How do Urban Factors Control the Severity of COVID-19?

Abstract

AbstractHuman health in urban environment has emerged as a primary focus of sustainable development during the time of global pandemic caused by a severe acute respiratory syndrome due to the SARS-CoV-2 coronavirus, COVID-19. It has reshaped the world with the way our communities interact, people work, commute, and spend their leisure time. While different mitigation solutions for controlling COVID-19 virus transmission have already been established, global models that would explain and predict the impact of urban environments on the case fatality ratio CFR of COVID-19 (defined as the number of deaths divided by the number of cases over a time window) are missing. Here, with readily available data from public sources, we study the CFR of the coronavirus for 118 locations (city zip-codes, city boroughs, and cities) worldwide to identify the links between the CFR and outdoor, indoor and personal urban factors. We show that a probabilistic model, optimized on the sample of 20 districts from 4 major US cities, provides an accurate predictive tool for the CFR of COVID-19 regardless of the geographical location. When adjusted for the population, our model can be used to evaluate risk and severity of the disease at multi-geospatial scales worldwide ranging from zip-codes and neighborhoods to cities and countries for different waves of the pandemic. Our results suggest that although disease screening and vaccination policies to containment and lockdowns remain critical in controlling the spread of airborne diseases, urban factors such as population density, humidity, or order of buildings, should all be taken into consideration when identifying resources and planning targeted responses to mitigate the impact and severity of the viruses transmitted through air. We advocate the study of urban factors as a path towards facilitating timely deployment of targeted countermeasures and confinement strategies where sharing of personal information and availability of tests may be restricted or limited.