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GCS_Hartebeesthoek_1994
Angular Unit: Degree (0.017453)
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XTools Pro Metadata
<div style="font-family:'Segoe UI';font-size:14px;font-style:normal;font-weight:400;line-height:20px;">This dataset represents the municipal‑level distribution of human disease risk across the study area. It is derived from a multi‑criteria spatial model integrating key environmental and population‑related determinants of disease burden, including reclassified land‑use exposure factors, water quality indicators, population density, land‑based pollution, and air pollution. These factors were combined using a weighted‑sum raster overlay to generate a continuous Human Disease Potential surface. The resulting raster was summarised using zonal statistics for each Local Municipality to produce a municipal‑level <strong>Human_Disease</strong> score. Additional capacity‑to‑cope indicators were joined to the municipal dataset and used to compute a composite <strong>Vulnerability_Risk</strong> index. The final dataset enables disaster management practitioners, health analysts, planners, and risk professionals to identify municipalities with elevated human‑disease vulnerability and incorporate this information into multi‑hazard assessments, health‑risk planning, early‑warning systems, and resource‑allocation strategies.</div>
SRK_Munic_Human_Disease_Risk
2025-12-15T00:00:00
28.870109
32.959680
-26.801840
-31.085137
1
Human Disease
Vulnerability
Public Health
Pollution
Water Quality
Population Density
Multi‑Criteria Analysis
Weighted Overlay
Zonal Statistics
Hazard Mapping
Municipality
South Africa
GIS
The purpose of this dataset is to provide a spatially standardised representation of human‑disease risk at the municipal scale. It supports public‑health risk profiling, vulnerability assessments, multi‑hazard analysis, and the prioritisation of mitigation interventions in areas affected by environmental pollution, population‑driven exposure, and reduced capacity to manage disease outbreaks. The dataset ensures a consistent, evidence‑based foundation for informing disaster management planning, health surveillance programmes, resilience strategies, and municipal‑level decision‑making.
Prepared by: Herman Booysen, Principal GIS Scientist / Associate Partner
Organisation: SRK Consulting
Additional sources:
Environmental pollution rasters (air, land)
Water quality indicators
Population density datasets
Local Municipality boundaries
Internal SRK modelling documentation and multi‑criteria analysis methods
Hazard analysis and interpretation findings contained in:
KZN DRA
<div style="font-family:'Segoe UI';font-size:14px;font-style:normal;font-weight:400;line-height:20px;">This dataset is intended for public‑health and disaster‑risk assessment, strategic planning, hazard profiling, and municipal vulnerability analysis.<br>It is <strong>not suitable for clinical decision‑making or fine‑scale epidemiological modelling</strong> without additional field studies or verified health datasets.</div>
Esri ArcGIS 13.6.0.59527
dataset
20260311
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SRK_Munic_Human_Disease_Risk
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CATEGORY
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CAT2
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Human_Disease
Human_Disease
Double
8
38
8
A municipal‑level human‑disease exposure score representing the summed weighted contribution of environmental, demographic, and pollution‑related disease drivers within each municipal boundary. The value is derived through Zonal Statistics (SUM) applied to the weighted composite disease‑risk raster, which integrates reclassified land‑use risk, water‑quality indicators, population density, land pollution, and air pollution using a weighted‑sum overlay model. Higher values indicate municipalities with greater cumulative spatial extent or intensity of conditions associated with human‑disease hazard.
SRK Consulting Human Disease Hazard and Vulnerability Modelling Process (WeightedSum raster model + ZonalStatisticsAsTable workflow).
Vulnerability_Risk
Vulnerability_Risk
Double
8
38
8
A composite municipal‑level vulnerability index representing the interaction between disease exposure and local capacity to cope with human‑disease hazards. The value is calculated by multiplying the municipal Human_Disease score (derived from the zonal summation of the weighted human‑disease raster) with the municipality‑specific Capacity‑to‑Cope indicator. This field expresses the relative vulnerability of each municipality, where higher values indicate areas where high disease exposure coincides with lower institutional, infrastructural, or socio‑economic capacity to manage and mitigate human‑disease impacts.
SRK Consulting Human Disease Vulnerability Modelling Process (WeightedSum raster model + ZonalStatisticsAsTable + capacity‑to‑cope integration).
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