ABSTRACT. Plasmodium malariae ( P. malariae ) and Plasmodium ovale ( P. ovale ) spp. are underappreciated contributors to residual malaria transmission, especially in near-elimination settings. They remain absent from routine surveillance in Bangladesh, where field diagnosis relies on Plasmodium falciparum ( P. falciparum )/ Plasmodium vivax ( P. vivax )-specific rapid diagnostic tests (RDTs) and microscopy. Cases escaping detection by ongoing malaria surveillance in Bandarban, Bangladesh, were investigated in the present study. Blood samples collected in 2025 from febrile patients that tested negative for P. falciparum/P. vivax via RDT underwent microscopic examination and molecular testing. Genomic DNA was screened using a SYBR-Green-based real-time quantitative polymerase chain reaction (qPCR) test targeting the 18S ribosomal RNA (rRNA) gene. Plasmodium ovale- positive cases were confirmed via a probe-based qPCR assay, with P. ovale curtisi and P. ovale wallikeri identified using a validated assay targeting small subunit rRNA and Po-ldh genes. Archived laboratory records (2014–2024) were reviewed to identify previously detected P. malariae infections. In 2025, five P. ovale spp. (four P. ovale curtisi and one P. ovale wallikeri) and three P. malariae cases were detected in Alikadam Subdistrict, Bandarban. All cases were RDT-negative despite microscopically detectable parasitemia (mean 4,536 parasites/ µ L for P. ovale and 6,053 parasites/ µ L for P. malariae ). Field microscopy was used to correctly diagnose only one P. ovale case, with the remaining four being misclassified as P. vivax or mixed P. malariae / P. vivax infections. Analysis of archived data revealed 25 additional qPCR-confirmed P. malariae infections. Cases were detected across multiple ethnic communities, predominantly among adult males in forest-adjacent settlements. Integrating pan-species molecular diagnostics into routine surveillance, along with species-specific case reporting, is essential to effectively detect, monitor, and eliminate these underappreciated malaria species.
ABSTRACT. There has been significant progress toward eliminating human African trypanosomiasis (HAT), and Nigeria has not recorded a confirmed case in more than a decade. However, there is concern that this reflects underreporting rather than true elimination. Accurate tracking of the HAT burden in Nigeria remains limited because of weak surveillance systems, gaps in diagnostic capacity, and a lack of knowledge among healthcare workers and surrounding communities. This perspective article examines the urgent need to strengthen active surveillance, improve diagnostic testing and confirmation capacity, and address barriers to care in Nigeria and other West African countries. The importance of visibility and data sharing is also emphasized, drawing attention to local research, and the consequences of missed diagnoses. To support the WHO 2030 elimination goal, this article call for coordinated investments in laboratory infrastructure, healthcare training, public education, and sustainable surveillance systems.
ABSTRACT. Dengue continues to expand globally, increasing pressure on health systems across tropical and subtropical regions. Despite advances in surveillance, data availability, and predictive modeling, early warning often remains insufficiently linked to timely public health action. The challenge, therefore, is not prediction alone but translating heterogeneous surveillance information into actionable intelligence. Key determinants, including climate, human mobility, adult female mosquito abundance, vector infection, asymptomatic infection, and population immunity, vary in feasibility, spatial and temporal resolution, and early-warning value. Climate indicators provide important context but may lack local specificity, and symptomatic case surveillance is constrained by underascertainment and reporting delays. Human mobility can improve spatial risk assessment and, in selected settings, forecasting, whereas adult mosquito surveillance provides complementary information on local vector abundance. The authors of the present study propose an Operationally Prioritized Early Warning (OPEW) framework that integrates sentinel surveillance, scale-aware interpretation of complementary signals, feasibility-based prioritization, event-triggered intensification, and explicit links between surveillance thresholds and predefined actions. The OPEW framework is not a validated prediction model but a testable operational framework that prioritizes information according to epidemiological relevance, timeliness, feasibility, and decision value. Prospective evaluation should assess predictive performance, actionable lead time, resource requirements, and public health outcomes against existing approaches.
