Routines for epidemiological contact tracing
    and visualisation of network of contacts.

Creates simple or stacked epidemic curves for hourly, daily, weekly or monthly outcome data.

The Economic Policy Institute (<https://www.epi.org/>) provides
    researchers, media, and the public with easily accessible, up-to-date, and
    comprehensive historical data on the American labor force. It is compiled
    from Economic Policy Institute analysis of government data sources. Use
    it to research wages, inequality, and other economic indicators over time
    and among demographic groups. Data is usually updated monthly.

The Delphi 'Epidata' API provides real-time access to epidemiological surveillance data for influenza, 'COVID-19', and other diseases for the USA at various geographical resolutions, both from official government sources such as the Center for Disease Control (CDC) and Google Trends and private partners such as Facebook and Change 'Healthcare'. It is built and maintained by the Carnegie Mellon University Delphi research group. To cite this API: David C. Farrow, Logan C. Brooks, Aaron 'Rumack', Ryan J. 'Tibshirani', 'Roni' 'Rosenfeld' (2015). Delphi 'Epidata' API. <https://github.com/cmu-delphi/delphi-epidata>.

Package for data exploration and result presentation. Full 'epicalc' package with data management functions is available at '<https://medipe.psu.ac.th/epicalc/>'.

Contains utilities and functions for the cleaning, processing and
    management of patient level public health data for surveillance
    and analysis held by the UK Health Security Agency, UKHSA.

Mathematical models of infectious diseases in humans and animals.
    Both, deterministic and stochastic models can be simulated and plotted.

Tools to quantify transmissibility throughout
    an epidemic from the analysis of time series of incidence as described in
    Cori et al. (2013) <doi:10.1093/aje/kwt133> and Wallinga and Teunis (2004) 
    <doi:10.1093/aje/kwh255>.

Analysis and visualization of plant disease progress curve data. Functions for
    fitting two-parameter population dynamics models (exponential, monomolecular, logistic
    and Gompertz) to proportion data for single or multiple epidemics using either linear
    or no-linear regression.  Statistical and visual outputs are provided to aid in model
    selection. Synthetic curves can be simulated for any of the models given the parameters.
    See Laurence V. Madden, Gareth Hughes, and Frank van den Bosch (2007) <doi:10.1094/9780890545058>
    for further information on the methods.