Creating a risk assessment model at the district level for tracking COVID-19 infections in India is important for identifying populations at risk. Risk assessment can additionally be computed through case studies, cohort studies and cross sectional studies.
The analysis of geographically logical segregation of population (district wise) can qualify as a valid cohort study and can be compared with actual incidence and prevalence of cases. This analysis should consider known determinants and risk factors such as high volume of international and domestic visitors, high rates and intensity of migration, and high population density per se.
The paper draws up a strategic framework based on these factors and assesses the risks based on its implementation. It collates information about incidences of COVID 19 infection in all 736 districts of India and specifies its findings in 36 districts of Maharashtra State of India and finds that Current Actual Scores (as on April 11, 2020) for the state can be used to assess risk of COVID 19 incidence in the state.
Keywords: COVID 19 India risk assessment, Incidence, Prevalence, Mortality, Odds ratio, Morbidity, Relative risk, Hazards ratio, Standardized mortality ratio, Standardized incidence ratio, COVID-19 Risk, District Level COVID 19 Risk, Risk assessment model, District level, COVID infections India, Identifying populations, Cohort sectional analysis, Geographically logical segregation, Risk factors, High volume international domestic visitor rates , Risk Assessment Tools, Morbidity specific categories, SIR, SMR