The U.S. President's Malaria Initiative's Support for Improving the Quality of Malaria Case Management Services: Fifteen Years of Progress and Learning.

Since its launch in 2005, the U.S. President's Malaria Initiative's (PMI) investment in malaria case management has evolved based on lessons learned from its support to countries. An initial focus on updating malaria treatment policies to adopt artemisinin-based combination therapies achieved limited success, in part because of the poor quality of diagnostic and treatment services in targeted countries. In response, the PMI supported the development, refinement, and expansion of Outreach Training and Supportive Supervision (OTSS), a quality improvement approach that combines structured, competency-based supervision with corrective measures, including on-the-job training, coaching, troubleshooting, action planning, and timely follow-up. With 15 years of experience, the OTSS approach has been adopted by more than a dozen countries, and its effectiveness in improving the quality of malaria case management services has been documented. Through the PMI Impact Malaria Project, launched in 2018, the OTSS approach was expanded beyond case management of uncomplicated malaria to support quality improvement of inpatient management of severe malaria and malaria in pregnancy services delivered through antenatal care clinics. The OTSS platform also enabled targeted countries to respond rapidly to the COVID-19 pandemic by adding modules related to clinical management and laboratory diagnosis of suspected cases. The OTSS approach has been established as an effective approach to improve the quality of clinical malaria services and can be expanded to cover other health priorities. Further innovations to improve the quality of inpatient and community-based services, and further integration and institutionalization of OTSS into country health systems are needed.

Developing High-Resolution Population and Settlement Data for Impactful Malaria Interventions in Zambia.

Foundational high-resolution geospatial data products for population, settlements, infrastructure, and boundaries may greatly enhance the efficient planning of resource allocation during health sector interventions. To ensure the relevance and sustainability of such products, government partners must be involved from the beginning in their creation, improvement, and/or management, so they can be successfully applied to public health campaigns, such as malaria control and prevention. As an example, Zambia had an ambitious strategy of reaching the entire population with malaria vector control campaigns by late 2020 or early 2021, but they lacked the requisite accurate and up-to-date data on infrastructure and population distribution. To address this gap, the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) program, Akros, and other partners developed maps and planning templates to aid Zambia's National Malaria Elimination Program (NMEP) in operationalizing its strategy.

Guiding placement of health facilities using multiple malaria criteria and an interactive tool.

BACKGROUND: Access to healthcare is important in controlling malaria burden and, as a result, distance or travel time to health facilities is often a significant predictor in modelling malaria prevalence. Adding new health facilities may reduce overall travel time to health facilities and may decrease malaria transmission. To help guide local decision-makers as they scale up community-based accessibility, the influence of the spatial allocation of new health facilities on malaria prevalence is evaluated in Bunkpurugu-Yunyoo district in northern Ghana. A location-allocation analysis is performed to find optimal locations of new health facilities by separately minimizing three district-wide objectives: malaria prevalence, malaria incidence, and average travel time to health facilities. METHODS: Generalized additive models was used to estimate the relationship between malaria prevalence and travel time to the nearest health facility and other geospatial covariates. The model predictions are then used to calculate the optimisation criteria for the location-allocation analysis. This analysis was performed for two scenarios: adding new health facilities to the existing ones, and a hypothetical scenario in which the community-based healthcare facilities would be allocated anew. An interactive web application was created to facilitate efficient presentation of this analysis and allow users to experiment with their choice of health facility location and optimisation criteria. RESULTS: Using malaria prevalence and travel time as optimisation criteria, two locations that would benefit from new health facilities were identified, regardless of scenarios. Due to the non-linear relationship between malaria incidence and prevalence, the optimal locations chosen based on the incidence criterion tended to be inequitable and was different from those based on the other optimisation criteria. CONCLUSIONS: This study findings underscore the importance of using multiple optimisation criteria in the decision-making process. This analysis and the interactive application can be repurposed for other regions and criteria, bridging the gap between science, models and decisions.

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

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.

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

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.

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

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.

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.

Outdoor-sleeping and other night-time activities in northern Ghana: implications for residual transmission and malaria prevention.

BACKGROUND: Despite targeted indoor residual spraying (IRS) over a six-year period and free mass distribution of long-lasting insecticide-treated nets (ITNs), malaria rates in northern Ghana remain high. Outdoor sleeping and other night-time social, cultural and economic activities that increase exposure to infective mosquito bites are possible contributors. This study was designed to document these phenomena through direct observation, and to explore the context in which they occur. METHODS: During the late dry season months of February and March 2014, study team members carried out continuous household observations from dusk to dawn in one village in Ghana's Northern Region and one in Upper West Region. In-depth interviews with health workers and community residents helped supplement observational findings. RESULTS: Study team members completed observations of 182 individuals across 24 households, 12 households per site. Between the two sites, they interviewed 14 health workers, six community health volunteers and 28 community residents. In early evening, nearly all study participants were observed to be outdoors and active. From 18.00-23.00 hours, socializing, night school, household chores, and small-scale economic activities were common. All-night funerals, held outdoors and attended by large numbers of community members, were commonly reported and observed. Outdoor sleeping was frequently documented at both study sites, with 42% of the study population sleeping outdoors at some time during the night. While interviewees mentioned bed net use as important to malaria prevention, observed use was low for both indoor and outdoor sleeping. Net access within households was 65%, but only 17% of those with access used a net at any time during the night. Participants cited heat as the primary barrier and reported higher net use during the rainy season. DISCUSSION: Outdoor sleeping and other night-time activities were extensive, and could significantly increase malaria risk. These findings suggest that indoor-oriented control measures such as ITNs and IRS are insufficient to eliminate malaria in this setting, especially given the low net use observed. Development and evaluation of complementary outdoor control strategies should be prioritized. A research agenda is proposed to quantify the relative risk of outdoor night-time activities and test potential vector control interventions that might reduce that risk.