Geographical disparities in core population coverage indicators for roll back malaria in Malawi

BACKGROUND: Implementation of known effective interventions would necessitate the reduction of malaria burden by half by the year 2010. Identifying geographical disparities of coverage of these interventions at small area level is useful to inform where greatest scaling-up efforts should be concentrated. They also provide baseline data against which future scaling-up of interventions can be compared. However, population data are not always available at local level. This study applied spatial smoothing methods to generate maps at subdistrict level in Malawi to serve such purposes. METHODS: Data for the following responses from the 2000 Malawi Demographic and Health Survey (DHS) were aggregated at subdistrict level: (1) households possessing at least one bednet; (2) children under 5 years who slept under a bednet the night before the survey; (3) bednets retreated with insecticide within past 6-12 months preceding the survey; (4) children under 5 who had fever two weeks before the survey and received treatment within 24 hours from the onset of fever; and (5) women who received intermittent preventive treatment of malaria during their last pregnancy. Each response was geographically smoothed at subdistrict level by applying conditional autoregressive models using Markov Chain Monte Carlo simulation techniques. RESULTS: The underlying geographical patterns of coverage of indicators were more clear in the smoothed maps than in the original unsmoothed maps, with relatively high coverage in urban areas than in rural areas for all indicators. The percentage of households possessing at least one bednet was 19% (95% credible interval (CI): 16-21%), with 9% (95% CI: 7-11%) of children sleeping under a net, while 18% (95% CI: 16-19%) of households had retreated their nets within past 12 months prior to the survey. The northern region and lakeshore areas had high bednet coverage, but low usage and re-treatment rates. Coverage rate of children who received antimalarial treatment within 24 hours after onset of fever was consistently low for most parts of the country, with mean coverage of 4.8% (95% CI: 4.5-5.0%). About 48% (95% CI: 47-50%) of women received antimalarial prophylaxis during their pregnancy, with highest rates in the southern and northern areas. CONCLUSION: The striking geographical patterns, for example between predominantly urban and rural areas, may reflect spatial differences in provider compliance or coverage, and can partly be explained by socio-economic and cultural differences. The wide gap between high bed net coverage and low retreatment rates may reflect variation in perceptions about malaria, which may be addressed by implementing information, education and communication campaigns or introducing long lasting insecticide nets. Our results demonstrate that DHS data, with appropriate methodology, can provide acceptable estimates at sub-national level for monitoring and evaluation of malaria control goals

The use of schools for malaria surveillance and programme evaluation in Africa

Effective malaria control requires information on both the geographical distribution of malaria risk and the effectiveness of malaria interventions. The current standard for estimating malaria infection and impact indicators are household cluster surveys, but their complexity and expense preclude frequent and decentralized monitoring. This paper reviews the historical experience and current rationale for the use of schools and school children as a complementary, inexpensive framework for planning, monitoring and evaluating malaria control in Africa. Consideration is given to (i) the selection of schools; (ii) diagnosis of infection in schools; (iii) the representativeness of schools as a proxy of the communities they serve; and (iv) the increasing need to evaluate interventions delivered through schools. Finally, areas requiring further investigation are highlighted

Fine resolution mapping of population age-structures for health and development applications

The age-group composition of populations varies considerably across the world, and obtaining accurate, spatially detailed estimates of numbers of children under 5 years is important in designing vaccination strategies, educational planning or maternal healthcare delivery. Traditionally, such estimates are derived from population censuses, but these can often be unreliable, outdated and of coarse resolution for resource-poor settings. Focusing on Nigeria, we use nationally representative household surveys and their cluster locations to predict the proportion of the under-five population in 1 × 1 km using a Bayesian hierarchical spatio-temporal model. Results showed that land cover, travel time to major settlements, night-time lights and vegetation index were good predictors and that accounting for fine-scale variation, rather than assuming a uniform proportion of under 5 year olds can result in significant differences in health metrics. The largest gaps in estimated bednet and vaccination coverage were in Kano, Katsina and Jigawa. Geolocated household surveys are a valuable resource for providing detailed, contemporary and regularly updated population age-structure data in the absence of recent census data. By combining these with covariate layers, age-structure maps of unprecedented detail can be produced to guide the targeting of interventions in resource-poor settings