Assessing the effects of malaria interventions on the geographical distribution of parasitaemia risk in Burkina Faso

Relative effects of climate factors and malaria control interventions on changes of parasitaemia risk in Burkina Faso from 2014 to 2017/2018

BACKGROUND

In Burkina Faso, the prevalence of malaria has decreased over the past two decades, following the scale-up of control interventions. The successful development of malaria parasites depends on several climatic factors. Intervention gains may be reversed by changes in climatic factors. In this study, we investigated the role of malaria control interventions and climatic factors in influencing changes in the risk of malaria parasitaemia.

METHODS

Bayesian logistic geostatistical models were fitted on Malaria Indicator Survey data from Burkina Faso obtained in 2014 and 2017/2018 to estimate the effects of malaria control interventions and climatic factors on the temporal changes of malaria parasite prevalence. Additionally, intervention effects were assessed at regional level, using a spatially varying coefficients model.

RESULTS

Temperature showed a statistically important negative association with the geographic distribution of parasitaemia prevalence in both surveys; however, the effects of insecticide-treated nets (ITNs) use was negative and statistically important only in 2017/2018. Overall, the estimated number of infected children under the age of 5 years decreased from 704,202 in 2014 to 290,189 in 2017/2018. The use of ITNs was related to the decline at national and regional level, but coverage with artemisinin-based combination therapy only at regional level.

CONCLUSION

Interventions contributed more than climatic factors to the observed change of parasitaemia risk in Burkina Faso during the period of 2014 to 2017/2018. Intervention effects varied in space. Longer time series analyses are warranted to determine the differential effect of a changing climate on malaria parasitaemia risk.

Safety and immunogenicity of BK-SE36 in a blinded, randomized, controlled, age de-escalating phase Ib clinical trial in Burkinabe children

Background

A blood-stage vaccine targeting the erythrocytic-stages of the malaria parasite Plasmodium falciparum could play a role to protect against clinical disease. Antibodies against the P. falciparum serine repeat antigen 5 (SE47 and SE36 domains) correlate well with the absence of clinical symptoms in sero-epidemiological studies. A previous phase Ib trial of the recombinant SE36 antigen formulated with aluminum hydroxyl gel (BK-SE36) was promising. This is the first time the vaccine candidate was evaluated in young children below 5 years using two vaccination routes.

Methods

Safety and immunogenicity of BK-SE36 was assessed in a double-blind, randomized, controlled, age de-escalating phase Ib trial. Fifty-four Burkinabe children in each age cohort, 25–60 or 12–24 months, were randomized in a 1:1:1 ratio to receive three doses of BK-SE36 either by intramuscular (BK IM) or subcutaneous (BK SC) route on Day 0, Week 4, and 26; or the control vaccine, Synflorix^®via IM route on Day 0, Week 26 (and physiological saline on Week 4). Safety data and samples for immunogenicity analyses were collected at various time-points.

Results

Of 108 subjects, 104 subjects (96.3%) (Cohort 1: 94.4%; Cohort 2: 98.1%) received all three scheduled vaccine doses. Local reactions, mostly mild or of moderate severity, occurred in 99 subjects (91.7%). The proportion of subjects that received three doses without experiencing Grade 3 adverse events was similar across BK-SE36 vaccines and control arms (Cohort 1: 100%, 89%, and 89%; and Cohort 2: 83%, 82%, and 83% for BK IM, BK SC, and control, respectively). BK-SE36 vaccine was immunogenic, inducing more than 2-fold change in antibody titers from pre-vaccination, with no difference between the two vaccination routes. Titers waned before the third dose but in both cohorts titers were boosted 6 months after the first vaccination. The younger cohort had 2-fold and 4-fold higher geometric mean titers compared to the 25- to 60-month-old cohort after 2 and 3 doses of BK-SE36, respectively.

Conclusion

BK-SE36 was well tolerated and immunogenic using either intramuscular or subcutaneous routes, with higher immune response in the younger cohort.

Clinical Trial Registration

https://pactr.samrc.ac.za/TrialDisplay.aspx?TrialID=934, identifier PACTR201411000934120.

Plasmodium falciparum parasite prevalence in East Africa: Updating data for malaria stratification

The High Burden High Impact (HBHI) strategy for malaria encourages countries to use multiple sources of available data to define the sub-national vulnerabilities to malaria risk, including parasite prevalence. Here, a modelled estimate of Plasmodium falciparum from an updated assembly of community parasite survey data in Kenya, mainland Tanzania, and Uganda is presented and used to provide a more contemporary understanding of the sub-national malaria prevalence stratification across the sub-region for 2019. Malaria prevalence data from surveys undertaken between January 2010 and June 2020 were assembled form each of the three countries. Bayesian spatiotemporal model-based approaches were used to interpolate space-time data at fine spatial resolution adjusting for population, environmental and ecological covariates across the three countries. A total of 18,940 time-space age-standardised and microscopy-converted surveys were assembled of which 14,170 (74.8%) were identified after 2017. The estimated national population-adjusted posterior mean parasite prevalence was 4.7% (95% Bayesian Credible Interval 2.6-36.9) in Kenya, 10.6% (3.4-39.2) in mainland Tanzania, and 9.5% (4.0-48.3) in Uganda. In 2019, more than 12.7 million people resided in communities where parasite prevalence was predicted ≥ 30%, including 6.4%, 12.1% and 6.3% of Kenya, mainland Tanzania and Uganda populations, respectively. Conversely, areas that supported very low parasite prevalence (<1%) were inhabited by approximately 46.2 million people across the sub-region, or 52.2%, 26.7% and 10.4% of Kenya, mainland Tanzania and Uganda populations, respectively. In conclusion, parasite prevalence represents one of several data metrics for disease stratification at national and sub-national levels. To increase the use of this metric for decision making, there is a need to integrate other data layers on mortality related to malaria, malaria vector composition, insecticide resistance and bionomic, malaria care-seeking behaviour and current levels of unmet need of malaria interventions.

Spatial and spatio-temporal methods for mapping malaria risk: a systematic review

Background

Approaches in malaria risk mapping continue to advance in scope with the advent of geostatistical techniques spanning both the spatial and temporal domains. A substantive review of the merits of the methods and covariates used to map malaria risk has not been undertaken. Therefore, this review aimed to systematically retrieve, summarise methods and examine covariates that have been used for mapping malaria risk in sub-Saharan Africa (SSA).

Methods

A systematic search of malaria risk mapping studies was conducted using PubMed, EBSCOhost, Web of Science and Scopus databases. The search was restricted to refereed studies published in English from January 1968 to April 2020. To ensure completeness, a manual search through the reference lists of selected studies was also undertaken. Two independent reviewers completed each of the review phases namely: identification of relevant studies based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, data extraction and methodological quality assessment using a validated scoring criterion.

Results

One hundred and seven studies met the inclusion criteria. The median quality score across studies was 12/16 (range: 7–16). Approximately half (44%) of the studies employed variable selection techniques prior to mapping with rainfall and temperature selected in over 50% of the studies. Malaria incidence (47%) and prevalence (35%) were the most commonly mapped outcomes, with Bayesian geostatistical models often (31%) the preferred approach to risk mapping. Additionally, 29% of the studies employed various spatial clustering methods to explore the geographical variation of malaria patterns, with Kulldorf scan statistic being the most common. Model validation was specified in 53 (50%) studies, with partitioning data into training and validation sets being the common approach.

Conclusions

Our review highlights the methodological diversity prominent in malaria risk mapping across SSA. To ensure reproducibility and quality science, best practices and transparent approaches should be adopted when selecting the statistical framework and covariates for malaria risk mapping. Findings underscore the need to periodically assess methods and covariates used in malaria risk mapping; to accommodate changes in data availability, data quality and innovation in statistical methodology.

Geospatial estimation of reproductive, maternal, newborn and child health indicators: a systematic review of methodological aspects of studies based on household surveys

BACKGROUND

Geospatial approaches are increasingly used to produce fine spatial scale estimates of reproductive, maternal, newborn and child health (RMNCH) indicators in low- and middle-income countries (LMICs). This study aims to describe important methodological aspects and specificities of geospatial approaches applied to RMNCH coverage and impact outcomes and enable non-specialist readers to critically evaluate and interpret these studies.

METHODS

Two independent searches were carried out using Medline, Web of Science, Scopus, SCIELO and LILACS electronic databases. Studies based on survey data using geospatial approaches on RMNCH in LMICs were considered eligible. Studies whose outcomes were not measures of occurrence were excluded.

RESULTS

We identified 82 studies focused on over 30 different RMNCH outcomes. Bayesian hierarchical models were the predominant modeling approach found in 62 studies. 5 × 5 km estimates were the most common resolution and the main source of information was Demographic and Health Surveys. Model validation was under reported, with the out-of-sample method being reported in only 56% of the studies and 13% of the studies did not present a single validation metric. Uncertainty assessment and reporting lacked standardization, and more than a quarter of the studies failed to report any uncertainty measure.

CONCLUSIONS

The field of geospatial estimation focused on RMNCH outcomes is clearly expanding. However, despite the adoption of a standardized conceptual modeling framework for generating finer spatial scale estimates, methodological aspects such as model validation and uncertainty demand further attention as they are both essential in assisting the reader to evaluate the estimates that are being presented.

A Scoping Review of Spatial Analysis Approaches Using Health Survey Data in Sub-Saharan Africa

Spatial analysis has become an increasingly used analytic approach to describe and analyze spatial characteristics of disease burden, but the depth and coverage of its usage for health surveys data in Sub-Saharan Africa are not well known. The objective of this scoping review was to conduct an evaluation of studies using spatial statistics approaches for national health survey data in the SSA region. An organized literature search for studies related to spatial statistics and national health surveys was conducted through PMC, PubMed/Medline, Scopus, NLM Catalog, and Science Direct electronic databases. Of the 4,193 unique articles identified, 153 were included in the final review. Spatial smoothing and prediction methods were predominant (n = 108), followed by spatial description aggregation (n = 25), and spatial autocorrelation and clustering (n = 19). Bayesian statistics methods and lattice data modelling were predominant (n = 108). Most studies focused on malaria and fever (n = 47) followed by health services coverage (n = 38). Only fifteen studies employed nonstandard spatial analyses (e.g., spatial model assessment, joint spatial modelling, accounting for survey design). We recommend that for future spatial analysis using health survey data in the SSA region, there must be an improve recognition and awareness of the potential dangers of a naïve application of spatial statistical methods. We also recommend a wide range of applications using big health data and the future of data science for health systems to monitor and evaluate impacts that are not well understood at local levels.

Distance sampling for epidemiology: an interactive tool for estimating under-reporting of cases from clinic data

BACKGROUND

Distance sampling methods are widely used in ecology to estimate and map the abundance of animal and plant populations from spatial survey data. The key underlying concept in distance sampling is the detection function, the probability of detecting the occurrence of an event as a function of its distance from the observer, as well as other covariates that may influence detection. In epidemiology, the burden and distribution of infectious disease is often inferred from cases that are reported at clinics and hospitals. In areas with few public health facilities and low accessibility, the probability of detecting a case is also a function of the distance between an infected person and the "observer" (e.g. a health centre). While the problem of distance-related under-reporting is acknowledged in public health; there are few quantitative methods for assessing and correcting for this bias when mapping disease incidence. Here, we develop a modified version of distance sampling for prediction of infectious disease incidence by relaxing some of the framework's fundamental assumptions. We illustrate the utility of this approach using as our example malaria distribution in rural Burkina Faso, where there is a large population at risk but relatively low accessibility of health facilities.

RESULTS

The modified distance-sampling framework was used to predict the probability of reporting malaria infection at 8 rural clinics, based on road-travel distances from villages. The rate at which reporting probability dropped with distance varied between clinics, depending on road and clinic positions. The probability of case detection was estimated as 0.3-1 in the immediate vicinity of the clinic, dropping to 0.1-0.6 at a travel distance of 10 km, and effectively zero at distances > 30-40 km.

CONCLUSIONS

To enhance the method's strategic impact, we provide an interactive mapping tool (as a self-contained R Shiny app) that can be used by non-specialists to interrogate model outputs and visualize how the overall probability of under-reporting and the catchment area of each clinic is influenced by changing the number and spatial allocation of health centres.

Bayesian Spatiotemporal Modeling of Routinely Collected Data to Assess the Effect of Health Programs in Malaria Incidence During Pregnancy in Burkina Faso

Control of malaria in pregnancy (MiP) remains a major challenge in Burkina Faso. Surveillance of the burden due to MiP based on routinely collected data at a fine-scale level, followed by an appropriate analysis and interpretation, may be crucial for evaluating and improving the effectiveness of existing control measures. We described the spatio-temporal dynamics of MiP at the community-level and assessed health program effects, mainly community-based health promotion, results-based financing, and intermittent-preventive-treatment with sulphadoxine-pyrimethamine (IPTp-SP). Community-aggregated monthly MiP cases were downloaded from Health Management Information System and combined with covariates from other sources. The MiP spatio-temporal pattern was decomposed into three components: overall spatial and temporal trends and space-time interaction. Bayesian hierarchical spatio-temporal Poisson models were used to fit the MiP incidence rate and assess health program effects. The overall annual incidence increased between 2015 and 2017. The findings reveal spatio-temporal heterogenicity throughout the year, which peaked during rainy season. From the model without covariates, 96 communities located mainly in the Cascades, South-West, Center-West, Center-East, and Eastern regions, exhibited significant relative-risk levels. The combined effect (significant reducing effect) of RBF, health promotion and IPTp-SP strategies was greatest in 17.7% (17/96) of high burden malaria communities. Despite intensification of control efforts, MiP remains high at the community-scale. The provided risk maps are useful tools for highlighting areas where interventions should be optimized, particularly in high-risk communities.

Effect of Free Healthcare Policy for Children under Five Years Old on the Incidence of Reported Malaria Cases in Burkina Faso by Bayesian Modelling: "Not only the Ears but also the Head of the Hippopotamus"

Burkina Faso has recently implemented an additional strategy, the free healthcare policy, to further improve maternal and child health. This policy targets children under five who bear the brunt of the malaria scourge. The effects of the free-of-charge healthcare were previously assessed in women but not in children. The present study aims at filling this gap by assessing the effect of this policy in children under five with a focus on the induced spatial and temporal changes in malaria morbidity. We used a Bayesian spatiotemporal negative binomial model to investigate the space–time variation in malaria incidence in relation to the implementation of the policy. The analysis relied on malaria routine surveillance data extracted from the national health data repository and spanning the period from January 2013 to December 2018. The model was adjusted for meteorological and contextual confounders. We found that the number of presumed and confirmed malaria cases per 1000 children per month increased between 2013 and 2018. We further found that the implementation of the free healthcare policy was significantly associated with a two-fold increase in the number of tested and confirmed malaria cases compared with the period before the policy rollout. This effect was, however, heterogeneous across the health districts. We attributed the rise in malaria incidence following the policy rollout to an increased use of health services combined with an increased availability of rapid tests and a higher compliance to the “test and treat” policy. The observed heterogeneity in the policy effect was attributed to parallel control interventions, some of which were rolled out at different paces and scales. Our findings call for a sustained and reinforced effort to test all suspected cases so that, alongside an improved case treatment, the true picture of the malaria scourge in children under five emerges clearly (see the hippopotamus almost entirely).

Evaluation of mosquito electrocuting traps as a safe alternative to the human landing catch for measuring human exposure to malaria vectors in Burkina Faso

BACKGROUND

Measuring human exposure to mosquito bites is a crucial component of vector-borne disease surveillance. For malaria vectors, the human landing catch (HLC) remains the gold standard for direct estimation of exposure. This method, however, is controversial since participants risk exposure to potentially infected mosquito bites. Recently an exposure-free mosquito electrocuting trap (MET) was developed to provide a safer alternative to the HLC. Early prototypes of the MET performed well in Tanzania but have yet to be tested in West Africa, where malaria vector species composition, ecology and behaviour are different. The performance of the MET relative to HLC for characterizing mosquito vector population dynamics and biting behaviour in Burkina Faso was evaluated.

METHODS

A longitudinal study was initiated within 12 villages in Burkina Faso in October 2016. Host-seeking mosquitoes were sampled monthly using HLC and MET collections over 14 months. Collections were made at 4 households on each night, with METs deployed inside and outside at 2 houses, and HLC inside and outside at another two. Malaria vector abundance, species composition, sporozoite rate and location of biting (indoor versus outdoor) were recorded.

RESULTS

In total, 41,800 mosquitoes were collected over 324 sampling nights, with the major malaria vector being Anopheles gambiae sensu lato (s.l.) complex. Overall the MET caught fewer An. gambiae s.l. than the HLC (mean predicted number of 0.78 versus 1.82 indoors, and 1.05 versus 2.04 outdoors). However, MET collections gave a consistent representation of seasonal dynamics in vector populations, species composition, biting behaviour (location and time) and malaria infection rates relative to HLC. As the relative performance of the MET was somewhat higher in outdoor versus indoor settings, this trapping method slightly underestimated the proportion of bites preventable by LLINs compared to the HLC (MET = 82.08%; HLC = 87.19%).

CONCLUSIONS

The MET collected proportionately fewer mosquitoes than the HLC. However, estimates of An. gambiae s.l. density in METs were highly correlated with HLC. Thus, although less sensitive, the MET is a safer alternative than the HLC. Its use is recommended particularly for sampling vectors in outdoor environments where it is most sensitive.

Geographical variation in the association of child, maternal and household health interventions with under-five mortality in Burkina Faso

Background

Over the past 15 years, scaling up of cost effective interventions resulted in a remarkable decline of under-five mortality rates (U5MR) in sub-Saharan Africa. However, the reduction shows considerable heterogeneity. We estimated the association of child, maternal, and household interventions with U5MR in Burkina Faso at national and subnational levels and identified the regions with least effective interventions.

Methods

Data on health-related interventions and U5MR were extracted from the Burkina Faso Demographic and Health Survey (DHS) 2010. Bayesian geostatistical proportional hazards models with a Weibull baseline hazard were fitted on the mortality outcome. Spatially varying coefficients were considered to assess the geographical variation in the association of the health interventions with U5MR. The analyses were adjusted for child, maternal, and household characteristics, as well as climatic and environmental factors.

Findings

The average U5MR was as high as 128 per 1000 ranging from 81 (region of Centre-Est) to 223 (region of Sahel). At national level, DPT3 immunization and baby post-natal check within 24 hours after birth had the most important association with U5MR (hazard rates ratio (HRR) = 0.89, 95% Bayesian credible interval (BCI): 0.86–0.98 and HRR = 0.89, 95% BCI: 0.86–0.92, respectively). At sub-national level, the most effective interventions are the skilled birth attendance, and improved drinking water, followed by baby post-natal check within 24 hours after birth, vitamin A supplementation, antenatal care visit and all-antigens immunization (including BCG, Polio3, DPT3, and measles immunization). Centre-Est, Sahel, and Sud-Ouest were the regions with the highest number of effective interventions. There was no intervention that had a statistically important association with child survival in the region of Hauts Bassins.

Interpretation

The geographical variation in the magnitude and statistical importance of the association between health interventions and U5MR raises the need to deliver and reinforce health interventions at a more granular level. Priority interventions are DPT3 immunization, skilled birth attendance, baby post-natal visits in the regions of Sud-Ouest, Sahel, and Hauts Bassins, respectively. Our methodology could be applied to other national surveys, as it allows an incisive, data-driven and specific decision-making approach to optimize the allocation of health interventions at subnational level.

Achieving explanatory depth and spatial breadth in infectious disease modelling: Integrating active and passive case surveillance

Ideally, the data used for robust spatial prediction of disease distribution should be both high-resolution and spatially expansive. However, such in-depth and geographically broad data are rarely available in practice. Instead, researchers usually acquire either detailed epidemiological data with high resolution at a small number of active sampling sites, or more broad-ranging but less precise data from passive case surveillance. We propose a novel inferential framework, capable of simultaneously drawing insights from both passive and active data types. We developed a Bayesian latent point process approach, combining active data collection in a limited set of points, where in-depth covariates are measured, with passive case detection, where error-prone, large-scale disease data are accompanied only by coarse or remotely-sensed covariate layers. Using the example of malaria, we tested our method's efficiency under several hypothetical scenarios of reported incidence in different combinations of imperfect detection and spatial complexity of the environmental variables. We provide a simple solution to a widespread problem in spatial epidemiology, combining latent process modelling and spatially autoregressive modelling. By using active sampling and passive case detection in a complementary way, we achieved the best-of-both-worlds, in effect, a formal calibration of spatially extensive, error-prone data by localised, high-quality data.

Socioeconomic and environmental factors associated with malaria hotspots in the Nanoro demographic surveillance area, Burkina Faso

BACKGROUND

With limited resources and spatio-temporal heterogeneity of malaria in developing countries, it is still difficult to assess the real impact of socioeconomic and environmental factors in order to set up targeted campaigns against malaria at an accurate scale. Our goal was to detect malaria hotspots in rural area and assess the extent to which household socioeconomic status and meteorological recordings may explain the occurrence and evolution of these hotspots.

METHODS

Data on malaria cases from 2010 to 2014 and on socioeconomic and meteorological factors were acquired from four health facilities within the Nanoro demographic surveillance area. Statistical cross correlation was used to quantify the temporal association between weekly malaria incidence and meteorological factors. Local spatial autocorrelation analysis was performed and restricted to each transmission period using Kulldorff's elliptic spatial scan statistic. Univariate and multivariable analysis were used to assess the principal socioeconomic and meteorological determinants of malaria hotspots using a Generalized Estimating Equation (GEE) approach.

RESULTS

Rainfall and temperature were positively and significantly associated with malaria incidence, with a lag time of 9 and 14 weeks, respectively. Spatial analysis showed a spatial autocorrelation of malaria incidence and significant hotspots which was relatively stable throughout the study period. Furthermore, low socioeconomic status households were strongly associated with malaria hotspots (aOR = 1.21, 95% confidence interval: 1.03-1.40).

CONCLUSION

These fine-scale findings highlight a relatively stable spatio-temporal pattern of malaria risk and indicate that social and environmental factors play an important role in malaria incidence. Integrating data on these factors into existing malaria struggle tools would help in the development of sustainable bottleneck strategies adapted to the local context for malaria control.

Spatial distribution and determinants of asymptomatic malaria risk among children under 5 years in 24 districts in Burkina Faso

BACKGROUND

In malaria endemic countries, asymptomatic cases constitute an important reservoir of infections sustaining transmission. Estimating the burden of the asymptomatic population and identifying areas with elevated risk is important for malaria control in Burkina Faso. This study analysed the spatial distribution of asymptomatic malaria infection among children under 5 in 24 health districts in Burkina Faso and identified the determinants of this distribution.

METHODS

The data used in this study were collected in a baseline survey on "evaluation of the impact of pay for performance on the quality of care" conducted in 24 health districts in Burkina Faso, between October 2013 and March 2014. This survey involved 7844 households and 1387 community health workers. A Bayesian hierarchical logistic model that included spatial dependence and covariates was implemented to identify the determinants of asymptomatic malaria infection. The posterior probability distribution of a parameter from the model was summarized using odds ratio (OR) and 95% credible interval (95% CI).

RESULTS

The overall prevalence of asymptomatic malaria infection in children under 5 years of age was estimated at 38.2%. However, significant variation was observed between districts ranging from 11.1% in the district of Barsalgho to 77.8% in the district of Gaoua. Older children (48-59 vs < 6 months: OR: 6.79 [5.62, 8.22]), children from very poor households (Richest vs poorest: OR: 0.85 [0.74-0.96]), households located more than 5 km from a health facility (< 5 km vs  ≥ 5 km: OR: 1.14 [1.04-1.25]), in localities with inadequate number of nurses (< 3 vs  ≥ 3: 0.72 [0.62, 0.82], from rural areas (OR: 1.67 [1.39-2.01]) and those surveyed in high transmission period of asymptomatic malaria (OR: 1.27 [1.10-1.46]) were most at risk for asymptomatic malaria infection. In addition, the spatial analysis identified the following nine districts that reported significantly higher risks: Batié, Boromo, Dano, Diébougou, Gaoua, Ouahigouya, Ouargaye, Sapouy and Toma. The district of Zabré reported the lowest risk.

CONCLUSION

The analysis of spatial distribution of infectious reservoir allowed the identification of risk areas as well as the identification of individual and contextual factors. Such national spatial analysis should help to prioritize areas for increased malaria control activities.

Nightly Biting Cycles of Anopheles Species in Rural Northwestern Burkina Faso

The biting behavior of anophelines is an important determinant of malaria transmission. Understanding the local vector host-seeking behavior, its outdoor/ indoor biting preference, and nocturnal biting periods is essential for effectively applying and improving vector control methods, such as Long Lasting Insecticidal Nets (LLINs) and personal protective measures. To better understand the biting and host-seeking patterns of Anopheles mosquitoes in Northwestern Burkina Faso, we performed biweekly Human Landing Catches (HLC) in six villages during the period of highest mosquito abundance and malaria transmission. We applied a negative binomial regression framework to statistically analyze the host-seeking activities of Anopheles species and test for differences across hours, months, and villages, as well as for differences between indoor and outdoor capture points. Anopheles gambiae s.l. was identified as the main malaria vector in this region, representing about 90% of the total anopheline population. Biting activity was significantly different across hours and showed a peaked plateau between 2000 and 0200 hours. Differences in the pattern of biting cycles were observed between the early and late rainy season. This study shows that anopheline biting activity in Northwest Burkina Faso is high throughout the night, at indoor and outdoor posts alike. Consequently, bed nets alone may not provide sufficient protection against early biting anophelines and should be complemented with additional strategies such as indoor residual spraying (IRS) and larval source management (LSM) to meet the WHO's ambitious goals that are reflected in the global technical malaria strategy for 2030.

Challenges of DHS and MIS to capture the entire pattern of malaria parasite risk and intervention effects in countries with different ecological zones: the case of Cameroon

BACKGROUND

In 2011, the demographic and health survey (DHS) in Cameroon was combined with the multiple indicator cluster survey. Malaria parasitological data were collected, but the survey period did not overlap with the high malaria transmission season. A malaria indicator survey (MIS) was also conducted during the same year, within the malaria peak transmission season. This study compares estimates of the geographical distribution of malaria parasite risk and of the effects of interventions obtained from the DHS and MIS survey data.

METHODS

Bayesian geostatistical models were applied on DHS and MIS data to obtain georeferenced estimates of the malaria parasite prevalence and to assess the effects of interventions. Climatic predictors were retrieved from satellite sources. Geostatistical variable selection was used to identify the most important climatic predictors and indicators of malaria interventions.

RESULTS

The overall observed malaria parasite risk among children was 33 and 30% in the DHS and MIS data, respectively. Both datasets identified the Normalized Difference Vegetation Index and the altitude as important predictors of the geographical distribution of the disease. However, MIS selected additional climatic factors as important disease predictors. The magnitude of the estimated malaria parasite risk at national level was similar in both surveys. Nevertheless, DHS estimates lower risk in the North and Coastal areas. MIS did not find any important intervention effects, although DHS revealed that the proportion of population with an insecticide-treated nets access in their household was statistically important. An important negative relationship between malaria parasitaemia and socioeconomic factors, such as the level of mother's education, place of residence and the household welfare were captured by both surveys.

CONCLUSION

Timing of the malaria survey influences estimates of the geographical distribution of disease risk, especially in settings with seasonal transmission. In countries with different ecological zones and thus different seasonal patterns, a single survey may not be able to identify all high risk areas. A continuous MIS or a combination of MIS, health information system data and data from sentinel sites may be able to capture the disease risk distribution in space across different seasons.

Prevalence, genetic variants and clinical implications of G-6-PD deficiency in Burkina Faso: a systematic review

BACKGROUND

It is now well-known that some antimalarials such as primaquine may induce severe hemolytic anemia in people with G-6-PD deficiency. Antimalarial drug prescriptions must, therefore take into account the patient's G-6-PD status in malaria endemic areas such as Burkina Faso, where the prevalence of this genetic abnormality is relatively high. Although great clinical heterogeneity is observed depending on the molecular nature of the deficiency and the residual enzyme activity in the red blood cell, there is very poor data on the prevalence of G-6-PD deficiency and the distribution of involved genetic variants in Burkina Faso. In this systematic review, we present a synthesis of the various studies carried out on the G-6-PD deficiency in Burkina Faso in order to determine its prevalence, probable distribution of the genetic variants involved and their clinical implications for a national systematic screening policy among the groups most vulnerable to malaria.

METHODS

A systematic review was carried out to analyze available published data on the prevalence, phenotypes and mutations responsible for G-6-PD deficiency in Burkina Faso. The key words used were "G-6-PD deficiency AND Burkina Faso" or "Déficit en G-6-PD AND Burkina Faso" in French. To identify the relevant articles, two independent reviewers reviewed the titles, abstracts and the full text of the selected papers.

RESULTS

An average prevalence of 16.6% (183/1100; CI 95%: 0.145-0.190) and 6.5% (69/1066; CI 95%: 0.051-0.081) of G-6-PD deficiency was found respectively in men and women in this systematic review. Although the predominance (99.8% of G-6-PD deficient cases) of 202A/376G G-6-PD A- variant, the Santamaria and Betica Selma variants were identified in Burkina Faso. Independently of the method used, the enzymatic deficiency was significantly higher in males (2.5-20.5%) compared to females (3.3-12.3%).

CONCLUSION

This systematic review suggests that despite the ubiquity of the 202A/376G G-6-PD A- variant in Burkina Faso, it will be necessary to consider the Santamaria and Betica Selma variants although their frequencies remain to be specified. A systematic screening of the G-6-PD deficiency is also needed to prevent the occurrence of iatrogenic hemolytic accidents.

The contribution of malaria control interventions on spatio-temporal changes of parasitaemia risk in Uganda during 2009-2014

BACKGROUND

In Uganda, malaria vector control interventions and case management with Artemisinin Combination Therapies (ACTs) have been scaled up over the last few years as a result of increased funding. Data on parasitaemia prevalence among children less than 5 years old and coverage of interventions was collected during the first two Malaria Indicator Surveys (MIS) conducted in 2009 and 2014, respectively. In this study, we quantify the effects of control interventions on parasitaemia risk changes between the two MIS in a spatio-temporal analysis.

METHODS

Bayesian geostatistical and temporal models were fitted on the MIS data of 2009 and 2014. The models took into account geographical misalignment in the locations of the two surveys and adjusted for climatic changes and socio-economic differentials. Parasitaemia risk was predicted over a 2 × 2 km2 grid and the number of infected children less than 5 years old was estimated. Geostatistical variable selection was applied to identify the most important ITN coverage indicators. A spatially varying coefficient model was used to estimate intervention effects at sub-national level.

RESULTS

The coverage of Insecticide Treated Nets (ITNs) and ACTs more than doubled at country and sub-national levels during the period 2009-2014. The coverage of Indoor Residual Spraying (IRS) remained static at all levels. ITNs, IRS, and ACTs were associated with a reduction in parasitaemia odds of 19% (95% BCI: 18-29%), 78% (95% BCI: 67-84%), and 34% (95% BCI: 28-66%), respectively. Intervention effects varied with region. Higher socio-economic status and living in urban areas were associated with parasitaemia odds reduction of 46% (95% BCI: 0.51-0.57) and 57% (95% BCI: 0.40-0.53), respectively. The probability of parasitaemia risk decline in the country was 85% and varied from 70% in the North-East region to 100% in Kampala region. The estimated number of children infected with malaria declined from 2,480,373 in 2009 to 825,636 in 2014.

CONCLUSIONS

Interventions have had a strong effect on the decline of parasitaemia risk in Uganda during 2009-2014, albeit with varying magnitude in the regions. This success should be sustained by optimizing ITN coverage to achieve universal coverage.

Knowledge of prevention, cause, symptom and practices of malaria among women in Burkina Faso

BACKGROUND

Malaria remains a major public health issue in most southern African countries as the disease remains hyper endemic. Burkina Faso continues to face challenges in the treatment of malaria, as the utilization of preventive measures remains low on a national scale. While it has been acknowledged that understanding women's health-seeking behaviours, perception of malaria and its preventive measures will aid in the control of malaria, there is paucity of information on Knowledge, Attitudes and Practices among women in the reproductive age of 15-49 years in Burkina Faso. This study investigated women's knowledge of malaria, attitudes towards malaria, and practices of malaria control in order to create a synergy between community efforts and governmental/non-governmental malaria control interventions in Burkina Faso.

METHODS

The analysis used data from the 2014 Burkina Faso Malaria Indicator Survey (MIS). In total 8111 women aged between 15-49 years were included in the present study. We assessed women's knowledge about 1) preventive measures, 2) causes and 3) symptoms of malaria, as well as malaria prevention practices for their children and during pregnancy. The socio-demographic characteristics were considered for Age, Religion, Education, Wealth index, Number of household members, Sex of household head, Household possession of radio, TV and Received antenatal care. Data were analyzed using STATA, version 14. Associations between variables were tested using a Chi-square and logistic regression, with the level of statistical significance set at 95%.

RESULTS

A preponderant proportion of respondents were aged 15-29 years (mean age was 28.63±9.41). About three-quarters of the respondents had no formal education. An estimated two-third of the participants were of Islamic faith, while access to media and behavioural communication were generally poor. The level of knowledge was 53% for rural women and 68.2% for urban dwellers. In sum, there was 56.1% level of accurate knowledge of malaria among women in Burkina Faso. In the multivariable logistic regression, women in rural location had 40% reduction in the odds of having accurate knowledge of malaria when compared to urban women (aOR = 0.60; 95%CI: 0.52-0.68). The educational level was a key factor in the knowledge of malaria. The odds of having accurate knowledge of malaria increased as the educational level increased, hence, women with secondary and higher education had 29% and 93% increase in the odds of having accurate knowledge of malaria when compared to the women without formal education. Results indicate that antenatal care (ANC) services were major sources of information on malaria. Women who reportedly received ANC were 3.9 times more likely to have accurate knowledge of malaria when compared to those who did not utilize skilled ANC services (aOR = 3.90; 95%CI = 3.34-4.56).

CONCLUSION

The overall knowledge of malaria prevention practices among a large proportion of women was found to be low, which implies that the knowledge about the prevention of malaria should be improved upon by both urban and rural dwellers. There is need for concerted behavioural communication intervention to improve the knowledge of malaria especially for rural dwellers regarding malaria prevention measures, causes and symptoms. Consistent efforts at providing relevant information by health organizations are needed to reduce and control incidences of malaria in the general public.

Geostatistical modelling of malaria indicator survey data to assess the effects of interventions on the geographical distribution of malaria prevalence in children less than 5 years in Uganda

BACKGROUND

Malaria burden in Uganda has declined disproportionately among regions despite overall high intervention coverage across all regions. The Uganda Malaria Indicator Survey (MIS) 2014-15 was the second nationally representative survey conducted to provide estimates of malaria prevalence among children less than 5 years, and to track the progress of control interventions in the country. In this present study, 2014-15 MIS data were analysed to assess intervention effects on malaria prevalence in Uganda among children less than 5 years, assess intervention effects at regional level, and estimate geographical distribution of malaria prevalence in the country.

METHODS

Bayesian geostatistical models with spatially varying coefficients were used to determine the effect of interventions on malaria prevalence at national and regional levels. Spike-and-slab variable selection was used to identify the most important predictors and forms. Bayesian kriging was used to predict malaria prevalence at unsampled locations.

RESULTS

Indoor Residual Spraying (IRS) and Insecticide Treated Nets (ITN) ownership had a significant but varying protective effect on malaria prevalence. However, no effect was observed for Artemisinin Combination-based Therapies (ACTs). Environmental factors, namely, land cover, rainfall, day and night land surface temperature, and area type were significantly associated with malaria prevalence. Malaria prevalence was higher in rural areas, increased with the child's age, and decreased with higher household socioeconomic status and higher level of mother's education. The highest prevalence of malaria in children less than 5 years was predicted for regions of East Central, North East and West Nile, whereas the lowest was predicted in Kampala and South Western regions, and in the mountainous areas in Mid-Western and Mid-Eastern regions.

CONCLUSIONS

IRS and ITN ownership are important interventions against malaria prevalence in children less than 5 years in Uganda. The varying effects of the interventions calls for selective implementation of control tools suitable to regional ecological settings. To further reduce malaria burden and sustain malaria control in Uganda, current tools should be supplemented by health system strengthening, and socio-economic development.