A methodological framework for ranking communicable and non-communicable diseases due to climate change-A focus on Ireland

被引:4
|
作者
Nag, Rajat [1 ]
机构
[1] Univ Coll Dublin, Sch Biosyst & Food Engn, Dublin 4, Ireland
关键词
Risk assessment; Ranking hazards; DALY; Communicable diseases; Non-communicable diseases; Climate change;
D O I
10.1016/j.scitotenv.2023.163296
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
There is currently a significant global focus from the public health community on addressing climate-related public health issues. Globally we are witnessing geological shifts, extreme weather events, and the associated incidents that may have a significant human health impact. These include unseasonable weather, heavy rainfall, global sea -level rise and flooding, droughts, tornados, hurricanes, and wildfires. Climate change can have a direct and indirect health impact. The global challenge of climate change requires global preparedness for potential human health effects due to climate change, including vigilance for diseases carried by vectors, foodborne and waterborne diseases, deteri-orated air quality, heat stress, mental health, and potential disasters. Therefore, it is essential to identify and prioritise the consequences of climate change to become future-ready. This proposed methodological framework aimed to de-velop an innovative modelling method using the 'Disability-Adjusted Life Year (DALY)', to rank potential direct and indirect human health impacts (communicable and non-communicable diseases) of climate change. This approach aims to ensure food safety, including water, in the wake of climate change. The novelty of the research will come from developing models with spatial mapping (Geographic Information System or GIS), which will also consider the influence of climatic variables, geographical differences in exposure and vulnerability and regulatory control on feed/food quality and abundance, range, growth, and survival of selected microorganisms. In addition, the outcome will identify and assess emerging modelling techniques and computational-efficient tools to overcome current limita-tions in climate change research on human health and food safety and to understand uncertainty propagation using the Monte Carlo simulation method for future climate change scenarios. It is envisaged that this research work will con-tribute significantly to developing a lasting network and critical mass on a national scale. It will also provide a template to implement from a core centre of excellence in other jurisdictions.
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页数:6
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