Malaria Journal最新文献

Malaria remains a leading health threat in sub-Saharan Africa, causing over 600,000 deaths annually. Ghana, ranked among the top 15 in malaria burden in Africa, relies heavily on microscopy for diagnosis due to its affordability and established use. However, limitations in sensitivity, turnaround time, and availability of skilled personnel despite ongoing national training efforts stress the need for improved diagnostics. This study evaluated miLab^™, an AI-assisted automated malaria detection platform, using nested PCR (nPCR) as the reference standard. We conducted a hospital-based cross-sectional study from August 2024 to June 2025 in three malaria-endemic communities in Kumasi, Ashanti region and enrolled 300 suspected malaria patients (168 females, 132 males; aged 1-87 years, median 24). Blood samples were analyzed independently by miLab^™, two independent mid-level microscopists, and nPCR. Discrepancies between the two microscopists were resolved by a WHO expert microscopist (adjudicated microscopy) to establish a microscopy reference standard. Diagnostic accuracy, correlation and measurement agreement were determined using GraphPad Prism Version 8. Parasite densities estimated by miLab^™ ranged from 0.95 to 5.34 log parasites/µL (median 3.52, IQR 2.93-3.91). For mid-level microscopist 1, densities ranged from 2.02 to 5.43, (median 4.02, IQR: 3.22-4.50), while Mid-level microscopist 2 measured densities between 1.98 and 5.22, (median 3.78, IQR: 3.15-4.23). When compared to nPCR, miLab^™ demonstrated a sensitivity of 94.23%, specificity of 98.98%, and accuracy of 97.33%, while adjudicated microscopy showed a sensitivity of 85.58%, specificity of 97.96%, and accuracy of 93.67%. These findings indicate that miLab^™ has better performance compared to microscopy for detection of malaria parasites. miLab™ could offer a reliable, rapid diagnostic alternative suitable for malaria-endemic, resource-limited settings where timely and accurate diagnosis is critical for effective case management and control.

Objective: Jacobabad, located in the northern region of Sindh, is characterized by an extremely hot and humid climate and is classified as a malaria-endemic area, with an annual parasite incidence (API) of 31 per 1000 population in 2024. The present study investigates the incidence of malaria among patients admitted to our hospital along with comparison of clinical and haematological profile of severe and uncomplicated malaria in the region and to determine any association with age. To the best of our knowledge, no prior study has systematically documented the malaria burden in this region.

Methods: A prospective clinical observational study was conducted in Pakistan Airforce Hospital, Shahbaz Base, Jacobabad, Sindh between 2024 to 2025. A total of 260 admitted malaria patients, irrespective of age and gender were included. Cases were categorized into severe and complicated based on WHO criteria. The clinical parameters and haematological profile of severe and uncomplicated cases were compared and data analysed using SPSS v 27. Frequency and percentage were calculated for categorical variables while mean and standard deviation was calculated for numerical variables. Chi square test was applied to find statistical significance. The p-value of ≤ 0.05 was considered statistically significant. Statistical significance of haematological parameters with type of malaria was derived using Kruskal Wallis test while statistical significance of haematological parameters with severity of disease was derived by Mann Whitney U test.

Results: Uncomplicated and severe malaria cases were 217 (83.5%) and 43 (16.5%) respectively. Severe malaria was significantly associated with jaundice, bleeding, pallor, respiratory distress, fits, cerebral malaria, anaemia and thrombocytopenia. Overall, case fatality was 16.2% seen in paediatric age group (0.1-15 yrs) and most fatal complication was cerebral malaria.

Conclusion: Clinical and haematological parameters serve as prognostic indicators for disease progression and warrant close monitoring to prevent adverse clinical outcomes.

Background: Malaria remains a leading cause of morbidity and mortality among children under five years of age in Nigeria. While microscopy is the World Health Organization (WHO) gold standard for malaria diagnosis, rapid diagnostic tests (RDTs), such as the Standard Diagnostic Bioline Malaria Antigen Plasmodium falciparum (SD Bioline Malaria Ag P.f.), are increasingly used in healthcare and field settings. However, recent reports show variable performances of these tests, and evidence on their performance metrics from large, nationally representative Nigerian samples is limited. This study, therefore, aimed to evaluate the performance of the SD Bioline Malaria Ag P.f. RDT using a nationally representative dataset.

Methods: We conducted a secondary analysis of the 2021 Nigerian Malaria Indicator Survey (NMIS), a nationally representative household survey that used a two-stage stratified cluster sampling design. Children aged 6-59 months with valid results for both microscopy and SD Bioline Malaria Ag P.f were included. The performance metrics for the RDT were calculated against microscopy as the reference standard, accounting for the survey design.

Results: Among the surveyed children, a 9067-unweighted sample with complete RDT and microscopy test results was analyzed (weighted sample, n = 9131). The SD Bioline Malaria Ag P.f. demonstrated a sensitivity of 88.6%, a specificity of 75.2%, a positive predictive value (PPV) of 49.5%, a negative predictive value (NPV) of 96.0%, and an accuracy of 78.1%. Cohen's kappa indicated moderate agreement with microscopy (κ = 0.496), and the overall weighted ROC AUC was 0.816.

Conclusion: SD Bioline Malaria Ag P.f. shows high sensitivity and negative predictive value, confirming its reliability for ruling out malaria in children aged 6-59 months in Nigeria. However, moderate specificity and low positive predictive value with a large microscopy-RDT estimated prevalence gap indicate a risk of overestimating malaria prevalence. False negatives may occur, potentially due to PfHRP2/3 deletions, test handling, or non-falciparum infections. These findings underscore the need for confirmatory testing where feasible, with the consideration of complementary diagnostic strategies to optimize surveillance and case management, and ongoing postmarketing evaluation of RDT performance.

Background: Ethiopia has been faced with the continual resurgence of malaria. It affects the health of the young workforce, which is believed to affect and slow economic growth.

Objective: Analyze and forecast the incidence of malaria in the next years (2026-2030) on the basis of historical data from Bahir Dar city in the Amhara National Regional State of Ethiopia.

Methods: A forecasting framework-seasonal autoregressive integrated moving average with exogenous factors (SARIMAX) model-was developed using malaria data from Amhara regional health bureau and exogenous regressors, weather data, from World Weather Online. The dataset comprising 90 monthly data points, spanning from January 1, 2018 to June 30, 2025, was split to develop and validate the model, reserving the first 80% (January 1, 2018-December 31, 2023) for training the model and the final 20% (January 1, 2024-June 30, 2025) for testing forecasting performance. We used the fitted model to forecast for the next 5 years using Python version 3.11.

Results: The SARIMAX (1, 2, 2) (1, 2, 2, 12, exog) model, with weather data as exogenous regressors, fit the historical data well. It revealed an increasing trend, as evidenced by the in-sample fit, out-of-sample forecast and future prediction values, which consistently increased over the prediction horizon. None of the weather condition data showed a statistically significant predictive relationship with malaria incidence (p > 0.05). The evaluation metrics, mean absolute percentage error (MAPE), confirmed reasonable predictive accuracy (28.3%).

Conclusion: Our study demonstrates an upward trend in forecasted malaria cases for the upcoming years, suggesting a potential breakdown in current strategies. The result underscores the necessity of a targeted, localized early warning system to manage resource allocation.

Background: Understanding the composition, host feeding patterns, and infection status of all potential vectors is essential to understand changing disease transmission dynamics and inform future vector control strategies. This study assessed anopheline species composition, abundance, distribution, and host feeding preferences in Southern Province, Zambia to identify potential contributors to residual malaria transmission beyond primary vectors.

Methods: Adult mosquitoes were collected along a 100 km transect between the districts of Pemba, Monze and Gwembe in Southern Province, Zambia, an area of low malaria transmission. Mosquitoes were sampled from 12 randomly selected households at 5 km intervals along the transect. Centers for Disease Control and Prevention light traps were used to collect adult mosquitoes indoors and outdoors. Mosquitoes were identified using morphological keys and molecular approaches. A multiplexed PCR assay was utilized to identify mammalian hosts and Plasmodium falciparum (Pf) sporozoite infection was determined using an enzyme linked immunosorbent assay.

Results: A total of 5697 female anopheline mosquitoes were collected from both indoor and outdoor traps, revealing a diverse range of species. Nine species of Anopheles mosquitoes were identified, dominated by Anopheles rufipes (n = 1527, 26.8%), and An. pretoriensis (n = 1427, 25.1%). Host blood meal analysis of 401 visibly blood-fed mosquitoes revealed that Anopheles species in the study area fed primarily on goats (n = 176; 62.5%), humans (n = 55; 19.4%) and cows (n = 29; 10.2%). The human blood index across all captured anophelines was estimated at 0.22. Human blood meals were detected in secondary malaria vectors, with notably high HBI values of An. pretoriensis and An. rufipes mosquitoes captured outdoors near goat pens. Out of the 5697 female anophelines tested for sporozoite infectivity, one An. rufipes specimen was positive for P. falciparum.

Conclusion: This study demonstrates that malaria transmission risk in the surveyed areas may extend beyond well-recognized primary vectors. Species that are not well studied, often exophagic and assumed to be zoophagic, were found to have fed on humans and the study showed some preliminary evidence of P. falciparum infectivity. These findings indicate that peri-domestic human activity may sustain residual transmission despite high Insecticidal-Treated Nets and indoor residual spraying coverage.

Background: Almost 500,000 children under 5 years die annually from severe malaria in Africa. Prompt access to effective antimalarial treatment is crucial to reduce mortality. Current clinical guidelines recommend pre-referral rectal artesunate (RAS) followed by injectable artesunate and a 3-day course of artemisinin-based combination therapy (ACT). However, adherence to this treatment algorithm is not always feasible due to many reasons. Integrated community case management (iCCM) presents a promising strategy to improve timely access to care through community health workers (CHWs). This study aims to: (i) assess the feasibility of providing rapid treatment of severe malaria with RAS to children aged 6 months-5 years by CHWs or in health facilities (HFs) without injectable artesunate; (ii) evaluate recrudescence rates in children under 5 following RAS by either ACT for whom referral was not feasible or those after referral completion; and (iii) assess the impact of upgrading iCCM services on access to the formal healthcare system, including severe malaria care.

Methods: This is an effectiveness-implementation hybrid Type 3 study. The study is being conducted in Nchelenge, Zambia and Kapolowe, Democratic Republic of Congo using phased rollout of upgraded iCCM according to national guidelines. CHWs will diagnose, treat and monitor study participants, while research assistants will visit each participant on day 14 to complete a questionnaire, conduct in-depth interviews (IDIs) as well as focus group discussions (FGDs) with caregivers of sampled study participants. Primary outcomes include: (i) time from symptom onset to treatment initiation in the participants who seek care via CHWs or HFs; (ii) 28-day PCR-corrected cure rates following RAS + ACT or RAS + injectable artesunate + ACT treatment; and (iii) the proportion of study population utilizing formal healthcare services within the preceding 6 months, including suspected severe malaria cases.

Discussion: This study will provide essential evidence on the feasibility and effectiveness of community-based pre-referral treatment for severe malaria in resource-limited settings, address access barriers to injectable artesunate and facility-based care, inform policy and programmatic adaptations and guide scalable strategies to enhance timely treatment, reduce mortality and mitigate drug resistance in high-burden malaria regions.

Introduction: Malaria is the leading cause of morbidity and mortality in the Democratic Republic of the Congo (DRC), posing a significant public health challenge, especially among children aged 6-59 months. This study aims to determine the prevalence and factors associated with malaria in this age group.

Methods: The study analyzed secondary data from a weighted sample of 10,013 children aged 6-59 months who underwent a malaria rapid diagnostic test, drawn from the 2023/24 DRC Demographic and Health Survey. Descriptive, bivariate, and multivariable modified Poisson regression analyses were conducted. A factor was considered significant if the p-value was less than 0.05, with a 95% confidence interval (CI).

Results: The overall prevalence of malaria among children aged 6-59 months in the DRC was 33% (95% CI = 30.2, 35.6), varying significantly between provinces, from 5% in Kinshasa to 61% in Bas-Uele province. Factors associated with malaria in this age group included children aged 24-59 months (APR = 1.25, 95% CI = 1.15, 1.36), children of mothers with no education (APR = 1.15, 95% CI = 1.03, 1.29) and those with primary education (APR = 1.13, 95% CI = 1.02, 1.30), children from the poor wealth quintile (APR = 1.52, 95% CI = 1.08, 2.13) and the middle wealth quintile (APR = 1.42, 95% CI = 1.03, 1.95), children who never slept under an insecticide-treated net (ITN) (APR = 1.18, 95% CI = 1.06, 1.30), children from households without a television (APR = 1.73, 95% CI = 1.22, 2.45), and those living in houses with unimproved floor material (APR = 1.54, 95% CI = 1.10, 2.08) or unimproved roof material (APR = 1.27, 95% CI = 1.04, 1.54).

Conclusion: The prevalence of malaria remains high among children aged 6-59 months. The study highlights the need for strategies that include scaling up the distribution of insecticide-treated nets (ITNs) and educating caregivers on their proper use, improving access to timely diagnosis and treatment, and integrating multisectoral approaches that address socioeconomic vulnerabilities.

Background: Identity-by-descent (IBD), which describes recent genetic co-ancestry between pairs of genomes, is a fundamental concept in population genomics. It has been used to estimate genetic relatedness, detect selection signals, and understand population demography. The IBD detection method hmmIBD demonstrates high accuracy in inferring IBD segments between haploid genomes, including Plasmodium falciparum, and is widely used in malaria genomic surveillance. However, the current single-threaded implementation of hmmIBD does not utilize the full capacity of multi-processor computers, making it difficult to apply to large data sets, and does not accommodate non-uniform recombination rates across the genome.

Methods: We developed an enhanced implementation of hmmIBD, named hmmibd-rs, which leverages multi-threaded computing to parallelize IBD inference over genome pairs and which supports optional, user-defined recombination rate maps for more accurate IBD detection and filtration from genomes with non-uniform recombination. We further streamlined large-scale IBD detection by incorporating auxiliary built-in functionalities to preprocess input directly from the standard binary variant call format (BCF) and filter IBD output to reduce disk usage.

Results: Our new implementation significantly reduces IBD detection computation time nearly linearly with the increased number of CPU threads used; using 128 threads shortens IBD detection time from 5.2 days to 1.3 h for 220 million pairs of simulated Plasmodium falciparum-like chromosomes, increasing computational speed by approximately 100 × over the single-threaded hmmIBD algorithm. Incorporating non-uniform recombination rates in hmmibd-rs enhances the accuracy of IBD inference by mitigating the overestimation of IBD breakpoints in recombination cold spots and their underestimation in hot spots. Non-uniform rates also improve length filtration of IBD segments, dramatically reducing the rate of false positive in recombination cold spots. When applied to empirical data sets, hmmibd-rs completes the detection of IBD from MalariaGEN Pf7 (n ≈ 10,000 monoclonal samples) within hours, enabling a single-day IBD analysis pipeline for large genomic data sets.

Conclusion: hmmibd-rs builds upon, accelerates, and enhances hmmIBD for efficient and accurate IBD detection, serving as a crucial tool for advancing large-scale malaria genomic surveillance.

Background: Malaria remains a major global public health concern with the greatest burden in tropical and subtropical regions, particularly sub-Saharan Africa. Uganda ranks among the world's highest burden countries, with its warm temperatures, abundant rainfall and diverse mosquito breeding habitats sustaining year-round malaria transmission in malaria endemic areas. This study assessed malaria incidence trends and their association with climate variables in Yumbe district, Uganda.

Methods: A retrospective ecological time-series study analysed malaria incidence (2017-2021) in Yumbe district, Uganda, using District Health Information System reports and Uganda National Meteorological Authority climate data (daily temperature and rainfall). Data were cleaned in Excel and analysed in R software V4.5.1. Monthly/annual summaries, seasonal pattern graphs, Kendall's tau correlations for non-linear associations, and Multiple Linear and Poisson regressions with lag effects were done. Time series analysis involved seasonal decomposition, cross-correlation, and ARIMAX modelling. A multivariable OLS regression on log(1 + cases) with best-lagged rainfall and minimum temperature further assessed climate influence.

Results: Between 2017 and 2021, a total of 2,066,711 malaria cases were reported in Yumbe district. Malaria trends closely followed rainfall patterns, peaking during the period of high precipitation. Time-series analysis showed that rainfall was positively associated with malaria incidence at one-month lag (β = 0.38, p < 0.05), while minimum temperature was inversely associated (β = - 0.29, p < 0.05). Statistical analysis revealed rainfall (mm) strongly led malaria cases by 1 month (r = 0.759, p < 0.001). Maximum temperature showed no significant effect on malaria incidence.

Conclusion: Malaria incidence in Yumbe district is strongly influenced by rainfall and minimum temperature. This study highlights the role of climate variability in malaria transmission in malaria endemic areas. Integrating climate data into surveillance and early warning systems could enhance timely interventions in malaria endemic areas like Yumbe district.

Background: Compliance with evidence-based treatment guidelines, supported by quality-assured parasitological diagnosis, is the mainstay of malaria case-management in Nigeria. However, despite increased attention, the quality of inpatient paediatric and adult, test-and-treat malaria case-management, and routine accuracy of malaria microscopy, has rarely been examined in public and private hospitals.

Methods: A cross-sectional assessment was undertaken at 18 public and private hospitals in September 2024 in Kano State, Nigeria. Data collection included hospital assessments, interviews with inpatient health workers, review of all paediatric and medical ward admission files for August 2024, and re-checking of routine malaria slides archived during the 3-month post-assessment period. Descriptive analyses included 18 hospitals, 72 health workers, 2,814 suspected malaria admissions, and 211 malaria slides.

Results: Nearly all hospitals (94.4%) provided parasitological diagnostic services (microscopy or RDT) and stocked recommended antimalarials (injectable artesunate and ACT). Most health workers had received training on severe malaria (73.6%), but only 16.7% received supportive supervision. The composite test-and-treat performance was 39.3%, higher for children than adults (45.7% vs 26.5%) and in public compared to private hospitals (39.8% vs 30.8%). Among suspected malaria patients, 73.7% were tested on admissions and 90.2% of those with severe malaria were treated with artesunate. Children, compared to adults, were more commonly tested (79.8% vs 61.7%) and treated with artesunate (93.5% vs 80.1%). Patients in private hospitals, compared to public, were more often tested (84.3% vs 73.0%) but less frequently treated with artesunate (73.1% vs 91.2%). Only 30.0% of artesunate-treated patients were prescribed ACT-more commonly among adults than children (48.3% vs 23.0%) and in private than in public hospitals (89.2% vs 26.9%). ACT use for admitted non-severe cases was rare (2.4%), whereas non-compliance with test negative results was high (75.8%). The sensitivity, specificity, positive and negative predictive values of routine microscopy compared to expert readings were 93.2%, 42.5%, 29.9% and 95.9%, respectively.

Conclusions: Inpatient compliance with malaria test-and-treat guidelines varied between performance tasks, age groups, and hospital sectors. Clinicians can be confident in negative slides but should be cautious with positive results. Quality assurance of malaria diagnosis and continuous clinical and laboratory quality improvement interventions, with enhanced linkages, are needed.