Perspectives and lessons from the Philippines’ decades-long battle with dengue

Ong, Erika P; Obeles, Arianne Justine T; Ong, Bradley Ashley G; Tantengco, Ourlad Alzeus G.

doi:10.1016/j.lanwpc.2022.100505

Cited by 10 publications

(12 citation statements)

References 2 publications

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“…In the last decade, dengue has been an increasing trend in the country, especially since 2015, and recorded the highest-ever case burden of 437,563 cases in 2019 [ 2 ]. The lack of stakeholder empowerment, difficulty in eradicating local breeding habitats, and less efficient solid waste management have been identified as several contributory factors to the recent surge in cases [ 39 ], undermining efforts of the National Dengue Prevention and Control Program established in 1993 [ 40 ]. Despite its historical presence and growing public health importance, the number of scientific publications on dengue in the Philippines has been strikingly low [ 21 ] since dengue became a notifiable disease in the country in 1958 [ 40 ].…”

Section: Discussionmentioning

confidence: 99%

Genetic Diversity and Dispersal of DENGUE Virus among Three Main Island Groups of the Philippines during 2015–2017

Koo

Privaldos

et al. 2023

Viruses

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Dengue has been one of the major public health concerns in the Philippines for more than a century. The annual dengue case burden has been increasing in recent years, exceeding 200,000 in 2015 and 2019. However, there is limited information on the molecular epidemiology of dengue in the Philippines. We, therefore, conducted a study to understand the genetic composition and dispersal of DENV in the Philippines from 2015 to 2017 under UNITEDengue. Our analyses included 377 envelope (E) gene sequences of all 4 serotypes obtained from infections in 3 main island groups (Luzon, Visayas, and Mindanao) of the Philippines. The findings showed that the overall diversity of DENV was generally low. DENV-1 was relatively more diverse than the other serotypes. Virus dispersal was evident among the three main island groups, but each island group demonstrated a distinct genotype composition. These observations suggested that the intensity of virus dispersal was not substantive enough to maintain a uniform heterogeneity among island groups so that each island group behaved as an independent epidemiological unit. The analyses suggested Luzon as one of the major sources of DENV emergence and CAR, Calabarzon, and CARAGA as important hubs of virus dispersal in the Philippines. Our findings highlight the importance of virus surveillance and molecular epidemiological analyses to gain deep insights into virus diversity, lineage dominance, and dispersal patterns that could assist in understanding the epidemiology and transmission risk of dengue in endemic regions.

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Section: Discussionmentioning

confidence: 99%

Genetic Diversity and Dispersal of DENGUE Virus among Three Main Island Groups of the Philippines during 2015–2017

Koo

Privaldos

et al. 2023

Viruses

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“… Dialogue between health systems and experts that led national authorities to invest in R&D for dengue technologies in the Philippines [ 90 ]; Forging of connections between medical authorities and regional scientific resources to propel a molecular biology-driven cancer research agenda in Brazil, establishing its technical and political feasibility through claims of scientific impact allied with its public health relevance [ 91 ]; Management of knowledge about Ebola through local medical and scientific collaborations in Guinea, Mali, Ghana, and Kenya [ 92 ]; Negotiations within an international consortium of experts on responsible innovation for Zika Virus [ 93 ]. Collaboration between health systems and scientists in China and Brazil to establish platforms for genomic data for use in precision medicine [ 94 ].…”

Section: Autonomous Experimentation In Emerging Economiesmentioning

confidence: 99%

The advancement of artificial intelligence in biomedical research and health innovation: challenges and opportunities in emerging economies

da Silva

2024

Global Health

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The advancement of artificial intelligence (AI), algorithm optimization and high-throughput experiments has enabled scientists to accelerate the discovery of new chemicals and materials with unprecedented efficiency, resilience and precision. Over the recent years, the so-called autonomous experimentation (AE) systems are featured as key AI innovation to enhance and accelerate research and development (R&D). Also known as self-driving laboratories or materials acceleration platforms, AE systems are digital platforms capable of running a large number of experiments autonomously. Those systems are rapidly impacting biomedical research and clinical innovation, in areas such as drug discovery, nanomedicine, precision oncology, and others. As it is expected that AE will impact healthcare innovation from local to global levels, its implications for science and technology in emerging economies should be examined. By examining the increasing relevance of AE in contemporary R&D activities, this article aims to explore the advancement of artificial intelligence in biomedical research and health innovation, highlighting its implications, challenges and opportunities in emerging economies. AE presents an opportunity for stakeholders from emerging economies to co-produce the global knowledge landscape of AI in health. However, asymmetries in R&D capabilities should be acknowledged since emerging economies suffers from inadequacies and discontinuities in resources and funding. The establishment of decentralized AE infrastructures could support stakeholders to overcome local restrictions and opens venues for more culturally diverse, equitable, and trustworthy development of AI in health-related R&D through meaningful partnerships and engagement. Collaborations with innovators from emerging economies could facilitate anticipation of fiscal pressures in science and technology policies, obsolescence of knowledge infrastructures, ethical and regulatory policy lag, and other issues present in the Global South. Also, improving cultural and geographical representativeness of AE contributes to foster the diffusion and acceptance of AI in health-related R&D worldwide. Institutional preparedness is critical and could enable stakeholders to navigate opportunities of AI in biomedical research and health innovation in the coming years.

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“…In particular, Nepal should proactively implement Aedes mosquito vector control measures, such as encouraging the use of antilarval and anti-adult sprays, publishing personal protection guidelines, and effecting legislative control in line with its national guidelines (14). Nepal should also learn lessons, both positive and negative, from other countries that have been engaged in decade-long battles with dengue (12,15). For example, the Philippines government adopted environmental control measures, intensified chemical fogging, and reminded its citizens to follow the "4 o'clock habit" (i.e., emptying water containers, which are potential breeding sites for Aedes mosquitos, on a daily basis).…”

Section: Early Warning and Reporting Of Dengue Outbreaksmentioning

confidence: 99%

A major dengue epidemic in 2022 in Nepal: need of an efficient early-warning system

et al. 2023

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Dengue has become a recurrent and growing threat to public health in Nepal. The epidemic in 2022 was the largest ever reported, with cases being reported in all of the country’s seven provinces and 77 districts. Despite the establishment of an early-warning and reporting system (EWARS) in 1997, the lack of clear criteria for alarm signals and outbreak definitions in national guidelines delayed the epidemic declaration in 2022, which resulted in an increased number of cases and fatalities. For this article, we analyzed national data from previous years, which demonstrate that an epidemic could have been declared early in July, and that that would have resulted in fewer cases and fatalities if clear criteria for outbreak declarations had also been put in place. We also reviewed the existing national guidelines for dengue prevention and control, and propose recommendations to improve their implementation, particularly with regard to vector control measures. This article also highlights the need for a coordinated effort between multisector stakeholders, strengthened disease surveillance systems, and the establishment of predefined alarm signals and epidemic declaration criteria so that future epidemics are identified in a timely manner. The early outbreak warning system can potentially prevent future large outbreaks and minimize their negative impacts on the country’s health systems and economy.

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Perspectives and lessons from the Philippines’ decades-long battle with dengue

Cited by 10 publications

References 2 publications

Genetic Diversity and Dispersal of DENGUE Virus among Three Main Island Groups of the Philippines during 2015–2017

Genetic Diversity and Dispersal of DENGUE Virus among Three Main Island Groups of the Philippines during 2015–2017

The advancement of artificial intelligence in biomedical research and health innovation: challenges and opportunities in emerging economies

A major dengue epidemic in 2022 in Nepal: need of an efficient early-warning system

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