Disease Rt Effective Reproduction
Estimates Rt from R0 and susceptible population fraction.
Rt
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Understanding Rt (Effective Reproduction Number)
Think of Rt as R₀ that moves with time. It measures how many people, on average, each infected person passes the disease to once a partially immune population has been reached at time t. You can approximate it with Rt = R₀ × (susceptible fraction). When Rt drops below 1 the epidemic is fading. Above 1 it spreads. At exactly 1 it holds steady on a plateau.
When health authorities want to know in real time whether lockdowns, masks, distancing or vaccination are actually working, Rt is the number they watch. The current estimates lean on Bayesian methods, notably the Cori et al. (2013) framework built into the EpiEstim R package, which works backward from daily case counts and the serial interval distribution.
Applications
Through the COVID-19 pandemic, FIOCRUZ and the Imperial College London team put out daily Rt figures for Brazil and other countries so policymakers had something concrete to act on. Those numbers help decide when to loosen or tighten restrictions, where to send hospital capacity, and when to raise early alarms. Once Rt stays under 1 for a while, that is the usual sign an outbreak has been brought to heel.
FAQ
Why does Rt change? Plenty of things push it around: how much people move and whether they mask, vaccination, immunity that builds up after past infections, new variants, and the season itself.
What is a "safe" Rt? As long as it holds below 1.0, cases will keep falling. Authorities frequently aim for Rt < 0.8 so the decline is fast and there is some room to spare.
Why is my Rt different from the news? Each method (Cori, Wallinga-Teunis, Bettencourt-Ribeiro) makes its own assumptions about the serial interval, so the estimates come out a little apart. Watch the trend rather than the exact figure.
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