Role of Multi-resolution Vulnerability Indices in COVID-19 spread: A Case Study in India

IntroductionThe outbreak of COVID-19 has differentially affected countries in the world, with health infrastructure and other related vulnerability indicators playing a role in determining the extent of the COVID-19 spread. Vulnerability of a geographical region/country to COVID-19 has been a topic of interest, particularly in low- and middle-income countries like India to assess the multi-factorial impact of COVID-19 on the incidence, prevalence or mortality data. Datasets and MethodsBased on publicly reported socio-economic, demographic, health-based and epidemiological data from national surveys in India, we compute contextual, COVID-19 Vulnerability Indices (cVIs) across multiple thematic resolutions for different geographical and spatial administrative regions. These multi-resolution cVIs were used in regression models to assess their impact on indicators of the spread of COVID-19 such as the average time-varying instantaneous reproduction number. ResultsOur observational study was focused on 30 districts of the eastern Indian state of Odisha. It is an agrarian state, prone to natural disasters and one of the largest contributors of an unprotected migrant workforce. Our analyses identified housing and hygiene conditions, availability of health care and COVID preparedness as important spatial indicators. ConclusionOdisha has demonstrated success in containing the COVID-19 infection to a reasonable level with proactive measures to contain the spread of the virus during the first wave. However, with the onset of the second wave of COVID, the virus has been making inroads into the hinterlands and peripheral districts of the state, burdening the already deficient public health system in these areas. The vulnerability index presented in this paper identified vulnerable districts in Odisha. While some of them may not have a large number of COVID-19 cases at a given point of time, they could experience repercussions of the pandemic. Improved understanding of the factors driving COVID-19 vulnerability will help policy makers prioritise resources and regions leading to more effective mitigation strategies for the COVID-19 pandemic and beyond. O_TEXTBOXWHAT IS ALREADY KNOWNMeasuring vulnerability to COVID-19 and other pandemics is a complex and layered subject. In Low-to-Middle-Income Country (LMIC) like India, complete reliance on incidence, prevalence or mortality data of the disease may not be the best measure since this data from the health system and DHS in public domain is limited. ADDED VALUE OF THIS STUDYTo our knowledge, this is the first study at the district level concerning the COVID-19 situation in Odisha, characterized by a large tribal and migrant population. We defined vulnerability through relevant socio-economic domains that have an influence on mitigation strategies. Although we applied our methods to the districts of Odisha, we believe they can be used in other LMIC regions. IMPLICATIONS OF THE FINDINGSRegions with higher overall or theme-specific vulnerability index might experience potentially severe consequences of the COVID-19 outbreak demanding precise, dynamic and nimble policy decisions to prevent a potentially dire situation. C_TEXTBOX