Malaria Journal

Growing insecticide resistance and other causes of residual transmission of malaria parasites have led to a global stagnation in progress in malaria control, despite widespread deployment of insecticide-treated bed nets (ITNs). New bed net technologies including dual active ingredient (AI) and piperonyl butoxide plus pyrethroid (PBO + P) nets have been developed to address these problems and be more effective malaria prevention tools. Two types of dual-AI ITNs and PBO + P ITNs were evaluated across five countries in pilot studies coupled with economic evaluations. Chlorfenapyr + pyrethroid (C + P) ITNs showed the best overall performance in terms of incidence rate reduction (Incidence rate ratio 0.62 vs. standard ITN) and generally in terms of incremental cost-effectiveness ratio, but using any dual-AI or PBO + P ITN was favored over standard pyrethroid-only ITNs alone. There was significant overlap between the recommended strategy in any given study location due to high uncertainty in cases averted and relatively similar product costs. While the addition of indoor residual spraying (IRS) to standard ITNs was a more effective strategy than dual-AI or PBO + P ITNs, this evidence was based on only one study site and the incremental cost for the addition of IRS was substantially greater than the incremental cost of dual-AI or PBO ITNs compared to standard ITNs (ICER 18.59 USD per case averted vs. 1.51 USD per case averted for C + P ITN in this settings). The switch from standard ITNs to dual-AI or PBO ITNs is recommended in most African settings, with the chlorfenapyr + pyrethroid (C + P) nets being the broadly favored choice. Ultimately programs will need to incorporate local information on the malaria burden and up to date product price information to determine the most efficient malaria prevention strategy in the settings in which they serve.

Background: Malaria remains a major cause of morbidity and mortality among children under five years in Ghana. This study examined household, maternal, and child characteristics associated with malaria prevalence. Methods: Data were drawn from the 2019 Ghana Malaria Indicator Survey. The analytic sample comprised 2,867 children with valid malaria rapid diagnostic test results. Analyses accounted for the survey's multistage cluster design, including primary sampling units, strata, and sampling weights. Survey-weighted descriptive statistics, Rao-Scott corrected chi-square tests, and survey-weighted logistic regression with a quasibinomial link were used. Results: Overall, 22.9% of children tested positive for malaria. At the bivariate level, child age, number of children under five, household wealth, residence, region, household net usage, electricity, television ownership, maternal education, household size, and anaemia level were significantly associated with malaria status (p < 0.05). In the fully adjusted model, children in the poorest and poorer households had higher odds of testing positive than those in the richest households (AOR = 4.13 and 3.13, respectively). Rural children had higher odds than urban children (AOR = 2.36). The highest regional odds were observed in the Eastern Region (AOR = 15.3) compared with Greater Accra. Older children and those with severe anaemia had higher odds of testing positive (AOR = 4.17 and 24.5, respectively). Maternal education significantly interacted with household wealth and household net usage. Conclusion: Household wealth, region, residence, maternal education, child age, and anaemia level were important correlates of malaria prevalence. Findings support interventions addressing socioeconomic and regional inequalities in childhood malaria.

Attractive targeted sugar baits (ATSBs) are a novel vector intervention targeting the sugar feeding behaviour of mosquitos by providing toxic sugar meals. ATSBs have shown strong efficacy in terms of mosquito population reduction in entomological trials but their epidemiological impact remains incompletely understood. This modelling study explores the impact of ATSBs on entomological and epidemiological outcomes over a wide range of transmission settings. We quantify the required killing probabilities to achieve target incidence reductions and demonstrate the sensitivity of ATSB efficacy to mosquito characteristics such as sugar feeding frequency and sac rate. Furthermore, we show that ATSBs can maintain reduced incidence levels previously achieved by long-term insecticide-treated net campaigns. Despite mixed results from clinical trials, these results highlight the high potential of ATSBs as a complementary vector control strategy, while underscoring the critical importance of entomological parameters in predicting public health impact. Realizing this potential will require accurate characterization of mosquito behavior and optimized deployment strategies to ensure sufficient population-level killing probabilities of mosquitoes.

Background: Community case management has been scaled up nationally in Zambia over the last decade. However, there is limited evidence on how this nationwide implementation has affected febrile patients' access to malaria diagnosis and treatment in Zambia. Methodology: This study analyzed four rounds of Malaria Indicator Survey (MIS) data (2012-2021) to evaluate: 1) proportion of all-ages individuals with fever who sought treatment from a formal provider, 2) proportion of individuals going to CHWs over time, among those who sought treatment at a formal provider, 3) time duration between fever onset and treatment seeking at a formal provider, and 4) proportion of children <5 with malaria that received Artemether-Lumefantrine (AL) treatment. Mixed-effect logit models were employed to examine determinants of treatment-seeking behavior and factors affecting AL receipt among children <5 with malaria cases. Results: The proportion of febrile patients seeking treatment remained below 60% throughout 2012-2021, and AL receipt among children with malaria cases consistently stayed below 50%. The mean interval between fever onset and initial treatment-seeking encounter decreased from 2.42 days in 2012 to 1.71 days in 2021. Among formal care seekers, CHW utilization increased from 1.5% in 2012 to 10.0% in 2018 before declining to 3.2% in 2021. Longer walking time to the nearest health facility was associated with lower odds of treatment seeking, whereas CHW density was not associated with treatment seeking or AL receipt. Children who did not went to formal providers had lower odds of AL receipt than those who sought treatment from CHWs. Conclusion: Despite nationwide CCM scale-up over the last decade, significant barriers persist in malaria patients' access to diagnosis and treatment in Zambia. Our results indicate that while CCM coverage should be maintained and further expanded, additional complementary interventions are also needed to overcome remaining access barriers.

Introduction: Integrated Vector Management (IVM) (Beier et al., 2008) is considered to be one of the most cost-effective tools to reduce malaria transmission. This rational decision-making tool supports the design of an intelligent and optimal management of resources meant for malaria prevention and vector control. Some of the most widespread components of IVM include the distribution of bed nets, spraying operations and environmental management to reduce mosquito density. IVM was launched in Kenya in 2001, and during the last two decades the country has advocated for the use of this tool to combat malaria. IVM, however, requires a customized choice of interventions in order to achieve the optimal use of resources for vector control in the area of interest. Methods: In this article, we present a malaria simulation model that helps us assess the potential impact of different future IVM strategies to achieve optimal malaria reduction results in Kenya. The model used for this analysis is inspired by the Malaria Management Model (MMM) (Pedercini, Movilla Blanco, & Kopainsky, 2011), which has been developed by means of the System Dynamics methodology. The version of the model presented in this paper is adapted for Kenya, and the study includes the assessment of the cost and main socio-economic benefits from eliminating malaria in the country. The model also integrates the main impacts of malaria transmission into the socio-economic development, evaluating the effect of malaria on GDP production, literacy rate and life expectancy, among others. Results: Our model includes data collected from 1980 until 2018, before the RTS,S/AS01 vaccine was piloted in Kenya, and the simulation results confirm that the IVM programs in Kenya would not achieve malaria elimination within this decade. In addition to a substantial increase in the malaria budget, a reallocation of such a budget across interventions would be necessary in order to reach a malaria-free country by 2030 (Kenya Malaria Strategic Plan). The results also confirm that, despite the need for further efforts, malaria reduction in Kenya has provided sufficient economic benefits to cover the costs of malaria control. Conclusions: The System Dynamics simulation model illustrates how a computer-aided scenario analysis tool can inform the design of malaria control policies and assist decision-makers. Simulation models create systematic mechanisms for analyzing alternative interventions and inform about the different tradeoffs.

BackgroundAntimalarial drug efficacy is threatened by the development of drug resistance. In Rwanda, high levels of resistance have been reported in the past, including mutations in the Pfk13 gene associated with partial resistance to artemisinin, leading to delayed parasite clearance of Artemether-Lumefantrine (AL). Therefore, continuous molecular surveillance of drug resistance markers is required. Here, we report polymorphisms in the Pfcrt, Pfdhps, and Pfdhfr genes in samples collected in Rwanda in 2018. MethodsSamples from three sites (Masaka, Rukara, and Bugarama) were collected during a therapeutic efficacy study (TES) conducted in 2018. Targeted amplification of resistance genes of interest was performed by PCR, and products were sequenced by Sanger sequencing. ResultsThe K76T Pfcrt mutation was found in 10% of the samples, only in Bugarama. For Pfdhps, the A437G, K540E and A581G mutations were detected in 94%, 94% and 55% of the samples, respectively. For Pfdhfr, the N51I, S198N, C59R and I164L mutations were found in 99%, 99%, 88% and 16% of samples, respectively. The latter was only detected in Masaka and Rukara. ConclusionsWe confirm the slow and partial recovery of chloroquine susceptibility in the country. All previously reported Pfk13 mutants were Pfcrt wild type, thus possibly selected by AL. The prevalence of Pfdhps and Pfdhfr mutants, including those with the highly resistant I164L mutation, is high and increasing, despite the absence of drug pressure. It is imperative to closely monitor resistance and efficacy of AL and other treatment options as part of the malaria surveillance program and resistance mitigation strategy in the country.

Asymptomatic Plasmodium falciparum carriers are cryptic reservoirs that sustain malaria transmission, undermining control efforts. However, its temporal dynamics and drivers remain underexplored. A total of 845 asymptomatic individuals in Simiw were screened for P. falciparum carriage in May, August, and October 2021, as well as February 2022, representing the pre-peak, peak and post peak malaria transmission seasons that fall in either the wet or dry seasons. Meteorological data from March 2021 to March 2022 was obtained. Descriptive and inferential statistical analyses, such as Poisson Generalised Linear and Distributed Lag Nonlinear Models, were conducted in R to investigate the influence of seasonality and meteorological factors on PET-PCR-detected asymptomatic Plasmodium falciparum infections. In Simiw, the prevalence of asymptomatic P. falciparum infections ranged from 6.2% to 14.0% by RDT and 13.4% to 32.0% by PET-PCR during the study period. Asymptomatic malaria cases were highest in February 2022, during the dry season. Younger participants (median age: 14 years) had more infections than adults. Seasonal trend showed the strongest nonlinear relationship (exp({beta}) = 190.38, p = 0.01). Features of the dry season predicted asymptomatic malaria cases, as average maximum temperature (exp({beta}) = 1.30, p < 0.001) was a positive nonlinear predictor, whereas average humidity (exp({beta}) = 0.73, p = 0.02) and precipitation (exp({beta}) = 0.99, p < 0.001) were negative nonlinear predictors. According to regression models, the highest counts of asymptomatic malaria cases occur at a monthly maximum temperature of 32oC, monthly average relative humidity of 91% and monthly precipitation of 20 mm, similar to records in February 2022 in the dry season. Additionally, a precipitation of 150 mm forecasted the highest number of cases two months later (exp({beta}) = 3.20, p < 0.001). In this study, the seasonal trend had a much stronger effect on asymptomatic malaria than meteorological factors, such as rainfall.

Insecticide-treated net (ITN) use - defined as the proportion of a population that use ITNs - is a measure of ITN uptake that is used in the estimation of malaria burden and evaluation of intervention programs. However, binary classification of individuals as users or non-users does not account for variations in ITN-related protection attributed to deleterious factors such as chemical and physical degradation, and increased insecticide resistance in vector populations. In this paper, we present a parsimonious model for malaria dynamics in mosquito-human populations in the presence of varying ITN use conditions. Using this model, we propose a new standardised measure of ITN coverage termed the "efficacy-adjusted use" defined as the equivalent level of use, assuming fully efficacious nets, that would be required to achieve the same level of theoretical EIR reduction. This more nuanced measure is used as a proxy for studying ITN-attributed protection across 44 African countries. We find that estimated protection levels in current ITN paradigms is significantly lower than indicated by crude ITN use metrics, with insecticide resistance having the largest deleterious effect. Furthermore, recent adoption of next-generation nets is estimated to have mitigated a 13% reduction in protection compared to a counterfactual pyrethroid only scenario.

Background The COVID-19 pandemic was associated with reported disruptions to healthcare delivery and malaria control activities in remote, malaria-endemic indigenous communities with limited access to healthcare. Remote indigenous communities in the Peruvian Amazon may have been especially vulnerable due to interruptions in malaria surveillance, diagnosis, and treatment. We investigated the impact of the COVID-19 pandemic on malaria burden, healthcare access, and community perceptions in hard-to-reach indigenous communities in the Amazonas region of Peru. In malaria-endemic regions, these lessons are particularly important because future health emergencies may similarly affect surveillance, diagnosis, prevention, and treatment activities, potentially reversing gains achieved through malaria control programs. Methods A convergent parallel mixed-methods study was conducted in 2021 and 2022 across four indigenous communities in the Rio Santiago district, Amazonas region, Peru. Quantitative data were collected through cross-sectional malaria surveys, and qualitative data were obtained through semi-structured interviews with inhabitants, community health workers, and local health personnel. Malaria infections were detected by microscopy and confirmed by PCR. Factors associated with the occurrence of malaria infection were studied based on a generalized estimating equation (GEE) approach applied to clustered binary outcome data and accounting for repeated observations within participants across study years. Qualitative data were analyzed thematically, and both components were integrated using the Pillar Integration Process framework. Results A total of 514 participants were included. PCR-based malaria prevalence was 17.6% in 2021 and 26.09% in 2022. P. falciparum prevalence was particularly high in the Alianza Progreso community (2021: 24.19%, 2022: 16.16%) compared to the other studied communities. Previous malaria infection and chills were associated with PCR-confirmed malaria infection. Qualitative findings indicated that COVID-19-related disruptions affected malaria control activities by interrupting diagnosis and treatment availability, reducing community follow-up, and prioritizing COVID-19 response activities over malaria control. Participants also described fear of COVID-19, temporary migration to farm areas, and reliance on herbal medicine during the pandemic. Conclusions The COVID-19 pandemic may have contributed to exacerbated pre-existing challenges to malaria control in remote indigenous communities in the Peruvian Amazon. Strengthening malaria surveillance, ensuring continuity of diagnosis and treatment, and improving healthcare access in geographically isolated communities will be critical to supporting malaria elimination efforts in Peru.

Larval source management (LSM) is a complementary malaria control intervention, yet evidence to guide context-specific implementation remains limited. Nigeria's recent national commitment to LSM scale-up makes the need for operational evidence particularly urgent. Informal settlements embedded within wards of differing dominant settlement archetypes may present distinct Anopheles larval habitat profiles with implications for how LSM strategies should be tailored. We evaluated Anopheles larval habitats within informal settlement areas across wards with contrasting settlement archetypes in Ibadan metropolis, Nigeria, to inform targeted larval source management. Potential breeding habitats were surveyed in dry and wet seasons within informal settlement areas across three wards -- Olopomewa, Challenge, and Agugu -- representing formal, informal, and slum settlement-dominant archetypes respectively. Habitats were characterized and assessed for Anopheles larval presence. Pareto analysis identified habitats accounting for 80% of larval abundance. Breeding habitat density per km{superscript 2} was estimated using a simulated pathway technique. Associations between mosquito dispersal scale and household malaria infections identified through Rapid Diagnostic Testing were evaluated using kernel-based distance-decay weighting. Environmental drivers of habitat suitability were modeled in MaxEnt. Of 420 potential breeding habitats identified, 31 (7.4%) contained Anopheles larvae, predominantly during the wet season (26, 83.9%). Puddles, dug wells, drainages/gutters/ditches and canals accounted for 80% of site-level larval abundance when standardized by sampling effort. Larval and breeding habitat density were highest in Agugu, the slum-dominant ward, across both seasons. Modeled mosquito dispersal scale showed best fit at 30-32m in Challenge (OR 1.41, 95% CI: 1.05-1.89) during the wet season and 16-18m in Agugu (OR 1.29, 95% CI: 1.04-1.60) during the dry season. Habitat suitability in Agugu was higher farther from large water bodies and in areas with higher population density and positive Normalized Difference Water Index values. In Challenge, suitability was higher in areas with lower nighttime light levels, positive Normalized Difference Water Index values, and negative Normalized Difference Moisture Index values. Further studies incorporating multiple wards across diverse urban settings are needed to determine whether differences in larval ecology between settlement archetypes provide a reliable basis for planning larval source management.

Abstract Background Malaria remains a major public health challenge in Ghana, despite recent reductions in cases due to various interventions. The endemicity of the disease varies across regions, influenced by diverse seasonal and temporal factors that support mosquito proliferation and malaria cases. This study used a Generalised Additive Models to explore the impact of weather conditions on malaria cases in Ghana. Methods Generalised Additive Models were used to examine the nonlinear effects of weather conditions on malaria cases. Monthly aggregated malaria cases from the District Health Information Management System II and average monthly rainfall and temperature data from the Ghana Meteorological Agency were analysed, covering 2012 to 2023. Regional Generalised Additive Models incorporating weather variables were developed, fitted, and validated against observed data using model diagnostics to identify the most suitable model for each region. Results The analysis revealed complex temporal patterns in malaria cases across Ghana, influenced by seasonal and long-term trends. Regions constituting the Coastal and Transitional Forest zones exhibited bimodal peak malaria seasons, while the Guinea Savannah showed a unimodal peak. Significant interactions between rainfall and temperature were identified, particularly in the Eastern region, where higher rainfall combined with temperatures around 27-28 {degrees}C were associated with higher malaria cases, reflecting the complex and region-specific nature of meteorological influences. Conclusions The findings point to the dynamic and heterogeneous nature of malaria caseloads in Ghana, emphasising the need for region-specific control strategies tailored to local climatic conditions. A key recommendation is the systematic integration of meteorological data into the National Malaria Data Repository to enable continuous monitoring of climatic influences and support timely, evidence-based intervention decisions. Future research should incorporate socio-economic factors, intervention coverage data, vector surveillance, and demographic characteristics into mathematical modelling frameworks for a more comprehensive understanding of malaria cases in Ghana.

Malaria parasite virulence will be impacted by naturally occurring variation in multiplication rates. Clinical isolates of Plasmodium falciparum exhibit a range of multiplication rates under exponential growth conditions in culture, but it needs to be discovered if relative multiplication rates under competitive conditions are principally defined by this underlying multiplication rate potential. Relative multiplication rates of P. falciparum lines were investigated in 14-day competition assays against a standard competitor clone HB3, with other long-term laboratory-adapted clones showing similar or higher mean per-48-hour rates ranging from 0.98 to 1.51 relative to HB3. In contrast, thirteen Ghanaian clinical isolates cultured for close to two months prior to assay had lower rates, ranging from 0.46 to 0.76 relative to HB3. Analysing the single-genotype clinical isolates and laboratory-adapted clones, there was a highly significant correlation between the competitive rates and previously determined exponential rates (Spearmans rho = 0.95, P = 0.0003), which accounted for most of the observed variance (Pearsons r2 = 0.77, P = 0.004). Testing the effect of alternative nutritional supplementation with human serum or Albumax showed a majority of parasites had consistent competitive rates under either condition, indicating that intrinsic differences determine most variation among parasites.

Prolonged use of the few insecticide classes available for long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) has driven widespread physiological resistance of malaria vector mosquitoes to this limited arsenal of active ingredients. However, recent innovations like next-generation LLINs (NG-LLINs) containing two complementary insecticides and new insecticide classes for IRS offer new opportunities for pre-emptive resistance management by deploying more diversified actives as mixtures, combinations, rotations or mosaics. Here a deterministic model of mosquito foraging behaviour was formulated to predict the probabilities of deterrence, mortality or successful feeding across repeated feeding attempts in scenarios with different combinations of NG-LLINs and/or IRS micro-mosaics with varying levels of insecticide diversification between neighbouring houses. Final fates were classified based on whether or not the mosquito eventually died or successfully fed, and whether the latter occurred indoors or outdoors after exposure to zero, one or several IRS insecticides. The primary outcome was the probability that a single F mosquito carrying a novel resistance trait to a new IRS insecticide successfully feeds, survives and reproduces, thereby establishing those traits within the population. The secondary outcome was the selection coefficient governing the spread of such novel resistance traits from the F generation onwards. For highly anthropophagic and endophagic vectors like Anopheles funestus, combining NG-LLINs with IRS micro-mosaics using two insecticides may reduce emergence rates for novel resistance traits against IRS insecticides by approximately 2 to 2.5-fold, mainly through direct killing by NG-LLINs, although exposure to both IRS actives when forced to visit multiple houses also contributes to a lesser extent. However, such resistance management benefits are fundamentally constrained by outdoor feeding behaviours that limit or completely prevent indoor insecticide exposure. Increasing IRS micro-mosaic insecticide diversity beyond two actives is unlikely to further dampen resistance emergence rates because few mosquitoes survive long enough without feeding to encounter several IRS treatments. Once a resistance trait becomes established in the vector population, selection coefficients remain consistently high enough to force the spread of those traits, regardless of intervention combination. For more exophagic, zoophagic vectors like An. arabiensis, NG-LLINs plus IRS micro-mosaics are not expected to provide any meaningful resistance management benefit because frequent outdoor feeding, often on animals, allows them to largely avoid insecticide exposure altogether. Exclusively indoor-focused vector control strategies may not satisfactorily slow insecticide resistance emergence and spread, so new outdoor protection measures that close these coverage gaps with complementary insecticides will be needed.

Background: Human mobility is increasingly recognized as a key factor influencing malaria transmission dynamics, particularly in low-transmission settings approaching elimination. This study aimed to assess mobility patterns and their association with malaria risk in two hypoendemic communities in the Peruvian Amazon. Method: A longitudinal study was conducted in the communities of Libertad and Urcomirano (Mazan River basin). Monthly population screenings were combined with weekly active and passive case detection. A total of 678 individuals were enrolled. Mobility patterns were assessed through structured questionnaires, and social network analysis was used to characterize travel connections. Log-binomial regression analysis was applied to identify risk factors associated with malaria infection. Result: Internally, mobile individuals in Libertad showed a higher malaria incidence (>32.47 cases per 1,000 person-months) than those in Urcomirano (<10.15 cases per 1,000 person-months). Travel networks were mainly connected to Mazan district and Iquitos city, followed by local streams such as Armas and Arahuana. Mobility was primarily driven by family, administrative and occupational activities. Male sex (PR = 2.15, 95% CI: 1.37 - 3.37) and age [&ge;]15 years (PR = 1.98, 95% CI: 1.24 - 3.19) were significantly associated with malaria infection (p-value < 0.05). Conclusion: Internally mobile populations represent a key high-risk group sustaining malaria transmission in hypoendemic settings. Targeted interventions focusing on mobile individuals should be integrated into malaria elimination strategies in the Peruvian Amazon and similar endemic regions.

The effectiveness of malaria vector control is increasingly threatened by widespread insecticide resistance, particularly to pyrethroids. In response, the World Health Organization recommends dual-active ingredients (dual-A.I.) insecticide-treated nets (ITNs) in resistant settings. This study evaluated the efficacy of several dual-A.I. ITNs in two experimental hut trial sites an area with high insecticide resistant malaria vectors in Tanzania with differing vector species composition and bionomics. Five ITNs were evaluated: a pyrethroid-only net (MAGNet(R)), three pyrethroid-piperonyl butoxide (PBO) nets (OlysetTM Plus, Veeralin(R), and PermaNet(R) 3.0), one dual-A.I. net (Interceptor(R) G2; chlorfenapyr + alpha-cypermethrin), and an untreated control net. Mosquitoes were collected from huts, morphologically identified, and monitored for mortality up to 72 h. WHO cone and tunnel tests using susceptible An. gambiae s.s. were conducted for quality control, while field-collected mosquitoes were used for bio-efficacy monitoring. Molecular species identification was performed using PCR assays, and genomic DNA was extracted from An. funestus s.l. and An. gambiae s.l. collected from the trials. All ITNs met WHO bio-efficacy criteria in cone and tunnel tests. An. gambiae s.l. predominated in Mwagagala (77%) but was rare in Magu (4%), where An. funestus complex was dominant. In Magu, Interceptor(R) G2 and Veeralin(R) achieved significantly higher mortality than MAGNet(R) at 24 h (53% and 45% vs 24%) and 72 h (61% and 53% vs 24%). In contrast, no significant mortality differences were observed among ITNs in Mwagagala. High resistance intensity was detected in both vector groups (mortality <20% in bioassays). In An. funestus from Magu, the 4.3 kb-SV resistant genotype was fixed, while G454A-CYP9K1 resistance was highly prevalent (RR: 0.70-1.00). Interceptor(R) G2 and Veeralin(R) outperformed the pyrethroid-only reference net against An. funestus complex but not against predominantly An. arabiensis populations.

Malaria remains a significant global health challenge. Intermittent Preventive Treatment of malaria in school-age children (IPTsc) is recommended to reduce disease burden, but optimal drug choice is unclear. Dihydroartemisinin-Piperaquine (DP) is highly efficacious but there are concerns about widespread use given emerging artemisinin resistance and its role as an alternative first line treatment. Thus, non-artemisinin alternatives to DP are needed. 646 Malawian primary school children participated in the second stage of a 3-arm randomized controlled trial. Participants were allocated to IPTsc with 1) DP, 2) Sulfadoxine-Pyrimethamine+Chloroquine (SP+CQ) or 3) Control (no treatment). Study drugs were administered at three six-weekly visits. Outcomes were measured 6-8 weeks later. The primary outcome was Plasmodium falciparum (Pf) prevalence detected by qPCR. Secondary outcomes included clinical malaria and anemia. Analysis was modified intention-to-treat. Outcome assessment included 588 (91%) participants. Prevalence of Pf infection was 18% (34/198) in the IPTsc-DP arm, 27% (52/200) in the IPTsc-SP+CQ arm, and 48% (89/190) in the control arm. Compared to control, both IPTsc-DP (adjusted Odds Ratio [aOR] 0.22, 95%CI:0.14-0.36, p<0.001) and IPT-SP+CQ (aOR 0.38, 95%CI:0.24-0.59, p<0.001) significantly reduced odds of infection. Both regimens also decreased anemia (DP: aOR 0.45, 95%CI:0.21-0.93, p=0.035; SP+CQ: aOR 0.47, 95%CI:0.22-0.98, p=0.048) and clinical malaria (DP: adjusted Incidence Rate Ratio [aIRR] 0.41, 95%CI:0.28-0.60), p<0.001; SP+CQ: aIRR 0.60, 95%CI:0.43 - 0.84, p=0.003). In Malawi and settings with similar malaria drug resistance profiles, SP+CQ may be a suitable alternative to DP for IPTsc. Clinical Trial Registration ClinicalTrials.gov ID: NCT05980156

The movement of people across country borders has implications for malaria control and elimination. Namibia is a low transmission country in southern Africa that borders two high transmission countries, Angola and Zambia, yet the extent to which cross-border connectivity constrains progress toward elimination remains unclear. In this study, we aimed to explore the feasibility of pre-elimination in Namibia, accounting for local transmission dynamics, climatic variability, international connectivity and current intervention coverage levels. A compartmental mathematical metapopulation model of malaria transmission was used to estimate the change in cases relative to the present status quo. Our findings suggest that Namibia could achieve pre-elimination status by 2034 through robust cross-border management targeting 50% of migrants and travelers while simultaneously scaling up the effectiveness of vector control interventions across Angola, Namibia, and Zambia. Within a coordinated multi-country approach, managing cross-border travel without additional interventions reduces Namibias case burden by up to 33% over 10 years. In contrast, isolated national strategies were insufficient to offset importation pressure from neighbouring high-transmission settings. Cross-border management poses challenges but is necessary for elimination in low-transmission settings. Simulated insecticide resistance resulted in marginal increases in incidence rate in Angola and Zambia, indicating possible health system resilience to increasing insecticide resistance. Overall, this study provides a quantitative framework for regional malaria policy, shifting from isolated national efforts to a synchronised, multi-country approach to achieve elimination in low-transmission settings.

Transmission-blocking vaccines (TBVs) are a promising strategy to reduce malaria transmission by targeting parasite stages within the mosquito. However, parasite genetic diversity may limit vaccine efficacy. We used next-generation amplicon deep sequencing to identify non-synonymous single nucleotide polymorphisms (SNPs) in Pfs25 from 184 Plasmodium falciparum isolates from Senegal, Tanzania, Ghana, and Burkina Faso. Prioritized SNPs were introduced into P. falciparum via CRISPR-Cas9. For the G116C variant, gametocyte development was evaluated by microscopy and qPCR, and mosquito infectivity was assessed by SMFAs. We identified 26 SNPs, including 24 novel variants. Functional assays showed that the Pfs25 G116C mutation did not affect gametocyte development or exflagellation. SMFA showed no significant differences in oocyst prevalence or intensity between mutant and WT parasites. These findings highlight the importance of integrating genetic surveillance with functional validation to guide the development of effective transmission blocking interventions

Antimalarial resistance is one of the greatest threats to malaria elimination. Following an outbreak of Plasmodium falciparum infection in Sabah Malaysia in 2019, 98 samples were sequenced to search for adaptations driving the outbreak. The genomic data revealed evidence of clonal expansion of a strain carrying multiple copies of the chloroquine resistance transporter gene (pfcrt) in 86 cases. A TaqMan qPCR assay was developed to quantify pfcrt copy number, confirming the in silico evidence of duplication. Whilst point mutations in pfcrt have been associated with resistance to chloroquine and other drugs, copy number amplification has not been widely explored as a resistance mechanism. We investigated the genetic architecture of the duplication, revealing a wildtype haplotype (3D7 reference-type with 76K variant) and a novel mutant (with 76T mutation). Application of the TaqMan assay in 43 P. falciparum cases from neighbouring Palawan Island, the Philippines, identified a further two cases with pfcrt duplication. Assessment of the global genomic data in the MalariaGEN Pf8 repository identified a further 86 cases, including 73 (85%) from West Africa with evidence of pfcrt duplication. Amongst 47 monoclonal MalariaGEN cases, majority (95%) comprised wild type and mutant variants at codon 76. Our study reveals a potential previously unconsidered antimalarial resistance mechanism for P. falciparum and provides an assay for surveillance in other populations.

Malaria elimination is shaped by complex interactions among climatic, environmental, socioeconomic, demographic, health-system, and intervention-related factors. However most studies examine only subsets of these drivers, limiting understanding of their combined influence on epidemiological risks. In this study, we integrated 25 years of data from 44 African countries on malaria burden and control, climate, environmental and land-use conditions, socioeconomic and demographic characteristics, and health-system capacity within a unified geospatial, explainable machine-learning, and forecasting framework to characterize spatiotemporal patterns of malaria, quantify the relative contributions of key determinants, and generate 10-year Africa-wide and country-specific forecasts of malaria incidence and mortality rates per 1,000 people at risk. We identified and mapped malaria incidence and mortality hotspots using the Getis-Ord Gi* statistic. Our analyses showed that both incidence and mortality burden remained highly heterogeneous across Africa, with persistent hotspots concentrated in the West and Central Africa. The explainable machine-learning model, that achieved high predictive performance (i.e., XGBoost for incidence, holdout R$^2$ = 0.92; Random Forest for mortality, holdout R$^2$ = 0.91), identified lower availability of hospital beds (per 1,000 people), higher mortality rate attributed to unsafe WASH (per 100,000), and lower percentage (\%) of people using handwashing facilities as the top three most influential determinants of higher risk of infection across Africa whereas higher mortality rate attributed to unsafe WASH (per 100,000), lower \% of people using at least basic sanitation services, and access to electricity (\%) were associated with worse mortality outcomes. Forecasting models also demonstrated strong predictive accuracy (Naive persistence and Elastic Net, holdout R$^2$ = 0.98 for incidence and 0.97 for mortality). Assuming current intervention and structural conditions persist, Africa-wide malaria incidence was projected to remain broadly stable, with a modest upward trend by 2035, whereas mortality was projected to decline initially and subsequently remain relatively unchanged. However, substantial country-level heterogeneity showed both emerging transmission hotspots and persistently high-burden countries. this suggests there is a need for sustained control and accelerated elimination efforts. Overall, this study demonstrates that integrating geospatial analysis, explainable machine learning, and forecasting provides a robust framework for understanding malaria dynamics, identifying the key determinants of burden, anticipating future trends, and supporting geographically targeted malaria control across Africa. Beyond malaria, our analyses can be applied as a generalizable approach for infectious disease surveillance, early-warning systems, hotspot detection, resource prioritization, and precision public health using large-scale longitudinal health data.