REffectivePred - Pandemic Prediction Model in an SIRS Framework
A suite of methods to fit and predict case count data
using a compartmental SIRS (Susceptible – Infectious –
Recovered – Susceptible) model, based on an assumed
specification of the effective reproduction number. The
significance of this approach is that it relates epidemic
progression to the average number of contacts of infected
individuals, which decays as a function of the total
susceptible fraction remaining in the population. The main
functions are pred.curve(), which computes the epidemic curve
for a set of parameters, and estimate.mle(), which finds the
best fitting curve to observed data. The easiest way to pass
arguments to the functions is via a config file, which contains
input settings required for prediction, and the package offers
two methods, navigate_to_config() which points the user to the
configuration file, and re_predict() for starting the
fit-predict process. The main model was published in Razvan G.
Romanescu et al. <doi:10.1016/j.epidem.2023.100708>.
