossible to measure every single member of a population and therefore

the true population mean cannot be determined. Instead, a representative sample is taken

and the sample mean is used as an estimate of the population mean. Although the sample

is intended to be representative, a different sample from the same population may provide

a different result simply by chance. A confidence interval, over unlimited repetitions of the

sample, should contain the true value of a parameter (such as the true population mean)

no less than its confidence interval. It is usual to calculate the 95% confidence interval.

That means that if we were to draw several independent, random samples from the same

population and calculate 95% confidence intervals from each of them, then 95% of such

confidence intervals would contain the true population mean. If we took 20 samples from

the same population and calculated 95% confidence intervals then 19 of 20 (95%) of these

95% confidence intervals would contain the true population meanwhile 1 of 20 (5%) will

not.

Denominator: The lower portion of a rate or ratio. This should reflect the population at risk

of developing a disease.

Epidemiology: Study of the occurrence and distribution of events (mostly health-related)

in a population.

Gram-negative: Class of bacteria that do not retain crystal violet stain as used as part of a

differential staining technique (called the Gram stain). The Gram stain is used as a way of



73

identifying bacteria and the difference in staining results are due to differences in the

bacterial cell wall, which has important implications for antimicrobial usage.

Incidence and incidence rate: New cases of a disease occurring in a study population.

An incidence rate is then the number of new cases that occur in a defined population in a

defined period of time.

NHS Local Office: An administrative unit of the NHS. NHS England has four

administrative regions; North of England, Midlands and East of England, London and

South of England. Below these four regions are 13 administrative geographies referred to

as Local offices.

Mean: The arithmetic mean is often what people think of when they say “average value”.

The mean is calculated by summing all of the values in a series (𝑎1 + 𝑎1 + ⋯ + 𝑎𝑛) and

then dividing by the number of values included in the series (𝑛). Mathematically, this is

described by the following formula:

mean =𝑎1 + 𝑎1 + ⋯ + 𝑎𝑛

𝑛

A real-world example would be if you wanted to calculate the mean amount spent on food

shopping over a four-week period (ie the average amount per week) having spent £51 in

week one, £59 in week two, £67 in week three and £52 in week four:

mean cost of food per week =£51 + £59 + £67 + £52

4= £57.25

Median: The median of a series of numbers is the mid-point of that series. This provides a

measure of an average value that is not overly affected by a few extreme values. The

median of the following set of numbers [1, 2, 3] is 2, while the median of the set of

numbers [1, 1, 1, 2, 10, 15, 16, 20, 100, 105, 110] is 15. To calculate the median value,

the set of numbers needs to be arranged in order of magnitude, the median is the number

that is exactly in the middle. If there is an even number of values in a set, then the median

value is the arithmetic mean of the two central values.

Mode: Is the most frequent value in a set of data (numbers or text values), for example, in

the following set of numbers [1, 1, 1, 2, 10, 15, 16, 20, 100, 105, 110] the mode is 1 as it

was included in the set three times, while the other numbers were only included once.



74

Rate ratio: Is the ratio between two rates. For example, if the rate of MRSA bacteraemia

was 2 per 100,000 population in a year among men, and 4 per 100,000 population in a

year among women, the rate ratio would be 2.0. The rate would be two times higher

among women than men.

Secular trends: Changes over long periods of time.

Methods

Inclusion criteria for reporting to the surveillance system

MRSA bacteraemia

The following positive blood cultures must be reported to PHE, for the mandatory MRSA

surveillance: all cases of bacteraemia caused by S. aureus resistant to meticillin, oxacillin,

cefoxitin or flucloxacillin.

MSSA bacteraemia

The following positive blood cultures must be reported to PHE, for the mandatory MSSA

surveillance: all cases of bacteraemia caused by S. aureus which are susceptible to

meticillin, oxacillin, cefoxitin, or flucloxacillin ie not subject to MRSA reporting.

E. coli bacteraemia

The following E. coli positive blood cultures must be reported to PHE: all laboratory

confirmed cases of E. coli bacteraemia.

C. difficile infection

Any of the following defines a C. difficile infection in patients aged 2 years and above and

must be reported to the PHE:

• diarrhoea stools (Bristol Stool types 5-7) where the specimen is C. Difficile toxin

positive1

• toxic megacolon or ileostomy where the specimen is C. difficile toxin positive

1 DH/APRHAI have released guidance which incorporates C. difficile testing recommendations:

http://www.dh.gov.uk/prod_consum_dh/groups/dh_digitalassets/@dh/@en/documents/digitalasset/dh_133016.pdf

http://www.dh.gov.uk/prod_consum_dh/groups/dh_digitalassets/@dh/@en/documents/digitalasset/dh_133016.pdf



75

• pseudomembranous colitis revealed by lower gastro-intestinal endoscopy or Computed

Tomography

• colonic histopathology characteristic of C. difficile infection (with or without diarrhoea or

toxin detection) on a specimen obtained during endoscopy or colectomy

• faecal specimens collected post-mortem where the specimen is C. difficile toxin

positive or tissue specimens collected post-mortem where pseudomembranous colitis

is revealed or colonic histopathology is characteristic of C. difficile infection

Methods of reporting data on the HCAI Data Capture System (DCS)

The HCAI DCS is a web portal designed by PHE to facilitate the collection of the enhanced

data set.

Trusts using the website have access to all the data they have entered, which enables

them to assess their burden of these HCAIs. This can be compared to a regional and

national aggregate also available to trusts from the website. Clinical Commissioning

Groups (CCGs), Local Authorities, NHS Local Offices, and Directors of Public Health

(DPHs) are also able to register users, allowing them to access data specific to their

patients.

The dataset to be collected is described in the mandatory HCAI surveillance protocol

available on the DCS(pdf) and in the case capture user guide available on the same site

here(pdf) Case unlocks can be requested by reporting organisations using the process

described in the Unlock Requests User Guide. Revisions to data are covered by a data

specific revisions and correction policy(pdf).

An R package for working with data downloaded from the DCS can be found on github.

Deadline for entering data

All cases reported by the NHS with specimen dates during the previous month must be

entered onto the website by the 15 of the following month. The previous month’s data must

then be signed off by the trust’s Chief Executive Officer (CEO) by the 15th of every month.

For example, data concerning specimens collected in October must be entered and signed

off by 15 November.

https://hcaidcs.phe.org.uk/ContentManagement/LinksAndAnnouncements/HCAIDCS_Mandatory_Surveillance_Protocol_v4.1.pdf

https://hcaidcs.phe.org.uk/ContentManagement/LinksAndAnnouncements/HCAIDCS_Case_Capture_UserGuide_V2.0.pdf

https://github.com/PublicHealthEngland/hcaidcs



76

CCG attribution process

All cases of bacteraemia and C. difficile infection are attributed to a CCG, regardless of

their trust apportioning status or PIR assignment.

PHE’s HCAI DCS does not currently request NHS organisations to record patient CCG

details for any of bacteraemia or C. difficile infection cases. To obtain this data an extract,

comprising patient NHS number and date of birth are submitted to NHS Digital, via

Demographics Batch Services (DBS), on a daily basis to identify patient GP registration

details and patient residential postcode.

Overview of CCG attribution

The CCG for each case is attributed, in the following order:

• if patient’s GP practice code is available (and is based in England), the case will be

attributed to the CCG at which the patient’s GP is listed

• if the patient’s GP practice code is unavailable but the patient is known to reside in

England, the case is attributed to the CCG catchment area in which the patient resides

• if both the patient’s GP practice code and patient post code are unavailable or if a

patient has been identified as residing outside England, then the case is attributed to a

CCG based upon the postcode of the HQ of the acute trust that reported the case

Note that the retrospective attribution of cases to a CCG may become less accurate the

older the data are. Therefore, the data contained in this report for time periods prior to

2013/14 should be treated with caution and only used as an indication of the trend over

time for a given CCG.

Algorithms for apportioning cases

Please note that the algorithm applied for the apportioning of bacteraemia versus C.

difficile infection uses a different number of days between specimen collection and

admission to apportion cases; the principle is the same however. All cases of bacteraemia

and C. difficile infection are either trust-apportioned or non-trust-apportioned based on the

algorithms below (see also Appendix Figure A1). Previously, E. coli bacteraemia were not

trust-apportioned, however this changed in 2017 and cases were retrospectively

apportioned.



77

It is not possible for PHE to change the apportionment of a case, as apportionment is

based on the data entered by the acute trust and the algorithm is applied to the entire

dataset not on a case by case basis; a case may only change from one category to

another if the relevant case details are incorrect and require amendment by the trust.

In addition to apportioning, all cases are also attributed to a CCG (see above). Thus, all

trust-apportioned and non-trust-apportioned cases will be attributed to a CCG. The

apportioning algorithm changed slightly with the launch of the new DCS. Prior to the

launch on 26/10/2015, there was no category for ‘Unknown’ patient location; the field was

simply left blank. An ‘Unknown’ patient location was introduced with the launch and new

cases from patients whose location was given as ‘Unknown’ at time of specimen were

trust-apportioned if the met the other criteria for trust-apportioned cases.

Bacteraemia

Hospital-onset:

Any NHS patient specimens taken on the third day of admission onwards (eg day 3 when

day 1 equals day of admission) at an acute trust (including cases with unspecified

specimen location) for Inpatients, Day-patients, Emergency Assessment, or unspecified

patient category.

Records with a missing admission date (where the specimen location is acute trust or

missing and the patient category is Inpatient, Day-patient, Emergency Assessment, or

unspecified) are also included.

Community-onset:

Any NHS patient specimens not apportioned to the above. This will typically include the

following groups: * any acute trust specimens taken on either the day of admission or the

subsequent day (eg days 1 or 2, where day 1 equals day of admission) * any specimens

from patients attending an acute trust who are not Inpatients, Day patients or under

Emergency Assessment (ie non admitted patients) * any specimens from patients

attending an identifiable healthcare location except an acute trust. This will typically

include GP, nursing home, non-acute NHS hospital and private patients



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C. difficile

Hospital-onset:

Any NHS patient specimens taken on the third day of admission onwards (e.g. day 3 when

day 1 equals day of admission) at an acute trust (including cases with unspecified

specimen location) for Inpatients, Day-patients, Emergency Assessment, or unspecified

patient category. Records with a missing admission date (where the specimen location is

acute trust or missing and the patient category is Inpatient, Day-patient, Emergency

Assessment, or unspecified) are also included.

Community-onset:

Any NHS patient specimens not apportioned to the above. This will typically include the

following groups:

• any acute trust specimens taken on either the day of admission or the subsequent

day (e.g. days 1, 2 where day 1 equals day of admission)

• any specimens from patients attending an acute trust who are not Inpatient, Day-

patient or under Emergency Assessment (e.g. non-admitted patients)

• any specimens from patients attending an identifiable healthcare location except an

acute trust. This will typically include GP, nursing home, non-acute NHS hospital

and private patients.

Assignment of MRSA cases through the Post Infection Review

All NHS organisations reporting positive cases of MRSA bacteraemia from the 1 April

2013, were required to complete a Post Infection Review (PIR) until 1 April 2018.

A PIR was undertaken on all MRSA bacteraemias with the purpose of identifying how a

case occurred, to identify actions which will prevent a reoccurrence and to identify the

organisation best placed to ensure improvements are made (this is known as “assigning” a

case to an organisation).

Between 01 April 2013 and 31 March 2014 this was limited to either the NHS acute trust

who reported the case or the Clinical Commissioning Group with responsibility for

commissioning care for the patient; however, on 1 April 2014 an additional category was

included in the PIR process allowing for assignment to a Third Party. This provision was

made to acknowledge the increasingly complex nature of MRSA bacteraemias being

reported.

https://www.england.nhs.uk/patientsafety/wp-content/uploads/sites/32/2014/02/post-inf-guidance2.pdf



79

Example of Third Party Assignment to a “Third Party” occurred through the arbitration

process for MRSA bacteraemias and has been available for any cases with an MRSA

positive blood culture post 1st April 2014. This category was designed to capture instances

where the MRSA case could not legitimately be assigned to either the trust or the CCG.

Therefore, for the purposes of the published data on MRSA cases, these Third-Party

cases were not be assigned to either the trust or the CCG. An example of “Third Party”

assignment is below.

Third Party Provider (England) Patient “A”

Background

A CCG in Berkshire commissions specialist services for Patient “A” from a London

specialist provider. After a few days, the patient returns to Berkshire Trust and is found to

test positive for MRSA bacteraemia. Since the sample was taken on the day of admission,

the Post Infection Review is led by the CCG. During the Post Infection Review process it

has been established that the patient had received no clinical care in Berkshire in the

immediate period prior to admission and that it is most likely that the bacteraemia

developed in trust A. In view of these facts, the CCG feels that the case should not be

assigned to them on the Data Capture System.

The matter is, therefore, referred to the arbitration panel led by the Regional Medical

Director and the Regional Director of Nursing.

Outcome

The arbitration panel agrees with the CCG and recommends that the case is assigned on

the Data Capture System to a Third Party. In the interests of patient safety, the CCG in

Berkshire (which commissioned the service) should inform the London provider to support

clinical learning and minimise the risk of a reoccurrence.

Further examples can be found in the PIR toolkit.

Prior trust exposure algorithm

In April 2017, the mandatory surveillance captured information on prior trust exposure, and

introduced specific prior healthcare categories, detailed below:

https://improvement.nhs.uk/uploads/documents/post-infection-guidance.pdf



80

Hospital-onset, healthcare associated (HOHA) - Cases where the date of onset is two

or more days after the date of admission, where date of admission is day zero and the

patient was admitted to an NHS acute trust at time of specimen.

Community-onset, healthcare associated (COHA) - Cases which are not HOHA but

have previously been discharged from the reporting organisation within the 28 days prior

to specimen date.

Community-onset, indeterminate association (COIA) - Cases which are not HOHA but

have previously been discharged from the reporting organisation but have been

discharged from the reporting organization between 28 and 84 days prior to specimen

date.

Community-onset, community associated (COCA) - Cases which are not HOHA and

have not previously been discharged from the reporting organisation within the past 84

days.

Analysis of data

Time to onset calculations

To describe time to onset of an episode (bacteraemia or C. difficile) among inpatients, the

number of days between the date of admission to an NHS acute trust and the date of

positive specimen were calculated. This was only performed for patients who were admitted

to an acute trust (defined as either an inpatient, day patient or emergency assessment, ie

patients who should have an admission date to an acute trust) and for those whose

specimen was taken on or after the date of admission also at an NHS acute trust.

The number of days between the date of admission and the date of specimen can then be

described in two different ways; by grouping the number of days into meaningful

categories or by describing the “average”. Both have been provided in this report. As

mentioned in the glossary, there are three metrics which can be used to describe the

average value; the mean, median and mode. In this report, the median was used,

providing us with the central value of the number of days between date of admission and

date of positive specimen. The median was selected rather than the mean, because the

latter can provide spurious ‘average’ values if the data are skewed, ie if a few inpatients

had very long hospital stays before they had a C. difficile infection, then the mean value



81

would become much greater as it would be largely influenced by the value of the numbers

in the range.

Denominator data

Trust denominators NHS acute trust-level population data does not currently exist in

England as NHS acute trusts do not treat patients within defined geographical boundaries.

Therefore, a suitable proxy for population is required in order to calculate trust

apportioned/assigned rates. The occupied overnight beds (from the national KH03

dataset) provides the daily average overnight bed occupation for a specific time period; full

financial years for 2007/08 to 2009/10 and by quarter for financial years 2010/11 to

2017=8/19. This dataset is an open access return published by NHS England and

provides a measure of clinical activity in each trust, which is used as a proxy measure of

the patient population.

KH03 data can be found at NHS England’s website here.

Where data for trusts were missing, data for the same quarter in the preceding year were

used. These included the following trusts and periods:

Moorfields Eye Hospital NHS Foundation Trust (RP6) – KH03 data was missing for FY 2007/08. Last recorded data from 2006/07 were used as a proxy.

• Moorfields Eye Hospital NHS Foundation Trust (RP6) – KH03 data was missing for FY

2007/08. Last recorded data from 2006/07 were used as a proxy.

• The Rotherham NHS Foundation Trust (RFR) – KH03 data were missing for FY

2009/10, Q1 2010/11 to Q1 of 2011/12. Last recorded data from 2008/09 were used

as a proxy

• Sheffield Teaching Hospitals NHS Foundation Trust (RHQ) – KH03 data were missing

for Q1 2010/11 to Q1 2011/12. Data from 2009/10 were used as a proxy

• The Princess Alexandra Hospital NHS Trust (RQW) – Data were missing from Q1

2014/15. Data from Q1 2013/14 were used as a proxy. Data were missing from Q

2014/15 and Q3 2013/14 data were used as a proxy

KH03 data are published 6-8 weeks after the end of the relevant period. When this report

was produced, the final quarter of 2018/19 (i.e. January-March 2019) had not yet been

published. The KH03 data used in both the Annual Epidemiological Commentary and the

Annual Tables for 2018/19 has had this quarter replaced with the same quarter from the

previous financial year (i.e. KH03 data for 2018/19 includes data for April-June 2018, July-

http://www.england.nhs.uk/statistics/statistical-work-areas/bed-availability-and-occupancy/bed-data-overnight/



82

September 2018, October-December 2018 and January-March 2018 in place of January-

March 2019). This is in line with our standard approach. In Annual Epidemiological

Commentaries published prior to 7 July 2016, April-June 2014 to October-December 2014

quarterly KH03 figures for one acute trust (RWD) had a percentage change of more than

20% compared to the previous quarter and the same quarter in the previous year. As a

result it was replaced with the KH03 data of the same quarter in the previous year (April-

June 2013 to October-December 2013).

However, PHE has reviewed its policy for processing KH03 data. All data irregularities

identified are now flagged with colleagues at NHS England (data owners of the KH03

dataset). Until we receive confirmation that any identified change in the occupied overnight

bed-days for an acute trust is anomalous, PHE will use the data as published in the KH03

dataset. This affects all reports published since 1 December 2015. In order for the KH03

data used to calculate rates included in this report to be consistent over the full-time

period, previously amended KH03 data for trust RWD for FY 2014/2015 has been altered

to reflect that published in the KH03 dataset. Please note that this could lead to slight

differences in trust-apportioned/assigned rates when compared with publications prior to 1

December 2015.

Other affected organisations and time periods include:

• Shrewsbury and Telford Hospital NHS Trust (RXW) Financial year 2009/10

• Imperial College Healthcare NHS Trust (RYJ) April-June 2012

Rate calculations

CCG rates

All cases are attributed to a CCG (see above) and using this data we calculate rates per

100,000 population for each CCG. Data at a CCG level can be scaled up to both NHS

Commissioning Board Local Office and a national level; therefore, to calculate rates for

CCGs, local offices and nationally the following equation is applied:

Rate, per 100,000 population = (𝑛 new cases attributed to CCG

Financial year population) × 100,000

We use the ONS mid-year population estimated data for relevant time periods, adjusted as

described above. For instance, for financial year 2010/11 mandatory surveillance data we



83

have used mid-year 2010/11 population estimates. Rates for CCG assigned MRSA cases

for 2013/14 onwards have also been calculated using the following equation:

Rate, per 100,000 population = (𝑛 new cases assigned to CCG

Financial year population) × 100,000

Trust rates

We calculate acute trust rates using trust-apportioned (or trust-assigned cases). The total

occupied bed days (KH03) data are used as an indicator of the total activity in each trust

during the relevant time period(s). Since 2010/11 KH03 have been published quarterly,

prior to this they were published on a financial year basis. The average daily overnight bed

occupancy for all acute trusts has been multiplied by the number of days in the relevant

time period. The relevant rate per 100,000 bed days was calculated as follows:

Rate, per 100,000 bed days = (𝑛 new cases reported by trust

Average daily occupancy × 𝑛 days in period) × 100,000

Prior to trust apportioning, all-reports rates were calculated per acute trust. Therefore, for

historical purposes to retain the time series, we also calculate an all-reports rate per acute

trust. “All reported cases” refers to all bacteraemias or C. difficile infections that were

detected by the acute trust that processed the specimen. It is important to note that this

does not necessarily imply that the infection was acquired there.

Healthcare associated infections in Wales, Scotland and Northern Ireland

Surveillance for C. difficile infections and MRSA and MSSA bacteraemias is also

performed in Wales, Scotland and Northern Ireland. Links to the relevant web pages are

as follows:

Wales: http://www.wales.nhs.uk/sites3/page.cfm?orgid=457&pid=25224

Northern Ireland: http://www.publichealth.hscni.net/directorate-public-health/health-

protection/healthcare-associated-infections-antimicrobial-resistanc

Scotland: http://www.hps.scot.nhs.uk/haiic/news/details?Id=23489

Please note that there are several differences between the English mandatory surveillance

systems and the systems run by the devolved administration, including case

definitions/protocols for diagnosing the infections, definitions re: inpatient episode vs. trust

apportioned/assigned episodes and the way in which data are presented. Therefore, the

http://www.wales.nhs.uk/sites3/page.cfm?orgid=457&pid=25224

http://www.publichealth.hscni.net/directorate-public-health/health-protection/healthcare-associated-infections-antimicrobial-resistanc

http://www.publichealth.hscni.net/directorate-public-health/health-protection/healthcare-associated-infections-antimicrobial-resistanc



84

data provided in the published reports from Public Health Agency Northern Ireland, Public

Health Wales and Health protection Scotland are not directly comparable with those data

published by Public Health England, found in this report and annual tables.



85

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