Detecting local risk factors for residual malaria in northern Ghana using Bayesian model averaging

Abstract Background There is a need for comprehensive evaluations of the underlying local factors that contribute to residual malaria in sub-Saharan Africa. However, it is difficult to compare the wide array of demographic, socio-economic, and environmental variables associated with malaria transmission using standard statistical approaches while accounting for seasonal differences and nonlinear relationships. This article uses a Bayesian model averaging (BMA) approach for identifying and comparing potential risk and protective factors associated with residual malaria. Results The relative influence of a comprehensive set of demographic, socio-economic, environmental, and malaria intervention variables on malaria prevalence were modelled using BMA for variable selection. Data were collected in Bunkpurugu-Yunyoo, a rural district in northeast Ghana that experiences holoendemic seasonal malaria transmission, over six biannual surveys from 2010 to 2013. A total of 10,022 children between the ages 6 to 59 months were used in the analysis. Multiple models were developed to identify important risk and protective factors, accounting for seasonal patterns and nonlinear relationships. These models revealed pronounced nonlinear associations between malaria risk and distance from the nearest urban centre and health facility. Furthermore, the association between malaria risk and age and some ethnic groups was significantly different in the rainy and dry seasons. BMA outperformed other commonly used regression approaches in out-of-sample predictive ability using a season-to-season validation approach. Conclusions This modelling framework offers an alternative approach to disease risk factor analysis that generates interpretable models, can reveal complex, nonlinear relationships, incorporates uncertainty in model selection, and produces accurate predictions. Certain modelling applications, such as designing targeted local interventions, require more sophisticated statistical methods which are capable of handling a wide range of relevant data while maintaining interpretability and predictive performance, and directly characterize uncertainty. To this end, BMA represents a valuable tool for constructing more informative models for understanding risk factors for malaria, as well as other vector-borne and environmentally mediated diseases

Characterizing local-scale heterogeneity of malaria risk: a case study in Bunkpurugu-Yunyoo district in northern Ghana

Abstract Background Bayesian 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. Methods In 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. Results The 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. Conclusions This 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

Impact of indoor residual spraying on malaria parasitaemia in the Bunkpurugu-Yunyoo District in northern Ghana

Abstract Background Since 2008 indoor residual spraying (IRS) has become one of the interventions for malaria control in Ghana. Key partners in the scale-up of IRS have been the US President’s Malaria Initiative (PMI) and AngloGold Ashanti (AGA). This study was designed to assess the impact of IRS on malaria parasitaemia among children less than 5 years-old in Bunkpurugu-Yunyoo, one of PMI-sponsored districts in northern Ghana, where rates of parasitaemia significantly exceeded the national average. Methods Two pre-IRS cross-sectional surveys using microscopy were conducted in November 2010 and April 2011 to provide baseline estimates of malaria parasitaemia for the high and low transmission seasons, respectively. IRS for the entire district was conducted in May/June to coincide with the beginning of the rains. Alpha-cypermethrin was used in 2011 and 2012, and changed to pirimiphos-methyl in 2013 and 2014 following declining susceptibility of local vectors to pyrethroids. Post-IRS cross-sectional surveys were conducted between 2011 and 2014 to provide estimates for the end of high (2011–2014) and the end of low (2012–2013) transmission seasons. Results The end of high transmission season prevalence of asexual parasitaemia declined marginally from 52.4% (95% CI: 50.0–54.7%) to 47.7% (95% CI: 45.5–49.9%) following 2 years of IRS with alpha-cypermethrin. Prevalence declined substantially to 20.6% (95% CI: 18.4–22.9%) following one year of IRS with pirimiphos-methyl. Conclusions The use of a more efficacious insecticide for IRS can reduce malaria parasitaemia among children less than 5 years-old in northern Ghana

A reduction in malaria transmission intensity in Northern Ghana after 7 years of indoor residual spraying

Abstract Background Indoor residual spraying (IRS) is being implemented as one of the malaria prevention methods in the Northern Region of Ghana. Changes in longevity, sporozoite and entomological inoculation rates (EIRs) of major malaria vectors were monitored to assess the impact of IRS in selected districts. Methods Monthly human landing catches (HLCs) were used to collect mosquitoes from sentinel sites in three adjacent districts between July 2009 and December 2014: Savelugu Nanton (SND) where IRS had been implemented from 2008 to 2014; Tolon Kumbungu (TKD) where IRS had been implemented between 2008 and 2012 and Tamale Metropolis (TML) with no history of IRS. Mosquitoes were morphologically identified to species level and into sibling species, using PCR. Samples of Anopheles gambiae sensu lato (s.l.) were examined for parity and infectivity. EIR was calculated from biting and infectivity rates of malaria vectors. Results Parity rates of An. gambiae s.l. decreased significantly (p < 0.0001) in SND from 44.8% in 2011 to 28.1% by 2014, and in TKD from 53.3% in 2011 to 46.6% in 2012 (p = 0.001). However 2 years after IRS was discontinued in TKD, the proportion of parous An. gambiae s.l. increased significantly to 68.5% in 2014 (p < 0.0001). Parity rates in the unsprayed district remained high throughout the study period, ranging between 68.6% in 2011 and 72.3% in 2014. The sum of monthly EIRs post-IRS season (July–December) in SND ranged between 2.1 and 6.3 infective bites/person/season (ib/p/s) during the 3 years that the district was sprayed with alphacypermethrin. EIR in SND was reduced to undetectable levels when the insecticide was switched to pirimiphos methyl CS in 2013 and 2014. Two years after IRS was withdrawn from TKD the sum of monthly EIRs (July–December) increased by about fourfold from 41.8 ib/p/s in 2012 to 154.4 ib/p/s in 2014. The EIR in the control area, TML, ranged between 35 ib/p/s in 2009 to 104.71 ib/p/s by 2014. Conclusions This study demonstrates that IRS application did have a significant impact on entomological indicators of malaria transmission in the IRS project districts of Northern Ghana. Transmission indicators increased following the withdrawal of IRS from Tolon Kumbungu District