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epiforecasts
EpiNow2:Estimate Real-Time Case Counts and Time-Varying Epidemiological Parameters
Estimates the time-varying reproduction number, rate of spread, and doubling time using a range of open-source tools (Abbott et al. (2020) <doi:10.12688/wellcomeopenres.16006.1>), and current best practices (Gostic et al. (2020) <doi:10.1101/2020.06.18.20134858>). It aims to help users avoid some of the limitations of naive implementations in a framework that is informed by community feedback and is actively supported.
Maintained by Sebastian Funk. Last updated 1 months ago.
backcalculationcovid-19gaussian-processesopen-sourcereproduction-numberstancpp
123 stars 11.86 score 210 scripts
epinowcast
epidist:Estimate Epidemiological Delay Distributions With brms
Understanding and accurately estimating epidemiological delay distributions is important for public health policy. These estimates influence epidemic situational awareness, control strategies, and resource allocation. This package provides methods to address the key challenges in estimating these distributions, including truncation, interval censoring, and dynamical biases. These issues are frequently overlooked, resulting in biased conclusions. Built on top of 'brms', it allows for flexible modelling including time-varying spatial components and partially pooled estimates of demographic characteristics.
Maintained by Sam Abbott. Last updated 22 days ago.
14 stars 6.52 score 7 scripts