Journal
PLOS ONE
Volume 12, Issue 9, Pages -Publisher
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0185528
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Funding
- National Science Foundation Graduate Research Fellowship
- Center for Health and Wellbeing at Princeton University
- Research and Policy for Infectious Disease Dynamics program of the Science and Technology Directorate, Department of Homeland Security
- Fogarty International Center, National Institutes of Health
- Bill and Melinda Gates Foundation
- U.S. Centers for Disease Control and Prevention
- 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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