South African Centre for Epidemiological Modelling and Analysis (SACEMA)

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https://scholar.sun.ac.za/handle/10019.1/96225
The South African Centre for Epidemiological Modelling and Analysis (SACEMA) is a national research centre established under the Centre of Excellence programme of the Department of Science and Technology and the National Research Foundation. The Centre focuses on research in quantitative modelling of the spatial and temporal patterns of disease. The immediate aim of the research is to understand and predict the development of various diseases, and thereby to provide advice on how best to combat them. Our research focuses on issues pertaining to HIV, TB and malaria, although not to the exclusion of other epidemiological problems.

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Browsing South African Centre for Epidemiological Modelling and Analysis (SACEMA) by Author "Adetokunboh, Olatunji"

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    Does economic growth reduce childhood stunting? a multicountry analysis of 89 demographic and health surveys in sub-Saharan Africa
    (BMJ Publishing, 2020-01) Yaya, Sanni; Uthman, Olalekan A.; Kunnuji, Michael; Navaneetham, Kannan; Akinyemi, Joshua O.; Kananura, Rornald Muhumuza; Adjiwanou, Visseho; Adetokunboh, Olatunji; Bishwajit, Ghose
    Background: There is mixed evidence and lack of consensus on the impact of economic development on stunting, and likewise there is a dearth of empirical studies on this relationship in the case of sub-Saharan Africa. Thus, this paper examines whether economic growth is associated with childhood stunting in low-income and middle-income sub-Saharan African countries. Methods: We analysed data from 89 Demographic and Health Surveys conducted between 1987 and 2016 available as of October 2018 using multivariable multilevel logistic regression models to show the association between gross domestic product (GDP) per capita and stunting. We adjusted the models for child’s age, survey year, child’s sex, birth order and country random effect, and presented adjusted and unadjusted ORs. Results: We included data from 490 526 children. We found that the prevalence of stunting decreased with increasing GDP per capita (correlation coefficient=−0.606, p<0.0001). In the unadjusted model for full sample, for every US$1000 increase in GDP per capita, the odds of stunting decreased by 23% (OR=0.77, 95% CI 0.76 to 0.78). The magnitude of the association between GDP per capita and stunting was stronger among children in the richest quintile. After adjustment was made, the association was not significant among children from the poorest quintile. However, the magnitude of the association was more pronounced among children from low-income countries, such that, in the model adjusted for child’s age, survey year, child’s sex, birth order and country random effect, the association between GDP per capita and stunting remained statistically significant; for every US$1000 increase in GDP per capita, the odds of stunting decreased by 12% (OR=0.88, 95% CI 0.87 to 0.90). Conclusion: There was no significant association between economic growth and child nutritional status. The prevalence of stunting decreased with increasing GDP per capita. This was more pronounced among children from the richest quintile. The magnitude of the association was higher among children from low-income countries, suggesting that households in the poorest quintile were typically the least likely to benefit from economic gains. The findings could serve as a building block needed to modify current policy as per child nutrition-related programmes in Africa.
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    Engaging community health workers in maternal and infant death identification in Khayelitsha, South Africa : a pilot study
    (BMC (part of Springer Nature), 2020-11-26) Igumbor, Jude; Adetokunboh, Olatunji; Muller, Jocelyn; Bosire, Edna N.; Ajuwon, Ademola; Phetlhu, Rene; Mbule, Marjorie; Ronan, Agnes; Burtt, Fiona; Scheepers, Esca; Schmitz, Kathrin
    Background: Engaging community health workers in a formalised death review process through verbal and social autopsy has been utilised in different settings to estimate the burden and causes of mortality, where civil registration and vital statistics systems are weak. This method has not been widely adopted. We piloted the use of trained community health workers (CHW) to investigate the extent of unreported maternal and infant deaths in Khayelitsha and explored requirements of such a programme and the role of CHWs in bridging gaps. Methods: This was a mixed methods study, incorporating both qualitative and quantitative methods. Case identification and data collection were done by ten trained CHWs. Quantitative data were collected using a structured questionnaire. Qualitative data were collected using semi-structured interview guides for key informant interviews, focus group discussions and informal conversations. Qualitative data were analysed thematically using a content analysis approach. Results: Although more than half of the infant deaths occurred in hospitals (n = 11/17), about a quarter that occurred at home (n = 4/17) were unreported. Main causes of deaths as perceived by family members of the deceased were related to uncertainty about the quality of care in the facilities, socio-cultural and economic contexts where people lived and individual factors. Most unreported deaths were further attributed to weak facilitycommunity links and socio-cultural practices. Fragmented death reporting systems were perceived to influence the quality of the data and this impacted on the number of unreported deaths. Only two maternal deaths were identified in this pilot study. Conclusions: CHWs can conduct verbal and social autopsy for maternal and infant deaths to complement formal vital registration systems. Capacity development, stakeholder’s engagement, supervision, and support are essential for a community-linked death review system. Policymakers and implementers should establish a functional relationship between community-linked reporting systems and the existing system as a starting point. There is a need for more studies to confirm or build on our pilot findings.