DESA: Detecting Epidemics using School Absenteeism

Provides a comprehensive framework for early epidemic detection through school absenteeism surveillance. The package offers three core functionalities: (1) simulation of population structures, epidemic spread, and resulting school absenteeism patterns; (2) implementation of surveillance models that generate alerts for impending epidemics based on absenteeism data and (3) evaluation of alert timeliness and accuracy through alert time quality metrics to optimize model parameters. These tools enable public health officials and researchers to develop and assess early warning systems before implementation. Methods are based on research published in Vanderkruk et al. (2023) <doi:10.1186/s12889-023-15747-z> and Ward et al. (2019) <doi:10.1186/s12889-019-7521-7>.

Getting started

Package details

AuthorVinay Joshy [aut, cre, cph], Zeny Feng [aut, cph, ths], Lorna Deeth [aut, cph, ths], Justin Slater [aut, cph, ths], Kayla Vanderkruk [aut, com, ctb]
MaintainerVinay Joshy <joshy@uoguelph.ca>
LicenseGPL (>= 3)
Version1.0.0
URL https://github.com/vjoshy/DESA
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("DESA")

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DESA documentation built on June 8, 2025, 10:19 a.m.