IH5426_Gutschmidt_J_EPI Final Exam, Concept Map

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share, and use commercially. Text,Epidemiology by Leon Gordis, Saunders,

2014, Amazon Kindle Version.

Epidemiology:"The study of how disease is distributed

in populations and the factors thatinfluence or determine this distribution"(Gordis, 2014)

History of Epidemiology adapted from "Table 2-2, Selected Historical Contributions of Men and Women to Epidemiology: From"Essential Epidemiology" by William A. Olenckno, copyright 2002, Waveland Press, page 16." Photos obtained using "Bing SearchEngine. All photos are covered under the Creative Commons license. Free to modify, share, and use commercially.

John Snow (1813-1858). Used in-person interviews, maps, and

keen observational skills to tie aLondon cholera outbreak to awater pump located on Broad

Street.

Hippocrates (460-377 BCE)was the fist person known tooffer rational explanations for

disease that were notsupernatural in nature. Heconsidered environmental

and other factors in his

analysis.

Ignas Semmelweis (1818-1865) usedepidemiological theory to identify the cause of

childbirth fever

Girolamo Fracastoro (1478 - 1553) was the firstperson known to offer a formal theory of disease

that used the contagion theory of diseasetransmission.

Edward Jenner (1749-1823): Invented a vaccine against small pox

through observational and experimental skills.

William Farr (1807-1883), used statistics to describe

epidemiology problems

John Gaunt (1620-1674), described disease occurrence systematically using Bills of Mortality.

Peter Ludwig Panum (1820-1885) showed thatpeople could acquire immunity to measels through

infection.

Thomas Sydenham (1624-1689), insisted that thenatural history of disease be guided by observationinstead of by theory alone.

Robert Koch (1843-1910), credited, along withPasture for the Germ Theory of Disease.

Established criteria for bacterial disease causation.

Anna Wessels Williams (1863-1954), made aantitoxin against diphtheria by isolating thebacterium.

Joseph Goldberger (1874-1929), showed thatpellagra was caused by a diet deficient in proteinthrough observation and experiment.

James Lind (1716-1794), showed how to

treat and preventscurvy using an

experimentalapproach.

Louis Pasture (1822-1895), demonstrated theveracity of the germ theory of disease and showedthat vaccines could be used to control them.

Florence Nightingale(1820-1910),Improved hygiene atmilitary hospitalsusing mortalitystatistics as ajustification.

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Study Types: Adapted from Epidemiology byLeon Gordis, Saunders, 2014, Amazon

Kindle Version.

Scientific Studies

Randomized Trials: A trial where, from the totalpopulation, a defined population is identified and a

subset of that defined population is studied (Gordis,2014).

Validity

Image

copyright Epidemiology by LeonGordis, Saunders, 2014, Amazon

Kindle Version

Internal: Valid only within study population. #

External: Validity outside of study population # #

Design

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Gordis, Saunders, 2014,Amazon Kindle Version

MethodsRandom Number Table

Computer Selection

Possible Effects

Stratification by age, for instance, may increase validityof results, or by sex?


Gordis, Saunders, 2014,Amazon Kindle Version

Masking (blinding): Hiding from subjects andresearchers who is in the treatment versus control group

to mitigate the placebo effect. (Gordis, 2014)

Crossover: Planned versus unplanned. When patients inthe treatment group cross over to the non-treatment

group and vice versa. (Gordis, 2014)

Non-Compliance: Effects of patients not complying withassigned treatments.

Testing: Do Treatments Differ?

Type I Error #

Type II Error #

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Number of patients needed in each group to establishAlpha and Beta at different confidence intervals. (Thesymbol "/" for this purpose stands for the mathematicaloperator for division.)

One sided Test

Image copyright Epidemiologyby Leon Gordis, Saunders,


Two sided test

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Leon Gordis,Saunders, 2014,

Amazon KindleVersion.

NNT: Number needed to treat [NNT=1/(rateinuntreated)-(rate in treated)]How many patients needed to treat to prevent one

adverse outcome. (Gordis, 2014)

Efficacy: (rate in those who received a placebo)-(rate inthose who received a vaccine)/(Rate in those whoreceived the placebo)Tells of the extent reduction in disease by use off

treatment. (Gordis, 2014)

Alpha = probability of making a Type I error #

Beta = probability of making a type II error #

Image copyrightEpidemiology byLeon Gordis,Saunders, 2014,Amazon KindleVersion

Clinical Trials: Used in theUS to test new drugs(Gordis, 2014)

Phase II: Clinical investigation of 100-300 patients todetermine efficacy of new drug or treatment (Gordis,

2014)

Phase III: Large scale randomized controlled trialsmeant to assess effectiveness relative to safety (Gordis,

2014).

Phase I: Clinical, pharmalogical studies of 20-80 patientsto assess safety of new drug or treatment (Gordis, 2014)

Phase IV: Post marketing surveillance is used todetermine if drug or treatment has any long-term

negative effects after final approval in phase III. PhaseIV is not a randomized study (Gordis, 2014).

Studies without comparisons: Case Study or CaseSeries for example. (Gordis, 2014)

Descriptive Studies:Time, Place, and PersonAdapted from Centers for Disease Control and

Prevention, Principles of Epidemiology in PublicHeath Practice, Third Edition An to AppliedEpidemiology and Bio statistics, Lesson1:

Introduction to Epidemiology, Section 6: DescriptiveEpidemiology, November 2016

Time Secular Trends: Annual cases graphed over a period ofyears (CDC, 2016).

Seasonality: Graphed over weeks or months, or a yearor more to show seasonal characteristics (CDC, 2016)

Two dimensional graph showing number or rate versustime in weeks, days, or months (CDC, 2016)

EPI Curve

Continuousexposure example.

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Singe exposure, commonvehicle outbreak exampleEpi Curve:

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Place

Contain the 5 W's: Who, what, where, when, andwhy/how (CDC, 2016)

Person: Age, Race, Ethnicity, Socio-Econonmic Status.

Study Types

Case-Control Study: Compares diseased to non-diseased. Easier to administer, less expensive, better for

comparing rare diseases. (Gordis, 2014)

Selection bias: If subjects are selected from a singlehospital, for instance, risk factors observed may be

specific to that institution. (Gordis, 2014)

Bias: Incident versus prevalent cases usage: prevalentcases are more abundant but risk factors associatedwith the study of prevalent cases may be moreassociated with living with the disease than from havingcaused it. (Gordis, 2014)

Information bias #

Problems with recall.

Limitation in recall: Can't remember answer to questionduring interview.

Recall bias: Affected subjects recalling a perceivedtriggering event that non-affected subjects forgot aboutbut did happen.

MatchingGroup: Controlling for proportionality of characteristicsbetween cases and controls. (Gordis, 2014)

Individual: Pairing case subjects with similar controlsubjects each of whom has similar characteristics withonly the disease status differentiating them. Matchescase/control pairs. (Gordis, 2014)

Choosing to use multiple controls?

Same?Increases statistical power of the study. (Gordis, 2014) #

Different?: Choose to use over concern that pool ofexposed persons (i.e. a hospital setting) do notrepresent the population and for that reason maychoose to use more controls that differ in terms of traits.(Gordis, 2014)

Use when an association is suspected and moreevidence is needed to suggest an association between a

risk factor and an outcome. (Gordis, 2014)

Ecologic: Looks at and compares data for populationsand not individuals.

Ecologic fallacy: Results for groups cannot necessarilybe transferable to individuals in groups. Cannot drawconclusions about individuals. (Gordis, 2014)

Cohort: Compares exposed population to non-exposed.Either prospective or retrospective. Prospective studiesfollow participants for years and can be very expensiveespecially for comparing rare conditions.(Gordis, 2014

Selection bias: Bias of non-participation or non-response. (Gordis, 2014)

Information bias:bias based on the quality of theinformation obtained and the bias on the part of theperson who assigns diseased or non status based onknown exposure. (Gordis, 2014)

Intervention: Compares the effects of an intervention onsubjects, for instance, the effects of smoking cesassionintervention on pregnant women who smoke. (Gordis,2014)

Cross-SectionalPlace and time interview. Captures a snapshot.

Scientific Studies : Drug Trials, for example. (Gordis,2014)

#

Agents of human disease/conditions:Adapted from Epidemiology by Leon Gordis,Saunders, 2014, Amazon Kindle Version. #

Paracites/Prototzoal infectionsMalaria

Rocky Mountain Spotted Fever

Giardia

Heart Attack/Stroke

Mental IllnessSchitzophrenia

Post-traumatic Stress Disorder

Bipolar Disorder

Depression

Accidents/InjuriesBroken bones

Sprains and strains

Lasserations

Cancer/Tumor

Example: Smoking and lung cancer

Colon Cancer

Uterine Cancer

Prostate Cancer

Bacterial Infections

Typhoid: Typhoid Mary

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E. Coli from contaiminated food.

Legionella

Siphalis: Treponema pallidum

Graham Negative bacillus associated with virulance

Viral InfectionsMarburg

Influenza

Ebola

Hepatitus

Addiction/Substance AbuseHeroine

Nicotine

Alcohol

Cocaine

Genetic and Environmental Factors Genetic

Associated with Leukemia, Down's Syndrome, andAlzheimer's Disease

Human genome project.

Concordance vs. discordance measures in twin studies.

EnvironmentalLikely the cause when observed changes in populationsare over short periods of time like decades.

Occurance Measurments: (Symbol"/" used in the context of anexample equation is intended todenote mathematical division)Adapted form Riccetti-MastersonK,Lopes B, Yeatts KB, Summary ofEpidemiologic Measures. UNCGiddings School of Global PublicHealth 2/14 and Epidemiology byLeon Gordis, Saunders, 2014,Amazon Kindle Version.

Image,

intended as a reference forequations listed in this section andtaken from from Bing Search,Creative Commons License. Freeto modify, share, and usecommercially.

Odds: Ratio of cases and non-cases (Ricchetti et al,2014)

Exposed Odds (EO)

PO: (a+c)/(b+d) or diseased divided by non-diseased;EO: (a+b)/(c+d) or exposed divided by non-exposed

Prevalent Odds (PO)

Denominator does not typically include diseasedsubjects. Only in EO are diseased subjects included in

the denominator.

AKA: Incidence Odds (Ricchetti et al, 2014).

Associated with: Cast-Control Study; Cross SectionalStudy (PO); Cohort Study; Experimental Study; and

Ecologic Study (group level), Associated with: CohortStudies; Experimental Studies; and Ecologic Studies

(group-level), (Ricchetti et al, 2014).

Rate: Proportion of population who developcondition per unit time at risk (Ricchetti et al, 2014) #

(a+c)/(total person-time at risk). Numerator is incidentcases (Ricchetti et al, 2014).

Denominator does not include diseased subjects.

AKA: Incidence Rate or Incidence Density (Ricchetti etal, 2014). #

Associated with: Cohort Studies; Experimental Studies;and Ecologic Studies (group-level), (Ricchetti et al,

2014).

Risk: Proportion of population who, over a specifiedamount of follow-up time develop the heathcondition (Ricchetti et al, 2014).

AKA: Cumulative Incidence (Ricchetti et al, 2014).

(a+c)/(a+b+c+d). Numerator is incident cases.Denominator is total at-risk baseline study population

(Ricchetti et al, 2014).

Denominator does not include diseased subjects(Ricchetti et al, 2014).

Associated with: Cohort Studies; Experimental Studies;and Ecologic Studies (group-level), (Ricchetti et al,

2014).

Prevalence: At a point in time the proportion of apopulation living with a health condition (or with ahistory of the same condition), (Ricchetti et al,2014).

Period Pravalence: How many people have a givendisease at any point during a time period (Gordis, 2014)

Point Prevalence: The prevalence of a disease at aparticular point and time (Gordis, 2014)

Denominator includes diseased subjects: Yes!

(a+c)/(a+b+c+d)

AKA: Prevalence Proportion (Ricchetti et al, 2014).

Associated with: Cross-sectional Study; Cohort Study(baseline/non-outcome variables); Ecologic Study

(group-level), Associated with: Cohort Studies;Experimental Studies; and Ecologic Studies (group-

level), (Ricchetti et al, 2014).


Gordis, Saunders,2014, Amazon Kindle

Version.

Prevalence = Incidence x duration. (Gordis, 2014)

Person Time:When each individual in thedenominator is not followed for the full length of thestudy person time is sometimes used as asurrogate. Person time can be expressed as personyears, days, months, etc. (Gordis, 2014) #



Version.

Terns

Vector: According ot Merriam Webster "an organism(as an insect) that transmits a pathogen from one

organism or source to another <fleas are vectors ofplague>" [ Merriam Webster #

Agent: According to CDC "The agent is the cause of the disease. Whenstudying the epidemiology of most infectious diseases, the agent is a

microbe an organism too small to be seen with the naked eye. Diseasecausing microbes are bacteria, virus, fungi, and protozoa (a type of

parasite). They are what most people call “germs.”" CDC #

Endemic: According to Gordis endemic refers to thepresence of a disease within a geographic area thatis habitual.

Epidemic: According to Gordis an epidemic thepresence of disease in a community or regionclearly in excess of normal expectancy.

According to a current example of an epidemic inthe US is the Heroine epidemic.

CDC

Pandemic: According to Gordis a pandemic is an aworldwide epidemic.

1968 Pandemic of H3N2, according to CDC

1957 pandemic of H2N2, according to CDC

2009 pandemic of H1N1 pandemic, according to CDC

1918 pandemic of H1N1, according to CDC

Immunity: According to Gordis, refers to people in apopulation that are not susceptible for acquiring a

particular disease.

Herd immunity, according to Gordis is the resistancetoward acquiring a particular disease by a group ofpeople, due to immunity, by a large proportion of thatgroup.

Incubation Period: "the interval from the receipt ofinfection to the time of onset of clinical illness."(Gordis, 2014)

Resevoir: According to CDC, "A reservoir of aninfectious agent, such as a virus, is any animal,

person, plant, soil, substance—or combination ofany of these — in which the infectious agent

normally lives. In addition, the infectious agent mustprimarily depend on the reservoir for its survival,and must be able to multiply there. It is from the

reservoir that the infectious substance is transmittedto a human or other susceptible host." .CDC

Image

from Bing.com, Creative Commons License.

Host: According to Merriam Webster "a living animalor plant on or in which a parasite lives."

Merriam

Webster #

Environment: According to Merriam Webster "thecomplex of physical, chemical, and biotic factors (as

climate, soil, and living things) that act upon anorganism or an ecological community and ultimatelydetermine its form and survival" Merriam Webster #

Public Health: According to , "Public health isthe science of protecting and improving the healthof families and communities through promotion ofhealthy lifestyles, research for disease and injuryprevention and detection and control of infectiousdiseases."

CDC

Etiology: Cause of disease. (Gordis, 2014)

Passive and active surveillance: Passivesurveillance uses available data, active surveillanceuses program staff to collect data. (Gordis, 2014)

Ratio, according to :"Thequantitative relation between two amounts showing

the number of times one value contains or iscontained within the other:

‘the ratio of men's jobs to women's is 8 to 1"’

Oxford Dictionary on-line

Proportion according to : "Therelationship of one thing to another in terms of quantity,

size, or number; ratio:‘the proportion of examination to coursework’

‘the bleach can be diluted with water in the proportionone part bleach to ten parts water’"


Rate according to : "Ameasure, quantity, or frequency, typically one

measured against another quantity or measure:‘the island has the lowest crime rate in the world’

‘buying up sites at a rate of one a month’"


Screening Tests: Adapted from Epidemiologyby Leon Gordis, Saunders, 2014, Amazon

Kindle Version #

Specificity # #

Predictive Value


Positive Predictive Value


Dichotomous results

Positive versus negative result

Image copyright Epidemiologyby Leon Gordis, Saunders,2014, Amazon Kindle Version

Tests for pregnancy, HIV status, cancer screening

Continuous variables Establish cut-off levelBllood pressure screening, blood glucose level

screening


Sensitivity #

Prevalence


#

Validity versus Reliability

Image copyrightEpidemiology by LeonGordis, Saunders, 2014,Amazon Kindle Version

Effectivemess? #Natural history of disease?

Primary, Secondary, or Tertiary Intervention?

Outcome measuresImprovement to quality of life in screened individuals

Prevention of or reduction in recurrences.

Rection in complications.

Increase in percent of cases detected earlier

Reduction in case-fatality

Reduction in mortality

Effects of lead time bias on five-year survival?May make screening appear to extend life but onlyactually reduces years of perceived heath with nochange in outcome.

Effects of randomized screening trials versus non-randomized: Randomized is usually better but may bedifficult to carry out or precluded for ethical reasons.

Occurrence of Disease adapted fromEpidemiology by Leon Gordis, Saunders,2014, Amazon Kindle Version.

Where: Geographic distribution is not random, islocalized by time and place in a region - clustering.

(Gordis, 2014)

When: Certain diseases occur periodically:Annually, seasonally, etc. (Gordis, 2014)

Who: Age, sex, and race of human host? (Gordis,2014)

Disease Transmission from Epidemiology byLeon Gordis, Saunders, 2014, Amazon

Kindle Version. Direct.Person to person. (Gordis, 2014

Indirect: Through common vehicle, such ascontaminated water or air. (Gordis, 2014)

Type of organism: Characteristics of organism/rateof growth (Gordis, 2014). Mode of transmission/portal of entry: skin, respiratory

tract, urogenital tract, alimentary tract, arthropod,conjunctiva, etc. (Gordis, 2014)

Individual characteristics: Scratches, injuries,susceptibility (immunity), (Gordis, 2014)

Clinical versus sub-clinical disease

Bing.com search,Creative Commons

License.Clinical disease = signs and symptoms. (Gordis, 2014)

Noncliniccal disease = preclinical or subclinical disease.Either not yet clinically apparent and either destined ornot destined to progress to clinical disease. (Gordis,2014). Peristent disease is a lingering condition thatlasts for years or life. An example is polio myelitis.(Gordis, 2014)Carrier status: Person with disease who does not

develop symptoms. (Gordis, 2014) #

Measures of Morbidity and Mortality adaptedfrom Epidemiology by Leon Gordis,Saunders, 2014, Amazon Kindle Version.For the purposes of this discussion thesymbol "/" represents the mathematicaloperation of division.

Morbidity: Incidence Rate per 1,000 = (No. of newcases of a disease occurring in a population duringa period of time/No. of persons who are at risk ofdeveloping the disease during that period of time) x1,000 (Gordis, 2014)Morbidity - a transition from non-disease to disease.

(Gordis, 2014)

Mortality Rate: Annual mortality rate for all causes(per 1,000 population) = (Total no. of deaths from

all causes in a year/No. of persons in the populationat midyear) x 1,000. (Gordis, 2014)

Case Fatality Percent: (No. of individuals dyingduring a specific period of time after disease

onset/No. of individuals with the specified disease)x 100. (Gordis, 2014) #

Mortality data may be inaccurate due to how deathsare coded on death certificates. (Gordis, 2014)

Mortality rates can be adjusted to a standardpopulation (today the year 2000 census is used inthe US). Applying standardization to mortality rateseliminates population effects on differencesbetween rates. (Gordis, 2014)

Indirect age adjustments are used when ages of subjectpopulation are unknown. Here a standard age

distribution in the standard population is used as ansurrogate of the population of interest. (Gordis, 2014)

Rates indicate the speed of disease progression ina population. Proportions tell us the fraction of the

people who are impacted. (Gordis, 2014)

YPLL: Years of potential life lost: Age at deathsubtracted form perdetermined age at death or

standard age. (Gordis, 2014)

The cohort effect: A potential error that results formcross-sectional reading of data that relates to

different cohorts that age together over time. Whencomparing mortality data could be effected by: 1)

Changes in survivor-ship without changes inincidence; 2) Changes in incidence; 3) Changes in

the age composition of the populations; 4) Acombination of factors. (Gordis, 2014)

Quality of life: impact of disease on individualsbeyond mortality. (Gordis, 2014)

Future burden of disease: Measured in DALY (disabilityadjusted life years) or years of life lost to prematuredeath and years of life lived with disability. (Gordis,

2014)

Outbreak adapted from Epidemiology byLeon Gordis, Saunders, 2014, AmazonKindle Version. #

Cross Tabulation

.Image copyrightEpidemiology by Leon

Gordis, Saunders, 2014,Amazon Kindle Version.

Attack rate: The number of people at risk, in whoma certain illness develops divided by the totalnumber of people at risk. (Gordis, 2014)

Food specific attack rate is based on the number ofpeople who at the food and became ill divided by the

total number of people who at the food. (Gordis, 2014)

Natural History of Disease, Adapted fromEpidemiology by Leon Gordis, Saunders,2014, Amazon Kindle Version.

OutcomeCure

Death

Control

Signs and Symptoms

Clinical Phase #Seeks Medical Treatment

Treatment

Preclinical Phase # #Biological Onset

Pathological Evidence

Expression of outcomes in terms ofCase-Fatality

Person Years

Life Table #


Gordis, Saunders, 2014,Amazon Kindle Version.

Use of life tables assumes no secular (temporal)changes in treatment over calendar time and lack of

knowledge of outcomes due to loss to follow-up(outcomes do not necessarily need to be mortality).

(Gordis, 2014)

Kaplan-Meirer Method

Image copyrightEpidemiology byLeon Gordis,Saunders, 2014,Amazon KindleVersion.

Median Survival Time: Average of survival times.

Relative Survival: Ratio of observed survival to expectedsurvival #

Lead time bias: Bias that results from an earlierdiagnosis that does not affect actual survival andmay rob someone of years of perceived health.Related to early screening tests that do not actuallyincrease survival rates. (Gordis, 2014)



Version.

Stage Migration: Apparent improvements fromearlier diagnosis may be misleading? (Gordis, 2014)

Image copyrightEpidemiology by

Leon Gordis,Saunders, 2014,

Amazon KindleVersion.

Estimating Risk Adapted from Epidemiologyby Leon Gordis, Saunders, 2014, Amazon

Kindle Version.

Relative Risk: is the risk in the exposed divided bythe risk in the non-exposed. Use ratio of risks or

incidence rates.

Bing.com search,Creative CommonsLicense.

Odds Ratio #

Bing.com search.Creative Commons

License.

Use when?Controls studied are representative (Gordis, 2014)

Disease studied does not occur frequently. (Gordis,2014)

Cased studied are representative (Gordis, 2014)

Attribution risk: Incidence in exposed group minusincidence in non-exposed group. (Gordis, 2014)

Evaluating Health ServicesAdapted fromEpidemiology by Leon Gordis, Saunders,


Effectiveness: Dose the agent produce the rightresult in real world trails?

Efficient: What is the ratio of cost to benefit?

Efficacy: Dose the intervention/agent work underideal conditions.

Studies of outcome

Studies of process

Randomized versus non-randomized?

PreventionAdapted from Epidemiology byLeon Gordis, Saunders, 2014, AmazonKindle Version.

Secondary: Early detection.

Tertiary: Reducing impact.

Primary: Prevent disease

Prevention Adapted from Epidemiology byLeon Gordis, Saunders, 2014, Amazon

Kindle Version.

Looks at factors that determine exposure (helpselect for risk factors) along with socialpsychological, family, economic, and communityeffects (come about as a result of disease).

Environmental and social factors that influencesuseptability?

Genetic factors influencing susceptibility orvulnerability

Population ApproachDirect intervention toward population.

High Risk ApproachDirect intervention toward high risk persons within thepopulation.

Risk AssessmentAdapted from Epidemiology byLeon Gordis, Saunders, 2014, Amazon Kindle

Version.

Dose-Response Assessment

Exposure Assessment: Review recordsPhysician records.

Hospital records.

Disease registry records

Employment records

Interview both subject and surrogate

Death certificates.

Hazard Identfiication

Risk Characterization

Metal Analysis: Aggregation of separate trials to uncoverassociations and make inferences. However, these

aggregate studies have drawbacks and can come toerroneous conclusions.

Does the study include all published data or is it cherrypicked?

Are non-randomized trials included?

Publication Bias: Tendency to only report concordantdata.

EthicsUse of race versus ethnicity?

Conflicts of interest?

Who owns the data?

Jeffrey Gutschmidt, December 12, 2016 – IH5426:Advanced Epidemiology – Final Exam, Concept Map.

Current Issues inEpidemiology

Breaking Issues in Epidemiology USHeroine Epidemic

Global issues in epidemilogyCholera in Haiti. Post Matthew, CNN

Ebola in Africa. .CDC

Zika in Central and South America. Is Southern USsafe, Zika 101 by NPR

, December 6, 2016Private sector implements measures to avert 1m malariadeaths by 2020

US Based Infectious Disease Outbreaks Raw Milk – Listeria monocytogenes, announced March2016, .CDC

Elizabethkingia anophelis in the Midwest, announcedJanuary 2016, .CDC

Dairy Bull Calves – Multidrug-resistant SalmonellaHeidelbergAnnounced November 2016, CDC

International Outbreaks Affecting TravelersZika in Bahamas, Nov 2016, .CDC

Zika in Palau, November 2016, .CDC

Measels in Romania, November 2016, .CDC

Association to Causation Adapted fromEpidemiology by Leon Gordis, Saunders, 2014,

Amazon Kindle Version.

CausalDirect: Factor to disease, no intermittent steps.

Indirect: factor + step 1 + step 2 = disease

Determining CuasalityCessation of exposure.

Consideration of alternate explanations.

Biological plausibility

Replication of findings.

Dose response relationship

Strength of association as measured by the risk or oddsratio. (Gordis, 2014)

Temporal relationship

Confounding

Third factor X confounds the causation of risk factor A ina study if:

X is a known risk factor for the disease

X is associated with factor A.

Control for confounding byStratify data and adjust data to a standard population.

Conduct individual or group matching

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http://www.cdc.gov/ophss/csels/dsepd/ss1978/lesson1/section6.html

https://www.merriam-webster.com/dictionary/vector#medicalDictionary

https://www.cdc.gov/bam/teachers/documents/epi_1_triangle.pdf

http://www.cdc.gov/vitalsigns/heroin/index.html

http://www.cdc.gov/flu/pandemic-resources/basics/past-pandemics.html




http://www.cdc.gov/hantavirus/resources/glossary.html

https://www.merriam-webster.com/dictionary/host#medicalDictionary

https://www.merriam-webster.com/dictionary/environment#medicalDictionary

http://www.cdcfoundation.org/content/what-public-health

https://en.oxforddictionaries.com/definition/ratio

https://en.oxforddictionaries.com/definition/proportion

https://en.oxforddictionaries.com/definition/rate

http://www.cnn.com/2016/10/10/americas/hurricane-matthew-haiti/index.html

https://www.cdc.gov/vhf/ebola/outbreaks/2014-west-africa/

http://www.npr.org/sections/goatsandsoda/2015/11/18/456515544/zika-virus-101-one-more-mosquito-borne-disease-to-worry-about

http://www.vanguardngr.com/2016/12/private-sector-implements-measures-avert-1m-malaria-deaths-2020/

http://www.cdc.gov/outbreaks/index.html






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IH5426_Gutschmidt_J_EPI Final Exam, Concept Map

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