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The Nigerian HIV/AIDS pandemic is made up of multiple epidemics spatially located in different parts of the country with most of them having the potential of being sustained into the future given information on some risk factors.It is hoped that the findings of this research will be a ready tool in the hands of policy makers in the formulation of policy and design of programs to combat the epidemic in the country.
Estimates of cumulative HIV infection in Nigeria were obtained from both parametric and nonparametric back-calculation methods.
Step and spline functions were assumed for the HIV infection curve in the parametric case.
Results confirmed significant spatial effects and some ecological factors were significant in explaining the variation.
Also, variation due to various levels of aggregation was prominent.
The constant hazard of routine testing and the proportionality coefficient of symptom-related tests were estimated from the data and incorporated into the HIV induction distribution function.
Estimates of HIV prevalence differ widely (about three times higher) from those obtained using parametric and ordinary nonparametric back-calculation methods.
Cumulative HIV infection estimates obtained using the step function models were comparable with those obtained using nonparametric back-calculation methods.
Estimates from nonparametric back-calculation were obtained using the EMS algorithm.
GAM and local regression fit on the data revealed spatial trends on the north-south and east - west axis.
Analysis of hierarchical, spatial and ecological factor effects on the geographical variation of HIV prevalence using variance component and spatial multilevel models was performed using restricted maximum likelihood implemented in R and empirical and full Bayesian methods in Win BUGS.