Abstract

Background: Detailed information regarding the spatial and/or spatial–temporal distribution of mortality is required for the efficient implementation and targeting of public health interventions.Objectives: Identify high risk clusters of mortality within the Agincourt subdistrict for targeting of public health interventions, and highlight areas for further research.Design: Mortality data were extracted from the Agincourt health and socio-demographic surveillance system (HDSS) for the period 1992–2007. Mortality rates by age group and time were calculated assuming a Poisson distribution and using precise person-time contribution estimates. A spatial scan statistic (Kulldorff) was used to test for clusters of age group specific all-cause and cause-specific mortality both in space and time.Results: Many statistically significant clusters of higher all-cause and cause-specific mortality were identified both in space and time. Specific areas were consistently identified as high risk areas; namely, the east/south- east and upper east central regions. This corresponds to areas with higher mortality due to communicable causes (especially HIV/TB and diarrhoeal disease) and indicates a non-random element to the distribution of potential underlying causative factors e.g. settlements comprising former Mozambican refugees in east/south-east of the site, corresponding higher poverty areas, South African villages with higher HIV prevalence, etc. Clusters of older adult mortality were also observed indicating potential non-random distribution of non-communicable disease mortality.Conclusion: This study has highlighted distinct clusters of all-cause and cause-specific mortality within the Agincourt subdistrict. It is a first step in prioritizing areas for further, more detailed research as well as for future public health follow-on efforts such as targeting of vertical prevention of HIV/TB and antiretroviral rollout in significant child and adult mortality clusters; and assessment and provision of adequate water and sanitation in the child mortality clusters particularly in south-east where diarrheal mortality appears high. Underlying causative factors need to be identified and accurately quantified. Other questions for more detailed research are discussed.

Highlights

  • Detailed information regarding the spatial and/or spatialÁtemporal distribution of mortality is required for the efficient implementation and targeting of public health interventions

  • Temporal trends A significant increase in the mortality rate over time was observed from 4.7 deaths per 1,000 person years in 1992 to 12.5 deaths per 1,000 person years in 2007

  • Demographic surveillance systems provide a viable method for the collection of reliable data on vital events in rural sub-Saharan Africa, especially in the absence of accurate routine mortality statistics

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Summary

Introduction

Detailed information regarding the spatial and/or spatialÁtemporal distribution of mortality is required for the efficient implementation and targeting of public health interventions. Specific areas were consistently identified as high risk areas; namely, the east/southeast and upper east central regions This corresponds to areas with higher mortality due to communicable causes (especially HIV/TB and diarrheal disease) and indicates a non-random element to the distribution of potential underlying causative factors e.g. settlements comprising former Mozambican refugees in east/southeast of the site, corresponding higher poverty areas, South African villages with higher HIV prevalence, etc. Conclusion: This study has highlighted distinct clusters of all-cause and cause-specific mortality within the Agincourt subdistrict It is a first step in prioritizing areas for further, more detailed research as well as for future public health follow-on efforts such as targeting of vertical prevention of HIV/TB and antiretroviral rollout in significant child and adult mortality clusters; and assessment and provision of adequate water and sanitation in the child mortality clusters in the south-east where diarrheal mortality appears high.

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