Post on 18-Dec-2015
Syphilis and HIV screening initiativesin North Carolina jails
Lynne A. Sampson PhD, MPH
HIV/STD UpdateSeptember 25, 2008
Syphilis — Reported cases by stage of infection: United States, 1941–2006
Cases (in thousands)
P&SEarly LatentTotal Syphilis
0
120
240
360
480
600
1941 46 51 56 61 66 71 76 81 86 91 96 2001 06
Data from CDC STD Report, 2006
Primary and secondary syphilis — Rates: Total and by sex: United States, 1987–2006 and the Healthy People 2010 target
Note: The Healthy People 2010 target for P&S syphilis is 0.2 case per 100,000 population.
Rate (per 100,000 population)
MaleFemaleTotal2010 Target
0
5
10
15
20
25
1987 89 91 93 95 97 99 2001 03 05
Syphilis and HIV Epidemiology
• Mode of transmission
• Synergy
• Subpopulations at risk:– Trade sex for drugs or money– Use cocaine– Use injection drugs– History of incarceration
Syphilis, HIV and Incarceration
• High prevalence in populations screened in US jails and prisons:– Syphilis
• Women: 1 – 22 % • Men: <1 – 6 %
– HIV• Women: 1 – 26 % • Men: 1 – 16 %
• Associated with behaviors that are associated with incarceration:– Trading sex for drugs or money– Use of illegal drugs, especially cocaine (syphilis) and injection
drug use (HIV)
Why Screen in Jail?
• Risk profile of current cases
• Population outside of health care system
• Revolving population (50% bond out in less than 2 days)
• Available for education and treatment
Characteristics of Jails & Prisons
Maintain health of inmate population
Form of community screening
Goal of STD screening programs
1 year to life< 24 hours to 1 yearDuration of stay
Persons convicted of crimes and sentenced to 1 year
Persons charged with crimes & awaiting trial
Persons convicted of crimes with short sentences (< 1 year)
Inmate Population
State or FederalLocal
(County or City)
Level of oversight
PrisonJail
HIV and Early Syphilis (PSEL) rates in NC
0
5
10
15
20
25
30
35
40
2000 2001 2002 2003 2004 2005 2006 2007
Ra
te /
10
0,0
00
po
p
PSEL-men
PSEL-women
HIV-men
HIV-women
CDC National Plan to Eliminate Syphilis
• 1998 – CDC identified 28 US Counties that reported over 50% of ALL P&S Syphilis Cases in US
• 5 of these Counties are in NC (Forsyth, Guilford, Mecklenburg, Robeson, Wake)
• Durham added to SEP effort by State of NC
• All 6 Targeted for “Elimination”– US P&S cases <1000 and 90% US Counties reporting no new
cases by 2005– Not reached (in 2004 US P&S cases n=7,980)
NC Reported Early Syphilis (PSEL) Cases
0200400600800
10001200140016001800
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
SEP Counties All Other
PSEL Rates in SEP Counties
0
20
40
60
80
100
120
140
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Durham
Forsyth
Guilford
Mecklenburg
Robeson
Wake
STATE
NC Syphilis Elimination Jail Screening Program
• Screen for syphils (n=7 jails) and HIV (n=2 jails)
• Screening staff access inmates in the jail and offer education and screening – Risk questionnaire– Blood sample(s) for testing
• Data linked to surveillance records to determine case status and stage of syphilis infection
Syphilis Analysis
• Study population– Male and female inmates screened for syphilis in 7 NC jails
2002-2005 (n=24,010)
• Outcome– new syphilis case
• Descriptive Analyses– Frequencies, distributions, missing values– Demographic, risk factors, outcomes– Unadjusted OR and 95% CI for each covariate and outcome
Syphilis Analysis
• Modeling– Logistic regression for clustered data to account for multiple
observations for individuals– Separate models for males and females
• Reference Model– Variables with bivariate associations p 0.25– Other variables from literature
• Reduced Model– Backward elimination– Examine area under ROC curves to assess change– Goal is to achieve parsimonious, easy to use model
HIV Analysis
• Study population– M/F inmates screened for syphilis in 2 NC jails 2002-2005– Include only first observation for each individual
• Outcome– HIV infection, new syphilis case, either infection
• Descriptive Analyses– Frequencies, distributions, missing values– Demographic, risk factors, outcomes– Unadjusted OR and 95% CI for each covariate and outcome
HIV Analysis
• Modeling– Multivariable logistic regression
– Single model that includes gender
• Reference Model– Variables with bivariate associations p 0.25
– Other variables from literature
• Reduced Model– Backward elimination
– Examine area under ROC curves to assess change
– Goal is to achieve parsimonious, easy to use model
Summary of Analyses
• Syphilis– Screened women much more likely to have new
syphilis cases– Difficult to predict risk among women– Among men, STD history, race/ethnicity, and age
are associated with new syphilis cases
• HIV– Women and men who have sex with men much
more likely to be infected with HIV– HIV testing history, race/ethnicity, and age are
associated with HIV infection