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These indicators were compiled in the LocalMunicipalities_InfrastructureVulnerability dataset and include measures of sanitation type, cooking fuel source, and refuse disposal practices.For district\u2011level aggregation, centroid point features were generated from the LocalMunicipalities_InfrastructureVulnerability polygons, with each centroid retaining the associated municipal\u2011level infrastructure vulnerability attributes. These centroid points were spatially joined to pre\u2011existing district municipality polygons using a spatial containment relationship.A one\u2011to\u2011one spatial join was applied, and municipal\u2011level infrastructure vulnerability values were summed for each district. The resulting field represents the aggregated infrastructure vulnerability score for each district municipality and reflects the combined contribution of local municipalities within that district.Infrastructure vulnerability values are relative and comparative, not absolute measures of infrastructure condition or service adequacy. Districts with higher aggregated values are interpreted as exhibiting greater concentrations of infrastructure\u2011related vulnerability, particularly in relation to sanitation, energy access, and waste management deficiencies. This dataset is intended to be interpreted alongside district\u2011level social and economic vulnerability layers as part of an integrated, multi\u2011dimensional vulnerability assessment.This is a screening\u2011level analytical product and does not represent real\u2011time service delivery conditions or engineering\u2011level infrastructure assessments.", "geometryType": "esriGeometryPolygon", "sourceSpatialReference": { "wkid": 4148, "latestWkid": 4148, "xyTolerance": 8.98315284119521E-9, "zTolerance": 0.001, "mTolerance": 0.001, "falseX": -400, "falseY": -400, "xyUnits": 9.999999999999999E8, "falseZ": 0, "zUnits": 1, "falseM": 0, "mUnits": 1 }, "copyrightText": "Produced by Herman Booysen, SRK Consulting.\nProject context: Disaster Management and climate risk assessment for KwaZulu\u2011Natal.", "parentLayer": null, "subLayers": [], "minScale": 0, "maxScale": 0, "referenceScale": 0.0, "drawingInfo": { "renderer": { "type": "classBreaks", "authoringInfo": { "type": "classedColor", 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Infrastructure vulnerability reflects the degree to which households and communities are exposed to service delivery failures and infrastructure deficiencies that can amplify disaster impacts and constrain recovery.The base local municipality polygon dataset originates from nationally maintained municipal boundary datasets updated through multiple redetermination cycles between 2009 and 2016. These boundaries were progressively standardised, attributed, and prepared for analysis, including the creation of composite naming fields and the retention of district and provincial identifiers. No geometry edits were applied during the infrastructure vulnerability modelling phase.Infrastructure vulnerability indicators were derived primarily from household service delivery data, focusing on access to basic infrastructure and the reliability of essential services. Key dimensions of infrastructure vulnerability included sanitation, cooking fuel type, and refuse disposal practices. These indicators were sourced from external tabular datasets and joined to the local municipality layer using attribute\u2011based joins.Sanitation vulnerability reflects reliance on toilet types such as chemical toilets, pit latrines (ventilated and unventilated), ecological toilets, and bucket systems. These systems are associated with elevated health risks, environmental contamination, and reduced resilience during service delivery disruptions. Cooking fuel vulnerability captures dependence on non\u2011electric fuels such as paraffin, wood, coal, animal dung, and other biomass sources, which are linked to indoor air pollution, health impacts, and limited adaptive capacity during energy supply failures. Refuse disposal vulnerability considers the prevalence of communal dumps, own dumps, or unregulated dumping, indicating deficiencies in municipal waste management systems and increased exposure to environmental and public\u2011health hazards.Service delivery indicators were expressed as proportions at municipal level and classified using Natural Breaks (Jenks) to identify relative vulnerability classes. Selected vulnerability components were combined into a composite infrastructure vulnerability score, TotalInfrastructureVulnerability, representing the relative level of infrastructure\u2011related vulnerability for each local municipality.Intermediate fields and attributes unrelated to infrastructure vulnerability (including social vulnerability components, join artefacts, and temporary classification fields) were removed during schema cleanup to produce a focused, analysis\u2011ready dataset.Infrastructure vulnerability values in this dataset are relative and comparative, not absolute measures of service adequacy or infrastructure condition. 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