Only a combination of social distancing and massive testing can effectively stop COVID-19 progression in densely populated urban areas

ABSTRACT

We present a simple epidemiological model that includes demographic density, social distancing, and efficacy of massive testing and quarantine as the main parameters to model the progression of COVID-19 pandemics in densely populated urban areas (i.e., above 5,000 inhabitants km2). Our model demonstrates that effective containment of pandemic progression in densely populated cities is achieved only by combining social distancing and widespread testing for quarantining of infected subjects. Our results suggest that extreme social distancing without intensive testing is ineffective in extinguishing COVID-19. This finding has profound epidemiological significance and sheds light on the controversy regarding the relative effectiveness of widespread testing and social distancing. Our simple epidemiological simulator is also useful for assessing the efficacy of governmental/societal responses to an outbreak. This study also has relevant implications for the concept of smart cities, as densely populated areas are hotspots that are highly vulnerable to epidemic crises.