Open AccessDISTRICT WISE ANALYSIS OF COVID-19 PANDEMIC TRENDS DURING SECOND WAVE IN THE STATE ANDHRA PRADESH, INDIA USING SEIR-RGS MODEL
Author(s) -
MSLB Subrahmanyam,
Vajjha Hem Kumar
Publication year - 2021
Publication title -
international journal of engineering applied science and technology
Language(s) - English
Resource type - Journals
ISSN - 2455-2143
DOI - 10.33564/ijeast.2021.v06i05.042
Subject(s) - covid-19 , pandemic , welfare , incubation period , geography , statistics , demography , socioeconomics , mathematics , incubation , medicine , biology , economics , infectious disease (medical specialty) , sociology , political science , law , disease , pathology , biochemistry
— Andhra Pradesh is one of the south Indian states inIndia and having 13 districts. This is one of the most Covid-19effected state in India during first and second waves. In Indiadistrict is the major administrative block for implementinggovernment policies and schemes under control of districtcollector. So, estimating or forecasting trends in district levelmore important than state wise or entire country wise. In thispaper we are proposing Susceptible, Exposed, Infected andRecovered – Regression and Grid Search (SEIR-RGS) modelfor analyzing Covid -19 district wise trends during secondwave. The SEIR-RGS, initially collects daily wise covid datafor each district from Department of Health, medical andfamily welfare, AP and estimates the model parameters likecontact rate, incubation rate and recovery rate. To calculaterecovery rate the proposed model uses regression techniquebetween daily active cases vs cumulative recoveries. Thepresent model uses two phases for estimating contact rate andincubation rate using grid search approach. After that theproposed method calculates the infectious period, incubationperiod and basic reproduction of infection in all 13 districts toanalyze trends in the state during second wave and also topredict possibility of third wave in each district.