Modelling spatiotemporal patterns of childhood HIV/TB related mortality and malnutrition: applications to Agincourt data in rural South Africa

Musenge, Eustasius
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Background: South Africa accounts for more than a seventh of the global population living with HIV/AIDS and TB, and ranks highest in HIV/TB co-infection worldwide. Consequent high child mortality is exacerbated by child malnutrition, which is an important indicator of health status and is associated with morbidity as well as mortality. Rural areas usually present with the greatest burden of morbidity and mortality, yet the extent of geographical disparities in child mortality, malnutrition and HIV/TB has hardly been explored. This is a reservoir of information useful for effective public health interventions. In this thesis we investigated the factors associated with childhood HIV/TB mortality and malnutrition, how they interrelate and their spatial distribution in the rural Agincourt sub-district located in north-east South Africa close to the border with Mozambique. Rationale: Africa at large lacks data that are routinely and reliably collected then validated, to guide policy and intervention programmes. Causes of deaths and even death counts are often misclassified and underestimated respectively, especially for children. To bridge this gap, a health and socio-demographic surveillance systems located in the rural Agincourt sub-district hosts which annually collects and collates data on vital events including fertility, mortality and migration. These data have been collected since 1992 to-date and now cover 80,000 people living in more than 16,000 households situated in 27 villages; all households are fully geo-coded. These hierarchical data allow us to address several epidemiological questions on how person, place (spatial) and time (temporality) have impacted on mortality and malnutrition patterns in children living in the rural Agincourt sub-district. Objectives: The aims of this thesis were both methodological and applied: Methodological (1) To investigate the presence of spatial autocorrelation in the Agincourt sub-district and model this using geographical and geo-statistical procedures (2) To model large spatial random effects accurately and efficiently (3) To model hierarchical data with zero inflated outcomes Applied (1) To investigate childhood HIV/TB mortality determinants and their geographical distribution using retrospective and cross-sectional data (2) To determine factors associated with malnutrition outcomes adjusting for their multivariate spatial random effects and selection bias for children under five years (3) To model how the associated factors were interrelated as either underlying or proximate factors of child mortality or malnutrition using pathway analysis. Methods: We conducted a secondary data analysis based on retrospective and cross-sectional data collected from 1992 to 2010 from the Agincourt sub-district in rural northeast South Africa. During the period of our study 71,057 children aged 0 to 9 years from 15,703 households were observed. All the data in the thesis were for children aged 1 to under 5 except for the chapter 6 (last paper) who were aged from 0 to 9 years of age. Child HIV/TB death and malnutrition were the outcome measures; mortality was derived from physicianbased verbal autopsy. We investigated presence of spatial autocorrelation using Moran’s and Geary’s coefficients, semi-variograms and estimated the spatial parameters using Bayesianbased univariate and multivariate procedures. Regression modelling that adjusted for spatial random effects was done using linear regression and zero inflated variants for logistic, Poisson and Negative Binomial regression models. Structural equation models were used in modelling the complex relationships between multiple exposures and child HIV/TB mortality and malnutrition portrayed by conceptual frameworks. Risk maps were drawn based on spatial residuals (posteriors) with prediction (kriging) procedures used to estimate for households where no data were observed. Statistical inference on parameter estimation was done using both the frequentist; maximum likelihood estimation and Bayesian; Markov Chain Monte Carlo (MCMC) directly and sometimes aided with Metropolis Hastings or Integrated Nested Laplace Approximations (INLA). Results: The levels of child under-nutrition in this area were: 6.6% wasted, 17.3% stunted and 9.9% underweight. Moran’s (I) and Geary’s (c) coefficients indicated that there was global and local clustering respectively. Estimated severity of spatial variation using the partial-sill-to-sill ratio yielded 12.1%, 4.7% and 16.5%, for weight-for-age, height-for-age and weight-for-height Z-scores measures respectively. Maternal death had the greatest negative impact on child HIV/TB mortality. Other determinants included being a male child and belonging to a household that had experienced multiple deaths. A protective effect was found in households with better socio-economic status and where older children were present. Pathway analyses of these factors showed that HIV had a significant mediator effect and the greatest worsening effect on malnutrition after controlling for low birth-weight selection bias Several spatial hot spots of mortality and malnutrition were observed, with these regions consistently emerging as areas of greater risk, which reinforces geographical differentials in these public health indicators. Conclusion: Modelling that adjusts for spatial random effects, is a potentially useful technique to disclose hidden patterns. These geographical differences are often ignored in epidemiological regression modelling resulting in reporting of biased estimates. Proximate and underlying determinants, notably socioeconomic status and maternal deaths, impacteddirectly and indirectly on child mortality and malnutrition. These factors are highly relevant locally and should be used to formulate interventions to reduce child mortality. Spatial prediction maps can guide policy on where to best target interventions. Child interventions can be more effective if there is a dual focus: treatment and care for those already HIV/TB infected, coupled with prevention in those geographical areas of greatest risk. Public health population-level interventions aimed at reducing child malnutrition are pivotal in lowering morbidity and mortality in remote areas. Keywords: HIV/TB, Child mortality, Child malnutrition, Conceptual framework, Spatial analysis, MCMC, Path analysis, South Africa
child mortality, HIV/TB, conceptual framework, spatial analysis, path analysis, South Africa