Abstract
BackgroundBayesian methods have been used to generate country-level and global maps of malaria prevalence. With increasing availability of detailed malaria surveillance data, these methodologies can also be used to identify fine-scale heterogeneity of malaria parasitaemia for operational prevention and control of malaria.MethodsIn this article, a Bayesian geostatistical model was applied to six malaria parasitaemia surveys conducted during rainy and dry seasons between November 2010 and 2013 to characterize the micro-scale spatial heterogeneity of malaria risk in northern Ghana.ResultsThe geostatistical model showed substantial spatial heterogeneity, with malaria parasite prevalence varying between 19 and 90%, and revealing a northeast to southwest gradient of predicted risk. The spatial distribution of prevalence was heavily influenced by two modest urban centres, with a substantially lower prevalence in urban centres compared to rural areas. Although strong seasonal variations were observed, spatial malaria prevalence patterns did not change substantially from year to year. Furthermore, independent surveillance data suggested that the model had a relatively good predictive performance when extrapolated to a neighbouring district.ConclusionsThis high variability in malaria prevalence is striking, given that this small area (approximately 30 km × 40 km) was purportedly homogeneous based on country-level spatial analysis, suggesting that fine-scale parasitaemia data might be critical to guide district-level programmatic efforts to prevent and control malaria. Extrapolations results suggest that fine-scale parasitaemia data can be useful for spatial predictions in neighbouring unsampled districts and does not have to be collected every year to aid district-level operations, helping to alleviate concerns regarding the cost of fine-scale data collection.
Highlights
Bayesian methods have been used to generate country-level and global maps of malaria prevalence
The outcome used throughout this paper was microscopy-based malaria status of individuals sampled by parasitaemia household surveys that were conducted between October 2010 and March 2013 in the Bunkpurugu-Yunyoo district (BYD), Northern Region, Ghana
Malaria prevalence The study included 10,518 children aged 6–59 months of age with a complete microscopy diagnostic test result for malaria parasitaemia collected in 438 communities across 3 rainy seasons and 3 dry seasons
Summary
Bayesian methods have been used to generate country-level and global maps of malaria prevalence. Over the past two decades, Ghana has made significant progress towards reducing malaria mortality [1] This progress can be attributed to increasing coverage and improving access to rapid diagnostic tests and artemisinin-based combination therapy, implementing universal access to insecticide-treated bed nets, scaling-up indoor residual spraying (IRS) [2, 3] as well as climate change, urbanization patterns and infrastructural development [4, 5]. Despite these country-wide efforts for malaria control and prevention [6], and improved infrastructure, malaria morbidity remains relatively high [7]. The 2016 Ghana Malaria Indicator Survey (MIS) revealed regional childhood prevalence estimates ranging between 5 and 31%, but these aggregated estimates may understate substantial heterogeneity within and between districts in each region [5]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
