E malaria vaccine  and seasonal malaria chemoprevention (four monthly cycles per year) was markedly more effective than either intervention given alone in preventing clinical malaria, severe malaria, and deaths from malaria.A recent trial of 5920 children in Burkina Faso and Mali showed that the combination of seasonal vaccination with the RTS,S/AS01E when deployed seasonally, by comparing the group who received the combination of SMC and RTS,S/AS01E with the group who received SMC alone. The duration of protection from SMC was also estimated comparing the combined intervention group with the group who received RTS,S/AS01E alone. Three methods were used: Piecewise Cox regression, Flexible parametric survival models and Smoothed Schoenfeld residuals from Cox models, stratifying on the study area and using robust standard errors to control for within-child clustering of multiple episodes.In order to help optimise the timing of these two interventions, trial data were reanalysed to estimate the duration of protection against clinical malaria provided by RTS,S/AS01E over 6 months was at least 60% following the primary series and the two seasonal booster doses and remained at a high level over the full malaria transmission season. Beyond 6 months, protective efficacy appeared to wane more rapidly, but the uncertainty around the estimates increases due to the lower number of cases during this period (coinciding with the onset of the dry season). Protection from SMC exceeded 90% in the first 2–3 weeks post-administration after several cycles, but was not 100%, even immediately post-administration. Efficacy begins to decline from approximately day 21 and then declines more sharply after day 28, indicating the importance of preserving the delivery interval for SMC cycles at a maximum of four weeks.The overall protective efficacy from RTS,S/AS01The efficacy of both interventions was highest immediately post-administration. Understanding differences between these interventions in their peak efficacy and how rapidly efficacy declines over time will help to optimise the scheduling of SMC, malaria vaccination and the combination in areas of seasonal transmission with differing epidemiology, and using different vaccine delivery systems.The RTS,S-SMC trial in which these data were collected was registered at clinicaltrials.gov: NCT03143218The online version contains supplementary material available at 10.1186/s12916-022-02536-5. Seasonal malaria chemoprevention (SMC) is now deployed at scale in West Africa, with approximately 33.5 million children receiving treatments in 2020 . SulfadoE malaria vaccine was markedly more effective than either intervention given alone in preventing clinical malaria, severe malaria requiring admission to hospital, and deaths from malaria [E vaccine may add to protection in children receiving SMC because its longer mode of action provides protection outside the months covered by SMC, when children are still highly exposed to malaria transmission, and because it adds to the incomplete protection from SMC during the months when SMC is administered. It was hypothesised that seasonal administration of the vaccine, with the third dose of the primary series ) administered one month before SMC starts, might optimise this impact by aligning the period of peak protection from the vaccine with the period of highest malaria risk [A recent trial conducted in Burkina Faso and Mali showed that the combination of SMC and seasonal vaccination with the RTS,S/AS01 malaria . Relativria risk .E malaria vaccine in areas with persisting high malaria transmission, including the possibility of seasonal administration in areas with seasonal transmission [E to be deployed at scale to protect children under 5 years of age, it is important to understand in more detail the extent and duration of additional protection provided when the interventions are given in combination, compared to either intervention given alone. This has implications for how these two interventions might best be timed in relation to the period of peak risk, and in relation to each other. In turn, this might have implications for which delivery systems might be most appropriate in different locations, balancing the potentially competing priorities of ideal timing, achieving high coverage, and cost-effectiveness and sustainability of delivery.On 6 October 2021, the World Health Organisation (WHO) recommended the deployment of the RTS,S/AS01smission . With thE malaria vaccine changes over time, when administered seasonally, and (2) the duration of protection following SMC treatments.To help inform decisions that might be taken by policy makers and programme managers on how to combine SMC and seasonal malaria vaccination for optimal impact in areas with differing patterns of seasonal transmission, and to help inform mathematical modelling analyses that might support these decisions, we undertook a secondary analysis of data from the seasonal malaria vaccination trial. The purpose of these analyses was to estimate (1) how the efficacy of the RTS,S/AS01P. falciparum (>90%) and the predominant malaria vector is Anopheles gambiae in each of the two study areas. A high proportion (>75%) of children sleep under a long-lasting insecticidal net (LLIN); all study children received a new LLIN upon enrolment. The trial protocol and findings have been described in detail elsewhere [The data analysed in the present study were collected during the RTS,S-SMC individually-randomised, controlled trial conducted in Bougouni and Ouélessébougou districts, Mali and in Houndé district, Burkina Faso. Malaria transmission in these districts is intense and highly seasonal, with a peak in incidence lasting from July to November . The domlsewhere , 9.E vaccine and placebo SMC), and (3) ‘Combined’ intervention group . All SMC doses  were given as four monthly treatment courses every year, beginning in July. SMC or placebo SMC was given over 3 days, dosed according to age, as directly observed therapy, documented using a tablet PC, with QR codes on the photo ID card and drug packs to ensure each treatment was given to the correct child, and that all doses administered were recorded. All vaccine doses  were administered in April, May, and June of 2017 prior to the rainy season (July to October) and in the month of June in 2018 and 2019. RTS,S/AS01E was provided by GSK, Belgium. Control vaccines without antimalarial activity consisted of three doses of rabies vaccine  in 2017, followed by annual hepatitis A vaccine . Children were not screened for malaria infection at the time of vaccination or SMC, unless they were febrile or had other features suggestive of malaria. Children who were found to have malaria were treated according to national guidelines, offered vaccination when they had recovered and were eligible to receive the next round of SMC or placebo SMC.Briefly, children were enrolled if the child would be aged 5–17 months on 1 April 2017 and randomised to one of three groups, referred to as (1) ‘SMC alone’ (Control vaccines and SMC), (2) ‘RTS,S alone’ . RDT-confirmed cases were managed with artemether-lumefantrine, following national guidelines. A case of malaria was suspected if a child presented at a health facility in the study area with fever or a history of fever within the past 48 h  and without other symptoms that could explain the fever. A blood film was obtained from all suspected malaria cases for subsequent microscopy, read by two independent microscopists. Parasite density was estimated and discrepancies were resolved by a third reader, when necessary, using a standardised algorithm . The priE over time were based on a comparison of the Combined and SMC alone groups. Both groups received active SMC; the only difference between these groups was that one was randomly assigned to receive the RTS,S/AS01E vaccine (the Combined group) and the other to receive control vaccines   their comparison can be interpreted as vaccine efficacy.Protective efficacy was assessed separately for each ‘study year’, following the scheduled date for receipt of the third dose of the primary series (given in 2017), the scheduled date of the first booster (fourth dose) given in June 2018, and the scheduled date of the second booster (fifth dose) given in June 2019, including all children remaining in the SMC alone and Combined intervention groups at the time that these vaccination doses were scheduled. The analysis period in each study year began 14 days after the administration of the third dose of the primary series or 14 days after the administration of the annual booster  until the end of the corresponding study year, including the period of low malaria transmission . Although the underlying risk in both the SMC alone and Combined groups was reduced by SMC during the period when SMC was administered between approximately 1 and 5 months post-vaccination , stratified by study country.Initially, to facilitate comparisons with other malaria vaccine studies, the protective efficacy of RTS,S/AS01The profile of protective efficacy over time since the final dose in each study year was then investigated in more detail by comparing malaria incidence in the Combined group to that in the SMC-alone group, using three regression approaches, referred to as ‘Piecewise Cox Regression’, ‘Flexible Parametric Models’ and ‘Smoothed Schoenfeld Residuals’, as described in more detail below. Three methods were used in order to avoid the estimated profile of protection being dependent on a single set of assumptions from a particular model. In each case, country was a stratification factor, and robust standard errors were used to account for recurrent events in the same child when calculating confidence intervals. The first two methods used Stata , and the third used R (version 3.6.3).E . The hazard ratio (HR) comparing the Combined group to the SMC group was estimated for each 90-day period by including a term for the interaction between time period and intervention group in the Cox model. The hazard ratio was assumed to be constant within each 90-day period (this was a compromise between assuming efficacy would remain constant over each stratum and having sufficient events within each stratum that there was reasonable precision around the estimated HR). The average protective efficacy of RTS,S/AS01E during each period was estimated as (1-HR), expressed as a percentage.Person-time at risk time was stratified more finely into 90-day periods, starting from 14 days after the third, fourth or fifth doses of RTS,S/AS01E vaccine (relative to control vaccines) to be estimated. Models were fitted with 1 to 10 degrees of freedom for the cubic spline, and 1 to 10 degrees of freedom for the effect of intervention group ) as a time-varying covariate. All combinations of the degrees of freedom for the cubic spline and intervention effect were fitted, i.e. 100 candidate models for each study year. The Bayesian information criterion (BIC) was used to compare models. The hazard ratio comparing the Combined group to the SMC alone group, as a function of time since vaccination, and its 95% confidence interval, were estimated from the best fitting model for each year. Time-specific efficacy, as a percentage, was calculated as (1-HR).The second approach fitted flexible parametric survival models (Royston-Parmar models) to the data using the ‘stpm2’ commands in Stata , which mThe third approach estimated the changing log hazard ratio over time since vaccination in each study year, by smoothing the scaled Schoenfeld residuals after fitting a Cox regression model, as described previously , 14. TheE alone group. Both groups received the RTS,S/AS01E vaccine, but differed with respect to whether they were randomly assigned to receive active SMC or placebo SMC  was assFor each 30-day period, all clinical malaria episodes were included starting from the date of the first daily dose of SMC (with the same rule applied as described above to avoid double counting). Hazard ratios (assumed constant within each 30-day period) were estimated from piecewise Cox regression models, stratified on study country, with a robust standard error to account for multiple episodes per child. Average protective efficacy during each period was estimated as (1-HR), expressed as a percentage.To understand the effectiveness of SMC with different levels of adherence , this analysis was repeated with three analysis populations, using the information on daily doses recorded by study staff who administered SMC on each day. The first analysis population, referred to as ‘Scheduled SMC’, included all children remaining in follow-up at the time of the SMC cycle, irrespective of whether any SMC was received in practice . For children who did not receive SMC in a particular month, the median date of administration for that cycle in the same country and month, was used to define the start of the 30-day period. The second analysis population, referred to as ‘Received SMC’, included children who received at least the first daily dose of the SMC cycle, (whether or not they received the subsequent daily doses). Thirdly, the ‘Full SMC’ analysis population was restricted to children for whom all three daily doses of SMC or placebo SMC were recorded as having been successfully administered as DOT.A pooled estimate of the average protective efficacy of SMC over 30 days post-treatment, combining the data for all 12 cycles of SMC, was also calculated for each of these three analysis populations, using a Cox model stratified by country and SMC cycle. Finally, to give an estimate of the protection provided by incomplete SMC, a pooled estimate of protective efficacy over all 12 cycles was calculated for children who received the first dose of SMC or SMC placebo in a particular month but who did not receive doses 2 and 3 (i.e. it was documented on the tablet PC that AQ was not administered on days 2 and 3).To investigate the level of protection in the first 3 weeks post SMC (prior to the period when efficacy is thought to wane), estimates of protection in the first 21 days after each SMC cycle were also calculated for the ‘Received SMC’ population and compared to the results over the first 30 days.The profile of SMC protection over time is important when considering the suitability of the current monthly scheduling of SMC, and interpreting the frequent observation that, in the context of SMC programmes, a large number of malaria episodes occur shortly before the next monthly administration is due. The profile of protection was estimated over two periods: the first 30 days after SMC administration, including data from all 12 SMC cycles, and the first 60 days post-administration, including data from SMC cycles 4, 8 and 12 . Figure In the regression models described below, the specific SMC cycle was included as a 12-level categorical variable in the analysis of malaria incidence up to 30 days after all SMC cycles, and as a 3-level categorical variable in the analysis of incidence up to 60 days after SMC 4, 8 and 12.As for the analysis of vaccine protection over time, both flexible parametric models and smoothed Schoenfeld residuals from Cox regression were used to obtain smooth estimates of the additional protective efficacy offered by SMC over time over these periods. The first of these, flexible parametric survival models, adjusted for study country and SMC cycle, with a robust variance estimator to account for multiple episodes in the same child, and models were fitted with up to 10 degrees of freedom for the baseline hazard and 10 degrees of freedom for the effect of SMC as a time-varying covariate. The Bayesian Information Criterion (BIC) was used to compare models. The hazard ratio and its 95% CI was predicted over time, with protective efficacy  estimated for the period of interest (30 days or 60 days).E alone), adjusted for SMC cycle as described above, included a robust standard error, and stratified on study country.The second method smoothed the scaled Schoenfeld residuals from a Cox model to estimate the log hazard ratio for SMC, and its confidence interval, over time. Protective efficacy was calculated from the exponentiated hazard ratio. Analyses were conducted pooling all events and person-time for the first 30 days after all SMC cycles, and for the first 60 days after the final SMC cycle each year. The Cox models included the intervention group  are shown in Table As described above, the protective efficacy of RTS,S/AS01E, among SMC recipients, in the first 6 months was 75.9% . Between months 6-12, this was 31.1% , the wide CI reflecting the small number of events in this period. Starting 14 days after the fourth dose, the efficacy was 63.6%  in the first 6 months and 61.4%  between 6 and 12 months post-dose four. Starting 14 days after the fifth dose, efficacy was 60.1%  in the first 6 months and 35.9%  between 6 and 12 months post-dose five.Efficacy in 6-month periods: Starting 14 days after the third priming dose, the overall estimated efficacy of RTS,S/AS01Figure Figure The central panels of Fig. Finally, the right-hand panels of Fig. E alone group, and 13 in total from the combined group), and thus estimates of protective efficacy are imprecise. From SMC 2 onwards, the additional protective efficacy of SMC remained high over the remaining 11 cycles, with the lowest point estimates of protective efficacy of 74.9% in children scheduled to receive SMC (irrespective of whether they received SMC), 81.5% in children who received at least one dose of SMC, and 80.9% in children who received all 3 daily SMC doses. Pooling across all 12 SMC cycles, the point estimate of the additional protective efficacy offered by SMC, over RTS,S/AS01E alone, was 82.5%, 87.4% and 87.7% in children who were scheduled to receive SMC, received at least one dose, and received all three doses, respectively. Over the 12 cycles, pooling children who received only SP-AQ on the first day, the protective efficacy was 79.8%, although the 95% CI ranged from 33.7 to 93.8%, as relatively few children were not adherent in the trial.As described above, the protective efficacy of SMC was estimated through comparisons of the Combined intervention group with the RTS,S alone group. The number of children who were scheduled to receive SMC, received at least one dose of SMC, and received all three daily doses  is shown in Additional file Exploratory analysis of protection, stratifying follow-up to include only episodes occurring in the first 21 days after receipt of SMC indicated a higher level of protection than over the first 30 days. However, even in this shorter period, closer to the time of SMC administration, protection was not complete after most of the SMC cycles , but also the later timing of the SMC cycles with respect to the transmission season, which resulted in SMC protection persisting until transmission had declined to low levels. After SMC 8 and SMC 12, the number of malaria episodes in the Combined group increased markedly after approximately 30 days.Figure Figure Combining data from the final SMC cycle each year, in order to estimate protection over 60 days, protective efficacy was observed to decline slowly initially, and then more rapidly after 30 days. The estimated time at which the additional protective efficacy was completely lost appeared to be at around 45 days after SMC administration using Flexible Parametric Models, and slightly shorter (at about 38 days) using Smoothed Cox Residuals. Similar results and a similar estimate of protection at 30 days were obtained when these models were fitted separately to data from the last SMC cycle in each individual year , and 38.9% (95% CI: 36.3 to 44.0) between 6 and 12 months [E and thus obtain slightly higher efficacy in the initial period post-vaccination, than in the earlier trial in which vaccination was age-based rather than seasonally-targeted. The average efficacy of RTS,S/AS01E in our study is also comparable with a recent phase 2b trial of the R21/Matrix M vaccine, delivered largely before the rainy season in Nanoro, Burkina Faso [The estimates of protective efficacy provided by RTS,S/AS01 3 trial , in whic2 months ; the comina Faso , in whicE over time after vaccination, estimated with three different methods, indicates that protection remains at a relatively high level over the first 6 months post-vaccination in each study year . This was observed for the primary series, and also for the fourth and fifth doses (first and second boosters), which supports the use of seasonal booster doses of RTS,S/AS01E. All three methods indicated a possible decline in efficacy in the period beyond 6 months post-vaccination, and all three methods suggested that this was most marked in the third year of the study. The finding of declining efficacy is compatible with anti-CSP antibody responses, which had declined to low levels prior to the fourth and fifth doses of RTS,S/AS01E [E (six and seventh doses), and assessment of whether efficacy continues to decline with successive doses. However, a feature of our study design  is that relatively few cases of malaria occur in the period 6–12 months post-vaccination, since this period falls in the dry season. Consequently, there is considerable uncertainty around the estimated protective efficacy beyond 6 months, and the precise extent to which efficacy declines is not clear. The public health importance of any drop in efficacy during this period is likely to be relatively small, due to the small number of cases . The approach using smoothed Cox residuals avoids this limitation, as the baseline hazard is not modelled. The consistency of results using the three methods provides reassurance that the estimated profile of protection over time is not strongly dependent on a specific set of model assumptions.E. However, because the efficacy of RTS,S/AS01E was consistent with the phase 3 trial, and the efficacy of SMC consistent with previous studies, an adverse interaction seems unlikely and there was no evidence of differences in anti-circumsporozoite protein (anti-CSP) responses to the RTS,S/AS01E vaccine among children who received active SMC or placebo SMC [A key limitation is that the study design did not include a group who received neither intervention, so it is not possible to formally assess the evidence for an interaction between SMC and RTS,S/AS01cebo SMC . Since tcebo SMC ), ratherE and protection from SMC) is that these include only children who remained in follow-up, which is a sub-set of the group of children who were originally randomised to the study arms. Loss to follow-up was quite low, at 11% overall over the 3-year period of the trial, and very similar between treatment arms . The incidence of malaria in the second and third years of the study may be influenced by the ageing of the study cohort with time, and by the different prior experiences of malaria up to that point (which is influenced by the intervention group to which children were randomised). It is possible that estimates of protective efficacy after doses 4 and 5 of the RTS,S/AS01E vaccine, for example, are conservative because the reference group , may have acquired more protective immunity through exposure to malaria than the Combined intervention group.A possible limitation of the separate analyses in each year  will differ with respect to the time of year, and the age range, when children can receive their vaccine doses and are best protected. Understanding the optimum strategy will require consideration of the profile of protective efficacy over time in relation to the timing and duration of the transmission season, as well as the coverage that can be achieved in practice. Use of the combination of vaccination and SMC may increase the percentage of the population that has access to at least one effective intervention. Modelling exercises could also help to understand how the combined intervention of SMC and malaria vaccination might compare with other available control options. For example, the effectiveness of SMC itself may be improved by increasing the number of monthly courses (as discussed above) or extending the age range to which it is administered. Vector control may be improved through more effective LLIN and/or new tools. This could have implications for the absolute impact of adding malaria vaccination to SMC.Profiles of protective efficacy over time will be needed to select optimum dose timings for the RTS,S/AS01E, but waned faster . Quantifying these key differences between these interventions may help to optimise scheduling of SMC, malaria vaccination and their combination in areas of seasonal transmission with differing malaria epidemiology, and where different vaccine delivery systems are available. If optimisation of the combination of SMC and malaria vaccination can be achieved, it could have a marked impact on the malaria burden in areas of intense and seasonal malaria transmission.The efficacy of both interventions was highest immediately post-administration. The peak efficacy of SMC was higher than for RTS,S/AS01Additional file 1: Table S1. Number of clinical malaria episodes by time since vaccination in each year of the study, using 90-day periods (as used in the Piecewise Cox regression models). Table S2. Number of clinical malaria episodes by time since vaccination in each year of the study, using 60-day periods . Table S3. Number and percentage of children who were scheduled to receive SMC, received SMC, and received all daily SMC doses (full SMC) over the course of the study. Figure S1. Observed hazard function and Cumulative hazard function, and the fitted cumulative hazard and estimated protective efficacy from flexible parametric survival models used to estimate vaccine efficacy in each year of the study. Figure S2. Protective Efficacy of SMC in the first 21 days and first 30 days after SMC received, by cycle. Figure S3. Protective Efficacy by time since the final SMC cycle in each year. Figure S4. Comparison of the SMC protective efficacy profile obtained in this study with the profile estimated for an earlier placebo-controlled trial of SMC.


Plasmodium falciparum malaria through their efficient, cost-effective, and user-friendly qualities in detecting the antigen HRP2 (histidine-rich protein 2), among other proteins. However, the testing mechanism and management of malaria with RDTs presents a variety of limitations. This paper discusses the numerous factors  that limit the performance of RDTs. Additionally, the paper explores outside factors that can hinder RDT performance. By understanding these factors that affect the performance of HRP2-based RDTs in the field, researchers can work toward creating and implementing more effective and accurate HRP2-based diagnostic tools. Further research is required to understand the extent of these factors, as the rapidly changing interplay between parasite and host directly hinders the effectiveness of the tool.The recent COVID-19 pandemic has profoundly impacted global malaria elimination programs, resulting in a sharp increase in malaria morbidity and mortality. To reduce this impact, unmet needs in malaria diagnostics must be addressed while resuming malaria elimination activities. Rapid diagnostic tests (RDTs), the unsung hero in malaria diagnosis, work to eliminate the prevalence of  In 2000, malaria was pinpointed as a major burden for global health and development, and efforts have since increased to reduce malaria cases and associated mortality ,2. AccorPlasmodium specific antigens in a drop of fresh blood positive for malaria. The target antigens in current commercially available malaria RDTs are histidine-rich protein 2 (HRP2), specific for Plasmodium falciparum (Pf), and the parasite enzymes lactate dehydrogenase (pLDH) and aldolase, present in all Plasmodium species infective to humans [Pf HRP2 is encoded by the pfhrp2 gene (PlasmoDB gene ID: PF3D7_0831800), which is located subtelomerically on chromosome 8 [Pfhrp2 bears significant polymorphism rates [pfhrp3 gene [pfhrp2 gene have been collected globally in recent years, rendering concerns over its implications in malaria diagnostics and case management . Wheiewed in ,13. Onceiewed in ,15.Pf-specific HRP2 are the most commonly used due to their efficient qualities including high thermal stability, sensitivity, specificity, cost effectiveness and easy-to-use abilities [Pf and other Plasmodium species. Regardless of their noted success, RDTs are not a perfect malaria diagnosis tool as poor product design or quality, inadequate storage, and incorrect use can limit their performance and accuracy [RDTs that detect bilities ,17. The accuracy ,18. The accuracy . As COVIaccuracy . Multiplaccuracy , furtherOverall, the performance of HRP2-targeting RDTs and their usefulness in different transmission settings depends, among other factors, on the interplay between the parasite, its host and the RDT itself. This review seeks to present the factors that engage in this interplay and have an overall influence on RDTs as a tool for malaria diagnosis and case management.Pf malaria as significant yields of false-positive results have been observed, particularly in areas of high transmission [Once HRP2 is released into the peripheral circulation during schizogony, it can persist for several weeks in the bloodstream, even when the infection is cleared, leading to false-positive RDT results ,13,14,15smission ,22. SuchPf parasites of the 3D7 strain produce 1.4 × 10−13 g of HRP2 per parasite for each replication cycle. In addition, it was demonstrated that the antigen’s persistence would cause the tests to stay positive for a minimum of seven days after treatment [The first study (1993) to describe HRP2 persistence found detectable antigen levels in the blood of 10 cases 25%) 5 days after treatment in a Tanzanian longitudinal cohort, 4 of which remained positive for 14 days . Later s% 5 days reatment .−1 among countries, resulting in median half-lives of 4.5, 4.7, and 3 days in Angola, Tanzania, and Senegal, respectively. Such consistency in HRP2 clearance across different African regions suggests the presence of a common biological mechanism influencing HRP2 dynamics upon resolution of Pf infection [The duration of a positive RDT result after recommended treatment is mainly dependent on the density and duration of parasitemia before treatment, as well as the parasite-specific expression of HRP2. In one study, the mean duration of persistent antigenicity in Ugandan children who had a successful antimalarial treatment was 32 days . This dunfection . It has nfection .Pf infections (<100 parasites/µL). hsRDTs (with a LOD of 80 pg/mL) allow the detection of low-density Pf malaria infections (<100 parasites/µL), performing closely to expert microscopy (detection limit of 4–20 parasites/µL) [Highly sensitive RDTs (hsRDTs) claimed to have a 10-fold increase in sensitivity compared to the RDTs routinely available in the market . Therefoites/µL) . Howeverites/µL) ,33. In fites/µL) .While the persistence of HRP2 can be seen as a drawback for malaria diagnosis and clinical management, it can also be used as a method to assess recent infections in non-infected people and consequently more accurately determine ongoing transmission ,35,36. APf genome encodes several proteins, including HRP2 and its structural homologue HRP3, that uncommonly contain repetitive sequences comprising a small handful of amino acids [The no acids ,37,38. Tno acids ,18,39. Pno acids . HRP2 haP. falciparum lines and field isolates from 19 countries [Pf isolates, as well as in the total number of repeats, its order within the sequence, and the number of each repeat within HRP2. These variations led them to identify 56 unique HRP2 sequences. Regarding the role such diversity could play on the performance of RDTs, they reported that isolates with higher numbers of type 2 and type 7 repeats were better recognized, particularly at low parasitemias (<250 parasites/µL). Remarkably, it was shown that the laboratory Pf D10 clone, lacking the pfhrp2 gene but positive for pfhrp3, could be detected by HRP2-based RDTs, suggesting that the candidate antigen for this cross-reactivity is HRP3. This aligns with a previous study that reported an 85–90% homology in nucleotide sequence-flanking repeats between pfhrp2 and pfhrp3 and an amino acid substitution of D/N in the major repeat of AHHAAD/N in a single parasite line [The first study to observe extensive diversity in HRP2/3 sequences sequenced 75 Pf isolates, 93% (n = 13/14) of different HRP2 repeats identified in previous studies were detected in 229 successfully amplified pfhrp2 fragments, while for HRP3 protein, seven out of eight repeats were identified [pfhrp2 sequence analysis predicted that 9% of Malagasy isolates would not be detected at parasite densities ≤250 parasites/μL [Pf HRP2 Type A comprises the higher number of defined epitopes, the part of an antigen molecule to which an antibody attaches itself, followed by Type B and Type C. However, the predictability of RDT sensitivity using type 2 and type 7 repeats was not confirmed, as no correlation between detection rate using RDT and gene structure was identified, especially when the parasite density was <200 parasites/µL [In Madagascar entified . pfhrp2 sites/μL . The PfHsites/μL . A latersites/μL . Moreovesites/µL .Pf isolates from India [p = 0.046). The authors reported an increase in the number of isolates predicted to be non-sensitive to HRP2 RDTs based on HRP2 sequence for the years 2009 to 2011, suggesting the possibility of diagnostic selection pressure at play [Studies in om India ,42,43,44om India , Myanmarom India , Yemen [om India , Senegalom India ,48,49, Mom India , Uganda om India , French om India , Kenya [om India ,52, Mozaom India , Tanzaniom India , Nigeriaom India , Sudan [om India , Ethiopiom India , and Colom India  identifiom India  demonstrom India . In thisom India . Similar at play . Consist at play . Recent  at play ,52 and IP. falciparum antigen HRP2 presents significant variation, but findings regarding the effect of such variability in RDT reactivity are divergent. This discordance among the several studies on the functional relevance of HRP2 repeats indicates that there is no established relationship between the RDT performance in the field and the number of repeats. However, it has been shown that recombinant HRP2 protein Type A is recognized with greater sensitivity in immunoassays compared with Types B and C [To summarize, the  B and C . TherefoP. falciparum hrp2 and hrp3 genes do not only undergo extensive polymorphism but are also subject to deletions. Increasing false-negative HRP2-based RDT reports have rendered concerns, which have in turn led to the need for inclusion of other assays in malaria case management and elimination programs [Pf isolates with pfhrp2 gene deletion came in 2010 from Peru [pfhrp2 gene and six lacked both pfhrp2 and pfhrp3 genes when tested by PCR. Plasma HRP2 levels were also not detectable by ELISA [Pf isolates collected between 2003 and 2007 revealed that 41 and 70% of the isolates presented pfhrp2 and pfhrp3 gene deletions, respectively. In addition, 22% of the isolates lacked both pfhrp2 and pfhrp3 genes [Pf isolates collected between 1998 and 2001 had a deleted pfhrp2 gene [pfhrp2 deleted Pf isolates (40%) were observed in samples collected from Peru between 2003 and 2005, suggesting that pfhrp2 deletion has occurred many times in the Pf isolates collected from this country [programs ,11. The rom Peru , where eby ELISA . A retrop3 genes . Anotherrp2 gene . Increas country .pfhrp2 deletions is not just confined to South America but has also affected malaria endemic regions in Africa and Asia [pfhrp2/3 deletions came from several countries in Africa , Asia , South America  and Central America (Honduras), which have been previously reviewed [pfhrp2/3 deletions  can lead to numerous negative consequences in public health. Thus, the WHO should endorse synchronized tactics to examine, map, and report pfhrp2/3 gene deletions through the provision of standardized protocols and procedures. At present, there are a few traditional methods to determine pfhrp2/3 deletions including PCR, PCR followed by DNA sequencing, and ELISA-based assays [pfhrp2/3 gene deletion analysis and its validation, as well as laboratories that can perform complementary serological assays. A common approach will have a huge impact on malaria diagnosis using RDTs in the field as well as on future policy development.The continuous use of HRP2-based RDTs in malaria endemic areas  such as gene deletions and duplications can be determined based on the mean depth of coverage of individual amplicons between the reference sample  and test sample. This approach can also be combined with other aspects of malaria elimination activities including capturing low-frequency resistant mutants [pfhrp2/3 deletions [pfhrp2 and pfhrp3 deletions lies in the screening of large sample sets by multi-antigen detection, particularly in the WHO African Region, where Pf infections are dominant. The recent development of highly sensitive laboratory-based assays that detect pLDH [pfhrp2 deletions in samples in which pLDH and/or pAldo are positive, but HRP2 is not. However, such an approach would need to be accompanied by further testing with molecular assays to confirm the gene deletions. Rapid and efficient methods to assess diagnostic failure trends can help to guide the most useful and efficient forms of malaria case management. Such surveillance is critical during malaria elimination activities, when mass drug administration is rolled out in the community and fast detection of malaria parasites is crucial.Targeted deep sequencing of important genes could also be an alternative approach to identify genetic variations . Advance mutants ,61. Moreeletions ,63. Anotect pLDH ,65 or pLect pLDH  in combiPf Malayan Camp strain [Aotus monkeys with a fusion protein that contained the repeat Ala-His-His sequence and had high homology to HRP2 [Pf, immunized monkeys exhibited lower parasitemias compared with control monkeys, suggesting that the antigen was able to trigger antibodies production and confer protection [Pf-infected people produce anti-HRP2 antibodies, which raises the question of whether these antibodies would interfere with HRP2-detecting immunoassays [Host factors, including inherent and acquired immunity, age, and pregnancy, play an important role in the performance of HRP2-based RDTs, specifically their influences on detection of low-density infections and with comorbidities. The first study (1986) to produce antibodies against HRP2 immunized BALB/c mice with the p strain , and sin to HRP2 . After botection ,69. Thernoassays . NeverthWhile the persistence of HRP2 has been explored to test the sensitivity and function of RDTs, it also provides valuable insight into the relationship between patient age and acquired immunity. Researchers categorized RDT-related papers to demonstrate the average persistence of HRP2 and pLDH by 1) patient age, 2) RDT type, and 3) treatment received, which included artemisinin-based combination therapy (ACT) or non-ACT. They then utilized a Bayesian survival model to estimate the time needed for an RDT-positive patient to turn RDT-negative after treatment. In total, 67 individual study groups were included in the analysis. Through modeling, the study illustrated that HRP2 persistence is more prevalent in children than adults, and individuals treated with ACT have more persistent positivity rates compared to those with non-ACT. In addition, persistent positivity is predicted for a longer duration when using HRP2 RDTs than when using pLDH-only or HRP2/pLDH combination RDTs .Pf RDTs across differing age groups and transmission intensities [Among global malaria deaths, children under the age of five face the greatest threat from the malaria parasite. In areas of differing malaria transmission, the threat is even higher, as RDTs fluctuate in specificity and sensitivity in comparison to the “gold standard” of malaria microscopy . The WHOensities . They foensities . An addiensities . With woPf among the testing mechanisms as the RDTs were able to detect HRP2 in the placenta (due to the parasite’s characteristic sequestration), as well as in maternal peripheral blood (due to the antigen’s high persistence) [Research exploring the relationship between pregnancy and malaria has increased, especially in identifying the accuracy and limitations of RDT use on pregnant mothers . Malariaistence) . Althougistence) ,76.Intermittent preventive treatment of malaria in pregnancy with sulfadoxine-pyrimethamine (IPTp-SP) has been a tool to reduce the incidence of maternal anemia, low birth weight, and neonatal mortality in pregnancy from malaria . HoweverFurthermore, the difference in RDT sensitivities still raises concerns for the number of asymptomatic and low-density infections that are not identified by the RDT. Researchers in Colombia compared the performance of hsRDTs, light microscopy (LM), and conventional rapid diagnostic tests (Pf/Pv RDT and Pf RDT) on 737 peripheral and placental specimens collected from pregnant women. The improved sensitivity of the hsRDT resulted in better detection of HRP2 in comparison with both LM and conventional RDTs . AnotherP. falciparum hyperparasitemia (>5% infected red blood cells) [Since each infected person experiences differing levels of parasitemia, symptoms, and immunological responses, RDTs are placed at a disadvantage to provide an accurate reading for each individual case. As excess parasite antigens bind with antibodies without available epitopes for capture, commonly referred to as the test-band antibody, the high parasite density can lead to the prozone effect, also referred to as the high-doses hook phenomenon, which occurs when HRP2 is unable to be detected by the RDT ,93. Thisd cells) . Each ofd cells) . A simild cells) . These sd cells) .Issues with RDT diagnosing continues with the increase in complexities surrounding asymptomatic malaria (AM) cases in different levels of endemicity. AM is defined by the lack of fever or other identifying clinical symptoms, which oftentimes results in infected individuals not seeking treatment. Meanwhile, these asymptomatic cases are missed by passive surveillance while remaining an important gametocyte reservoir and contributing to the persistence of malaria transmission . IndividToxoplasma gondii . FurtheThe changing epidemiology of malaria, especially in low-transmission settings presents new challenges for malaria diagnosis and case management. In countries with low transmission, a higher proportion of asymptomatic infections are below the reliable detection limit of microscopy  and RDT The poor sensitivity of RDTs in low-density infections raises great concern on the performance of RDTs in areas of low malaria transmission . A studyPf infection in moderate-to-high-transmission settings is shown to be reliable [The performance of HRP2–based RDTs to detect reliable ,104. Witreliable . In a 20reliable . Additioreliable .Pf infection. In children, low specificity can cause over-estimation of malaria prevalence [High-transmission areas signify a high prevalence of parasitemia in the population and lead to frequent malarial infections, the majority being in children under the age of five . A studyevalence . OverallTransmission rates are shown to directly correlate with weather patterns, as rates of malaria infection are near zero during the end of the dry season . A studyA study conducted in Burkina Faso tested the sensitivity and specificity of RDTs in both the rainy and dry seasons . ResearcApart from the biological factors affecting testing accuracy, RDT performance is also greatly impacted by human error. Faulty handling, improper storage, and poor operation are all limitations of using RDTs in the field, especially in communities with few resources and training programs ,112. ForP. vivax after a needlestick injury in 2001 [In 2015, the WHO conducted a large-scale product examination to test the performance of RDTs on the market, which included testing of 46 products in the categories of panel detection scores, false-positive scores, heat stability, ease-of-use description, labeling and ease of instructions . For the in 2001 . Additio in 2001 . Other i in 2001 . These fDue to the sensitivity of the testing device and rural tropical locations (with varying temperatures) where testing is mainly conducted, RDT performance is widely affected by improper storage. Excess exposure to heat and humidity goes hand-in-hand with limited resources and training in a given area. Communities with low resources are less likely to have the facilities and equipment to keep RDTs in the recommended storage environment, leading to false readings . Most maA way to prevent denaturation and ensure functionality of the RDT is through the establishment and maintenance of a cool chain. By definition, a cool chain means ensuring an adequate temperature of the RDT through all levels of production and delivery, including stages of shipping, transportation, and storage . The cooAs delivery of care evolves, it is necessary to understand how the accessibility and acceptance of RDTs in a community can change depending on the current political, social, and economic status of a country. Currently, there are three prime modes of delivery for malaria care across the globe. These include public health care (sponsored by the government), the private sector , and care distributed by CHWs . While tIn Angola, the largest portion of healthcare demands is due to malaria, and differences in resources for each province lead to healthcare inequalities across the country . A healtAnother restraint to RDT testing is the acceptability of the diagnostic tool within the population . In a 20As the battle toward eliminating malaria continues, the need to understand and engage in the prevention of factors that hinder testing performance of RDTs becomes crucial. While these tools are facing a series of limitations, both with the testing device itself and the country of testing, their noted success in the field compared to previous diagnostic methods shows great promise in the detection and management of malaria cases around the globe. Rising issues, including the discovery of gene deletions and repeat sequences, require further work to identify where these genetic changes are occurring and expected to occur in future years. More historic issues, such as HRP2 persistence, problems diagnosing asymptomatic malaria cases, and limitations of RDTs in testing pregnant women, children, and patients with co-infections, continually contribute to a significant number of false-positive and false-negative results. Additionally, overarching issues regarding community access to resources, proper training, and acceptability of the diagnostic tool leave room for RDT testing improvement to be tackled with a public health lens.Regardless of their shortcomings, RDTs are the unsung hero of malaria diagnosing, and with advances in the issues discussed, can continue to be the most effective and leading tool for malaria diagnosis worldwide. With the current price of less than a dollar per RDT, this tool proves to be a cost-effective and viable option for low resource communities, especially in comparison with the other resource-intensive testing methods of a microscopy blood smear or PCR . Additiopfhrp2 and pfhrp3 deletions, especially in Sub-Saharan Africa where malaria is most endemic [Overall, RDTs are an effective tool for diagnosing malaria, especially in areas where resources are limited. They are cheap, user friendly, and provide testing results in a timely matter without the need for extensive laboratories or equipment. Previously, an ideal RDT was described as one that “would detect and differentiate between all human malaria species; distinguish low, medium and high parasitemia’s; be available in a temperature-stable format; have internal controls for antigens; be easy to use; produce an unambiguous result; and remain cheap” . Althoug endemic . The ide


Plasmodium falciparum malaria by 2025. Subclinical malaria infections that can be detected by highly sensitive polymerase chain reaction (PCR) testing in asymptomatic individuals represent a potential impediment to this goal, although the extent to which these low-density infections contribute to transmission is unclear. To understand the temporal dynamics of subclinical malaria in this setting, a cohort of 2,705 participants from three epidemiologically distinct regions of Myanmar was screened for subclinical P. falciparum and P. vivax infection using ultrasensitive PCR (usPCR). Standard rapid diagnostic tests (RDTs) for P. falciparum were also performed. Individuals who tested positive for malaria by usPCR were followed for up to 12 weeks. Regression analysis was performed to estimate whether the baseline prevalence of infection and the count of repeated positive tests were associated with demographic, behavioral, and clinical factors. At enrollment, the prevalence of subclinical malaria infection measured by usPCR was 7.7% , while P. falciparum prevalence measured by RDT was just 0.2%. Prevalence varied by geography and was higher among older people and in those with outdoor exposure and travel. No difference was observed in either the prevalence or count of subclinical infection by time of year, indicating that even in low-endemicity areas, a reservoir of subclinical infection persists year-round. If low-density infections are shown to represent a significant source of transmission, identification of high-risk groups and locations may aid elimination efforts.Countries in the Greater Mekong Subregion have committed to eliminate  Plasmodium falciparum malaria has decreased by 97% in the Greater Mekong Subregion, which is composed of Cambodia, China’s Yunnan Province, Laos, Myanmar, Thailand, and Vietnam.P. falciparum, the WHO has recommended that falciparum malaria be eliminated in the Greater Mekong Subregion by 2025, and all malaria by 2030.In the last 20 years, the number of reported cases of ,–One potential impediment to malaria elimination in the region is the large reservoir of low-density, generally asymptomatic malaria. Historically, most studies of asymptomatic malaria have relied on light microscopy or rapid diagnostic tests (RDTs), which have lower limits of detection (LoD) of about 50–100 parasites/mL . More recent surveys in the Greater Mekong Subregion have used ultrasensitive polymerase chain reaction (usPCR) assays that have LoDs of 16–22 parasites/mL.,The potential for these subclinical infections—especially low-density infections that can only be detected using usPCR—to contribute to transmission is uncertain, and the question of whether they should be targeted in elimination efforts remains unsettled. Scores of countries have eliminated malaria without specifically targeting low-density infections that are clinically silent, and transmission potential is strongly correlated with higher parasite densities, well above the LoDs for microscopy and RDTs. Still, some have called for treating all subclinical malaria infections,–P. falciparum and P. vivax infections was estimated to be 2 and 6 months, respectively,P. falciparum infection had a 20% risk of having parasitemia for 4 months or longer, which increased to 59% for P. vivax infections.The initial studies describing high prevalence of subclinical malaria in the Greater Mekong Subregion were cross-sectional surveys,,,Previous studies from the region have identified risk factors for subclinical malaria infection, including age (young adults) and male gender,P. falciparum and P. vivax as the predominant species, respectively. Sagaing Region has historically had low malaria endemicity overall but with several “hot-spot” areas, including Monywa Township where both P. falciparum and P. vivax were suspected to be highly endemic. Selection of study villages or communities within each study site was based on known clinical malaria burden , and on logistical considerations intended to ensure the integrity of study data and samples.A prospective cohort study was performed to characterize short-term changes in subclinical infection status among participants living in three epidemiologically distinct regions of Myanmar. The study sites were chosen to represent a range of malaria epidemiologies characteristic of the region, including three military bases and three villages in Monywa Township in Myanmar’s Sagaing Region (referred to henceforth as “Monywa” site); two villages and one refugee community in Laiza Township in Kachin State, located on Myanmar’s border with China’s Yunnan Province (“Laiza” site); and five villages in Ann Township in Myanmar’s Rakhine State (“Ann” site) . Based oTwo-step simple randomization was performed to select households within each study village or community, and participants within each household. A nearest next household was selected if originally selected household members were unavailable or declined to participate. Information about the study was disseminated within each study site by community engagement activities and by word-of-mouth, the most effective ways of research study recruitment in these remote communities, based on our previous experience. Inclusion criteria included age at least 6 months old, provision of a written informed consent or assent as appropriate, and ability and willingness to comply with the study protocol. Exclusion criteria included any clinical presentations that required immediate medical attention.After informed consent was obtained, demographic, medical and malaria history, behavioral, and travel-/mobility-related information were collected following a standardized questionnaire, using Open Data Kit (ODK) software, and uploaded to an Ona server and stored in a secure database at Duke University. Potential risk factors for malaria infection collected at baseline and during the follow-up period were age, gender, date of study data and sample collection , residence (defined as living in the study village for at least 6 months), type of occupation , setting of occupation (predominantly indoors versus predominantly outdoors), the presence of seasonal variation in primary occupation, and regular use of a bed net, defined as at least four+ nights per week. Travel patterns that were potentially related to malaria exposure were also investigated, including the distance from home to place of work or study, greatest distance traveled in a typical day, frequency of travel outside of the village in the last 6 months, mode of travel (nonmotorized or motorized vehicle), whether the participant stayed overnight at work, and frequency of exposure to known potential source of malaria, such as water source and forest.The presence of clinical symptoms associated with malaria within the past 2 months and the past 24 hours was investigated, including headache, body ache, nausea, vomiting, abdominal discomfort, decreased appetite, fatigue, fever with chill and rigor, and fever. Oral/axillary temperature was taken and recorded at baseline and during follow-up visits, and fever was defined as temperature > 99.5°F. All study procedures were approved by institutional review boards at Duke University Medical Center (Protocol No. Pro00091895), Department of Medical Research, Myanmar, the Defense Services Medical Research Center, Myanmar and the National Institute of Parasitic Diseases, China CDC.P. falciparum malaria infection, finger prick blood was tested by WHO-qualified RDT  at baseline and any time during study follow-up as clinically indicated. Finger prick blood was spotted onto Whatman 903 and 3MM filter paper at baseline, during scheduled follow-up visits and unscheduled visits for ill symptoms, air-dried, and labeled with a unique participant identification number, initials of blood collector, and date and time of blood collection. These dried blood spot (DBS) samples were stored in individual sealed plastic bags with desiccant in a temperature-controlled facility until transported to central laboratories for molecular analysis.For the diagnosis of patent For participants who were RDT-positive at baseline, venous blood (up to 5 mL) was collected and stored in liquid nitrogen for future genotyping of malaria parasites. Referral was made, appropriate treatment by a malaria care provider following the national treatment guideline was ensured, and the treated participant was discharged from the study.Participants who were RDT-negative and PCR-positive at visit #1 were followed for up to five additional visits (visit #2 to visit #6). In Laiza and Ann, the interval between visit #1 and visit #2 was 4 weeks, followed by biweekly interval for visits #3 to visit #6. In Monywa, the interval between visit #1 and visit #2 was 2 weeks, followed by 5 weekly follow-up visits. Participants who were RDT-negative and PCR-negative at baseline were tested again at visit #2, one week later in Monywa, and 2 weeks later in Laiza and Ann. Therefore, the total maximum number of observations for PCR-negative participants was two and for PCR-positive participants was six. The difference in the follow-up interval was due to logistical constraints for the military population at Monywa where lengthy follow-up (longer than 6 weeks) was not feasible.P. falciparum and P. vivax, with an estimated LoD of 16 parasites/mL for P. falciparum.,,From Whatman 3MM DBS samples, RNA and DNA were extracted using a β-mercaptoethanol-spiked guanidine thiocyanate-isopropanol buffer and purified using glass filter plates as previously described.P. falciparum and P. vivax were calculated by study site and subsite (by village or community), with exact binomial 95% CI, to visualize the heterogeneity in prevalence. Heterogeneity was quantified by the calculation of intraclass correlation coefficient (ICC) on village-level proportions using the analysis of variance (ANOVA) method.Statistics describing sociodemographic characteristics, malaria risk factors, and the history of clinical symptoms were computed and stratified by study site to characterize differences by geography. The sample baseline prevalence  of P. falciparum, P. vivax, and all malaria) at screening were ascertained using individual modified Poisson regressionsAssociations between sociodemographic characteristics, known malaria risk factors, and clinical symptom history and malaria positivity , a multiple imputation approach was used to fill in missing values that occurred at any point during follow-up and then to create a summary count of positives based on varying numbers of imputed values . Covariates used to impute missing values for malaria diagnosis were data collection site, baseline indicators for P. falciparum and P. vivax , age, occupation, hemoglobin result, distance to work/school, season occupation, occupation type (indoor versus outdoor), clinical symptoms , female gender, regular use of mosquito net, measured body temperature, and season of data collection (rainy versus dry season).A similar approach was used to estimate factors associated with counts of positive malaria tests for those who had positive tests at baseline and during the follow-up period. Counts of positive tests did not distinguish between P. falciparum and P. vivax . Because this study was exploratory, no formal power calculation or statistical significance testing was performed.Ten imputation datasets were produced for regression analysis, which used Poisson regression with robust standard errors and Rubin’s rules for combining results obtained from multiple imputation.Supplemental Figure 1). Three refugee villages or communities were enrolled at Laiza, with 240–480 participants enrolled per village or community. Five villages (80–345 per village) were enrolled at the Ann site, and six military communities (80–160 per community) were enrolled in Monywa. The number (%) of malaria-positive participants who remained in the study through the end of follow-up was 75 (78.1%), 84 (87.5%), and 6 (37.5%) in Laiza, Ann, and Monywa, respectively  and usPCR  by site. Of 2,705 enrolled, only 5 were positive for P. falciparum by RDT, all at the Ann site in Rakhine State. All RDT-positive participants also tested positive by usPCR. Using usPCR as a gold standard, the estimated specificity of the RDT for detecting P. falciparum was 100% (95% CI: 99.9–100.0%) with a sensitivity of the RDT of 2.4% (95% CI: 0.8–5.5%). By usPCR, malaria prevalence at baseline overall was similar (9.6%) in Laiza and Ann. All infections detected in Laiza were P. vivax, while P. falciparum prevalence was higher than P. vivax in Ann. Monywa had the lowest overall prevalence, with predominantly P. vivax infections. A small number (N = 7) of mixed P. falciparum and P. vivax infections was present only at the Ann site. Results of laboratory quality control procedures showed strong agreement between samples tested at site locations and Duke University. Specifically, at Department of Medical Research (DMR) (N = 96 samples), simple concordance was 96% (Cohen’s Kappa = 0.933) and at Defence Services Medical Research Centre (DSMRC) (N = 63), simple concordance was 95% (Cohen’s Kappa = 0.846).Supplemental Table 2). In Ann, the range was 7.5% (95% CI 2.8–15.6) to 13.0% (95% CI 8.7–18.5). In Monywa, prevalence ranged from 1.3% (95% CI 0.03–6.7) to 4.0% (95% CI 1.5–8.6). To assess heterogeneity in village-level prevalence of P. falciparum, P. vivax, and mixed P. falciparum/P. vivax infections, ICC estimates were compared between the three different infection states. The highest between-village heterogeneity was observed for P. vivax  and the lowest was observed for all malaria .Within each of the three study sites, usPCR-positive malaria prevalence varied among villages or communities. The range of prevalence in Laiza was 4.6% (95% CI 2.3–8.1) to 13.8% (95% CI 10.8–17.3)  tested negative by usPCR at baseline (visit #1), with 2,249 (90.1%) remaining PCR-negative at follow-up visit #2. Fifty-three (2.1%) who tested negative at visit #1 were positive by usPCR at visit #2, and 195 (7.8%) who were negative at visit #1 were lost to follow-up at visit #2.P. falciparum or P. vivax positive at visit #1 were still positive at visit #2 one month later, and 37.1% of P. falciparum or P. vivax positive participants remained positive at all six study visits . In Laiza and Ann, 72.4% of y visits . In MonyN = 54, 37.0%), participants who tested negative at least once and subsequently remained negative , and those who were intermittently positive and negative  . Persistence of infection at all six study visits was found in a higher number of participants at the Ann site  than the other sites, and those whose initial PCR results were positive for P. falciparum tended to remain positive throughout the study  compared with those who tested positive for P. vivax . No differences were seen in the proportion of participants at the different sites who were intermittently positive, comparing baseline P. falciparum and P. vivax infections.For the 146 participants who were positive by usPCR at baseline, the patterns of positive and negative tests were relatively equally split between participants who remained PCR-positive for all study visits . Those with symptoms suggestive of malaria both at enrollment and over the previous 2 months had slightly higher rates of baseline malaria infection compared with those who did not have symptoms. Likewise, those reporting more frequent trips to forest and water saw higher baseline prevalence of malaria compared with those reporting frequency of chores as rare or never. At baseline, 3.9% of “dependents” had subclinical infection, among the lowest malaria prevalence of all occupation categories. Plantation workers had the highest relative difference in prevalence of subclinical infection for any occupation category compared with dependents , after adjustment for site and age ; however, those with outdoor occupations also saw fewer subsequent positive tests  than individuals with indoor occupations who tested positive at baseline.At baseline, malaria infections were most common among refugees (15.8%), plantation workers (14.6%), and farmers (11.2%) and tended be more common among those with outdoor occupations (10.6% versus 5.8% for indoor occupations) , although the older age groups had fewer positive counts over the follow-up time points than younger children who had tested positive at baseline .Those who traveled farther in a typical day were more likely to have subclinical malaria at baseline, with rates of positivity increasing with increasing distance traveled  although travel history did not correlate with the subsequent number of positive tests.Individuals who performed chores involving frequent trips to water sources and forests were more likely to test positive for malaria at baseline . Subsequent counts of positive tests were modestly correlated with lower frequency of trips to forest  but not strongly correlated with lower frequencies of trips to water.versus peak season reference) or the subsequent number of positive tests for those who tested positive at baseline .The time of year during which screening occurred did not correlate well with either the probability of being positive at baseline . Self-reported symptoms suggestive of malaria in the 2 months preceding screening were not correlated with the probability of testing positive at baseline, although reports of body ache/pain  and vomiting  were associated with higher counts of positives tests for those testing positive at baseline.Individuals who tested positive for Supplemental Table 5), with only modest changes in estimated magnitudes of association between measured temperature and subclinical malaria at baseline and the counts of subsequent positive malaria results for individuals reporting abdominal discomfort in the 2 months preceding baseline screening.Results remained largely unchanged in a sensitivity analysis when data from Monywa were excluded .,,–Results from this study add to the growing body of evidence supporting the existence of a silent reservoir of subclinical malaria infections in the Greater Mekong Subregion that may pose a challenge to the continued progress toward malaria elimination in the region. The finding that almost all infections were both clinically silent  and undetected by standard testing (subpatent) suggests that traditional surveillance methods based on rapid diagnostic testing may be inadequate to detect residual malaria infections in these settings. It should be noted that screening was intentionally targeted to potential high-risk groups and communities; therefore, prevalence estimates may not be representative of the underlying target populations. Even so, the estimated prevalences were similar to those found in previous studies in the regionP. falciparum and P. vivax parasite densities can vary substantially over the course of 6–12 weeks. The PCR test used for this study has lower limits of detection of approximately 16 parasites/mL for P. falciparum and 49.5 copies/μL for P. vivax,Although parasite densities cannot be derived from the results of our nonquantitative PCR assay, the short-term temporal dynamics of subclinical malaria infection observed in this study suggest that both P. vivax infections had a lower rate of incident positive test results overall, which is likely related both to the parasite’s ability to go undetected during its latent liver stage infection, and to the comparatively lower sensitivity of the P. vivax usPCR. This suggests that even more P. vivax infections may go undetected when only a single test is performed. In this short-term cohort study, it was not possible to identify when new infections originated and when they permanently disappeared.These patterns of intermittent PCR-positivity suggest that even usPCR may miss a substantial number of infections if only a single test is done to ascertain infection status. Less-sensitive laboratory-based and point-of-contact molecular and flow-based detection methods will miss even more infections that fluctuate below the higher detection thresholds for these tests. As expected, participants with Mass  screening and treatment strategies involve testing all people in a given area or population, and treating only those who test positive. The regression analyses in this study support previous work showing that in this region, targeting certain groups based on older age, male gender, high-risk occupation, and frequent engagement in other outdoor activities, like collecting water and time spent in the forest, may improve the effectiveness of these screen-and-treat strategies. The high heterogeneity seen in prevalence of subclinical malaria even in adjacent villages is consistent with previous research,In this observational study, unmeasured confounding cannot be ruled out as a possible explanation for some findings. Furthermore, measurement error due to the imperfect sensitivity of our PCR test may have led to bias in PR estimates, although this bias would be small unless the proportion of participants who had baseline parasite densities below the lower limit of detection  was different across exposure strata. Finally, if false positives occurred , prevalence estimates could have been falsely elevated. The predominant pattern of repeated positive results suggests that any such false positives likely occurred rarely.The probability of continuous infection over time was lower in older people and those exposed to outdoor environments, the same factors found to increase prevalence of infection at baseline screening. It is possible that these groups are able to clear infection more rapidly because of higher levels of immunity acquired through repeated exposures. Irrespective of demographic characteristics, no individuals who had subclinical infection developed symptomatic malaria illness over the 6- or 12-week follow-up period. Again, additional cohort studies with longer follow-up will be needed to assess whether certain groups are able to resolve infections more quickly, and whether and how often these subclinical infections become symptomatic.–Importantly, the lack of any differences in either the prevalence or count of subclinical infections by season supports the possibility that transmission potential  could be maintained throughout the dry season in these low endemicity settings, raising the prospect of malaria elimination interventions that target this “silent” reservoir when transmission is not occurring.P. falciparum and P. vivax densities over time and the lack of highly sensitive tests that can be performed in the field. With the ability to detect evidence of recent past infection, serological testing may offer a more promising approach for surveillance in these elimination settings if reliable point-of-contact tests can be developed and validated.,Despite the dramatic progress toward eliminating malaria from the Greater Mekong Subregion, this study confirms that even in areas with very few reported cases of malaria illness, a reservoir of subclinical infection persists year-round. If these low-density infections are shown to represent a significant source of transmission, identification of high-risk groups and locations (“hot pops” and “hot spots”) may aid elimination efforts. However, identifying these populations will be difficult with available technologies, given the dynamic nature of Supplemental materials


Plasmodium falciparum infection in Phase IIa sporozoite challenge studies in adults in the United Kingdom and in a Phase IIb field efficacy trial in Kenyan adults. However, it failed to demonstrate efficacy in a phase IIb trial in 5-17 month-old children in an area of high malaria transmission in Burkina Faso. This secondary analysis investigated whether exposure to malaria or nutritional status might be associated with reduced responses to vaccination in this cohort. Parasite blood smears and anti-AMA-1 IgG titres were used to assess history of exposure to malaria and weight-for-length Z scores were calculated to assess nutritional status. Differences in vaccine-specific anti-TRAP IgG titre and ex vivo IFNγ ELISpot response were measured between groups. In total, n = 336 volunteers randomised to receive the experimental vaccine regimen were included in this analysis. A positive smear microscopy result was associated with reduced anti-TRAP IgG titre (geometric mean titre: 2775 (uninfected) vs 1968 (infected), p = 0.025), whilst anti-AMA-1 IgG titres were weakly negatively correlated with reduced ex vivo IFNγ ELISpot response . Nutritional status was not associated with either humoral or cellular immunogenicity. Vaccine efficacy was also measured separately for vaccinees with positive and negative blood smears. Although not significant in either group compared to controls, vaccine efficacy measured by Cox hazard ratio was higher in uninfected compared to infected individuals (19.8% [p = 0.50] vs 3.3% [p = 0.69]). Overall, this data suggests exposure to malaria may be associated with impaired vaccine immunogenicity. This may have consequences for the testing and eventual deployment of various vaccines, in areas with high endemicity for malaria.The experimental malaria vaccine ChAd63 MVA ME-TRAP previously showed protective efficacy against Pactr.org, identifier PACTR201208000404131; ClinicalTrials.gov, identifier NCT01635647. This vaccine was tested in a Phase IIb clinical trial in 5-17 month old infants in Banfora, Burkina Faso, an area of high endemicity for observed . This waobserved . CD8+ T observed  and T ceIt has long been thought that malaria infection has broad immunosuppressive effects on the host. Some evidence exists showing malaria-mediated suppression of vaccine responses , includiThis study is a follow-up to the data previously published reporting on the safety, efficacy and immunogenicity of the candidate malaria vaccine ChAd63 MVA ME-TRAP in a Phase IIb clinical trial in 5-17 month-old infants and children in Banfora, Burkina Faso . Here, w22.1P. falciparum malaria with peak transmission during the rainy season (between June to October).Full details on the design and conduct of the clinical trial from which samples were derived for this analysis can be found in the primary clinical trial publication  and the ClinicalTrials.gov [NCT01635647] and Pactr.org [PACTR201208000404131].The clinical trial protocol and associated documents were reviewed and approved by Centre National de Recherche et de Formation sur le Paludisme (CNRFP) institutional bioethics committee , the Ministry of Health Ethical Committee for Biomedical Research (Burkina Faso)  and Oxford Tropical Research Ethics Committee (OXTREC) . Regulatory approval was given in Burkina Faso by the national regulatory authority . Informed consent was given prior to enrolment by the study participants’ parents or legally acceptable representatives. Ethical review and informed consent included approval for the re-analysis of samples for exploratory immunology including transcriptomic and genetic analysis. The trial was conducted according to the principles of the Declaration of Helsinki and International Conference on Harmonization (ICH) Good Clinical Practice (GCP) guidelines. An independent data safety monitoring board (DSMB) and local safety monitors provided safety oversight and GCP compliance was independently monitored by an external organisation . The study was registered at 10 vp ChAd63 ME-TRAP followed by 1 x 108 pfu MVA ME-TRAP, or the control vaccine; Imovax Rabies Vaccine . For both trial arms, two vaccine doses were given at an interval of 8 weeks.Following community sensitisation, parents and participant infants aged between 5-17 months were invited to screening to assess eligibility and to collect basic demographic and anthropometric data including height and weight. Healthy participants meeting the inclusion and exclusion criteria (appended in the study protocol) were then enrolled into the trial, conducted between December 2012 and March 2014. Participants were not screened for malaria exposure prior to enrolment. In total, 700 participants were randomised 1:1 to receive either the candidate malaria vaccine regimen; 5 x 10Volunteers were monitored for solicited and unsolicited adverse events by study clinicians or trained field workers and were followed-up for malaria infection for 6 months following the last vaccination. Parents were advised to contact the study team if their child became unwell at any point during follow-up, in order to access medical treatment. Any symptoms compatible with malaria  were investigated with duplicate blood films and a malaria rapid diagnostic test. Positive diagnoses were promptly treated according to national guidelines and data recorded for analysis of vaccine efficacy. Only blood film results were used for efficacy analysis, as per the study protocol.The analysis presented here was performed after unblinding and therefore does not include data from volunteers in the rabies control group.2.22.2.1P. falciparum, P. malariae, or P. ovale), and counts for P. falciparum were made for both sexual and asexual parasites. The parasite presence and density were determined independently by two readers for the same slide; if readings were judged to be discordant, a third independent read was organised. The parasite density (parasites/μl) was calculated as the geometric mean of the two positive readings .Blood films were obtained by capillary sampling at screening, vaccination and pre-defined timepoints during follow-up, as well as in infants presenting acutely unwell with symptoms compatible with malaria infection. Thick and thin blood films were stained by Giemsa staining using standard methods and read under 100 x bright field microscopy by trained laboratory technicians for the assessment, speciation, and quantification of parasitaemia. The count was made by species  for the isolation of peripheral blood mononucleocytes (PBMCs) and plasma by standard methods using density gradient centrifugation with Lymphoprep . These methods have been described previously . Peptides spanned the length of the ME-TRAP antigenic insert of both the T9/96 and 3D7 strains of P. falciparum. Peptide sequences have been published previously . Standard curves were modelled using five parameter logistic curve fitting and test plasma endpoint titres were inferred from the x axis intercept values of dilutions which lay within the linear range of the curve. Seropositive cut-off values for each assay were established using the mean plus three standard deviations of the EU readings of 42 unvaccinated and malaria-naïve UK donor plasma samples. For the TRAP assay, this cut-off was 88 EU and for AMA-1, this was 14 EU.Total anti-TRAP and anti-AMA-1 IgG titres were measured separately using standardised sandwich ELISAs as previously described , 11, 17.2.3For exploratory immunology analysis, data were assessed by D’Agostino-Pearson normality testing and determined to be non-normally distributed. Non-parametric tests were applied using Prism . Weight-for-length Z scores were calculated using the WHO Child Growth Standards with the igrowup macro  in STATAP. falciparum malaria (episodes/person years at risk) were calculated for each group. The distribution of the survival time was compared with the Wilcoxon test (if efficacy appeared to vary with time) or the Log-rank test (if it did not). Vaccine efficacy was assessed using Cox regression models for the first episode. Vaccine efficacy is defined as 1-R where R is the hazard ratio of the malaria vaccine group (infected or uninfected) versus the rabies control group (with 95% CI). A primary case of malaria episode was defined as fever (axillary temperature ≥ 37.5°C) with P. falciparum count > 5,000 trophozoites/µL of blood. The secondary case definition is defined as fever (axillary temperature ≥ 37.5°C) with Plasmodium falciparum count > 0 trophozoites/µL of blood. Analyses were performed using STATA software (version 15) and GraphPad Prism (version 8 and 9).For calculation of efficacy, the incidence of first or only episodes of p value of 0.05 was used as the threshold of statistical significance.A 33.16 PBMC (95% CI: 290–387)] at one week post-boost (day 63). Antibody responses were similar to previous trials , however, higher titres were observed in females compared to males [p = <0.004]. No significant efficacy between vaccinees and controls against uncomplicated malaria was observed . Efficacy against severe malaria was found to be 19.4%  and -4.7%  in unadjusted and adjusted cohorts respectively .Phase IIb safety, immunogenicity and efficacy results were previously published . BrieflyIn total, 351 participants were assigned to the experimental malaria vaccine group. From these, 336 received both doses of vaccine per-protocol and are included in the analysis presented here. Participants were sampled at day 0 (baseline) and day 63 (one week post-boost) for collection of blood plasma and PBMCs for immunological analysis. Participants were also bled for smear microscopy at day 0 and day 57 (boost vaccination). Descriptive participant demographics for the cohort are shown in P. falciparum and geometric mean parasite density was 1823 [95% CI: 1303-2550] trophozoites/µl. Frequency of patent parasitaemia did not differ by gender, with 25.9% and 27.6% of males and females respectively having a positive microscopy result at either timepoint [p = 0.806]. The prevalence of parasitaemia increased with age. 15/107 [14%] of the 5-8 month age group had a positive microscopy result at either timepoint, compared to 36/120 [30%] and 39/109 [35.8%] of 9-12 month olds and 13-17 month olds respectively. The mean age of study participants was 9.9 [95% CI: 9.45-10.39] months and 11.4 [95% CI: 10.7-12.1] months in uninfected and infected infants respectively [p = 0.012].Malaria infection was assessed by smear microscopy at the time of vaccination. 26.8% [90/336] of participants had detectable parasitaemia at either vaccination timepoint. The causative species identified in all infections was 3.2Peak vaccine-specific immune responses at day 63 were compared between individuals who were parasite positive at either vaccination timepoint or negative throughout. At day 63, anti-TRAP IgG titres were significantly lower in participants who had a positive parasite blood smear , compared to participants who were parasite-negative throughout   were measured in sera at day 63 as a correlate of prior exposure to infection. Overall, 180/236 [76.3%] volunteers with an available sample had detectable levels of anti-AMA-1 IgG at day 63. The geometric mean titre was 33.6 [95% CI: 24.7-45.6] and this was not significantly different when stratified by sex or age group, however anti-AMA-1 IgG titres were significantly higher in the group with a positive smear microscopy result at vaccination , compared to the parasite-negative group   were calculated at the screening visit using the standardised WHO international reference population . The medWLZ were used to investigate a relationship between nutritional status and vaccine immunogenicity. Immune responses at day 63 were compared between participants who were classified as moderately or severely malnourished and those with a normal WLZ. No significant differences were observed for either antigen-specific IgG or T cell responses Figure 33.5p = 0.50] and in infected individuals was 3.3%  in adjusted analyses  for vaccine efficacy in uninfected individuals compared to the rabies control group was 19.8% [95% CI: 0-35.7; 4This study aimed to identify factors which may be associated with reduced immunogenicity of the candidate malaria vaccine ChAd63 MVA ME-TRAP in 5-17 months old infants and children in Burkina Faso. We previously published results showing the vaccine did not elicit significant efficacy against clinical malaria in this cohort despite promising results in adults . BecauseP. falciparum antigen, AMA-1, were also measured. Whilst anti-AMA-1 IgG titres were also elevated in smear-positive individuals, it is known that antibodies against blood-stage antigens are cumulatively acquired over repeated infections and it has previously been shown that they broadly correlate with intensity of prior exposure  vaccination in a controlled human malaria infection model  institutional bioethics committee. Ministry of Health Ethical Committee for Biomedical Research (Burkina Faso). Oxford Tropical Research Ethics Committee (OXTREC) (University of Oxford). Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.SS, AT, AH, KE, AO, NV, and IN developed the clinical trial protocol. SS, AT, AH, KE, AO, AD, NV, and IN were involved with conducting the clinical trial. AT, RM, and OH performed the laboratory procedures and data analysis presented here in collaboration with SS and KE. AT and RM drafted the original manuscript which was edited by SS, AH, KE, NV, AO, AD, OH, and IN. All authors read and approved the final manuscript.This work was supported by an award from the European and Developing Countries Clinical Trials Partnership (EDCTP) and was performed by the Malaria Vectored Vaccines Consortium (MVVC), (Grant number IP.2008.31100.001). The European Vaccine Initiative (EVI) was the coordinator of the EDCTP-funded MVVC project. Co-funding was provided by the Swedish International Development Cooperation Agency (SIDA), the UK Medical Research Council (MRC), the Austrian Federal Ministry of Science and Research, and Irish Aid, Department of Foreign Affairs and Trade, Ireland. RM was supported by a PhD studentship from the Wellcome Trust (Grant number 109026/Z/15/Z). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.We thank the CNRFP staff at the Banfora research unit for their collaboration and Ceri McKenna for study monitoring. We are thankful to the Data Safety Monitoring Board and all the study volunteers. We particularly note the contribution of the late Dr Egeruan Babatunde Imoukhuede to this work.AH is a named inventor on patent applications and issued patents relating to malaria vectored vaccines and immunization regimes.The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. 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