ABSTRACT
The SARS-CoV-2 infections continue to increase in Namibia and globally. Assessing and mapping the COVID-19 risk zones and modeling the response of COVID-19 using different scenarios are very vital to help decision-makers to estimate the immediate number of resources needed and plan for future interventions of COVID-19 in the area of interest. This study is aimed to identify and map COVID-19 risk zones and to model future COVID-19 response of Namibia using geospatial technologies. Population density, current COVID-19 infections, and spatial interaction index were used as proxy data to identify the different COVID-19 risk zones of Namibia. COVID-19 Hospital Impact Model for Epidemics (CHIME) V1.1.5 tool was used to model future COVID-19 responses with mobility restrictions. Weights were assigned for each thematic layer and thematic layer classes using the Analytical Hierarchy Process (AHP) tool. Suitably ArcGIS overlay analysis was conducted to produce risk zones. Current COVID-19 infection and spatial mobility index were found to be the dominant and sensitive factors for risk zoning in Namibia. Six different COVID-19 risk zones were identified in the study area, namely highest, higher, high, low, lower, and lowest. Modeling result revealed that mobility reduction by 30% within the country had a notable effect on controlling COVID-19 spread: a flattening of the peak number of cases and delay to the peak number. The research output could help policy-makers to estimate the immediate number of resources needed and plan for future interventions of COVID-19 in Namibia, especially to assess the potential positive effects of mobility restriction.
ABSTRACT
SARS-CoV-2 infections are now spreading across the world. Different measures were used by governments around the world to combat the spread of COVID-19. The efficacy of social distancing approaches in reducing the spread of COVID-19 in Ethiopia was investigated using geospatial technologies and the CHIME model. The COVID-19 response was predicted, measured, and compared after 25%, 75%, and 95% social distancing interventions in Ethiopia. Social distancing strategies flatten and delay the epidemic curve, according to the model findings. The model result shows that most new events and hospitalizations were avoided when social distancing measures were in effect. Social distancing can provide a critical time for increasing healthcare capability, and the research findings could assist policymakers in estimating the immediate number of resources required and planning for potential COVID-19 initiatives in Ethiopia.