An epidemiologist is tracking a disease outbreak in a small town with a population of 10,000. If 5% of the population is initially infected and the infection rate doubles every week, how many people will be infected after 3 weeks?

Wed, 06 May 2026 00:24:06 +0000

**How Infections Spread in Small Towns: A Data-Driven Look at a Rising Outbreak** Hearing about sudden disease surges in close-knit communities isn’t rare these days—especially when modeling doubles weekly. In a town of just 10,000 residents, an initial 5% infection rate ignites alarm when transmission accelerates exponentially. Understanding how quickly numbers grow can guide preparedness and informed decision-making. This scenario—where an epidemiologist monitors a fast-moving outbreak—is gaining attention across the US, driven by heightened awareness of infectious disease patterns, regional health vulnerabilities, and increased public inquiry into outbreak dynamics. When an epidemiologist studies such an outbreak, the core question emerges: how does doubling infection rates over time reshape total cases? Starting with 5% of 10,000, or 500 people infected, the doubling effect creates predictable—but steep—growth. The pattern follows simple exponential forecasting: each week, the infected count multiplies by two. **Breaking Down the Spread Over Time**