Mapping Covid-19 incidence hotspots in Pakistan using spatial-statistical approach

Abstract

COVID-19 pandemic is a top-level global emergency which has reduced the coping capacity several developed nations. The infected cases are growing very rapidly. The social interaction and travelling of people have further intensified the situation. Therefore, in this paper an attempt has been made to identify and assess COVID-19 hotspot in Pakistan and public health department to decelerate the exponential growth of patients. Point-level geo-coding technique is applied on patient’s record (25/03/2020 to 20/04/2020) and the relative location was converted into absolute location. A total 468 confirmed cases were geo-coded. Getis-OrdGi* statistical model is applied in ArcGIS10.2 to calculate Z-score and P-values for each location representing the COVID-19 incidence intensity. Then Inverse distance weighted (IDW) technique of spatial interpolation was applied on Z-score and spatial clusters of confirmed cases were geo-visualized in the form hotspot and cold spot. The spatial extent of hotspots and age group of infected persons is alarming. The study provides a suitable methodological framework for identification and analysis infectious disease hotspots. The results can also facilitate public health department and related authorities to win war against COVID-19 lethal outbreak. Similarly, it can help policy makers to restrict travelling and social interaction in hotspots.