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

Author(s): Becker, Alexander D.; Grenfell, Bryan T.

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Abstract: 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.
Publication Date: 28-Sep-2017
Electronic Publication Date: 28-Sep-2017
Citation: Becker, Alexander D., Grenfell, Bryan T. (2017). tsiR: An R package for time-series Susceptible-Infected-Recovered models of epidemics. PLOS ONE, 12 (9), e0185528 - e0185528. doi:10.1371/journal.pone.0185528
DOI: doi:10.1371/journal.pone.0185528
EISSN: 1932-6203
Pages: e0185528 - e0185528
Type of Material: Journal Article
Journal/Proceeding Title: PLOS ONE
Version: Final published version. This is an open access article.

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