To conduct epidemiological analysis R packages can be really handy. Here are some useful packages for epidemic modeling:

- surveillance: A great package for spatio-temporal analysis for epidemic.
- EpiEstim : Useful to estimate the average number of secondary cases caused by an infected individual (reproduction number) from a time series of disease incidence. Another similar package is R0.
- outbreaker : Useful for reconstructing transmission trees from sequence data.
- amei : Useful for finding optimal intervention strategies. (i.e. the proportion of the population to be vaccinated to prevent further disease spread from temporal data.)
- tscount: Useful for calculating the weekly number of reported infections of a particular disease.
- diseasesmapping: Great package for spatial analysis of disease occurrence.
- etasFLP : A package to fit spatio-temporal epidemic models.
- splancs: A package for space-time clustering.

Some additional spatial analysis packages that can be useful for epidemic modeling: spacetime, sp, xts

Some great tutorials for epi. modeling :

- A overview of SIR model: http://www.modelinginfectiousdiseases.org/
- A overview of disease modeling: http://staff.math.su.se/hoehle/pubs/Hoehle_SpaMethInfEpiModelling2015.pdf