Assessing environmental impacts on health in the Pacific Basin is challenged by significantly varying data types -quantities, qualities, and paucities -because of varying geographic sizes, environments, biodiversity, ecological assets, and human population densities, with highly varied and unequal socio-economic development and capacity to respond to environmental and health challenges. We discuss three case-based methodological examples from Pacific Basin environmental health impact assessments. These methods could be used to improve environmental health evidence at all country and regional levels across a spectrum of big data availability to no data. These methods are, 1) a risk assessment of airborne particulate matter in Korea based on the chemical composition of these particulates; 2) the use of system dynamics to appraise the influences of a range of environmental health determinants on child health outcomes in remote Solomon Islands; and 3) precision environmental public health methodologies based on comprehensive data collection, analyses, and modelling (including Bayesian belief networks and spatial epidemiology) increasing precision for good environmental health decision making to prevent and control a zoonotic disease in Fiji Islands. We show that while a common theme across the three examples is the value of high quality and quantity data to support stronger policy decisions and appropriate prioritizing of investment, it is also clear that for many countries in the Pacific Basin, sufficient data will remain a challenge to inform decision makers about environmental impact on health.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.