Mortality patterns, 1993–98, in a rural area of Burkina Faso, West Africa, based on the Nouna demographic surveillance system G. Kynast-Wolf 1 , O. A. Sankoh 1 , A. Gbangou 2 , B. Kouyate ´ 2 and H. Becher 1 1 Department of Tropical Hygiene and Public Health, University of Heidelberg Medical School, Heidelberg, Germany 2 Centre de Recherche en Sante´ de Nouna, Nouna, Burkina Faso, West Africa Summary The Nouna demographic surveillance system database was analysed for the period 1993–98. Basic demographic parameters, age-specific and age-standardized mortality rates were calculated and a seasonal variation in mortality was analysed. Poisson regression was used to model the calculated mortality rates and to investigate the seasonal mortality pattern. Both the population distribution by age and the mortality rates reflect a typical pattern of population structures and total mortality in rural Africa as a whole: high childhood mortality and a young population (about 60% are up to age 25; about 10% above age 64). We identified a significant seasonal pattern with highest mortality rates in February. Demographic surveillance systems in Africa provide a viable method for the collection of reliable data on vital events in rural Africa and should therefore be established and supported. keywords demographic surveillance, Poisson regression, sub-Saharan Africa, total mortality correspondence Prof. H. Becher, Department of Tropical Hygiene and Public Health, University of Heidelberg Medical School, Im Neuenheimer Feld 324, 69120 Heidelberg, Germany. E-mail: heiko.becher@urz.uni-heidelberg.de Introduction In 1978, African delegates joined the representatives of other nations in endorsing the Alma Ata Declaration, which committed all governments to the common goal of achieving ‘Health for all’ by the year 2000. A major task of epidemiologists is to assess to what extent this ambitious target has been realized. Good descriptive epidemiological data are required, and the difficult task of collecting and presenting them was started in a rather heterogeneous way in Africa. A comprehensive volume on mortality and morbidity data in sub-Saharan Africa (Feachem & Jamison 1991) highlighted achievements in the 1980s and shortcomings in terms of lack of data for a large number of countries. During the 1990s, the white spots on mortality maps gradually became smaller, but most estimates of overall mortality are subject to error and bias – especially for sub-Saharan Africa – as reliable mortality statistics cover- ing the total population hardly exist (Cooper et al. 1998). Consequently, many countries in Africa are now taking steps towards providing a reliable information base to support health development. An increasing number of field sites operating demographic surveillance systems (DSS) is being established in rural areas to continuously monitor geographically defined populations. To coordinate the activities of the sites, an International Network of Field Sites with Continuous Demographic Evaluation of Popu- lations and THeir Health in Developing Countries (INDEPTH; see http://www.indepth-network.org for the vision and goals of the network as well as its current activities) was established in Dar es Salaam, Tanzania, in 1998. Many DSS sites in Africa collaborate with interna- tional research institutions. For example, the Nouna DSS in Burkina Faso, on which this study is based, collaborates with the Department of Tropical Hygiene and Public Health at the University of Heidelberg in Germany. Sankoh et al. (2001) analyse a subset of the Nouna DSS data by concentrating on the clustering of children under five in the study area. They use a space and space–time scan statistic proposed by Kulldorff (1997) to identify clusters and test for their statistical significance. The paper reports several statistically significant clusters of higher childhood mortality rates comprising different sets of villages; one specific village was consistently identified in the study population, indicating non-random distribution of Tropical Medicine and International Health volume 7 no 4 pp 349–356 april 2002 ª 2002 Blackwell Science Ltd 349