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Accurate estimates of the under-five mortality rate in a developing world context are a key barometer of the health of a nation. This paper describes a new model to analyze survey data on mortality in this context. We are interested in both spatial and temporal description, that is wishing to estimate under-five mortality rate across regions and years and to investigate the association between the under-five mortality rate and spatially varying covariate surfaces. We illustrate the methodology by producing yearly estimates for subnational areas in Kenya over the period 1980-2014 using data from the Demographic and Health Surveys, which use stratified cluster sampling. We use a binomial likelihood with fixed effects for the urban/rural strata and random effects for the clustering to account for the complex survey design. Smoothing is carried out using Bayesian hierarchical models with continuous spatial and temporally discrete components. A key component of the model is an offset to adjust for bias due to the effects of HIV epidemics. Substantively, there has been a sharp decline in Kenya in the under-five mortality rate in the period 1980-2014, but large variability in estimated subnational rates remains. A priority for future research is understanding this variability. In exploratory work, we examine whether a variety of spatial covariate surfaces can explain the variability in under-five mortality rate. Temperature, precipitation, a measure of malaria infection prevalence, and a measure of nearness to cities were candidates for inclusion in the covariate model, but the interplay between space, time, and covariates is complex. [ABSTRACT FROM AUTHOR]

Background: The Kenya Demographic and Health Surveys (KDHS) data collected since 1989 indicate that malaria prone areas have consistently recorded the highest childhood mortality rates. Malaria control programme information also indicates that malaria contributes to about 20 per cent of the deaths among under-five year old children. The 2009-2017 National Malaria Strategy is being implemented to reduce malaria morbidity and mortality. Its key interventions include: bed nets use; anti-malaria drugs use during pregnancy for prevention; and, prompt treatment using anti-malaria drugs of children with fever. This study seeks to establish differentials in childhood mortality rates by these interventions in three malaria prone areas defined as highland epidemic, coast endemic and lake endemic. It also seeks to determine the effects of these interventions on childhood mortality. Methods: The data used is drawn from the 2008/9 KDHS. The study sample consists of 3,728 children born less than 60 months prior to the survey. The direct demographic method for estimation of childhood mortality rates and multivariate Poisson regression models are used to analyse the data. Results: The findings show that use of bed nets and anti-malaria drugs are not high in Kenya's malaria prone areas. On the average, only about 60% of the children are found to be in higher use category for each of the three intervention measures. The childhood mortality rates show that higher use of prompt treatment with anti-malaria drugs for children with fever has lower infant and under-five mortality rates in all malaria epidemic and endemic areas compared to lower use. Higher bed nets use has lower childhood mortality rates compared to lower use in coast and lake endemic areas. Higher use of anti-malaria drugs during pregnancy for prevention has lower childhood mortality rates in highland epidemic and lake endemic areas compared to lower use. The regression models fitted show that in highland epidemic area, higher use of anti-malaria drugs during pregnancy for prevention has significant reduction effect on childhood mortality compared to lower use in the presence of breastfeeding duration, toilet facility type and age of child variables. The regression models also show that in combined malaria prone areas, higher prompt treatment of children with fever using anti-malaria drugs has significant reduction effect on both infant and child mortality compared to lower prompt treatment in the presence of breastfeeding duration and toilet facility type variables. Conclusion: This study underscore the need for increasing uptake of malaria interventions and complementing them with longer breastfeeding duration and improved toilet facility in efforts towards reducing infant and child mortality rates in Kenya's malaria prone areas. There is also need to improve quality of individual household data for malaria module in future KDHS undertakings. [ABSTRACT FROM AUTHOR]

Background We describe trends in childhood mortality in Kenya, paying attention to the urban-rural and intra-urban differentials. Methods We use data from the Kenya Demographic and Health Surveys (KDHS) collected between 1993 and 2008 and the Nairobi Urban Health and Demographic Surveillance System (NUHDSS) collected in two Nairobi slums between 2003 and 2010, to estimate infant mortality rate (IMR), child mortality rate (CMR) and under-five mortality rate (U5MR). Results Between 1993 and 2008, there was a downward trend in IMR, CMR and U5MR in both rural and urban areas. The decline was more rapid and statistically significant in rural areas but not in urban areas, hence the gap in urban-rural differentials narrowed over time. There was also a downward trend in childhood mortality in the slums between 2003 and 2010 from 83 to 57 for IMR, 33 to 24 for CMR, and 113 to 79 for U5MR, although the rates remained higher compared to those for rural and non-slum urban areas in Kenya. Conclusions The narrowing gap between urban and rural areas may be attributed to the deplorable living conditions in urban slums. To reduce childhood mortality, extra emphasis is needed on the urban slums. [ABSTRACT FROM AUTHOR]

Summary The Kilifi Health and Demographic Surveillance System (KHDSS), located on the Indian Ocean coast of Kenya, was established in 2000 as a record of births, pregnancies, migration events and deaths and is maintained by 4-monthly household visits. The study area was selected to capture the majority of patients admitted to Kilifi District Hospital. The KHDSS has 260 000 residents and the hospital admits 4400 paediatric patients and 3400 adult patients per year. At the hospital, morbidity events are linked in real time by a computer search of the population register. Linked surveillance was extended to KHDSS vaccine clinics in 2008. KHDSS data have been used to define the incidence of hospital presentation with childhood infectious diseases (e.g. rotavirus diarrhoea, pneumococcal disease), to test the association between genetic risk factors (e.g. thalassaemia and sickle cell disease) and infectious diseases, to define the community prevalence of chronic diseases (e.g. epilepsy), to evaluate access to health care and to calculate the operational effectiveness of major public health interventions (e.g. conjugate Haemophilus influenzae type b vaccine). Rapport with residents is maintained through an active programme of community engagement. A system of collaborative engagement exists for sharing data on survival, morbidity, socio-economic status and vaccine coverage. [ABSTRACT FROM AUTHOR]

Abstract: Findings from previous studies linking the HIV/AIDS epidemic and fertility of populations have remained inconclusive. In sub-Saharan Africa, demographic patterns point to the epidemic resulting in fertility reduction. However, evidence from the 2003 Kenya Demographic and Health Survey (KDHS) has revealed interesting patterns, with regions most adversely affected with HIV/AIDS showing the clearest reversal trend in fertility decline. While there is suggestive evidence that fertility behaviour in some parts of sub-Saharan Africa has changed in relation to the HIV/AIDS epidemic, more rigorous empirical analysis is necessary to better understand this relationship. In this paper, we examine individual and contextual community HIV/AIDS factors associated with fertility patterns in Kenya, paying particular attention to possible mechanisms of the association. Multilevel models are applied to the 2003 KDHS, introducing various proximate fertility determinants in successive stages, to explore possible mechanisms through which HIV/AIDS may be associated with fertility. The results corroborate findings from earlier studies of the fertility inhibiting effect of HIV among infected women. HIV-infected women have 40 percent lower odds of having had a recent birth than their uninfected counterparts of similar background characteristics. Further analysis suggests an association between HIV/AIDS and fertility that exists through proximate fertility determinants relating to sexual exposure, breastfeeding duration, and foetal loss. While HIV/AIDS may have contributed to reduced fertility, mainly through reduced sexual exposure, there is evidence that it has contributed to increased fertility, through reduced breastfeeding and increased desire for more children resulting from increased infant/child mortality (i.e. a replacement phenomenon). In communities at advanced stages of the HIV/AIDS epidemic, it is possible that infant/child mortality has reached appreciably high levels where the impact of replacement and reduced breastfeeding duration is substantial enough to result in a reversal of fertility decline. This provides a plausible explanation for the patterns observed in regions with particularly high HIV prevalence in Kenya. [Copyright &y& Elsevier]

Objectives (1) To determine whether mortality rates were raised in sick children in the 30 days after visiting first-level health facilities in an area under demographic surveillance in western Kenya, (2) to identify the types of illnesses associated with increased mortality and (3) to estimate the effectiveness of appropriate treatment. Methods All sick children (2–59 months of age) who attended one of the seven participating first-level health facilities from May to August 2003 were identified. A standardized mortality ratio was computed to compare their mortality rate in the 30 days after a sick visit with that of the community under active demographic and health surveillance. A multivariate Cox Proportional Hazards model was used to identify illnesses associated with death and to estimate the protective effectiveness of appropriate treatment for potentially life-threatening diseases. Results A total of 1383 eligible children made 1697 sick visits; 33 (2.4%) died within 30 days. Compared with children 2–59 months in the general population, sick children had a 5.3 times greater mortality rate [95% confidence interval (CI) 3.8–7.5]. In a multivariate survival analysis, significant risk factors for mortality included age <24 months [Hazard Ratio (HR) 4.4, 95% CI 1.5–12.6], malnutrition (HR 15.5, 95% CI 6.1–39.8), severe pneumonia (HR 12.9, 95% CI 3.0–56.4) and anaemia (HR 3.3, 95% CI 1.5–7.2). Appropriate treatment for a child’s most severe illness reduced mortality by 78% (95% CI 57–89%). Conclusion We estimate that improvements in diagnosis and appropriate treatment at first-level health facilities for children 2–59 months could reduce overall under-5 mortality in the area by 12–14%. [ABSTRACT FROM AUTHOR]