Bad Numbers

If you lived through the pandemic, you probably heard words like "R number," "herd immunity," "excess mortality," and "statistical significance" more times than you can count. You were told to follow the science. But no one handed you the tools to understand what that actually meant.

This book is for:

• Undergraduate students trying to make sense of public health and health statistics

• Healthcare professionals, journalists, and policy analysts who work with medical research but were never taught how to interrogate it properly

• Curious readers who felt confused, misled, or overwhelmed by shifting expert guidance

• Early-career researchers who want the philosophical grounding their methods courses skipped

Bad Numbers is not a textbook. It is a detective story about how epidemiology really works.

Instead of dry definitions, you will follow real outbreaks, famous reversals, controversial studies, and the human beings behind the numbers. You will see how John Snow traced cholera to a water pump without knowing what a germ was. You will understand how researchers proved cigarettes cause lung cancer without running an experiment. You will discover why "doubled risk" can be both technically true and wildly misleading.

Along the way, you will learn how to:

• Interpret relative risk and absolute risk without being manipulated

• Understand case-control studies, cohort studies, and randomized trials in plain English

• Spot confounding, healthy user bias, and statistical sleight of hand

• Make sense of the R number and epidemic models

• Evaluate screening programs and early detection claims

• Read international health comparisons with a skeptical eye

• Live comfortably with uncertainty rather than demanding false certainty

Epidemiology is not a collection of formulas. It is a way of thinking about populations, evidence, and probability. It is messy, powerful, limited, and often misunderstood.

By the end of this book, you will not just know what the numbers mean. You will know what questions to ask when someone presents them.

This is your guide to understanding medical research without a PhD, following public health debates without panic, and recognizing the difference between honest uncertainty and bad science.