Citizen Science for Enhanced Dengue Vector Surveillance in Solomon Islands: A Methods Paper

Adam Craig, Nixon Panda, Rudgard Palapu, Geoffrey Oku, Clement Lifoia, Joanna Tatalu,Nigel Beebe, Gerard Kelly, Nathan Kama Jr, Charlie Iro’ofa,Hugo Bugoro

Citizen Science: Theory and Practice(2024)

引用 0|浏览0
暂无评分
摘要
Arthropod-borne arboviral diseases—including dengue, Zika, and chikungunya—place a substantial burden on the health of populations, globally. Dengue alone is endemic in more than 100 countries and causes more than 96 million symptomatic cases and approximately 40,000 deaths annually. The recent surge in arboviral disease outbreaks, coupled with the World Health Organization’s newly published vector control guidelines, accentuates the imperative to understand the dispersion of disease-carrying mosquitoes across diverse spatial and temporal scales. However, traditional surveillance mechanisms often fall short because of workforce limitations, logistical complexities, jurisdictional boundaries, and budgetary constraints, especially in low- and low-middle-income countries. In this article, we systematically report the design, implementation, and iterative enhancement of a groundbreaking school-based citizen science initiative for augmenting mosquito surveillance in the Solomon Islands. Key reflections encompass the initiative’s role in supporting routine government-led disease vector monitoring, sustainability through integration and fostering participant engagement, and the amalgamation of citizen-collected data with government surveillance activities. The article also discusses the impact of the citizen science initiative with regard to the Solomon Islands’ pursuit of the Sustainable Development Goals. Our findings underscore the potential of citizen science methods to support and extend public health surveillance activities and to serve as a community-engagement-for-behaviour-change tool in resource-constrained contexts.
更多
查看译文
关键词
citizen science,dengue,aedes,arboviral diseases,infectious diseases,surveillance,entomology
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要