Spatial Analysis of COVID-19 with Associated Multimorbidity and Environmental Dynamics using Google Earth Engine in Balochistan, Pakistan

COVID-19 has caused a death toll of over 7 million. COVID-19 has proven to have hostile effects on human health, industrial production, the economy, social functioning, and international relations. The pandemic of the SARS-CoV-2 virus is also causing mismanagement of other diseases such as respiratory, cardiovascular, arboviral, metabolic, neural diseases, and hypertension. These alarming situations of multiple co-infections are the cause of serious public health concerns globally. The study aims to explore the effect of the COVID-19 pandemic on routine and emergency care for multimorbidity in Balochistan. This involves both primary and secondary data sources. Primary data was collected through a field survey, while secondary data was obtained from the World Health Organization, the government of Balochistan, and remote sensing. Density analysis was carried out to generate the density maps of COVID-19 cases with associated multimorbidity across all the districts of Balochistan in a geographic information system environment using ArcMap 10.8.2. Remote sensing data acquired from Sentinel 5P through Google Earth Engine was used to analyze environmental parameters such as nitrogen dioxide, sulfur dioxide, carbon monoxide, ozone, and land surface temperature during the COVID-19 years. The findings of this study indicate that multimorbidity was a risk factor for COVID-19 severity and that the risk increased with the morbidity burden. This study also shows that urban populations are more vulnerable to the risk of multimorbidity with COVID-19 than those in rural areas. The results strongly recommend the implementation of modified tactics for patients with multimorbidity and a lack of facilities.