Predictive Modelling of Infectious Diseases

Epidemics and Pandemics are occurring more often and spreading faster and further than ever. Epidemics demand urgent responses, Planning and preparing for prevention and control are essential. (WHO, 2023). Epidemic modelling is essential for predicting disease dynamics and planning public health interventions. Allocating just the right number of resources is Essential. With limited resources and potentially dangerous diseases, accuracy in epidemic models is crucial, as inaccurate forecasts can lead to either over-preparation, which strains resources, or under-preparation, which leaves health systems vulnerable. In addition to guiding interventions, epidemic models inform healthcare providers and policy makers about the expected number of cases, peak infection times, and duration of an epidemic. This is significant for making decisions on where to deploy healthcare workers. This paper reviews some recently published papers on various methods that are used to predict epidemics. We also propose the use of Monte-Carlo methods to iterate over the hyperparameters dynamically. Moreover, models must account for social behaviours, demographics, and geography, as these factors strongly influence disease dynamics. Epidemic modelling is not a complete tool; rather, it must adapt to the disease at hand, the resources available and the specific characteristics of the affected population.