The erythrocyte membrane properties of beta thalassaemia heterozygotes and their consequences for Plasmodium falciparum invasion

Malaria parasites such as Plasmodium falciparum have exerted formidable selective pressures on the human genome. Of the human genetic variants associated with malaria protection, beta thalassaemia (a haemoglobinopathy) was the earliest to be associated with malaria prevalence. However, the malaria protective properties of beta thalassaemic erythrocytes remain unclear. Here we studied the mechanics and surface protein expression of beta thalassaemia heterozygous erythrocytes, measured their susceptibility to P. falciparum invasion, and calculated the energy required for merozoites to invade them. We found invasion-relevant differences in beta thalassaemic cells versus matched controls, specifically: elevated membrane tension, reduced bending modulus, and higher levels of expression of the major invasion receptor basigin. However, these differences acted in opposition to each other with respect to their likely impact on invasion, and overall we did not observe beta thalassaemic cells to have lower P. falciparum invasion efficiency for any of the strains tested.

Spatial cluster analysis of Plasmodium vivax and P. malariae exposure using serological data among Haitian school children sampled between 2014 and 2016

Background Estimation of malaria prevalence in very low transmission settings is difficult by even the most advanced diagnostic tests. Antibodies against malaria antigens provide an indicator of active or past exposure to these parasites. The prominent malaria species within Haiti is Plasmodium falciparum, but P. vivax and P. malariae infections are also known to be endemic. Methodology/Principal findings From 2014–2016, 28,681 Haitian children were enrolled in school-based serosurveys and were asked to provide a blood sample for detection of antibodies against multiple infectious diseases. IgG against the P. falciparum, P. vivax, and P. malariae merozoite surface protein 19kD subunit (MSP119) antigens was detected by a multiplex bead assay (MBA). A subset of samples was also tested for Plasmodium DNA by PCR assays, and for Plasmodium antigens by a multiplex antigen detection assay. Geospatial clustering of high seroprevalence areas for P. vivax and P. malariae antigens was assessed by both Ripley’s K-function and Kulldorff’s spatial scan statistic. Of 21,719 children enrolled in 680 schools in Haiti who provided samples to assay for IgG against PmMSP119, 278 (1.27%) were seropositive. Of 24,559 children enrolled in 788 schools providing samples for PvMSP119 serology, 113 (0.46%) were seropositive. Two significant clusters of seropositivity were identified throughout the country for P. malariae exposure, and two identified for P. vivax. No samples were found to be positive for Plasmodium DNA or antigens. Conclusions/Significance From school-based surveys conducted from 2014 to 2016, very few Haitian children had evidence of exposure to P. vivax or P. malariae, with no children testing positive for active infection. Spatial scan statistics identified non-overlapping areas of the country with higher seroprevalence for these two malarias. Serological data provides useful information of exposure to very low endemic malaria species in a population that is unlikely to present to clinics with symptomatic infections.

Malaria Prevalence and Associated Factors among Pregnant Women Attending their First Antenatal Care in Kole and Kyenjojo Districts in Uganda

Malaria during pregnancy has negative consequences to both the mother and fetus. In 2019, there were an estimated 33million pregnancies globally, of which 35% were exposed to malaria in Africa. To avert the consequences, the Uganda Ministry of Health is implementing approaches for effective prevention with intermittent preventive treatment, use Insecticide-Treated Nets (ITN), prompt diagnosis, and treatment through antenatal care (ANC). This study was conducted to determine the prevalence of malaria and associated factors among pregnant women attending their first ANC visit in Kole and Kyenjojo Districts in Uganda. A cross-sectional study design was conducted among 760 randomly selected pregnant women. Quantitative data was collected using a structured questionnaire to gather participants’ demographic, obstetric, coverage, and use of malaria preventive methods and laboratory results on malaria, anaemia, and HIV. Data was analyzed using STATA 15. Chi-square, odds ratio, and logistic regression were used to test for associations. The overall prevalence of malaria was 11.1%, varying from 6.8% in Kyenjojo to 15.3% in Kole District. Most cases were caused by P. falciparum. Factors associated with malaria were age of mother (aOR: 0.44, 95% CI: 0.21-0.88), residence in Kyenjojo (aOR: 0.48, 95% CI: 0.26-0.88), multiparity (aOR: 0.38, 95% CI: 0.16-0.91), anaemia (aOR: 2.12, 95% CI: 1.12-4.00) and ITN non-use (aOR: 6.17, 95% CI: 2.76-13.86). Malaria prevalence was low and varied between districts. Age, gravidity, gestational age, and ITN use had a significant association with malaria. Therefore, early screening and identification of mothers at most risk of complications during pregnancy is needed, plus improving ANC.

Synergism in Antiplasmodial Activities of Artemether and Lumefantrine in Combination with Securidaca longipedunculata Fresen (Polygalaceae)

Malaria is the most lethal parasitic disease in the world. The frequent emergence of resistance by malaria parasites to any drug is the hallmark of sustained malaria burden. Since the deployment of artemisinin-based combination therapies (ACTs) it is clear that for a sustained fight against malaria, drug combination is one of the strategies toward malaria elimination. In Sub-Saharan Africa where malaria prevalence is the highest, the identification of plants with a novel mechanism of action that is devoid of cross-resistance is a feasible strategy in drug combination therapy. Thus, artemether and lumefantrine were separately combined and tested with extracts of Securidaca longipedunculata, a plant widely used to treat malaria, at fixed extract–drug ratios of 4:1, 3:1, 1:1, 1:2, 1:3, and 1:4. These combinations were tested for antiplasmodial activity against three strains of Plasmodium falciparum (W2, D6, and DD2), and seven field isolates that were characterized for molecular and ex vivo drug resistance profiles. The mean sum of fifty-percent fractional inhibition concentration (FIC50) of each combination and singly was determined. Synergism was observed across all fixed doses when roots extracts were combined with artemether against D6 strain (FIC50 0.403 ± 0.068) and stems extract combined with lumefantrine against DD2 strain (FIC50 0.376 ± 0.096) as well as field isolates (FIC50 0.656 ± 0.067). Similarly, synergism was observed in all ratios when leaves extract were combined with lumefantrine against W2 strain (FIC50 0.456 ± 0.165). Synergism was observed in most combinations indicating the potential use of S. longipedunculata in combination with artemether and lumefantrine in combating resistance.

Regional Heterogeneity of Malaria Prevalence And Associated Risk Factors Among Children Under Five In Togo: Evidence From National Malaria Indicators Survey

Background: Malaria remains one of the main causes of morbidity and death among children less than 5. In Togo, despite intensification of malaria control interventions, persistence in malaria prevalence was observed and appears to vary from one region to another within the country. The aim of this study is to explore further regional heterogeneities in malaria prevalence and to determine associated risk factors.Methods: Data from the cross-sectional survey of the nationally representative 2017 Togo malaria indicator survey was used. Children aged 6–59 months in the selected households were tested for malaria using the rapid diagnostic test (RDT) and the microscopy. Univariate and multivariate logistic regression analysis were preformed using Generalized Linear Models.Results: A total of 3271 children under five (2441 in rural areas and 830 in urban areas was enrolled. Overall 26% of children tested positive for malaria, as confirmed by microscopy, ranging from 5.3% in the Lomé Commune region to 43.6% in the Plateaux region. In multivariate analysis, factors associated with malaria prevalence were living in the Plateaux region (aOR=4.24, 95%CI [2.38-7.65]), and the Maritime region (aOR=2.02, 95%CI [1.13-3.66], compared to Lomé Commune region); age 24 to 35 months (aOR=1.46, 95%CI [1.13-1.88) and age 36 to 59 months (aOR=2.5, 95%CI [2.04-3.09]) ], Compared to those age 6-23 months; households within the richest wealth quintile (a.OR=0.22, 95%CI [0.11-0.41], compared to poorest) and residence in rural areas (aOR=2.02, 95%CI [1.32-3.13], compared to resident in urban). Conclusion: Interventions that targeted use of combined prevention measures, adapted to older children living in rural areas and particularly in the regions of high malaria prevalence, could result in better malaria control in Togo.

Prevalence of Infection and Malaria Parasite Density among Under Five Children: A Case Study of Dunukofia Rural Community in Anambra State, Nigeria

Aim: Malaria still remains an overwhelming cause of morbidity and mortality among children under five years of age, especially in sub-Saharan Africa. The study was carried out to evaluate malaria prevalence amongst children less than five years old. Study Design: A cross sectional study was carried out. The study adopted a retrospective descriptive survey using the hospital records and diagnostic cross sectional survey by examination of blood samples across three variables: gender, age group and mosquito net usage. Duration: The study was done in 2021 from the month of March to April in the rural community. Methodology: Parasitological diagnosis was with Plasmodium falciparum histidine-rich protein 2-based malaria Rapid Diagnostic Test (RDT) and microscopy of giemsa-stained blood smears. Demographic information was collected using questionnaire. Results: Three hundred (300) children aged less than five years malaria infection status was investigate, 174 (58.00% ) of them were females while 126 (42.00%. ) were males. Twenty one percent (21.00%) of the respondents are <1 year, 23.33% (70) of them are between the ages of 2 to 3 years, while 55.67% (167) were 4 years and above. Current malaria prevalence was higher with microscopy (67.33%) than that of RDT (23.33%). Also, previous RDT results showed that there was a higher prevalence (73.56%) of malaria parasites in females than males (58.73%). The microscopy results showed that males had a higher prevalence (38.10%) of malaria parasites than females (12.64%). Overall gender result also revealed that males had a higher prevalence (96.83%) of malaria parasites than females (86.21%). There was a significant difference in the prevalence result with gender (P<0.05). Females had higher parasite density (28.05±15.390) than males (23.22±19.171), there was no significant difference (P>0.05). It further revealed that children from 4 years and above had higher intensity (29.68±17.357) while those of 1 year and below had the least (14.89±16.069). However, there was no significant difference in the malaria parasite among the age groups of patients (P>0.05). Conclusion: Prevalence of malaria parasitaemia was still high in Dunukaofia, Anamba State, Nigeria despite various control measures and interventions put in place by WHO.

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.

Maplaria: a user friendly web-application for spatio-temporal malaria prevalence mapping

Background Model-based geostatistical (MBG) methods have been extensively used to map malaria risk using community survey data in low-resource settings where disease registries are incomplete or non-existent. However, the wider adoption of MBG methods by national control programmes to inform health policy decisions is hindered by the lack of advanced statistical expertise and suitable computational equipment. Here, Maplaria, an interactive, user-friendly web-application that allows users to upload their own malaria prevalence data and carry out geostatistical prediction of annual malaria prevalence at any desired spatial scale, is introduced. Methods In the design of the Maplaria web application, two main criteria were considered: the application should be able to classify subnational divisions into the most likely endemicity levels; the web application should allow only minimal input from the user in the set-up of the geostatistical inference process. To achieve this, the process of fitting and validating the geostatistical models is carried out by statistical experts using publicly available malaria survey data from the Harvard database. The stage of geostatistical prediction is entirely user-driven and allows the user to upload malaria data, as well as vector data that define the administrative boundaries for the generation of spatially aggregated inferences. Results The process of data uploading and processing is split into a series of steps spread across screens through the progressive disclosure technique that prevents the user being immediately overwhelmed by the length of the form. Each of these is illustrated using a data set from the Malaria Indicator carried out in Tanzania in 2017 as an example. Conclusions Maplaria application provides a user-friendly solution to the problem making geostatistical methods more accessible to users that have not undertaken formal training in statistics. The application is a useful tool that can be used to foster ownership, among policy makers, of disease risk maps and promote better use of data for decision-making in low resource settings.

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.