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Abstract Background Control of malaria parasite transmission can be enhanced by understanding which human demographic groups serve as the infectious reservoirs. Because vector biting can be heterogeneous, some infected individuals may contribute more to human-to-mosquito transmission than others. Infection prevalence peaks in school-age children, but it is not known how often they are fed upon. Genotypic profiling of human blood permits identification of individual humans who were bitten. The present investigation used this method to estimate which human demographic groups were most responsible for transmitting malaria parasites to Anopheles mosquitoes. It was hypothesized that school-age children contribute more than other demographic groups to human-to-mosquito malaria transmission. Methods In a region of moderate-to-high malaria incidence in southeastern Malawi, randomly selected households were surveyed to collect human demographic information and blood samples. Blood-fed, female Anopheles mosquitoes were sampled indoors from the same houses. Genomic DNA from human blood samples and mosquito blood meals of human origin was genotyped using 24 microsatellite loci. The resultant genotypes were matched to identify which individual humans were sources of blood meals. In addition, Plasmodium falciparum DNA in mosquito abdomens was detected with polymerase chain reaction. The combined results were used to identify which humans were most frequently bitten, and the P. falciparum infection prevalence in mosquitoes that resulted from these blood meals. Results Anopheles females selected human hosts non-randomly and fed on more than one human in 9% of the blood meals. Few humans contributed most of the blood meals to the Anopheles vector population. Children ≤ 5 years old were under-represented in mosquito blood meals while older males (31–75 years old) were over-represented. However, the largest number of malaria-infected blood meals was from school age children (6–15 years old). Conclusions The results support the hypothesis that humans aged 6–15 years are the most important demographic group contributing to the transmission of P. falciparum to the Anopheles mosquito vectors. This conclusion suggests that malaria control and prevention programmes should enhance efforts targeting school-age children and males.

IntroductionAcute febrile illnesses (AFI) are a frequent chief complaint in outpatients. Because the capacity to investigate the causative pathogen of AFIs is limited in low- and middle-income countries, patient management may be suboptimal. Understanding the distribution of causes of AFI can improve patient outcomes. This study aims to describe the most common etiologies diagnosed over a 16-years period in a national reference center for tropical diseases in a large urban center in Rio de Janeiro, Brazil.MethodsFrom August 2004-December 2019, 3591 patients > 12 years old, with AFI and/or rash were eligible. Complementary exams for etiological investigation were requested using syndromic classification as a decision guide. Results. Among the 3591 patients included, endemic arboviruses such as chikungunya (21%), dengue (15%) and zika (6%) were the most common laboratory-confirmed diagnosis, together with travel-related malaria (11%). Clinical presumptive diagnosis lacked sensitivity for emerging diseases such as zika (31%). Rickettsia disease and leptospirosis were rarely investigated and an infrequent finding when based purely on clinical features. Respiratory symptoms increased the odds for the diagnostic remaining inconclusive.ConclusionsNumerous patients did not have a conclusive etiologic diagnosis. Since syndromic classification used for standardization of etiological investigation and presumptive clinical diagnosis had moderate accuracy, it is necessary to incorporate new diagnostic technologies to improve diagnostic accuracy and surveillance capacity.

Abstract In areas where malaria remains entrenched, novel transmission-reducing interventions are essential for malaria elimination. We report the impact screening-and-treatment of asymptomatic Malawian schoolchildren (n = 364 in the rainy season and 341 in the dry season) had on gametocyte—the parasite stage responsible for human-to-mosquito transmission—carriage. We used concomitant household-based surveys to predict the potential reduction in transmission in the surrounding community. Among 253 students with P. falciparum infections at screening, 179 (71%) had infections containing gametocytes detected by Pfs25 qRT-PCR. 84% of gametocyte-containing infections were detected by malaria rapid diagnostic test. While the gametocyte prevalence remained constant in untreated children, treatment with artemether-lumefantrine reduced the gametocyte prevalence (p

The RTS,S/AS01E vaccine targets the circumsporozoite protein (CSP) of the Plasmodium falciparum (P. falciparum) parasite. Protein microarrays were used to measure levels of IgG against 1000 P. falciparum antigens in 2138 infants (age 6–12 weeks) and children (age 5–17 months) from 6 African sites of the phase III trial, sampled before and at 4 longitudinal visits after vaccination. One month postvaccination, IgG responses to 17% of all probed antigens showed differences between RTS,S/AS01E and comparator vaccination groups, whereas no prevaccination differences were found. A small subset of antigens presented IgG levels reaching 4- to 8-fold increases in the RTS,S/AS01E group, comparable in magnitude to anti-CSP IgG levels (~11-fold increase). They were strongly cross-correlated and correlated with anti-CSP levels, waning similarly over time and reincreasing with the booster dose. Such an intriguing phenomenon may be due to cross-reactivity of anti-CSP antibodies with these antigens. RTS,S/AS01E vaccinees with strong off-target IgG responses had an estimated lower clinical malaria incidence after adjusting for age group, site, and postvaccination anti-CSP levels. RTS,S/AS01E-induced IgG may bind strongly not only to CSP, but also to unrelated malaria antigens, and this seems to either confer, or at least be a marker of, increased protection from clinical malaria.

Abstract Background The necessity to analyze medium-throughput data in epidemiological studies with small sample size, particularly when studying biomedical data may hinder the use of classical statistical methods. Support vector machines (SVM) models can be successfully applied in this setting because they are a powerful tool to analyze data with large number of predictors and limited sample size, especially when handling binary outcomes. However, biomedical research often involves analysis of time-to-event outcomes and has to account for censoring. Methods to handle censored data in the SVM framework can be divided into two classes: those based on support vector regression (SVR) and those based on binary classification. Methods based on SVR seem to be suboptimal to handle sparse data and yield results comparable to Cox proportional hazards model and kernel Cox regression. The limited work dedicated to assess methods based on of SVM for binary classification has been based on SVM learning using privileged information and SVM with uncertain classes. Results This paper proposes alternative methods and extensions within the binary classification framework, specifically, a conditional survival approach for weighting censored observations and a semi-supervised SVM with local invariances. Using simulation studies and some real datasets, we evaluate those two methods and compare them with a weighted SVM model, SVM extensions found in the literature, kernel Cox regression and Cox model. Conclusions Our proposed methods perform generally better under a wide variety of realistic scenarios about the structure of biomedical data. Specifically, the local invariances method using the conditional survival approach is the most robust method under different scenarios and is a good approach to consider as an alternative to other time-to-event methods. When analysing real data is a method to be considered and recommended since outperforms other methods in proportional and non-proportional scenarios and sparse data, which is something usual in biomedical data and biomarkers analysis.

Background: In a phase 3 trial in African infants and children, the RTS,S/AS01 vaccine (GSK) showed moderate efficacy against clinical malaria. We sought to further understand RTS,S/AS01-induced immune responses associated with vaccine protection. Methods: Applying the blood transcriptional module (BTM) framework, we characterized the transcriptomic response to RTS,S/AS01 vaccination in antigen-stimulated (and vehicle control) peripheral blood mononuclear cells sampled from a subset of trial participants at baseline and month 3 (1-month post-third dose). Using a matched case–control study design, we evaluated which of these ‘RTS,S/AS01 signature BTMs’ associated with malaria case status in RTS,S/AS01 vaccinees. Antigen-specific T-cell responses were analyzed by flow cytometry. We also performed a cross-study correlates analysis where we assessed the generalizability of our findings across three controlled human malaria infection studies of healthy, malaria-naive adult RTS,S/AS01 recipients. Results: RTS,S/AS01 vaccination was associated with downregulation of B-cell and monocyte-related BTMs and upregulation of T-cell-related BTMs, as well as higher month 3 (vs. baseline) circumsporozoite protein-specific CD4+ T-cell responses. There were few RTS,S/AS01-associated BTMs whose month 3 levels correlated with malaria risk. In contrast, baseline levels of BTMs associated with dendritic cells and with monocytes (among others) correlated with malaria risk. The baseline dendritic cell- and monocyte-related BTM correlations with malaria risk appeared to generalize to healthy, malaria-naive adults. Conclusions: A prevaccination transcriptomic signature associates with malaria in RTS,S/AS01-vaccinated African children, and elements of this signature may be broadly generalizable. The consistent presence of monocyte-related modules suggests that certain monocyte subsets may inhibit protective RTS,S/AS01-induced responses. Funding: Funding was obtained from the NIH-NIAID (R01AI095789), NIH-NIAID (U19AI128914), PATH Malaria Vaccine Initiative (MVI), and Ministerio de Economía y Competitividad (Instituto de Salud Carlos III, PI11/00423 and PI14/01422). The RNA-seq project has been funded in whole or in part with Federal funds from the National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services, under grant number U19AI110818 to the Broad Institute. This study was also supported by the Vaccine Statistical Support (Bill and Melinda Gates Foundation award INV-008576/OPP1154739 to R.G.). C.D. was the recipient of a Ramon y Cajal Contract from the Ministerio de Economía y Competitividad (RYC-2008-02631). G.M. was the recipient of a Sara Borrell–ISCIII fellowship (CD010/00156) and work was performed with the support of Department of Health, Catalan Government grant (SLT006/17/00109). This research is part of the ISGlobal’s Program on the Molecular Mechanisms of Malaria which is partially supported by the Fundación Ramón Areces and we acknowledge support from the Spanish Ministry of Science and Innovation through the ‘Centro de Excelencia Severo Ochoa 2019–2023’ Program (CEX2018-000806-S), and support from the Generalitat de Catalunya through the CERCA Program.

Introduction Clinically diagnosed pneumonia in children is a leading cause of paediatric hospitalisation and mortality. The aetiology is usually bacterial or viral, but malaria can cause a syndrome indistinguishable from clinical pneumonia. There is no method with high sensitivity to detect a bacterial infection in these patients and, as result, antibiotics are frequently overprescribed. Conversely, unrecognised concomitant bacterial infection in patients with malarial infections occur with omission of antibiotic therapy from patients with bacterial infections. Previously, we identified two combinations of blood proteins with 96% sensitivity and 86% specificity for detecting bacterial disease. The current project aimed to validate and improve these combinations by evaluating additional biomarkers in paediatric patients with clinical pneumonia. Our goal was to describe combinations of a limited number of proteins with high sensitivity and specificity for bacterial infection to be incorporated in future point-of-care tests. Furthermore, we seek to explore signatures to prognosticate clinical pneumonia.Methods and analysis Patients (n=900) aged 2–59 months presenting with clinical pneumonia at two Gambian hospitals will be enrolled and classified according to criteria for definitive bacterial aetiology (based on microbiological tests and chest radiographs). We will measure proteins at admission using Luminex-based immunoassays in 90 children with definitive and 160 with probable bacterial aetiology, and 160 children classified according to the prognosis of their disease. Previously identified diagnostic signatures will be assessed through accuracy measures. Moreover, we will seek new diagnostic and prognostic signatures through machine learning methods, including support vector machine, penalised regression and classification trees.Ethics and dissemination Ethics approval has been obtained from the Gambia Government/Medical Research Council Unit The Gambia Joint Ethics Committee (protocol 1616) and the institutional review board of Boston University Medical Centre (STUDY00000958). Study results will be disseminated to the staff of the study hospitals, in scientific seminars and meetings, and in publications.Trial registration number H-38462.

Abstract Background Vaccination and naturally acquired immunity against microbial pathogens may have complex interactions that influence disease outcomes. To date, only vaccine-specific immune responses have routinely been investigated in malaria vaccine trials conducted in endemic areas. We hypothesized that RTS,S/A01E immunization affects acquisition of antibodies to Plasmodium falciparum antigens not included in the vaccine and that such responses have an impact on overall malaria protective immunity. Methods We evaluated IgM and IgG responses to 38 P. falciparum proteins putatively involved in naturally acquired immunity to malaria in 195 young children participating in a case-control study nested within the African phase 3 clinical trial of RTS,S/AS01E (MAL055 NCT00866619) in two sites of different transmission intensity (Kintampo high and Manhiça moderate/low). We measured antibody levels by quantitative suspension array technology and applied regression models, multimarker analysis, and machine learning techniques to analyze factors affecting their levels and correlates of protection. Results RTS,S/AS01E immunization decreased antibody responses to parasite antigens considered as markers of exposure (MSP142, AMA1) and levels correlated with risk of clinical malaria over 1-year follow-up. In addition, we show for the first time that RTS,S vaccination increased IgG levels to a specific group of pre-erythrocytic and blood-stage antigens (MSP5, MSP1 block 2, RH4.2, EBA140, and SSP2/TRAP) which levels correlated with protection against clinical malaria (odds ratio [95% confidence interval] 0.53 [0.3–0.93], p = 0.03, for MSP1; 0.52 [0.26–0.98], p = 0.05, for SSP2) in multivariable logistic regression analyses. Conclusions Increased antibody responses to specific P. falciparum antigens in subjects immunized with this partially efficacious vaccine upon natural infection may contribute to overall protective immunity against malaria. Inclusion of such antigens in multivalent constructs could result in more efficacious second-generation multistage vaccines.

RTS,S/AS01E has been tested in a phase 3 malaria vaccine trial and has shown partial efficacy in children and infants. Here, the authors analyze IgG concentration and avidity to CSP in ~1000 participants and show that IgG avidity to the C-terminus of CSP is significantly associated with vaccine-mediated protection.

Abstract Background Support vector machines (SVM) are a powerful tool to analyze data with a number of predictors approximately equal or larger than the number of observations. However, originally, application of SVM to analyze biomedical data was limited because SVM was not designed to evaluate importance of predictor variables. Creating predictor models based on only the most relevant variables is essential in biomedical research. Currently, substantial work has been done to allow assessment of variable importance in SVM models but this work has focused on SVM implemented with linear kernels. The power of SVM as a prediction model is associated with the flexibility generated by use of non-linear kernels. Moreover, SVM has been extended to model survival outcomes. This paper extends the Recursive Feature Elimination (RFE) algorithm by proposing three approaches to rank variables based on non-linear SVM and SVM for survival analysis. Results The proposed algorithms allows visualization of each one the RFE iterations, and hence, identification of the most relevant predictors of the response variable. Using simulation studies based on time-to-event outcomes and three real datasets, we evaluate the three methods, based on pseudo-samples and kernel principal component analysis, and compare them with the original SVM-RFE algorithm for non-linear kernels. The three algorithms we proposed performed generally better than the gold standard RFE for non-linear kernels, when comparing the truly most relevant variables with the variable ranks produced by each algorithm in simulation studies. Generally, the RFE-pseudo-samples outperformed the other three methods, even when variables were assumed to be correlated in all tested scenarios. Conclusions The proposed approaches can be implemented with accuracy to select variables and assess direction and strength of associations in analysis of biomedical data using SVM for categorical or time-to-event responses. Conducting variable selection and interpreting direction and strength of associations between predictors and outcomes with the proposed approaches, particularly with the RFE-pseudo-samples approach can be implemented with accuracy when analyzing biomedical data. These approaches, perform better than the classical RFE of Guyon for realistic scenarios about the structure of biomedical data.

Abstract Background Developing and sustaining a data collection and management system (DCMS) is difficult in malaria-endemic countries because of limitations in internet bandwidth, computer resources and numbers of trained personnel. The premise of this paper is that development of a DCMS in West Africa was a critically important outcome of the West African International Centers of Excellence for Malaria Research. The purposes of this paper are to make that information available to other investigators and to encourage the linkage of DCMSs to international research and Ministry of Health data systems and repositories. Methods We designed and implemented a DCMS to link study sites in Mali, Senegal and The Gambia. This system was based on case report forms for epidemiologic, entomologic, clinical and laboratory aspects of plasmodial infection and malarial disease for a longitudinal cohort study and included on-site training for Principal Investigators and Data Managers. Based on this experience, we propose guidelines for the design and sustainability of DCMSs in environments with limited resources and personnel. Results From 2012 to 2017, we performed biannual thick smear surveys for plasmodial infection, mosquito collections for anopheline biting rates and sporozoite rates and year-round passive case detection for malarial disease in four longitudinal cohorts with 7708 individuals and 918 households in Senegal, The Gambia and Mali. Major challenges included the development of uniform definitions and reporting, assessment of data entry error rates, unstable and limited internet access and software and technology maintenance. Strengths included entomologic collections linked to longitudinal cohort studies, on-site data centres and a cloud-based data repository. Conclusions At a time when research on diseases of poverty in low and middle-income countries is a global priority, the resources available to ensure accurate data collection and the electronic availability of those data remain severely limited. Based on our experience, we suggest the development of a regional DCMS. This approach is more economical than separate data centres and has the potential to improve data quality by encouraging shared case definitions, data validation strategies and analytic approaches including the molecular analysis of treatment successes and failures.

Abstract Background The RTS,S/AS01E vaccine provides partial protection against malaria in African children, but immune responses have only been partially characterized and do not reliably predict protective efficacy. We aimed to evaluate comprehensively the immunogenicity of the vaccine at peak response, the factors affecting it, and the antibodies associated with protection against clinical malaria in young African children participating in the multicenter phase 3 trial for licensure. Methods We measured total IgM, IgG, and IgG1–4 subclass antibodies to three constructs of the Plasmodium falciparum circumsporozoite protein (CSP) and hepatitis B surface antigen (HBsAg) that are part of the RTS,S vaccine, by quantitative suspension array technology. Plasma and serum samples were analyzed in 195 infants and children from two sites in Ghana (Kintampo) and Mozambique (Manhiça) with different transmission intensities using a case-control study design. We applied regression models and machine learning techniques to analyze immunogenicity, correlates of protection, and factors affecting them. Results RTS,S/AS01E induced IgM and IgG, predominantly IgG1 and IgG3, but also IgG2 and IgG4, subclass responses. Age, site, previous malaria episodes, and baseline characteristics including antibodies to CSP and other antigens reflecting malaria exposure and maternal IgGs, nutritional status, and hemoglobin concentration, significantly affected vaccine immunogenicity. We identified distinct signatures of malaria protection and risk in RTS,S/AS01E but not in comparator vaccinees. IgG2 and IgG4 responses to RTS,S antigens post-vaccination, and anti-CSP and anti-P. falciparum antibody levels pre-vaccination, were associated with malaria risk over 1-year follow-up. In contrast, antibody responses to HBsAg (all isotypes, subclasses, and timepoints) and post-vaccination IgG1 and IgG3 to CSP C-terminus and NANP were associated with protection. Age and site affected the relative contribution of responses in the correlates identified. Conclusions Cytophilic IgG responses to the C-terminal and NANP repeat regions of CSP and anti-HBsAg antibodies induced by RTS,S/AS01E vaccination were associated with malaria protection. In contrast, higher malaria exposure at baseline and non-cytophilic IgG responses to CSP were associated with disease risk. Data provide new correlates of vaccine success and failure in African children and reveal key insights into the mode of action that can guide development of more efficacious next-generation vaccines.

An amendment to this paper has been published and can be accessed via the original article.

Naturally acquired immunity (NAI) to Plasmodium falciparum malaria is mainly mediated by IgG antibodies but the subclasses, epitope targets and effector functions have not been unequivocally defined. Dissecting the type and specificity of antibody responses mediating NAI is a key step toward developing more effective vaccines to control the disease. We investigated the role of IgG subclasses to malaria antigens in protection against disease and the factors that affect their levels, including vaccination with RTS,S/AS01E. We analyzed plasma and serum samples at baseline and 1 month after primary vaccination with RTS,S or comparator in African children and infants participating in a phase 3 trial in two sites of different malaria transmission intensity: Kintampo in Ghana and Manhiça in Mozambique. We used quantitative suspension array technology (qSAT) to measure IgG1−4 responses to 35 P. falciparum pre-erythrocytic and blood stage antigens. Our results show that the pattern of IgG response is predominantly IgG1 or IgG3, with lower levels of IgG2 and IgG4. Age, site and RTS,S vaccination significantly affected antibody subclass levels to different antigens and susceptibility to clinical malaria. Univariable and multivariable analysis showed associations with protection mainly for cytophilic IgG3 levels to selected antigens, followed by IgG1 levels and, unexpectedly, also with IgG4 levels, mainly to antigens that increased upon RTS,S vaccination such as MSP5 and MSP1 block 2, among others. In contrast, IgG2 was associated with malaria risk. Stratified analysis in RTS,S vaccinees pointed to novel associations of IgG4 responses with immunity mainly involving pre-erythrocytic antigens upon RTS,S vaccination. Multi-marker analysis revealed a significant contribution of IgG3 responses to malaria protection and IgG2 responses to malaria risk. We propose that the pattern of cytophilic and non-cytophilic IgG antibodies is antigen-dependent and more complex than initially thought, and that mechanisms of both types of subclasses could be involved in protection. Our data also suggests that RTS,S efficacy is significantly affected by NAI, and indicates that RTS,S vaccination significantly alters NAI.

Reducing variability of quantitative suspension array assays is key for multi-center and large sero-epidemiological studies. To maximize precision and robustness of an in-house IgG multiplex assay, we analyzed the effect of several conditions on variability to find the best combination. The following assay conditions were studied through a fractional factorial design: antigen-bead coupling (stock vs. several), sample predilution (stock vs. daily), temperature of incubation of sample with antigen-bead (22°C vs. 37°C), plate washing (manual vs. automatic) and operator expertise (expert vs. apprentice). IgG levels against seven P. falciparum antigens with heterogeneous immunogenicities were measured in test samples, in a positive control and in blanks. We assessed the variability and MFI quantification range associated to each combination of conditions, and their interactions, and evaluated the minimum number of samples and blank replicates to achieve good replicability. Results showed that antigen immunogenicity and sample seroreactivity defined the optimal dilution to assess the effect of assay conditions on variability. We found that a unique antigen-bead coupling, samples prediluted daily, incubation at 22°C, and automatic washing, had lower variability. However, variability increased when performing several couplings and incubating at 22°C vs. 37°C. In addition, no effect of temperature was seen with a unique coupling. The expertise of the operator had no effect on assay variability but reduced the MFI quantification range. Finally, differences between sample replicates were minimal, and two blanks were sufficient to capture assay variability, as suggested by the constant Intraclass Correlation Coefficient of three and two blanks. To conclude, a single coupling was the variable that most consistently reduced assay variability, being clearly advisable. In addition, we suggest having more sample dilutions instead of replicates to increase the likelihood of sample MFIs falling in the linear part of the antigen-specific curve, thus increasing precision.

Comprehensive assessment of cellular responses to the RTS,S/AS01E vaccine is needed to understand potential correlates and ultimately mechanisms of protection against malaria disease. Cellular responses recognizing the RTS,S/AS01E-containing circumsporozoite protein (CSP) and Hepatitis B surface antigen (HBsAg) were assessed before and 1 month after primary vaccination by intracellular cytokine staining and 16-color flow cytometry in 105 RTS,S/AS01-vaccinated and 74 rabies-vaccinated participants (controls) in a pediatric phase III trial in Africa. RTS,S/AS01E-vaccinated children had significantly higher frequencies of CSP- and HBsAg-specific CD4+ T cells producing IL-2, TNF-α, and CD40L and HBsAg-specific CD4+ T producing IFN-γ and IL-17 than baseline and the control group. Vaccine-induced responses were identified in both central and effector memory (EM) compartments. EM CD4+ T cells expressing IL-4 and IL-21 were detected recognizing both vaccine antigens. Consistently higher response rates to both antigens in RTS,S/AS01E-vaccinated than comparator-vaccinated children were observed. RTS,S/AS01E induced polyfunctional CSP- and HBsAg-specific CD4+ T cells, with a greater degree of polyfunctionality in HBsAg responses. In conclusion, RTS,S/AS01E vaccine induces T cells of higher functional heterogeneity and polyfunctionality than previously characterized. Responses detected in memory CD4+ T cell compartments may provide correlates of RTS,S/AS01-induced immunity and duration of protection in future correlates of immunity studies.

Multiplex bead-based immunoassays are used to measure concentrations of several analytes simultaneously. These assays include control standard curves (SC) to reduce between-plate variability and normalize quantitation of analytes of biological samples. Suboptimal calibration might result in large random error and decreased number of samples with analyte concentrations within the limits of quantification. Suboptimal calibration may be a consequence of poor fitness of the functions used for the SC, the treatment of the background noise and the method used to estimate the limits of quantification. Currently assessment of fitness of curves is largely dependent on operator and that may add additional error. Moreover, there is no software to automate data managing and quality control. In this article we present a R package, drLumi, with functions for managing data, calibrating assays and performing quality control. To optimize the assay the package implements: i) three dose-response functions, ii) four approaches for treating background noise and iii) three methods for estimating limits of quantifications. Other implemented functions are focused on the quality control of the fitted standard curve: detection of outliers, estimation of the confidence or prediction interval, and estimation of summary statistics. With demonstration purpose, we apply the software to 30 cytokines, chemokines and growth factors measured in a multiplex bead-based immunoassay in a study aiming to measure correlates of risk or protection from malaria of the RTS,S malaria vaccine nested in the Phase 3 randomized controlled trial of this vaccine.

Malaria surveillance and interventions in endemic countries often target young children at highest risk of malaria morbidity and mortality. We aimed to determine whether school-age children and adults not captured in surveillance serve as a reservoir for malaria infection and may contribute to malaria transmission. Cross-sectional surveys were conducted in one rainy and one dry season in southern Malawi. Demographic and health information was collected for all household members. Blood samples were obtained for microscopic and PCR identification of Plasmodium falciparum. Among 5796 individuals aged greater than six months, PCR prevalence of malaria infection was 5%, 10%, and 20% in dry, and 9%, 15%, and 32% in rainy seasons in Blantyre, Thyolo, and Chikhwawa, respectively. Over 88% of those infected were asymptomatic. Participants aged 6-15 years were at higher risk of infection (OR=4.8; 95%CI, 4.0-5.8) and asymptomatic infection (OR=4.2; 95%CI, 2.7-6.6) than younger children in all settings. School-age children used bednets less frequently than other age groups. Compared to young children, school-age children were brought less often for treatment and more often to unreliable treatment sources.School-age children represent an underappreciated reservoir of malaria infection and have less exposure to antimalarial interventions. Malaria control and elimination strategies may need to expand to include this age group.

Molecular interactions between male and female factors during mating profoundly affect the reproductive behavior and physiology of female insects. In natural populations of the malaria mosquito Anopheles gambiae, blood-fed females direct nutritional resources towards oogenesis only when inseminated. Here we show that the mating-dependent pathway of egg development in these mosquitoes is regulated by the interaction between the steroid hormone 20-hydroxy-ecdysone (20E) transferred by males during copulation and a female Mating-Induced Stimulator of Oogenesis (MISO) protein. RNAi silencing of MISO abolishes the increase in oogenesis caused by mating in blood-fed females, causes a delay in oocyte development, and impairs the function of male-transferred 20E. Co-immunoprecipitation experiments show that MISO and 20E interact in the female reproductive tract. Moreover MISO expression after mating is induced by 20E via the Ecdysone Receptor, demonstrating a close cooperation between the two factors. Male-transferred 20E therefore acts as a mating signal that females translate into an increased investment in egg development via a MISO-dependent pathway. The identification of this male-female reproductive interaction offers novel opportunities for the control of mosquito populations that transmit malaria.

Plasmodium falciparum infected erythrocytes (IE) accumulate in the placenta through the interaction between Duffy-binding like (DBL) domains of parasite-encoded ligand VAR2CSA and chondroitin sulphate-A (CSA) receptor. Polymorphisms in these domains, including DBL2X and DBL3X, may affect their antigenicity or CSA-binding affinity, eventually increasing parasitemia and its adverse effects on pregnancy outcomes. A total of 373 DBL2X and 328 DBL3X sequences were obtained from transcripts of 20 placental isolates infecting Mozambican women, resulting in 176 DBL2X and 191 DBL3X unique sequences at the protein level. Sequence alignments were divided in segments containing combinations of correlated polymorphisms and the association of segment sequences with placental parasite density was tested using Bonferroni corrected regression models, taking into consideration the weight of each sequence in the infection. Three DBL2X and three DBL3X segments contained signatures of high parasite density (P