Guest Editorial: Analyses of mortality clustering at member HDSSs within the INDEPTH Network – an important public health issue

T he fourth Millennium Development Goal (MDG) (1) aims to reduce child mortality according to the target: ‘Reduce by two-thirds, between 1990 and 2015, the under-5 mortality rate’ (U5MR). The 2009 MDG report (2) stated ‘Although data on this target are problematic and at times contentious, significant progress in individual African countries has been registered, although the rate of progress at the continental level is poor. The U5MR in Africa dropped from 166 per 1,000 live births in 2005 to 160 per 1,000 live births in 2006’ and later ‘It is clear that the continent as a whole is unlikely to meet this U5MR target, if current trends continue. This calls for renewed and intensified efforts by African governments and their development partners to scale up interventions to reduce the U5MR. Access to and utilisation of basic health services need to be increased and made more equitable. To reduce the wide gap between rural and urban areas, more resources should be allocated to public health interventions, including environmental health, in rural areas.’ One figure in the report cited above shows large variations between African countries in terms of their success in achieving this goal. About one-third of all countries show a decline of 30% or more in U5MR. On the other hand, there are countries that sadly show a considerable increase. Two reviews on that topic have been published recently (3, 4). Rajaratnam et al. (3) found that across 21 regions of the world, rates of neonatal, post-neonatal and childhood mortality are declining. The global decline from 1990 to 2010 is 2.2% per year for childhood mortality. Robust measurement of mortality in children under-5 years of age showed that accelerating declines are occurring in several low-income countries. Bhutta et al. (4) reviewed the progress between 1990 and 2010 in the coverage of 26 key interventions in 68 countdown priority countries, which account for more than 90% of maternal and child deaths worldwide, and found that 19 of the countries studied were on track to meet MDG 4, in 47 countries acceleration was found in the yearly rate of reduction in U5MR, and in 12 countries progress had decelerated since 2000. These are overall positive findings; however, the time trends in mortality at subnational level have not been addressed in these papers. Within less developed countries there are large variations in mortality, often between the capital city, other urban areas, and the countryside, both for young children and the rest of the population. The member health and demographic surveillance systems (HDSSs) within the INDEPTH Network typically cover relatively small areas, either urban or rural, and it is important to investigate whether within such small areas a heterogeneous pattern of mortality also exists. Why is this important? Firstly, it can show whether suspected disparities really exist. Secondly, spatial analysis helps to identify underlying causes, which is the first step in implementing targeted prevention strategies. The INDEPTH Network and its associated HDSS centres play a unique role in these efforts. Spatial and spatial temporal clustering of mortality was investigated at HDSSs in West, East, and South Africa, and in South Asia. Fig. 1 shows the countries that either contributed analyses to this Global Health Action Supplement or that previously published similar analyses. All these countries have their own specific characteristics, and differ substantially from each other. Nevertheless, the analyses presented here show that they have one thing in common: in each of the HDSSs considered, we found evidence of mortality being clustered. In this volume, clustering analyses of mortality for nine HDSS members within the INDEPTH Network are presented. Table 1 gives an overview of all the HDSSs, with some of their main characteristics, in which mortality clustering has been investigated, either in this supplement or in previous publications. With one exception, all centres included consideration of the 0 5-year age group. Some did additional analyses for other age groups and one centre combined age groups because of its smaller size. There are different statistical methods available to investigate mortality clustering (5). The method developed by Kulldorff (6) proved to be effective for analysing clustering of mortality in settings such as an HDSS. All papers in this volume and the previous studies listed in Table 1 have used the same statistical method to identify mortality clusters. SaTScanTM software was then used for analyses (7). It employs Kulldorff’s spatial scan statistic GUEST EDITORIAL INDEPTH Mortality Clustering Supplement