Mapping the temporal-spatial distribution of the Kwa-Zulu Natal SARSCoV-2 epidemic: May 2020-September 2021; from the first to the third wave.

Abstract

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in 2019 and has caused unparalleled morbidity and mortality. Like global trends, the South African epidemic waves were driven by variants of concern (VOC). In addition, early public restrictions characterized the pattern of spread of SARS-CoV-2 in South Africa. Methods: A retrospective database study was undertaken to identify patterns in temporal-spatial distribution of SARS-CoV-2 in Kwa-Zulu Natal (KZN) across the first three epidemic waves. ArcGIS® Pro was used to create thematic choropleth maps visualizing SARS-CoV-2 test positivity at sub-district level for each epidemic wave and inter-wave period. Moran’s I statistic was used to determine spatial autocorrelation in SARS-CoV-2 test positivity. The Getis-Ord Gi* statistic was used to detect and map SARS-CoV-2 hotspots. The identified hotspots were further characterized with respect to mean cycle threshold (CT) value and predominant circulating SARS-CoV-2 strain. Results: The eThekwini district had high positivity rates (>25%) during all three epidemic waves. Across all districts, higher test positivity rates were seen during waves compared to the interwave periods. The highest positivity rates were seen in wave 2, with majority of the province having a positivity rate above 25%. The hotspot analysis identified significant clustering in multiple study time periods. Further characterization of hotspots revealed that the mean CT values were lower during waves than post-wave periods. The predominantly circulating SARS-CoV-2 lineages in the province per hotspot corresponded with nationally detected variants as described in national genomic surveillance. Conclusion: Geospatial mapping of SARS-CoV-2 hotspots is a valuable tool for tracking epidemics and identifying areas for targeted responses and interventions. In this retrospective analysis, the KZN epidemic was observed to mirror national trends.