Covid-19 spread prediction and its correlation with social distancing, available health facilities using GIS mapping data models in Lahore, Pakistan

Abstract

Virus spreading and its mitigation is an important safety issue that has drawn wide attention of many countries and people. For researchers in this area, it is an interesting work to study virus spreading with safety theories and methods. In this paper, we worked on the spatial extent of SIR model, which considers the known facts of Covid-19 behavior i.e. its spreading extent with time, the total population of area concerned and dedicated health facilities. Also, a special relationship between Covid-19 cases and NLDI data driven by night-time satellite imagery is being discussed. Results predicted a huge gap between predicted and presently available facilities for number of hospitals, beds, and ventilators. Findings suggest that developing countries like our study area Lahore District, Pakistan needs to follow social distancing at immense level, which not only helps in reducing the numbers of infections and fatalities but also the time duration of the whole epidemic. Maps based on NLDI vales, predicted cases, hospitals and ventilators needs could be greatly helpful for policymakers to analyze situation and concentrate on areas which needs immediate attention. Dealing with the pandemic requires a pre-planned command and control structure that could make quick and informed decisions in the whole city. We recommend that the use of proper model prediction at Union Council level can help local government in policymaking related social distancing and healthcare systems. The decision of social distancing should be on time and like what percent of social distancing is needed, which tackle with the already available health care structure.