Global Health Action (Aug 2010)

Spatio-temporal clustering of mortality in Butajira HDSS, Ethiopia, from 1987 to 2008

  • Peter Byass,
  • Mesganaw Fantahun,
  • Anders Emmelin,
  • Mitike Molla,
  • Yemane Berhane

DOI
https://doi.org/10.3402/gha.v3i0.5244
Journal volume & issue
Vol. 3, no. 0
pp. 26 – 31

Abstract

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Background: Mortality in a population may be clustered in space and time for a variety of reasons, including geography, socio-economics, environment and demographics. Analysing mortality clusters can therefore reveal important insights into patterns and risks of mortality in a particular setting. Objective and design: To investigate the extent of spatio-temporal clustering of mortality in the Butajira District, Ethiopia, from 1987 to 2008. The Health and Demographic Surveillance System (HDSS) dataset recorded 10,696 deaths among 951,842 person-years of observation, with each death located by household, in which population time at risk was also recorded. The surveyed population increased from 28,614 in 1987 to 62,322 in 2008, in an area approximately 25 km in diameter. Spatio-temporal clustering analyses were conducted for overall mortality and by specific age groups, grouping the population into a 0.01° latitude–longitude grid. Results: A number of significantly high- and low-mortality clusters were identified at various times and places. Butajira town was characterised by significantly low mortality throughout the period. A previously documented major mortality crisis in 1998–1999, largely resulting from malaria and diarrhoea, dominated the clustering analysis. Other local high-mortality clusters, appreciably attributable to meningitis, malaria and diarrhoea, occurred in the earlier part of the period. In the later years, a more homogeneous distribution of mortality at lower rates was observed. Conclusions: Mortality was by no means randomly distributed in this community during the period of observation. The clustering analyses revealed a clear epidemiological transition, away from localised infectious epidemics, over a generation.

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