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Advancing whose interests? Corporate strategy and risks to food systems transformation and public health nutrition through academic partnerships in Africa.
Get PDFInnovative laboratory techniques shaping cancer diagnosis and treatment in developing countries.
Get PDFCancer is a major global health challenge, with approximately 19.3 million new cases and 10 million deaths estimated by 2020. Laboratory advancements in cancer detection have transformed diagnostic capabilities, particularly through the use of biomarkers that play crucial roles in risk assessment, therapy selection, and disease monitoring. Tumor histology, single-cell technology, flow cytometry, molecular imaging, liquid biopsy, immunoassays, and molecular diagnostics have emerged as pivotal tools for cancer detection. The integration of artificial intelligence, particularly deep learning and convolutional neural networks, has enhanced the diagnostic accuracy and data analysis capabilities. However, developing countries face significant challenges including financial constraints, inadequate healthcare infrastructure, and limited access to advanced diagnostic technologies. The impact of COVID-19 has further complicated cancer management in resource-limited settings. Future research should focus on precision medicine and early cancer diagnosis through sophisticated laboratory techniques to improve prognosis and health outcomes. This review examines the evolving landscape of cancer detection, focusing on laboratory research breakthroughs and limitations in developing countries, while providing recommendations for advancing tumor diagnostics in resource-constrained environments
Meta-analysis on the entomological effects of differentially treated ITNs in a multi-site experimental hut study in sub-Saharan Africa.
Get PDFBACKGROUND: Restricting the placement of active ingredients (AIs) to specific panels on insecticide-treated nets (ITNs) has the potential to reduce the amount of AI required to treat a net. If the restricted placement of the AIs can exploit mosquito behaviour, particularly where they interact with the bed net interface, and not impact the net's effectiveness, then the reduction in AI could result in cost reductions. METHODS: Nine individual experimental hut trials were conducted to compare the efficacy of three different partially-treated net relative to fully treated nets; roof-only treated nets, side-only treated nets, and nets with treated roof and pyrethroid-only side panels. These trials were conducted on a range of net products with different AIs, across a range of geographies in Africa (East and West), vector species (Anopheles gambiae, Anopheles coluzzii, Anopheles arabiensis, and Anopheles funestus), hut designs (East and West African style) and hosts (cows and humans). The combined data from these trials were analysed in a meta-analysis, and odds ratios for the effect of the different net designs on mortality and blood-feeding were estimated using mixed effects logistic regression. RESULTS: The results of this meta-analysis demonstrated that fully treated nets provide greater mosquito killing and reduction in blood-feeding effects than any configuration of insecticide treatment restricted to specific panels. CONCLUSIONS: This meta-analysis showed that partially-treated net that restrict the insecticide treatment to specific panels of an ITN do not give equivalency or superiority in either mortality or blood-feeding inhibition to fully treated nets. The implications of these findings are discussed
Measuring ENAP interventions for small and/or sick newborns in routine health information systems: indicators and considerations from a WHO expert consultation.
Get PDFBACKGROUND: Current trends indicate 63 low- and middle-income countries (LMICs) are not on track to achieve the 2030 Sustainable Development Goal 3.2 target of a neonatal mortality rate ≤12 per 1000 live births. The Every Newborn Action Plan (ENAP) prioritised four life-saving interventions for small and/or sick newborns (SSN) in health facilities: neonatal resuscitation, kangaroo mother care, antibiotic treatment of possible serious bacterial infections, and antenatal corticosteroids for women at risk of preterm birth at <34 weeks of gestation. Limited indicator reporting on the use of these interventions in routine health information systems (RHIS) is a barrier to scaling up SSN care. METHODS: The World Health Organization (WHO) led a multi-step process to agree coverage indicators for the four SSN interventions, which included a rapid review of existing research and programme reports; expert consultation to review available evidence, deliberate and propose coverage indicators, assess feasibility in RHIS, and identify research gaps. RESULTS: Expert working groups discussed and recommended definitions for each of the four coverage indicators. After considering feasibility and challenges, potential sources of data for each indicator were appraised. Data for these indicators is not always routinely collected in registers, requiring information from clinical case records, which can be challenging in resource-constrained health systems. The proposed indicators were also assessed against established indicator assessment criteria. The need for testing the indicators was emphasised and other research gaps were also identified. CONCLUSIONS: Reporting and monitoring the life-saving SSN interventions in routine health information systems (RHIS) is crucial for improving newborn care in LMICs. Urgent consideration must be given to how this data can be collected from health facilities and subsequently reported in RHIS. Improved RHIS measures for these interventions will enable programme managers and policy makers to scale up their use, accelerating reductions in preventable neonatal morbidity and mortality
Statins do not reduce the parasite burden during experimental Trypanosoma cruzi infection.
Get PDFCardiomyopathy is the most common pathology associated with Trypanosoma cruzi infection. Reports that statins have both cardioprotective and trypanocidal activity have generated interest in their potential as a therapeutic treatment. Using a highly sensitive bioluminescent mouse model, we show that a 5-day treatment with statins has no significant impact on parasite load. The free systemic concentrations fail to reach the level required for potency. Hence, clinical trials to investigate the trypanocidal activity of statins lack experimental justification
Co-developing a comprehensive disease policy model with stakeholders: The case of malaria during pregnancy.
Get PDFUnderstanding the holistic impact of malaria during pregnancy is essential for improving maternal and child outcomes in malaria endemic settings. To be able to design appropriate research and conduct robust policy analyses, a comprehensive model of the underlying disease, representing the current understanding of mechanisms and consequences, is needed. This study aimed to illustrate a methodology to co-develop a disease policy model with expert stakeholders using malaria during pregnancy as a case study. An initial steering group was convened to develop a first model of malaria during pregnancy and its consequences for mother and child based on their understanding of the literature. Subsequently, this model was refined using a Delphi process to gain consensus amongst twelve experts working in the field of malaria during pregnancy, representing the disciplines of health economics, mathematical modelling, epidemiology and clinical medicine. The experts reviewed drafts of the conceptual model and provided feedback in two rounds of semi-structured questionnaires with the aim of identifying the most important health outcomes and relationships in both mother and child as well as the most relevant stratifiers for the model. Final consensus on any areas of disagreement was reached after two online meetings. The final model is a comprehensive disease policy model of malaria during pregnancy, including ten maternal and ten child health outcomes with four stratifiers. The model developed in this study should be of value to malaria researchers, funders, evaluators and decision makers, though some adaptation will be required for each specific context and purpose. In addition, the methodology and process followed in this study is replicable and can guide researchers aiming to develop a conceptual model for other conditions. The model resulting from this study highlights the complexity required to depict fully the consequences of malaria during pregnancy for both the mother and the child. It also demonstrates how to conduct a rigorous process to develop a disease policy model. In addition, the study has helped to identify a number of areas with scarce data and need for further research
Quick buys for prevention and control of noncommunicable diseases.
Get PDFDespite their established effectiveness, uptake of the WHO best buys for tackling non-communicable diseases (NCDs) has been uneven and disappointing. Here we introduce the "quick buys", an evidence-based set of cost-effective interventions with measurable public health impacts within five years. We reviewed 49 interventions previously established as cost-effective (<$I20,000 per disability-adjusted life-year averted) to identify the earliest possible detectable effect on high-level population health targets. Using a strict evidence hierarchy, including Cochrane and systematic reviews, we estimated the effects of each intervention against global targets agreed upon by countries. Quick buys were defined as those interventions that could exhibit measurable effects within 5 years, aligning with average electoral cycles in across the WHO European Region. Of the 49 interventions, 25 qualified as quick buys, including those relating to tobacco (n = 5), alcohol (n = 4), unhealthy diet (n = 3), physical inactivity (n = 1), cardiovascular disease (n = 3), diabetes (n = 4), chronic respiratory disease (n = 1), and cancer (n = 4). These findings not only offer guidance to policymakers deciding on interventions that align with short-term political cycles but also have the potential to accelerate progress to global health targets, particularly the 2030 Sustainable Development Goal of reducing premature NCD mortality by one-third
Digital health technologies in Kurdistan region of Iraq: a narrative review of enhancing healthcare accessibility and quality
Get PDFDigital health refers to the use of information and communication technologies to increase healthcare’s efficiency and accessibility. Healthcare systems are increasingly recognizing the need to integrate modern technologies to optimize patient outcomes. However, promising innovations and integration into national strategies face challenges, especially in low- and middle-income regions, including Kurdistan. This review describes several digital health technologies in Kurdistan, including software implementation for data management, such as District Health Information Software 2, the establishment of telemedicine services, and the utilization of machine learning algorithms for mortality prediction, particularly during the COVID-19 pandemic. Despite the numerous advantages of digital health technologies, several challenges remain in their widespread adoption, such as the lack of a comprehensive regulatory and legal framework for the free adoption and use of digital technologies, technical challenges, and issues with patient satisfaction. Our key recommendations are the development of a robust digital health infrastructure to integrate digital health innovations, enhancement of healthcare professionals’ digital literacy through targeted training programs, and implementation of telemedicine services in remote and rural areas. In conclusion, digital health technologies, including machine learning, telemedicine, and electronic health records, have assisted healthcare accessibility and quality in Kurdistan, particularly in underserved areas, by providing immediate access to patient data and facilitating decision-making through clinical decision support tools, remote consultations, and cost-efficient healthcare services
A New Biomarker of Aging Derived From Electrocardiograms Improves Risk Prediction of Incident Cardiovascular Disease.
Get PDFBACKGROUND: A biomarker of cardiovascular aging, derived from a deep learning algorithm applied to digitized 12-lead electrocardiograms, has recently been introduced. This biomarker, δ-age, is defined as the difference between predicted electrocardiogram age and chronological age. OBJECTIVES: The purpose of this study was to assess the potential value of δ-age in enhancing the performance of primary prevention models for cardiovascular disease that incorporate traditional cardiovascular risk factors. METHODS: In this cohort study, we included 7,108 men and women from the Norwegian Tromsø Study in 2015 to 16, with follow-up through 2021 for incident fatal and nonfatal myocardial infarction (MI) and hemorrhagic or cerebral stroke. We used Cox proportional hazards regression models, Harrell's concordance statistic (C-index), and the net reclassification improvement. RESULTS: During a median follow-up of 5.9 years, we observed 155 cases of MI and 141 strokes. In men and women combined,HR per SD increment in δ-age, after adjustment for traditional risk factors included in the Norwegian risk model for acute cerebral stroke and myocardial infarction (NORRISK 2) score, was 1.24 (95% CI: 1.09-1.41) for the combined outcome, with similar HRs for MI and stroke. In men, the HR was significant for MI and in women for stroke. The C-index increased significantly but modestly when δ-age was added to a model with traditional risk factors. The net reclassification improvement was 26.0% (95% CI: 13.3%-38.1%) for the combined outcome, 17.5% (95% CI: 0.6%-33.5%) for MI, and 37.2% (95% CI: 20.1%-53.0%) for stroke. CONCLUSIONS: Incorporating δ-age into primary prevention risk prediction models significantly improved performance beyond traditional cardiovascular risk factors for the combined outcome and separately for MI and stroke
Crowdsourcing strategies to improve access to HIV pre-exposure prophylaxis in Australia, the Philippines, Thailand and China.
Get PDFBACKGROUND: Many Asian countries have yet to scale up HIV pre-exposure prophylaxis (PrEP). Crowdsourcing has a group of individuals solving a specific problem before sharing solutions with the public. This approach enhances community engagement and ownership of the solutions and can be used to generate culturally relevant solutions. We used crowdsourcing to seek innovative strategies to optimise PrEP access by increasing the uptake and effective use of PrEP. This study describes the experiences of crowdsourcing open calls in Australia, the Philippines, Thailand and China. METHODS: Four crowdsourcing open calls were conducted between 2021-2023 in Australia, the Philippines, Thailand and China. All open calls entailed: 1) problem identification; 2) committee formation with local groups; 3) community engagement for idea submission (e.g., texts, posters, pitches); 4) evaluation of submissions; 5) awarding incentives to finalists; and 6) solution dissemination via web and social media. We reported the number of total and high-quality submissions. We also identified themes across countries. RESULTS: The Australian, Filipino, Thai and Chinese teams received 9, 22, 9 and 19 eligible submissions, respectively. A total of 3, 10, 7 and 8 submissions had a mean score of 6/10 or greater. Three common solutions emerged across all the finalist ideas: enhanced service access, optimising promotional campaigns, and person-centred promotional materials. The winning ideas from the Australian, Filipino, Thai and Chinese teams were an anonymous online PrEP service, a printed ready-to-wear garment to create awareness about PrEP, PrEP and HIV self-testing kit dispensing kiosks and a poster on PrEP effectiveness, respectively. CONCLUSIONS: Crowdsourcing was a promising and versatile tool for developing PrEP strategies in the Asia-Pacific region. Further evaluations via clinical trials can bridge the gap between idea generation and implementation, creating the empirical evidence that is pivotal for the policy adoption of these innovations