Design of Epidemic Model For Covid-19 Disease Prediction Using Deep Learning

Abstract

Promising technologies are available in the developing field of Public Health Surveillance (PHS) to help public health authorities make decisions more quickly by expediting the process of monitoring, analysing, and using unofficial sources. The cornerstone of public health practice is public health surveillance. Influencing policy decisions, spearheading new program initiatives, improving public relations, and helping organisations assess their research expenditures all depend on surveillance data. Public health experts may find that mathematical models are an effective tool in controlling epidemics, which might result in a significant drop in the number of cases and deaths. Moreover, decision-makers can optimise prospective control strategies, including as vaccination campaigns, lockdowns, and containment measures, by using mathematical models to produce long- and short-term forecasts. This work suggests the evolution of epidemics.