Epidemiology finds the causes of disease by counting it in whole populations instead of experimenting on individuals. Two numbers underpin everything: prevalence (how many have the disease now) and incidence (how many new cases appear in a set period, out of the people at risk). Four designs read those numbers with increasing power: descriptive studies spot patterns, case-control studies look back from the sick to their exposures, cohort studies follow exposed and unexposed people forward, and intervention studies assign the exposure at random, which is the only design that can show cause. This is the real knowscape from knowhere, not a picture of one. Drag it. Watch what actually changes.
You can't run the experiment — you can't give people cancer to prove a cause. So epidemiology reads the population instead: patterns, rates, and correlations across whole groups, then argues from strength, consistency, and dose whether the link is causal. Every study is that same argument, built without a lab.
The same 120 people drawn four ways: a population coloured by disease, cases and controls traced back to exposure, exposed and unexposed cohorts followed along a five-year timeline, and randomly assigned trial arms, with incidence and prevalence counted live from the same dots.
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