An Epidemiologist investigates the patterns, causes, and effects of health and disease conditions in defined populations. They study the distribution and determinants of diseases (infectious and chronic), injuries, disabilities, and mortality; design and conduct studies; analyze data; and translate findings into public health interventions, policies, and practices. Unlike clinicians (who treat individual patients), epidemiologists focus on populations—identifying risk factors, tracking outbreaks, evaluating interventions, and informing public health policy. This role exists within government public health agencies (CDC (Centers for Disease Control and Prevention), state health departments, local/county health departments, NIH (National Institutes of Health), FDA (Food and Drug Administration), VA (Veterans Affairs), DOD (Department of Defense)), academic research (universities, medical schools, schools of public health — teaching, research, grant writing), hospitals and healthcare systems (infection prevention, healthcare epidemiology, quality improvement), pharmaceutical and biotechnology companies (clinical trials, pharmacoepidemiology, drug safety, real-world evidence), non-profit and global health organizations (WHO (World Health Organization), Bill & Melinda Gates Foundation, PATH, FHI 360, Population Council), health insurance companies (population health management, risk adjustment, utilization management), research institutes (RTI International, Westat, NORC, RAND Corporation), consulting firms (health economics, outcomes research, epidemiology consulting), and state and local public health laboratories. Titles vary: Epidemiologist, Research Epidemiologist, Infectious Disease Epidemiologist, Chronic Disease Epidemiologist, Environmental Epidemiologist, Occupational Epidemiologist, Pharmacoepidemiologist, Clinical Epidemiologist, Molecular Epidemiologist, Genetic Epidemiologist, Field Epidemiologist (disease detectives), Infection Prevention Epidemiologist, or Public Health Epidemiologist.
RIASEC Type: Investigative (I) Conventional (C), Social (S)
Disease Surveillance & Outbreak Investigation. Monitor disease trends using surveillance systems (NNDSS (National Notifiable Diseases Surveillance System), BioSense, ESSENCE, FluView, COVID-19 dashboards, state disease registries). Detect and investigate disease outbreaks (foodborne (Salmonella, E. coli, Listeria), waterborne (Giardia, Cryptosporidium), healthcare-associated infections (HAIs), emerging infectious diseases (Ebola, Zika, COVID-19, Mpox, avian influenza, Marburg)). Conduct case finding and contact tracing (identify exposed individuals, monitor for symptoms, recommend testing and quarantine). Analyze surveillance data to identify risk factors, transmission routes, and high-risk populations
Core Skills, Epidemiologic methods: Study design (cross-sectional, case-control, cohort, RCT, quasi-experimental, ecological, time series), sampling methods (simple random, stratified, cluster, systematic), bias (selection bias, information bias, confounding), confounding control (stratification, multivariable regression, propensity scores, instrumental variables, G-methods), effect modification (interaction), mediation analysis, causal inference (counterfactual framework, directed acyclic graphs (DAGs), Bradford Hill criteria), missing data methods (complete case, multiple imputation, inverse probability weighting), sensitivity analysis, meta-analysis, systematic reviews, Biostatistics: Descriptive statistics (mean, median, mode, standard deviation, range, percentiles), probability distributions (binomial, Poisson, normal, t, F, chi-square), hypothesis testing (t-tests, chi-square, ANOVA, Mann-Whitney, Kruskal-Wallis), confidence intervals, p-values, multiple testing correction (Bonferroni, FDR), regression (linear, logistic, Poisson, negative binomial, Cox proportional hazards, multinomial, ordinal, quantile), survival analysis (Kaplan-Meier, log-rank test, Cox model, competing risks), time series analysis (ARIMA, interrupted time series), spatial analysis (GIS, spatial autocorrelation, cluster detection), multilevel modeling (random effects, hierarchical models), Bayesian methods (MCMC, prior specification), machine learning (random forests, gradient boosting, neural networks), Surveillance: Case definitions (confirmed, probable, suspected), notifiable diseases, surveillance systems (NNDSS, BioSense, ESSENCE, FluView, COVID-19 dashboards, state disease registries), syndromic surveillance, laboratory surveillance, sentinel surveillance, active vs passive surveillance, surveillance evaluation (sensitivity, specificity, PPV, NPV, timeliness, representativeness), Outbreak investigation: Case finding, line listing, epidemic curve (epi curve), descriptive epidemiology (person, place, time), hypothesis generation, analytical studies (cohort, case-control), environmental investigation, laboratory confirmation, control measures (isolation, quarantine, vaccination, treatment, environmental cleaning), communication (public health alerts, press releases, social media), Infectious disease epidemiology: Transmission dynamics (R0 (basic reproduction number), Rt (effective reproduction number), herd immunity), incubation period, generation time, serial interval, attack rate, secondary attack rate, vaccine effectiveness, seroprevalence, molecular epidemiology (pathogen genomics, phylogenetic analysis, whole genome sequencing), contact tracing, outbreak modeling (compartmental models (SIR, SEIR, SEIR with vaccination, age-structured))