Week 4: Epidemiology, Biostatistics, & Data

Core Science of Public Health

Epidemiology

Epidemiology Function

Investigates causes of diseases

Identifies trends in disease occurrence

Evaluates effectiveness of medical and public health interventions

First Example of Use of Epidemiology to Study and Control a Disease

John Snow and the London Cholera Epidemic

Studies may be ___ or ___

Prospective: follow forward in time

Retrospective: looking back in time

Types of Epidemiologic Studies

1. Intervention Study

2. Cohort Study

3. Case-Control Study

Intervention Study

Two groups:

• Experimental group: gets the intervention or exposure

• Control group: closely matched and not exposed

  • Observe over time and compare outcomes

Randomized: subjects are assigned randomly to a group to reduce chance of bias

• Randomized, double-blind, placebo control is ideal

Limitations: subject may not follow prescribed behavior throughout study period

Cohort Study

• Used when doing an intervention study would be unethical or too difficult (considered the next most accurate to RCT)

• Observational; no intervention: Choose a large number of healthy people, collect data on their exposures, and track outcomes over time

• Differs from other interventions in that people choose their own exposures 

• Limitations: Sometimes it is hard to isolate which of many factors are responsible for health differences

Case-Control Study

***Least accurate approach

Two Groups:

• Cases: Choose people who already have disease

• Controls: Choose a healthy control group of individuals, as similar as possible to cases

  • Interview both cases and controls, and ask for their previous exposures (retrospective data collection)

Advantages: faster and cheaper

Limitations:

• Control group may not be truly comparable

• Errors may exist in reporting or recalls

Incidence

Number of new cases over a given time period

Prevalance

Number of existing cases of the disease per year that have not been cured or caused death at a given point of time

• Depends on incidence and prognosis

  • If causes or risk factors increase, incidence and prevalence increase

  • If ability to diagnose increases, incidence and prevalence appear to increase

• Most useful in assessing the societal impact of a disease and planning for healthcare services

Pattern of Disease Occurrence

Who is getting the disease?

• Sex, age, occupation, race, and economic status

When did they get the disease?

• Season, year (long-term trends), elapsed time since an exposure (epidemic curve)

• Crucial in tracking an outbreak of infectious diseases such as hepatitis (30 day incubation period)

Where is the disease occurring?

• Neighborhood (e.g. clusters), latitude (climate), urban/rural, national variations

• Looks at comparisons of disease frequency in different countries, states, countries

GOAL: control and prevnt the spread of disease

Endemic

Constant presence of disease within an area

• Ex. malaria (Africa), HTN, obesity, diabetes

Epidemic

Usually high occurrence of disease, within a community or region

• Ex. Cholera, Polio, Pertussis (Whooping Cough), Ebola, Zika Virus

Pandemic

When an epidemic spreads throughout the world

• Ex. SARS, HIV/AIDS, COVID-19

Epidemiologic Surveillance

Systematic collection, analysis and dissemination of health data for the planning, implementation and evaluation of public health programs

Purpose of Epidemiologic Surveillance

Control spread of known disease AND in recognizing new disease

• Importance increased w/ threat of bioterrorism

Disease Processes that Require Epidemiologic Surveillance

Require certain “notifiable” diseases to be reported as soon as they are diagnosed

• Certain disease must be reported at the state level

  • Voluntary for states to notify CDC at the federal level (varies by state)

• Typically infectious diseases, given their risk of spread

• Preventable if appropriate actions are taken

• MA: TB, tetanus, hepatitis, measles, anthrax, cholera, syphilis (60 dz at the federal level)

Causation

Research demonstrates the capacity of one variable to influence another

• Epidemiology determines the relationship or association between an exposure and frequency of disease in populations

  • If association is strong, we infer causation based upon the association and several other factors

• Ex. first variable (smoking) may bring the second variable (lung cancer) into existence

Association/Correlation

Link b/w or among variables; research demonstrates a relationship between two or more things

• Epidemiology determines the relationship or association b/w an exposure and frequency of disease in populations

• Association ≠ Causation

  • Ex: people who smoke also tend to drink alcohol, however smoking doesn’t cause alcoholism

  • Ex: sugary snacks are associated with tooth decay, however everyone who consumes sugar doesn’t develop dental cavities

Epidemiologic Triangle 

Multiple Causations: More than one factor must be present for disease to develop

• Agent (ex. firearm, pill overdose)

• Host (ex. susceptible young person)

• Environment (family, school, media)

Traditional approach to dealing w/ infectious diseases

Interventions can focus on any of the these targets

Model can also be used for other kinds of illnesses or injuries

Examples of Multiple Causation: Suicide

Agent (Cause): firearm or pill overdose

Host: susceptible young person

Environment: family, school, media

Examples of Multiple Causation: EEEV (Eastern Equine Encephalitis Virus)

Agent (Cause): Eastern equine encephalitis virus

Host: Mosquitoes; Birds; Horses; Susceptible Humans

Environment: Freshwater hardwood swamp; Ponds, tanks of fresh water; Late spring thru early fall

Examples of Multiple Causation: Tooth Decay

Agent (Cause): Specific bacteria; Bacterial biofilm

Host: Salivary Flow and composition; Structure of tooth enamel; Immunity or response to pathogens; Behavioral and lifestyle factors

Environment: Fluoride exposure; Dietary carbohydrates; Minerals and enzymes

Sources of Error that can Influence Epidemiological Studies

Confounding Variables

Bias

Confounding Variables

Distortion of an association between an exposure and an outcome because of the influence of a third variable not considered in the study design or analysis

• Ex. Study outcome yields high rate of mortality – however sample size included many subjects over age 75

Bias

Selection bias: choosing subjects who will yield desired outcome

• Ex. Dr. Noyes’ ACL patient of mine

Reporting bias or recall bias: retrospective studies

Ethical Failure of Tuskegee Study

Researchers misled participants by claiming they were being treated for “bad blood” w/o informed consent and did not provide actual treatments

• Men did not receive treatments and many of them and their offspring/spouses were infected and died

2 Protective Guidelines Developed After Tuskegee Study

Informed consent

Institutional Review Boards (IRB)

Most accurate form of data collection

Census: official count or survey of a population, typically recording various details of individuals

Where is data transmitted?

Local governments → states → National Center for Health Statistics (NCHS is part of CDC)

Impact of infectious disease in U.S. history and the role of vaccination played

Infectious disease encouraged research and epidemiology, reporting measures to ensure decrease of disease transmission

Vaccination decreased the prevalence of diseases when herd immunity was achieved

Purpose of the US Census

Serves as a denominator for most public health data (age, sex, race, ethnicity), determine political composition of the US Congress, and distribute federal funds to states and communities

• Mandated by the U.S. Constitution

• Conducted every ten years (2020)