Pandemic spread prediction and healthcare preparedness through financial and mobility data

The pandemics like Coronavirus disease 2019 (COVID-19) require Governments and health professionals to make time-sensitive, critical decisions about travel restrictions and resource allocations. This paper identifies various factors that affect the spread of the disease using transaction data and proposes a model to predict the degree of spread of the disease and thus the number of medical resources required in upcoming weeks. We perform a region-wise analysis of these factors to identify the control measures that affect the minimal set of population. Our model also helps in estimating the surges in clinical demand and identifying when the medical resources would be saturated. Using this estimate, we suggest the preventive as well as corrective measures to avoid critical situations.