Spatial distribution and Clustering of COVID-19 cases reveal the effect of urbanization and population density in Uganda

被引：0

作者：

Anthony Egeru ^{[1
]}

Gordon Yofesi Mwesigwa ^{[1
]}

Aggrey Siya ^{[1
]}

Eria Serwajja ^{[2
]}

Yazidhi Bamutaze ^{[3
]}

机构：

[1] Department of Environmental Management, Makerere University, P.O. Box 7062, Kampala

[2] Uganda Wildlife Research and Training Institute, P.O. Box 173, Kasese

[3] Department of Development Studies, Makerere University, P.O. Box 7062, Kampala

[4] Department of Geography, Geo-Informatics and Climatic Sciences, Makerere University, P.O. Box 7062, Kampala

来源：

SN Social Sciences | / 4卷 / 9期

关键词：

COVID-19; Epidemiology; GIS; Heterogeneity; Uganda; Variability;

D O I：

10.1007/s43545-024-00970-1

中图分类号：

学科分类号：

摘要：

Uganda reported its first case of COVID-19 on 21 March 2020 and thereafter, experienced three waves with varied prevalence and effects. However, the spatial analysis of COVID-19 cases over Uganda remained unexplored. This study analyzed the spatial distribution of COVID-19 cases, determined hotspot locations, and performed a projection of the potential patterns of COVID-19 prevalence in Uganda. COVID-19 data was obtained from the Uganda Ministry of Health and World Health Organization COVID-19 data portals. We applied a trend analysis, Inverse Distance Weighted (IDW) interpolation-a linearized regression in a GIS environment. We also implemented spatial autocorrelation of the COVID-19 cases using Moran’s I, while the Pearson correlation was used to assess the relationship between population density and COVID-19 prevalence. Results showed high variability in COVID-19 cases across weeks, months, and years of analysis. Kampala and Wakiso districts revealed the highest level of prevalence closely followed by other major urban areas such as; Tororo, Mbarara, Kasese, Soroti, and Gulu. The forecasted trend generally showed that there could have been continued decline in COVID-19 prevalence over the next 36 months but with possibilities of a rise if the public health interventions were not being adhered. Results also revealed random patterns of prevalence pointing to the heterogeneity of spatial distribution. Meanwhile, spatial clustering highly correlated with population density and COVID-19 prevalence. This study reveals the effect of urbanization and population density in influencing COVID-19 case dynamics in Uganda. Distance, proximity, and population heterogeneity-urban vs. rural played a key role in the transmission and disease incidence of COVID-19 in Uganda. We recommend for a geographical ecosystem approach that appreciates spatial dynamics to be considered when formulating public health interventions in Uganda, this will particularly be important for appropriately tackling urban public health needs in terms of safety and prevention in time of crisis. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

引用

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