The Susceptible Size of Coronavirus Spread, Epidemic Age, and Optimal Decisions

Abstract

This paper aims to determine the susceptible size used in the mathematical model that predicts the epidemic curve. It also aims to ascertain the age of the epidemic and its reliability system, further suggesting optimal decisions. This paper employs the mathematical induction and deduction methods to extract the parameter λ and the age of the epidemic. Functions techniques were also used to evaluate the susceptible size. It used the epidemiological forecasting models with r at 0.15 and ≤ 150 for Hubei, and ≤ 83 for Germany. It also used the shortest path and available data to calculate the recovery rate used in mixed strategies game with the decisions trees. This paper found that the susceptible size that added to infection size, to give the N size, should be determined by a function. This paper found that the longer the epidemic age, the greater the size that affects the virus reliability system. The virus spread active center is a community of unlimited and variable random. This means that is small and almost constant. The optimal decisions are to use the second strategy until the first strategy is available. The second strategy has two parts: searching for vaccine and accurate medicine and applying supportive therapy and protection. This paper therefore suggests explanations to many concepts that will contribute to a better understanding of many phenomena in modeling, epidemic, decisions, economic, and politics.