Plasmodium Falciparum Parasite Rate Research Articles

How useful are malaria risk maps at the country level? Perceptions of decision-makers in Kenya, Malawi and the Democratic Republic of Congo

BackgroundDeclining malaria prevalence and pressure on external funding have increased the need for efficiency in malaria control in sub-Saharan Africa (SSA). Modelled Plasmodium falciparum parasite rate (PfPR) maps are increasingly becoming available and provide information on the epidemiological situation of countries. However, how these maps are understood or used for national malaria planning is rarely explored. In this study, the practices and perceptions of national decision-makers on the utility of malaria risk maps, showing prevalence of parasitaemia or incidence of illness, was investigated.MethodsA document review of recent National Malaria Strategic Plans was combined with 64 in-depth interviews with stakeholders in Kenya, Malawi and the Democratic Republic of Congo (DRC). The document review focused on the type of epidemiological maps included and their use in prioritising and targeting interventions. Interviews (14 Kenya, 17 Malawi, 27 DRC, 6 global level) explored drivers of stakeholder perceptions of the utility, value and limitations of malaria risk maps.ResultsThree different types of maps were used to show malaria epidemiological strata: malaria prevalence using a PfPR modelled map (Kenya); malaria incidence using routine health system data (Malawi); and malaria prevalence using data from the most recent Demographic and Health Survey (DRC). In Kenya the map was used to target preventative interventions, including long-lasting insecticide-treated nets (LLINs) and intermittent preventive treatment in pregnancy (IPTp), whilst in Malawi and DRC the maps were used to target in-door residual spraying (IRS) and LLINs distributions in schools. Maps were also used for operational planning, supply quantification, financial justification and advocacy. Findings from the interviews suggested that decision-makers lacked trust in the modelled PfPR maps when based on only a few empirical data points (Malawi and DRC).ConclusionsMaps were generally used to identify areas with high prevalence in order to implement specific interventions. Despite the availability of national level modelled PfPR maps in all three countries, they were only used in one country. Perceived utility of malaria risk maps was associated with the epidemiological structure of the country and use was driven by perceived need, understanding (quality and relevance), ownership and trust in the data used to develop the maps.

Modelling and mapping the intra-urban spatial distribution of Plasmodium falciparum parasite rate using very-high-resolution satellite derived indicators

BackgroundThe rapid and often uncontrolled rural–urban migration in Sub-Saharan Africa is transforming urban landscapes expected to provide shelter for more than 50% of Africa’s population by 2030. Consequently, the burden of malaria is increasingly affecting the urban population, while socio-economic inequalities within the urban settings are intensified. Few studies, relying mostly on moderate to high resolution datasets and standard predictive variables such as building and vegetation density, have tackled the topic of modeling intra-urban malaria at the city extent. In this research, we investigate the contribution of very-high-resolution satellite-derived land-use, land-cover and population information for modeling the spatial distribution of urban malaria prevalence across large spatial extents. As case studies, we apply our methods to two Sub-Saharan African cities, Kampala and Dar es Salaam.MethodsOpenly accessible land-cover, land-use, population and OpenStreetMap data were employed to spatially model Plasmodium falciparum parasite rate standardized to the age group 2–10 years (PfPR2–10) in the two cities through the use of a Random Forest (RF) regressor. The RF models integrated physical and socio-economic information to predict PfPR2–10 across the urban landscape. Intra-urban population distribution maps were used to adjust the estimates according to the underlying population.ResultsThe results suggest that the spatial distribution of PfPR2–10 in both cities is diverse and highly variable across the urban fabric. Dense informal settlements exhibit a positive relationship with PfPR2–10 and hotspots of malaria prevalence were found near suitable vector breeding sites such as wetlands, marshes and riparian vegetation. In both cities, there is a clear separation of higher risk in informal settlements and lower risk in the more affluent neighborhoods. Additionally, areas associated with urban agriculture exhibit higher malaria prevalence values.ConclusionsThe outcome of this research highlights that populations living in informal settlements show higher malaria prevalence compared to those in planned residential neighborhoods. This is due to (i) increased human exposure to vectors, (ii) increased vector density and (iii) a reduced capacity to cope with malaria burden. Since informal settlements are rapidly expanding every year and often house large parts of the urban population, this emphasizes the need for systematic and consistent malaria surveys in such areas. Finally, this study demonstrates the importance of remote sensing as an epidemiological tool for mapping urban malaria variations at large spatial extents, and for promoting evidence-based policy making and control efforts.

Mapping the global prevalence, incidence, and mortality of Plasmodium falciparum, 2000–17: a spatial and temporal modelling study

SummaryBackgroundSince 2000, the scale-up of malaria control interventions has substantially reduced morbidity and mortality caused by the disease globally, fuelling bold aims for disease elimination. In tandem with increased availability of geospatially resolved data, malaria control programmes increasingly use high-resolution maps to characterise spatially heterogeneous patterns of disease risk and thus efficiently target areas of high burden.MethodsWe updated and refined the Plasmodium falciparum parasite rate and clinical incidence models for sub-Saharan Africa, which rely on cross-sectional survey data for parasite rate and intervention coverage. For malaria endemic countries outside of sub-Saharan Africa, we produced estimates of parasite rate and incidence by applying an ecological downscaling approach to malaria incidence data acquired via routine surveillance. Mortality estimates were derived by linking incidence to systematically derived vital registration and verbal autopsy data. Informed by high-resolution covariate surfaces, we estimated P falciparum parasite rate, clinical incidence, and mortality at national, subnational, and 5 × 5 km pixel scales with corresponding uncertainty metrics.FindingsWe present the first global, high-resolution map of P falciparum malaria mortality and the first global prevalence and incidence maps since 2010. These results are combined with those for Plasmodium vivax (published separately) to form the malaria estimates for the Global Burden of Disease 2017 study. The P falciparum estimates span the period 2000–17, and illustrate the rapid decline in burden between 2005 and 2017, with incidence declining by 27·9% and mortality declining by 42·5%. Despite a growing population in endemic regions, P falciparum cases declined between 2005 and 2017, from 232·3 million (95% uncertainty interval 198·8–277·7) to 193·9 million (156·6–240·2) and deaths declined from 925 800 (596 900–1 341 100) to 618 700 (368 600–952 200). Despite the declines in burden, 90·1% of people within sub-Saharan Africa continue to reside in endemic areas, and this region accounted for 79·4% of cases and 87·6% of deaths in 2017.InterpretationHigh-resolution maps of P falciparum provide a contemporary resource for informing global policy and malaria control planning, programme implementation, and monitoring initiatives. Amid progress in reducing global malaria burden, areas where incidence trends have plateaued or increased in the past 5 years underscore the fragility of hard-won gains against malaria. Efforts towards elimination should be strengthened in such areas, and those where burden remained high throughout the study period.FundingBill & Melinda Gates Foundation.

A combination of metabolic resistance and high frequency of the 1014F kdr mutation is driving pyrethroid resistance in Anopheles coluzzii population from Guinea savanna of Cameroon

BackgroundThe scale-up in the distribution of long-lasting insecticidal nets (LLINs) and indoor residual spraying has significantly reduced malaria burden and mortality. However, insecticide resistance, among other factors, is responsible for a recent rebound in malaria transmission in 2015–2016, threatening the progress so far made. As a contribution towards understanding patterns of resistance and its mechanism in the field we characterized a population of Anopheles gambiae (s.l.) from Gounougou, a Guinea savanna of north/central Cameroon.ResultsIndoor collection conducted in September 2017 identified Anopheles coluzzii and Anopheles arabiensis as the unique Anopheles vector species, with abundances of 83 and 17%, respectively. Analysis of infection with TaqMan assays using heads/thoraces of indoor collected females of An. coluzzii revealed a low Plasmodium falciparum parasite rate of 4.7%. Bioassays conducted with female An. coluzzii revealed extreme resistance, with low mortalities of only 3.75 ± 1.25%, 3.03 ± 1.59% and 1.45 ± 1.45%, respectively, for permethrin, deltamethrin and DDT. In contrast, high susceptibility was obtained with the organophosphates and carbamates, with mortalities in the range of 98–100%. Synergist assays with piperonyl butoxide (PBO) recovered some susceptibility with increased mortality for permethrin to 14.88 ± 8.74%, and for deltamethrin to 32.50 ± 10.51% (~27-fold increase compared to mortalities with deltamethrin alone, χ2 = 29, df = 1, P < 0.0001). These correlated with the results of cone bioassays which revealed complete loss of efficacy of Olyset®Net (0% mortality) and PermaNet®2.0 (0% mortality), and the considerable loss of efficacy of Olyset®Plus (mortality of 2 ± 2%), PermaNet®3.0 side panel (mortality of 2 ± 2%) and PermaNet3.0® roof (mortality of 16 ± 5.1%). Time-course bioassays conducted with deltamethrin established a high intensity of resistance, with LT50 of 309.09 (95% CI 253.07–393.71, Fiducial), and a resistance ratio of 93.09 compared with the fully susceptible Ngoussou laboratory colony. TaqMan genotyping revealed a high frequency of the 1014F allele (65.25%) in the An. coluzzii populations. Sequencing of a fragment of the voltage-gated sodium channel identified a single An. arabiensis female harbouring the 1014S kdr mutation.ConclusionsThis finding of high pyrethroid and DDT resistance in An. coluzzii from north-central Cameroon is a major obstacle to malaria control using pyrethroid bednets and indoor residual spraying with DDT.

A cross-sectional analysis of ITN and IRS coverage in Namibia in 2013

BackgroundAchieving vector control targets is a key step towards malaria elimination. Because of variations in reporting of progress towards vector control targets in 2013, the coverage of these vector control interventions in Namibia was assessed.MethodsData on 9846 households, representing 41,314 people, collected in the 2013 nationally-representative Namibia Demographic and Health Survey were used to explore the coverage of two vector control methods: indoor residual spraying (IRS) and insecticide-treated nets (ITNs). Regional data on Plasmodium falciparum parasite rate in those aged 2–10 years (PfPR2–10), obtained from the Malaria Atlas Project, were used to provide information on malaria transmission intensity. Poisson regression analyses were carried out exploring the relationship between household interventions and PfPR2–10, with fully adjusted models adjusting for wealth and residence type and accounting for regional and enumeration area clustering. Additionally, the coverage as a function of government intervention zones was explored and models were compared using log-likelihood ratio tests.ResultsIntervention coverage was greatest in the highest transmission areas (PfPR2–10 ≥ 5%), but was still below target levels of 95% coverage in these regions, with 27.6% of households covered by IRS, 32.3% with an ITN and 49.0% with at least one intervention (ITN and/or IRS). In fully adjusted models, PfPR2–10 ≥ 5% was strongly associated with IRS (RR 14.54; 95% CI 5.56–38.02; p < 0.001), ITN ownership (RR 5.70; 95% CI 2.84–11.45; p < 0.001) and ITN and/or IRS coverage (RR 5.32; 95% CI 3.09–9.16; p < 0.001).ConclusionsThe prevalence of IRS and ITN interventions in 2013 did not reflect the Namibian government intervention targets. As such, there is a need to include quantitative monitoring of such interventions to reliably inform intervention strategies for malaria elimination in Namibia.

Making sense of consensus: comparative modelling of malaria interventions.

Making sense of consensus: comparative modelling of malaria interventions.

Global, regional, and national causes of under-5 mortality in 2000–15: an updated systematic analysis with implications for the Sustainable Development Goals

SummaryBackgroundDespite remarkable progress in the improvement of child survival between 1990 and 2015, the Millennium Development Goal (MDG) 4 target of a two-thirds reduction of under-5 mortality rate (U5MR) was not achieved globally. In this paper, we updated our annual estimates of child mortality by cause to 2000–15 to reflect on progress toward the MDG 4 and consider implications for the Sustainable Development Goals (SDG) target for child survival.MethodsWe increased the estimation input data for causes of deaths by 43% among neonates and 23% among 1–59-month-olds, respectively. We used adequate vital registration (VR) data where available, and modelled cause-specific mortality fractions applying multinomial logistic regressions using adequate VR for low U5MR countries and verbal autopsy data for high U5MR countries. We updated the estimation to use Plasmodium falciparum parasite rate in place of malaria index in the modelling of malaria deaths; to use adjusted empirical estimates instead of modelled estimates for China; and to consider the effects of pneumococcal conjugate vaccine and rotavirus vaccine in the estimation.FindingsIn 2015, among the 5·9 million under-5 deaths, 2·7 million occurred in the neonatal period. The leading under-5 causes were preterm birth complications (1·055 million [95% uncertainty range (UR) 0·935–1·179]), pneumonia (0·921 million [0·812 −1·117]), and intrapartum-related events (0·691 million [0·598 −0·778]). In the two MDG regions with the most under-5 deaths, the leading cause was pneumonia in sub-Saharan Africa and preterm birth complications in southern Asia. Reductions in mortality rates for pneumonia, diarrhoea, neonatal intrapartum-related events, malaria, and measles were responsible for 61% of the total reduction of 35 per 1000 livebirths in U5MR in 2000–15. Stratified by U5MR, pneumonia was the leading cause in countries with very high U5MR. Preterm birth complications and pneumonia were both important in high, medium high, and medium child mortality countries; whereas congenital abnormalities was the most important cause in countries with low and very low U5MR.InterpretationIn the SDG era, countries are advised to prioritise child survival policy and programmes based on their child cause-of-death composition. Continued and enhanced efforts to scale up proven life-saving interventions are needed to achieve the SDG child survival target.FundingBill & Melinda Gates Foundation, WHO.

The current status of malaria epidemiology in Bolifamba, atypical Cameroonian rainforest zone: an assessment of intervention strategies and seasonal variations.

BackgroundGlobal malaria has been on the decline over the past decade due to expansion of interventions. The present study aimed at determining the current status of malaria epidemiology in the context of sustained interventions and seasonal variations in Bolifamba, which represents a typical semi-urban malaria endemic community in the Cameroonian rainforest.MethodsA monthly cross-sectional survey was carried out in Bolifamba, a multi ethnic semi-urban locality on the eastern flanks of Mt Cameroon, for a year during which blood samples were collected from participants and examined for malaria parasites by microscopy. Correlation analysis of seasonal/monthly malaria prevalence was done with weather data from Ekona, a nearby village with a meteorological station. Intervention strategy such as use of Insecticide Treated Bed Net (ITBN) and risk factors such as duration of stay in the locality, age and housing type were also investigated.ResultsThe results revealed a malaria prevalence of 38.3 % in the rainy season, which was significantly higher than 24.4 % observed in the dry season (P < 0.0001). A high prevalence of asymptomatic malaria which was more than double the prevalence of symptomatic malaria on a monthly basis was observed, 30.7 % vs 17.8 % in the rainy and dry season respectively (p < 0.0001) and asymptomatic malaria was significantly associated with anemia (p < 0.005). April was the peak month of malaria prevalence and coincided with peak periods of both asymptomatic and symptomatic malaria. The Plasmodium falciparum parasite rates in the 2- up to 10-years age group (PfPR(2–10)) was 40.8 %. The regular use of ITBN was significantly associated with low prevalence of 31.7 % as opposed to irregular or non-usage of ITBN 38.2 % (p < 0.05). Log of parasite load was found to initially increase to 2.49 with less than 5 years of stay, and decreased gradually with increasing duration of stay in the locality (p = 0.046). Climatic factors were significantly and positively associated with monthly malaria prevalence and the strongest predictors of malaria prevalence were rainfall and minimum temperature with r values of 0.563 and 0.6 respectively.ConclusionsThe study highlights the role of seasonal change in modifying malaria prevalence during the year and the beneficial effect of ITBN. It also underscores a sublime problem of asymptomatic malaria associated with anemia, and indicates that partial immunity is acquired with prolonged stay in Bolifamba. This preliminary result is the basis of ongoing work to identify the antigens involved in acquired immunity.

Re-examining environmental correlates of Plasmodium falciparum malaria endemicity: a data-intensive variable selection approach.

BackgroundMalaria risk maps play an increasingly important role in disease control planning, implementation, and evaluation. The construction of these maps using modern geospatial techniques relies on covariate grids: continuous surfaces quantifying environmental factors that partially explain spatial heterogeneity in malaria endemicity. Although crucial, past variable selection processes for this purpose have often been subjective and ad-hoc, with many covariates used in modeling with little quantitative justification.MethodsThis research consists of an extensive covariate construction and selection process for predicting Plasmodium falciparum parasite rates (PfPR) in Africa for years 2000-2012. First, a literature review was conducted to establish a comprehensive list of covariates used for malaria mapping. Second, a library of covariate data was assembled to reflect this list, a process that included the construction of multiple, temporally dynamic datasets. Third, the resulting set of covariates was leveraged to create more than 50 million possible covariate terms via factorial combinations of different spatial and temporal aggregations, transformations, and pairwise interactions. Fourth, the expanded set of covariates was reduced via successive selection criteria to yield a robust covariate subset that was assessed using an out-of-sample validation approach.ResultsThe final covariate subset included predominately dynamic covariates and it substantially out-performed earlier sets used by the Malaria Atlas Project (MAP) for creating global malaria risk maps, with the pseudo-R2 value for the out-of-sample validation increasing from 0.43 to 0.52. Dynamic covariates improved the model, with 17 of the 20 new covariates consisting of monthly or annual products, but the selected covariates were typically interaction terms that included both dynamic and synoptic datasets. Thus the interplay between normal (i.e., long-term averages) and immediate conditions may be key for characterizing environmental controls on parasite rate.ConclusionsThis analysis represents the first effort to systematically audit covariate utility for malaria mapping and then derive an objective, empirically based set of environmental covariates for modeling PfPR. The new covariates produce more reliable representations of malaria risk patterns and how they are changing through time, and these covariates will be used to characterize spatially and temporally varying environmental conditions affecting PfPR within a geostatistical-modeling framework, thus building upon previous research by MAP that produced global malaria maps for 2007 and 2010.Electronic supplementary materialThe online version of this article (doi:10.1186/s12936-015-0574-x) contains supplementary material, which is available to authorized users.

Insecticide resistance, Host preference and Plasmodium falciparum parasite rates in Anopheles mosquitoes in Mwea and Ahero rice schemes

The ability of Anopheles mosquito to transmit malaria in nature is partly enhanced by; resistance of mosquito to insecticides, feeding preference for human host and infection by Plasmodium falciparum . An assessment was conducted to determine the status of these parameters in Anopheles populations in Mwea and Ahero rice irrigation schemes in Kenya. This was important in order to understand their potential influence on local malaria transmission. A total of 1,200 female Anopheles mosquitoes (gravid and blood fed) were sampled from both sites by indoor and outdoor methods. Anopheles samples identification to their respective species in the field was done using morphological features and taxonomic keys. In Mwea scheme, all the 600 Anopheles mosquitoes collected were An. gambiae s.l out of which 195 were gravid. In Ahero, 250 An. gambiae s.l (out of which 81 were gravid) and 350 An. funestus (out of which 181 were gravid) were collected. Gravid Anopheles mosquitoes were allowed to oviposit to give F 1 generations in the insectary. These F 1 , (four replicates of 25 mosquitoes per species per insecticide) were assessed for susceptibility to permethrin, deltamethrin, dichlorodiphenyltrichloroethane (DDT), bendiocarb or fenitrothion using standard WHO protocol. Susceptible An. gambiae s.s Kisumu strain (25 mosquitoes per the 100 test mosquitoes) was used as positive control. The 1,200 field samples were further identified to their respective species using rDNA-PCR using their legs and wings. Source (s) of blood meal in 405 An. gambiae s.l from Mwea, 169 An. gambiae s.l and 269 An. funestus from Ahero were determined using blood meal Elisa. The presence of Plasmodium falciparum Welch, 1897 in the salivary glands was assessed by sporozoite Elisa in all the field collected samples. All Anopheles mosquito samples from Mwea were Anopheles arabiensis Patton, 1905, while those from Ahero were a mixed species of Anopheles arabiensis (41.7%), Anopheles funestus sensu stricto Giles , 1900 (57%), Anopheles rivulorum Leesoni, 1935 (0.66%), Anopheles leesoni Evans, 1931 (0.3%) and Anopheles parensis Gillies, 1935 (0.3%). Mosquito samples from both study sites showed reduced susceptibility to the test insecticides. An. arabiensis mosquitoes from Mwea had a human blood meal index at 0.22 (n=405). P. falciparum circumsporozoite infection in An. arabiensis from Mwea were reported in Murinduko village at 1.5% (n=200). In Ahero, human blood meal indices were at 0.00 (n=169) and 0.17 (n=269) for An. arabiensis and An. funestus respectively. P. falciparum circumsporozoite infections in An. funestus sampled from Kamagaga and Wagai villages in Ahero were at 5% (n=147) and 2.2% (n=183) respectively.

Malaria mortality in Africa and Asia: evidence from INDEPTH health and demographic surveillance system sites

Background Malaria continues to be a major cause of infectious disease mortality in tropical regions. However, deaths from malaria are most often not individually documented, and as a result overall understanding of malaria epidemiology is inadequate. INDEPTH Network members maintain population surveillance in Health and Demographic Surveillance System sites across Africa and Asia, in which individual deaths are followed up with verbal autopsies. Objective To present patterns of malaria mortality determined by verbal autopsy from INDEPTH sites across Africa and Asia, comparing these findings with other relevant information on malaria in the same regions. Design From a database covering 111,910 deaths over 12,204,043 person-years in 22 sites, in which verbal autopsy data were handled according to the WHO 2012 standard and processed using the InterVA-4 model, over 6,000 deaths were attributed to malaria. The overall period covered was 1992–2012, but two-thirds of the observations related to 2006–2012. These deaths were analysed by site, time period, age group and sex to investigate epidemiological differences in malaria mortality. Results Rates of malaria mortality varied by 1:10,000 across the sites, with generally low rates in Asia (one site recording no malaria deaths over 0.5 million person-years) and some of the highest rates in West Africa (Nouna, Burkina Faso: 2.47 per 1,000 person-years). Childhood malaria mortality rates were strongly correlated with Malaria Atlas Project estimates of Plasmodium falciparum parasite rates for the same locations. Adult malaria mortality rates, while lower than corresponding childhood rates, were strongly correlated with childhood rates at the site level. Conclusions The wide variations observed in malaria mortality, which were nevertheless consistent with various other estimates, suggest that population-based registration of deaths using verbal autopsy is a useful approach to understanding the details of malaria epidemiology.

The changing risk of Plasmodium falciparum malaria infection in Africa: 2000–10: a spatial and temporal analysis of transmission intensity

SummaryBackgroundOver a decade ago, the Roll Back Malaria Partnership was launched, and since then there has been unprecedented investment in malaria control. We examined the change in malaria transmission intensity during the period 2000–10 in Africa.MethodsWe assembled a geocoded and community Plasmodium falciparum parasite rate standardised to the age group 2–10 years (PfPR2–10) database from across 49 endemic countries and territories in Africa from surveys undertaken since 1980. The data were used within a Bayesian space–time geostatistical framework to predict PfPR2–10 in 2000 and 2010 at a 1 × 1 km spatial resolution. Population distribution maps at the same spatial resolution were used to compute populations at risk by endemicity class and estimate population-adjusted PfPR2–10 (PAPfPR2–10) for each of the 44 countries for which predictions were possible for each year.FindingsBetween 2000 and 2010, the population in hyperendemic (>50% to 75% PfPR2–10) or holoendemic (>75% PfPR2–10) areas decreased from 218·6 million (34·4%) of 635·7 million to 183·5 million (22·5%) of 815·7 million across 44 malaria-endemic countries. 280·1 million (34·3%) people lived in areas of mesoendemic transmission (>10% to 50% PfPR2–10) in 2010 compared with 178·6 million (28·1%) in 2000. Population in areas of unstable or very low transmission (<5% PfPR2–10) increased from 131·7 million people (20·7%) in 2000 to 219·0 million (26·8%) in 2010. An estimated 217·6 million people, or 26·7% of the 2010 population, lived in areas where transmission had reduced by at least one PfPR2–10 endemicity class. 40 countries showed a reduction in national mean PAPfPR2–10. Only ten countries contributed 87·1% of the population living in areas of hyperendemic or holoendemic transmission in 2010.InterpretationSubstantial reductions in malaria transmission have been achieved in endemic countries in Africa over the period 2000–10. However, 57% of the population in 2010 continued to live in areas where transmission remains moderate to intense and global support to sustain and accelerate the reduction of transmission must remain a priority.FundingWellcome Trust.

Is there preferential coverage for the most at risk? A survey-based analysis of malaria vector control by endemicity level

BackgroundAlthough US$2·3 billion in 2011 was spent on malaria control globally, a financing gap of $2·8 billion remains. While equity in intervention coverage is the ultimate goal, with limited resources, it is crucial to target interventions strategically. Developments in cartographic methods for estimating Plasmodium falciparum parasite rate (PfPR) at low geospatial levels and availability of household surveys with global positioning system (GPS) coordinates now allow for estimation of malaria intervention coverage stratified by level of infection risk. Taking advantage of this information, we aim to identify whether malaria interventions are targeted to those populations most at risk of malaria infection. MethodsOur study spanned 24 countries and used all 38 Malaria Indicator Surveys and Demographic and Health Surveys with GPS coordinates and survey questions on use of insecticide-treated mosquito nets (ITNs). For these surveys, conducted between 2003 and 2011, we obtained cluster-level PfPR by matching coordinates of surveyed clusters to coordinates from Malaria Atlas Project PfPR maps. For each survey, we calculated the proportion of household availability of ITNs and prevalence of indoor residual spraying (IRS) by level of malaria endemicity (low, intermediate, high). We sought to further explain variation in coverage of vector control interventions by examining PfPR by wealth quintile and urban or rural residence. FindingsCoverage of ITNs or IRS by endemicity level varies greatly by country and year. In only four (Burundi, Ethiopia, Senegal, Zimbabwe) of the 24 surveyed countries did the coverage of IRS or availability of ITNs increase monotonically with increasing endemicity level. While coverage of ITNs or IRS in Senegal in 2010 among populations at low risk was 16·4% (95% CI 13·2–19·6), coverage among those at intermediate and high risk was 31·7% (27·8–35·5) and 64·6% (30·0–99·0), respectively. By contrast, coverage in Tanzania in the same year was 73·5% (95% CI 69·3–77·6) among those at lowest risk, and 67·5% (64·4–70·7) and 53·0 (48·2–57·8) among those at medium and high risk, respectively. Nearly all surveys indicate lower coverage of vector control interventions and higher PfPR in poorer, more rural areas. InterpretationIn the countries examined in this study, coverage of vector control interventions did not necessarily increase with increasing malaria risk. If limited resources preclude protecting all persons at risk of malaria with vector control interventions, strategies for targeting interventions (such as on the basis of malaria risk) should be devised to achieve their greatest lifesaving potential. FundingNone.

Malaria risk mapping for control in the republic of Sudan.

Evidence shows that malaria risk maps are rarely tailored to address national control program ambitions. Here, we generate a malaria risk map adapted for malaria control in Sudan. Community Plasmodium falciparum parasite rate (PfPR) data from 2000 to 2010 were assembled and were standardized to 2–10 years of age (PfPR2–10). Space-time Bayesian geostatistical methods were used to generate a map of malaria risk for 2010. Surfaces of aridity, urbanization, irrigation schemes, and refugee camps were combined with the PfPR2–10 map to tailor the epidemiological stratification for appropriate intervention design. In 2010, a majority of the geographical area of the Sudan had risk of < 1% PfPR2–10. Areas of meso- and hyperendemic risk were located in the south. About 80% of Sudan's population in 2011 was in the areas in the desert, urban centers, or where risk was < 1% PfPR2–10. Aggregated data suggest reducing risks in some high transmission areas since the 1960s.

Mapping the receptivity of malaria risk to plan the future of control in Somalia

ObjectivesTo measure the receptive risks of malaria in Somalia and compare decisions on intervention scale-up based on this map and the more widely used contemporary risk maps.DesignCross-sectional community Plasmodium falciparum...

No evidence of association between HIV-1 and malaria in populations with low HIV-1 prevalence.

BackgroundThe geographic overlap between HIV-1 and malaria has generated much interest in their potential interactions. A variety of studies have evidenced a complex HIV-malaria interaction within individuals and populations that may have dramatic effects, but the causes and implications of this co-infection at the population level are still unclear. In a previous publication, we showed that the prevalence of malaria caused by the parasite Plasmodium falciparum is associated with HIV infection in eastern sub-Saharan Africa. To complement our knowledge of the HIV-malaria co-infection, the objective of this work was to assess the relationship between malaria and HIV prevalence in the western region of sub-Saharan Africa.Methodology/Principal FindingsPopulation-based cross-sectional data were obtained from the HIV/AIDS Demographic and Health Surveys conducted in Burkina Faso, Ghana, Guinea, Mali, Liberia and Cameroon, and the malaria atlas project. Using generalized linear mixed models, we assessed the relationship between HIV-1 and Plasmodium falciparum parasite rate (PfPR) adjusting for important socio-economic and biological cofactors. We found no evidence that individuals living in areas with stable malaria transmission (PfPR>0.46) have higher odds of being HIV-positive than individuals who live in areas with PfPR≤0.46 in western sub-Saharan Africa (estimated odds ratio 1.14, 95% confidence interval 0.86–1.50). In contrast, the results suggested that PfPR was associated with being infected with HIV in Cameroon (estimated odds ratio 1.56, 95% confidence interval 1.23–2.00).Conclusion/SignificanceContrary to our previous research on eastern sub-Saharan Africa, this study did not identify an association between PfPR and infection with HIV in western sub-Saharan Africa, which suggests that malaria might not play an important role in the spread of HIV in populations where the HIV prevalence is low. Our work highlights the importance of understanding the epidemiologic effect of co-infection and the relevant factors involved in this relationship for the implementation of effective control strategies.

Mapping the Risk of Anaemia in Preschool-Age Children: The Contribution of Malnutrition, Malaria, and Helminth Infections in West Africa

Childhood anaemia is considered a severe public health problem in most countries of sub-Saharan Africa. We investigated the geographical distribution of prevalence of anaemia and mean haemoglobin concentration (Hb) in children aged 1-4 y (preschool children) in West Africa. The aim was to estimate the geographical risk profile of anaemia accounting for malnutrition, malaria, and helminth infections, the risk of anaemia attributable to these factors, and the number of anaemia cases in preschool children for 2011. National cross-sectional household-based demographic health surveys were conducted in 7,147 children aged 1-4 y in Burkina Faso, Ghana, and Mali in 2003-2006. Bayesian geostatistical models were developed to predict the geographical distribution of mean Hb and anaemia risk, adjusting for the nutritional status of preschool children, the location of their residence, predicted Plasmodium falciparum parasite rate in the 2- to 10-y age group (Pf PR(2-10)), and predicted prevalence of Schistosoma haematobium and hookworm infections. In the four countries, prevalence of mild, moderate, and severe anaemia was 21%, 66%, and 13% in Burkina Faso; 28%, 65%, and 7% in Ghana, and 26%, 62%, and 12% in Mali. The mean Hb was lowest in Burkina Faso (89 g/l), in males (93 g/l), and for children 1-2 y (88 g/l). In West Africa, severe malnutrition, Pf PR(2-10), and biological synergisms between S. haematobium and hookworm infections were significantly associated with anaemia risk; an estimated 36.8%, 14.9%, 3.7%, 4.2%, and 0.9% of anaemia cases could be averted by treating malnutrition, malaria, S. haematobium infections, hookworm infections, and S. haematobium/hookworm coinfections, respectively. A large spatial cluster of low mean Hb (<80 g/l) and maximal risk of anaemia (>95%) was predicted for an area shared by Burkina Faso and Mali. We estimate that in 2011, approximately 6.7 million children aged 1-4 y are anaemic in the three study countries. By mapping the distribution of anaemia risk in preschool children adjusted for malnutrition and parasitic infections, we provide a means to identify the geographical limits of anaemia burden and the contribution that malnutrition and parasites make to anaemia. Spatial targeting of ancillary micronutrient supplementation and control of other anaemia causes, such as malaria and helminth infection, can contribute to efficiently reducing the burden of anaemia in preschool children in Africa.

The risks of malaria infection in Kenya in 2009

BackgroundTo design an effective strategy for the control of malaria requires a map of infection and disease risks to select appropriate suites of interventions. Advances in model based geo-statistics and malaria parasite prevalence data assemblies provide unique opportunities to redefine national Plasmodium falciparum risk distributions. Here we present a new map of malaria risk for Kenya in 2009.MethodsPlasmodium falciparum parasite rate data were assembled from cross-sectional community based surveys undertaken from 1975 to 2009. Details recorded for each survey included the month and year of the survey, sample size, positivity and the age ranges of sampled population. Data were corrected to a standard age-range of two to less than 10 years (PfPR2-10) and each survey location was geo-positioned using national and on-line digital settlement maps. Ecological and climate covariates were matched to each PfPR2-10 survey location and examined separately and in combination for relationships to PfPR2-10. Significant covariates were then included in a Bayesian geostatistical spatial-temporal framework to predict continuous and categorical maps of mean PfPR2-10 at a 1 × 1 km resolution across Kenya for the year 2009. Model hold-out data were used to test the predictive accuracy of the mapped surfaces and distributions of the posterior uncertainty were mapped.ResultsA total of 2,682 estimates of PfPR2-10 from surveys undertaken at 2,095 sites between 1975 and 2009 were selected for inclusion in the geo-statistical modeling. The covariates selected for prediction were urbanization; maximum temperature; precipitation; enhanced vegetation index; and distance to main water bodies. The final Bayesian geo-statistical model had a high predictive accuracy with mean error of -0.15% PfPR2-10; mean absolute error of 0.38% PfPR2-10; and linear correlation between observed and predicted PfPR2-10 of 0.81. The majority of Kenya's 2009 population (35.2 million, 86.3%) reside in areas where predicted PfPR2-10 is less than 5%; conversely in 2009 only 4.3 million people (10.6%) lived in areas where PfPR2-10 was predicted to be ≥40% and were largely located around the shores of Lake Victoria.ConclusionModel based geo-statistical methods can be used to interpolate malaria risks in Kenya with precision and our model shows that the majority of Kenyans live in areas of very low P. falciparum risk. As malaria interventions go to scale effectively tracking epidemiological changes of risk demands a rigorous effort to document infection prevalence in time and space to remodel risks and redefine intervention priorities over the next 10-15 years.

Predicting changing malaria risk after expanded insecticide-treated net coverage in Africa

The Roll Back Malaria (RBM) partnership has established goals for protecting vulnerable populations with locally appropriate vector control. In many places, these goals will be achieved by the mass distribution of insecticide treated bednets (ITNs). Mathematical models can forecast an ITN-driven realignment of malaria endemicity, defined by the Plasmodium falciparum parasite rate (PfPR) in children, to predict PfPR endpoints and appropriate program timelines for this change in Africa. The relative ease of measuring PfPR and its widespread use make it particularly suitable for monitoring and evaluation. This theory provides a method for context-dependent evaluation of ITN programs and a basis for setting rational ITN coverage targets over the next decade.

Defining the relationship between Plasmodium falciparum parasite rate and clinical disease: statistical models for disease burden estimation.

BackgroundClinical malaria has proven an elusive burden to enumerate. Many cases go undetected by routine disease recording systems. Epidemiologists have, therefore, frequently defaulted to actively measuring malaria in population cohorts through time. Measuring the clinical incidence of malaria longitudinally is labour-intensive and impossible to undertake universally. There is a need, therefore, to define a relationship between clinical incidence and the easier and more commonly measured index of infection prevalence: the "parasite rate". This relationship can help provide an informed basis to define malaria burdens in areas where health statistics are inadequate.MethodsFormal literature searches were conducted for Plasmodium falciparum malaria incidence surveys undertaken prospectively through active case detection at least every 14 days. The data were abstracted, standardized and geo-referenced. Incidence surveys were time-space matched with modelled estimates of infection prevalence derived from a larger database of parasite prevalence surveys and modelling procedures developed for a global malaria endemicity map. Several potential relationships between clinical incidence and infection prevalence were then specified in a non-parametric Gaussian process model with minimal, biologically informed, prior constraints. Bayesian inference was then used to choose between the candidate models.ResultsThe suggested relationships with credible intervals are shown for the Africa and a combined America and Central and South East Asia regions. In both regions clinical incidence increased slowly and smoothly as a function of infection prevalence. In Africa, when infection prevalence exceeded 40%, clinical incidence reached a plateau of 500 cases per thousand of the population per annum. In the combined America and Central and South East Asia regions, this plateau was reached at 250 cases per thousand of the population per annum. A temporal volatility model was also incorporated to facilitate a closer description of the variance in the observed data.ConclusionIt was possible to model a relationship between clinical incidence and P. falciparum infection prevalence but the best-fit models were very noisy reflecting the large variance within the observed opportunistic data sample. This continuous quantification allows for estimates of the clinical burden of P. falciparum of known confidence from wherever an estimate of P. falciparum prevalence is available.