4.6 Article

tsiR: An R package for time-series Susceptible-Infected-Recovered models of epidemics

Journal

PLOS ONE
Volume 12, Issue 9, Pages -

Publisher

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0185528

Keywords

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Funding

  1. National Science Foundation Graduate Research Fellowship
  2. Center for Health and Wellbeing at Princeton University
  3. Research and Policy for Infectious Disease Dynamics program of the Science and Technology Directorate, Department of Homeland Security
  4. Fogarty International Center, National Institutes of Health
  5. Bill and Melinda Gates Foundation
  6. U.S. Centers for Disease Control and Prevention
  7. EUNICE KENNEDY SHRIVER NATIONAL INSTITUTE OF CHILD HEALTH & HUMAN DEVELOPMENT [P2CHD047879] Funding Source: NIH RePORTER

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tsiR is an open source software package implemented in the R programming language designed to analyze infectious disease time-series data. The software extends a well-studied and widely-applied algorithm, the time-series Susceptible-Infected-Recovered (TSIR) model, to infer parameters from incidence data, such as contact seasonality, and to forward simulate the underlying mechanistic model. The tsiR package aggregates a number of different fitting features previously described in the literature in a user-friendly way, providing support for their broader adoption in infectious disease research. Also included in tsiR are a number of diagnostic tools to assess the fit of the TSIR model. This package should be useful for researchers analyzing incidence data for fully-immunizing infectious diseases.

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