SARS-CoV-2 Cases in uMgungundlovu District, KwaZulu-Natal, Wave 2 Analysis

uMgungundlovu district in KwaZulu-Natal, South Africa, is the geographic focus of this dataset. It contains geospatial and temporal analysis results for SARS-CoV-2 incidence across the first four waves of transmission, produced by Radiya Gangat using ESRI ArcGIS Pro and Python Seaborn. The dataset was last updated on April 15, 2026.

Use Cases

• Identify spatial clusters of COVID-19 cases based on Local Indicators of Spatial Association (LISA) analysis.
• Model temporal fluctuations in daily case counts across different waves using time series analysis.
• Analyze the relationship between infection density and social/built environment factors suggested in the description.
• Compare incidence rates and clustering patterns across different age groups.
• Guide resource allocation for testing, tracing, and vaccination based on kernel density estimation results.

Strengths

• Analysis covers four distinct waves of SARS-CoV-2 transmission.
• Includes specific statistical results, such as Moran's I values for each wave and kernel density estimation ranges.
• Data is licensed under CC-BY-4.0, allowing for open reuse.

Limitations

• Row count and column-level documentation are unknown, limiting suitability assessment.
• The dataset is 17.5 KB, indicating a very limited scope, likely containing summary statistics rather than raw case data.
• Description metadata is limited; actual data structure and field semantics must be inferred after download.

Provenance

Source

figshare

Collection Method

Spatial analysis using ESRI ArcGIS Pro and temporal analysis using Python Seaborn.

Time Range

Covers the first four waves of SARS-CoV-2 transmission.

Freshness

Last updated 2026-04-15 17:44:27; freshness should be verified.

Geography

uMgungundlovu district, KwaZulu-Natal, South Africa.