Abstract
On the 30 January 2020, the WHO declared a public health emergency of international concern due to the coronavirus disease 2019 (COVID-19). Social restrictions with different efficiencies were put in place to avoid transmission. Students living in student accommodation constitute an interesting group to test restrictions because they share living places, workplaces and daily routines, which are key factors in the transmission. In this paper, we present a new geospatial agent-based simulation model to explore the transmission of COVID-19 between students living in Newcastle University accommodation and the efficiency of simulated restrictions (e.g., facemask, lockdown, self-isolation). Results showed that facemasks could reduce infection peak by 30% if worn by all students; an early lockdown could keep 65% of the students safe in the best case; self-isolation could keep 86% of the students safe; while the combination of these measures could prevent disease in 95% of students in the best case-scenario. Spatial analyses showed that the most dangerous places were those where many students interact for a long time, such as faculties and accommodation. The developed ABM could help university managers to respond to current and future epidemics and plan effective responses to keep safe as many students as possible.
Highlights
Since the 30 January 2020 the world has faced a pandemic due to coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome, Coronavirus 2(SARS-CoV-2) [1]
We present a new agent-based simulation model to explore, from a geospatial perspective, the transmission of COVID-19 in a one-minute timestamp between students living in university accommodation and potential measures to reduce their risk of infection
Results are ininterpreted from a spatial-temporal perspective with the aim of testing the efficiency of the terpreted from a spatial-temporal perspective with the aim of testing the efficiency of the measures to reduce the risk of COVID-19 transmission between the students
Summary
Since the 30 January 2020 the world has faced a pandemic due to coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome, Coronavirus 2(SARS-CoV-2) [1]. Prior to the development of vaccines, the only available approach to stop the pandemic was the reduction of the exposure between the people by applying classical epidemic control measures, such as case isolation, contact tracing and quarantine, physical distancing, and hygiene measures [3]. The effectiveness of these measures must be tested to determine how, when and where to apply them. By testing the effectiveness of measures to reduce the transmission in this group, it could be possible to quantify the efficiency of measures and to apply the outcomes to the general population
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