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      Health & Demographic Surveillance System Profile: The Nairobi Urban Health and Demographic Surveillance System (NUHDSS)

      , , , , , ,
      International Journal of Epidemiology
      Oxford University Press (OUP)

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          Abstract

          The Nairobi Urban Health and Demographic Surveillance System (NUHDSS) was the first urban-based longitudinal health and demographic surveillance platform in sub-Saharan Africa (SSA). The NUHDSS was established in 2002 to provide a platform to investigate the long-term social, economic and health consequences of urban residence, and to serve as a primary research tool for intervention and impact evaluation studies focusing on the needs of the urban poor in SSA. Since its inception, the NUHDSS has successfully followed every year a population of about 65,000 individuals in 24,000 households in two slum communities--Korogocho and Viwandani--in Nairobi, Kenya. Data collected include key demographic and health information (births, deaths including verbal autopsy, in- and out-migration, immunization) and other information that characterizes living conditions in the slums (livelihood opportunities, household amenities and possessions, type of housing etc.). In addition to the routine data, it has provided a robust platform for nesting several studies examining the challenges of rapid urbanization in SSA and associated health and poverty dynamics. NUHDSS data are shared through internal and external collaborations, in accordance with the Centre's guidelines for publications, data sharing.

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          Childhood vaccination in informal urban settlements in Nairobi, Kenya: Who gets vaccinated?

          Background Recent trends in global vaccination coverage have shown increases with most countries reaching 90% DTP3 coverage in 2008, although pockets of undervaccination continue to persist in parts of sub-Saharan Africa particularly in the urban slums. The objectives of this study were to determine the vaccination status of children aged between 12-23 months living in two slums of Nairobi and to identify the risk factors associated with incomplete vaccination. Methods The study was carried out as part of a longitudinal Maternal and Child Health study undertaken in Korogocho and Viwandani slums of Nairobi. These slums host the Nairobi Urban Health and Demographic Surveillance System (NUHDSS) run by the African Population and Health Research Centre (APHRC). All women from the NUHDSS area who gave birth since September 2006 were enrolled in the project and administered a questionnaire which asked about the vaccination history of their children. For the purpose of this study, we used data from 1848 children aged 12-23 months who were expected to have received all the WHO-recommended vaccinations. The vaccination details were collected during the first visit about four months after birth with follow-up visits repeated thereafter at four month intervals. Full vaccination was defined as receiving all the basic childhood vaccinations by the end of 24 months of life, whereas up-to-date (UTD) vaccination referred to receipt of BCG, OPV 1-3, DTP 1-3, and measles vaccinations within the first 12 months of life. All vaccination data were obtained from vaccination cards which were sighted during the household visit as well as by recall from mothers. Multivariate models were used to identify the risk factors associated with incomplete vaccination. Results Measles coverage was substantially lower than that for the other vaccines when determined using only vaccination cards or in addition to maternal recall. Up-to-date (UTD) coverage with all vaccinations at 12 months was 41.3% and 51.8% with and without the birth dose of OPV, respectively. Full vaccination coverage (57.5%) was higher than up-to-date coverage (51.8%) at 12 months overall, and in both slum settlements, using data from cards. Multivariate analysis showed that household assets and expenditure, ethnicity, place of delivery, mother's level of education, age and parity were all predictors of full vaccination among children living in the slums. Conclusions The findings show the extent to which children resident in slums are underserved with vaccination and indicate that service delivery of immunization services in the urban slums needs to be reassessed to ensure that all children are reached.
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            Monitoring of Health and Demographic Outcomes in Poor Urban Settlements: Evidence from the Nairobi Urban Health and Demographic Surveillance System

            The Nairobi Urban Health and Demographic Surveillance System (NUHDSS) was set up in Korogocho and Viwandani slum settlements to provide a platform for investigating linkages between urban poverty, health, and demographic and other socioeconomic outcomes, and to facilitate the evaluation of interventions to improve the wellbeing of the urban poor. Data from the NUHDSS confirm the high level of population mobility in slum settlements, and also demonstrate that slum settlements are long-term homes for many people. Research and intervention programs should take account of the duality of slum residency. Consistent with the trends observed countrywide, the data show substantial improvements in measures of child mortality, while there has been limited decline in fertility in slum settlements. The NUHDSS experience has shown that it is feasible to set up and implement long-term health and demographic surveillance system in urban slum settlements and to generate vital data for guiding policy and actions aimed at improving the wellbeing of the urban poor.
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              The burden of disease profile of residents of Nairobi's slums: Results from a Demographic Surveillance System

              Background With increasing urbanization in sub-Saharan Africa and poor economic performance, the growth of slums is unavoidable. About 71% of urban residents in Kenya live in slums. Slums are characteristically unplanned, underserved by social services, and their residents are largely underemployed and poor. Recent research shows that the urban poor fare worse than their rural counterparts on most health indicators, yet much about the health of the urban poor remains unknown. This study aims to quantify the burden of mortality of the residents in two Nairobi slums, using a Burden of Disease approach and data generated from a Demographic Surveillance System. Methods Data from the Nairobi Urban Health and Demographic Surveillance System (NUHDSS) collected between January 2003 and December 2005 were analysed. Core demographic events in the NUHDSS including deaths are updated three times a year; cause of death is ascertained by verbal autopsy and cause of death is assigned according to the ICD 10 classification. Years of Life Lost due to premature mortality (YLL) were calculated by multiplying deaths in each subcategory of sex, age group and cause of death, by the Global Burden of Disease standard life expectancy at that age. Results The overall mortality burden per capita was 205 YLL/1,000 person years. Children under the age of five years had more than four times the mortality burden of the rest of the population, mostly due to pneumonia and diarrhoeal diseases. Among the population aged five years and above, HIV/AIDS and tuberculosis accounted for about 50% of the mortality burden. Conclusion Slum residents in Nairobi have a high mortality burden from preventable and treatable conditions. It is necessary to focus on these vulnerable populations since their health outcomes are comparable to or even worse than the health outcomes of rural dwellers who are often the focus of most interventions.
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                Author and article information

                Journal
                International Journal of Epidemiology
                International Journal of Epidemiology
                Oxford University Press (OUP)
                0300-5771
                1464-3685
                June 16 2015
                April 01 2015
                January 17 2015
                April 01 2015
                : 44
                : 2
                : 462-471
                Article
                10.1093/ije/dyu251
                25596586
                4ae25818-8691-4377-8f35-af6eef5441f3
                © 2015
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