Abstract

The Research Center for Human Development in Dakar (CRDH) with the technical assistance of ICF Macro and the National Malaria Control Programme (NMCP) conducted in 2008/2009 the Senegal Malaria Indicator Survey (SMIS), the first nationally representative household survey collecting parasitological data and malaria-related indicators. In this paper, we present spatially explicit parasitaemia risk estimates and number of infected children below 5 years. Geostatistical Zero-Inflated Binomial models (ZIB) were developed to take into account the large number of zero-prevalence survey locations (70%) in the data. Bayesian variable selection methods were incorporated within a geostatistical framework in order to choose the best set of environmental and climatic covariates associated with the parasitaemia risk. Model validation confirmed that the ZIB model had a better predictive ability than the standard Binomial analogue. Markov chain Monte Carlo (MCMC) methods were used for inference. Several insecticide treated nets (ITN) coverage indicators were calculated to assess the effectiveness of interventions. After adjusting for climatic and socio-economic factors, the presence of at least one ITN per every two household members and living in urban areas reduced the odds of parasitaemia by 86% and 81% respectively. Posterior estimates of the ORs related to the wealth index show a decreasing trend with the quintiles. Infection odds appear to be increasing with age. The population-adjusted prevalence ranges from 0.12% in Thillé-Boubacar to 13.1% in Dabo. Tambacounda has the highest population-adjusted predicted prevalence (8.08%) whereas the region with the highest estimated number of infected children under the age of 5 years is Kolda (13940). The contemporary map and estimates of malaria burden identify the priority areas for future control interventions and provide baseline information for monitoring and evaluation. Zero-Inflated formulations are more appropriate in modeling sparse geostatistical survey data, expected to arise more frequently as malaria research is focused on elimination.

Highlights

  • More than two hundred million cases of malaria were estimated worldwide in 2008 and the majority (85%) was in African countries

  • The main parasite transmitted by anopheline mosquitoes is Plasmodium falciparum and transmission occurs seasonally in the entire country, from June to November

  • We provide spatially explicit burden estimates of malaria in Senegal using the Senegal Malaria Indicator Survey (SMIS) data and Bayesian geostatistical Zero-Inflated Binomial models based on variable selection methods for spatial data

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Summary

Introduction

More than two hundred million cases of malaria were estimated worldwide in 2008 and the majority (85%) was in African countries. Malaria accounted for 850 thousand deaths in the same year, 89% of which occurred in Africa. Malaria incidence in children under five decreased from 400 000 suspected cases in 2006 to 30 000 confirmed cases in 2009 [4]. Routine surveillance provides some evidence that the number of malaria inpatient cases and deaths during the same period are decreasing. These estimates must be interpreted with caution since they are affected by poor reporting, introduction of RDTs as well as changes in case definition [1]. Few studies have been conducted in the rest of the country, in the regions of Tambacounda and Casamance

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