A Fuzzy Logic Scheme Based on Population and Spread Rate for the Management of Vaccination during Pandemics (preprint)

ABSTRACT

The pandemics like COVID-19 cause a massive shock to the global economy and its impacts are huge and endure across all domains of life. Effectively managing the limited vaccine supply is crucial in the fight against pandemics. A central issue in the management of pandemic vaccination is the allocation of vaccines from the central government to state authorities. The objective of this research was to make use of a fuzzy logic scheme for the management of vaccination to the local state authorities by a central Government based on population and spread rate. The proposed scheme utilizes a fuzzy logic inference system taking into account on population and spread rate to infer the vaccination rate. This scheme is in contrast to conventional approaches that often consider either a state's population or spread rate as the sole basis for vaccine allocation. The Covid-19 data of 6 southern states of India during the first week of October 2020 collected from the database maintained by the Ministry of Health and Family Welfare of Government of India was used for the verification of the proposed scheme. The proposed scheme was implemented using MATLAB/SIMULINK software and compared with the conventional schemes, one based on population and another based on spread rate. The results show that the proposed scheme ensures that sufficient doses of vaccines are allotted to the states on priority where spread rate is more and vaccines are not wasted in states where spread rate is less. At the same time, all states are eventually allotted sufficient vaccine doses to halt transmission. The proposed scheme ensures that sufficient vaccines are distributed in a quick, effective and unbiased way, and enhances the fight against pandemics.