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20211
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Subject: Veterinary Epidemiology and Preventive Medicine × End date: 2021 × Start date: 2021 × Thesis Type: Ph.D ×
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    ThesisItemOpen Access
    Study of epidemiological factors associated with covid-19 in India and network meta-analysis of therapeutic in treatment of covid-19
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2021-01) Singh, Pooja; Upadhyay, A.K.
    Covid-19 (Coronavirus Disease-2019) is a global general medical issue with a high pace of serious clinical cases. The present study was carried out to understand theepidemiological rates and socioeconomic-demographic factors associated with COVID-19, also its treatment efficacy by previous research using data available in the public domain. Statewise analysis of coronavirus disease 2019 (COVID-19) in India estimated that morbidity rating of first five states are Delhi, Goa, Maharastra, Puducherry and Tamil Nadu whereas Delhi, Puducherry, Goa, Maharastra, Chandigarh are stands for high mortality rate. The Punjab and Maharashtra, reported highest case fatality rate and highest recovery rate in Andhra Pradesh and Dadra and Nagar Haveli. The correlation analysis showed that total population, male, female, population above 60 ages, no. of literates, persons below poverty and private hospitalization respectively had significant positive correlation with covid-19 cases, recovery and death whereas population density, public hospitals, per capita income, Shikhs, Christians, vegetarian- nonvegetarian,tobacco smoker, toddy - country liquor, beer, imported alcohol and wine had not any significant correlations. Pairwise Meta-analysis result revealed that Lopinavir–ritonavir is the best treatment followed by Standard care, Placebo, Remdesivir other antiviral moreover network metaanalysis reverted that placebo had better role in recovery of Covid-19 than other treatments as Remdesivir, Standard care, Lopinavir/ Ritonavir, other antiviral. Obtaining definite and precise clinical history with epidemiological rates, relation between associated factors and treatment efficacy analysis may help in the identification of the highest disease burden areas that help us to improve our knowledge to develop a plan of action for effective control and prevention measures so that better and necessary medical care may be provided to expand the probabilities of survival of COVID-19 patients.