• Energy Research

Amblyomma americanum (the lone star tick) is a pathogen vector, mainly from eastern North America, that bites humans. With global integration and climate change, some ticks that are currently confined to a certain place may begin to spread out; some reports have shown that they are undergoing rapid range expansion. The difference in the potential geographic distribution of A. americanum under current and future climatic conditions is dependent on environment variables such as temperature and precipitation, which can affect their survival. In this study, we used a maximum entropy (MaxEnt) model to predict the potential geographic distribution of A. americanum. The MaxEnt model was calibrated at the native range of A. americanum using occurrence data and the current climatic conditions. Seven WorldClim climatic variables were selected by the jackknife method and tested in MaxEnt using different combinations of model feature class functions and regularization multiplier values. The best model was chosen based on the omission rate and the lowest Akaike information criterion. The resulting model was then projected onto the global scale using the current and future climate conditions modeled under four greenhouse gas emission scenarios.

BACKGROUND: Modeling suggests that climate change mitigation actions can have substantial human health benefits that accrue quickly and locally. Documenting the benefits can help drive more ambitious and health-protective climate change mitigation actions; however, documenting the adverse health effects can help to avoid them. Estimating the health effects of mitigation (HEM) actions can help policy makers prioritize investments based not only on mitigation potential but also on expected health benefits. To date, however, the wide range of incompatible approaches taken to developing and reporting HEM estimates has limited their comparability and usefulness to policymakers. OBJECTIVE: The objective of this effort was to generate guidance for modeling studies on scoping, estimating, and reporting population health effects from climate change mitigation actions. METHODS: An expert panel of HEM researchers was recruited to participate in developing guidance for conducting HEM studies. The primary literature and a synthesis of HEM studies were provided to the panel. Panel members then participated in a modified Delphi exercise to identify areas of consensus regarding HEM estimation. Finally, the panel met to review and discuss consensus findings, resolve remaining differences, and generate guidance regarding conducting HEM studies. RESULTS: The panel generated a checklist of recommendations regarding stakeholder engagement: HEM modeling, including model structure, scope and scale, demographics, time horizons, counterfactuals, health response functions, and metrics; parameterization and reporting; approaches to uncertainty and sensitivity analysis; accounting for policy uptake; and discounting. DISCUSSION: This checklist provides guidance for conducting and reporting HEM estimates to make them more comparable and useful for policymakers. Harmonization of HEM estimates has the potential to lead to advances in and improved synthesis of policy-relevant research that can inform evidence-based decision making and practice. https://doi.org/10.1289/EHP6745.

Ixodes scapularis is a vector of tick-borne diseases. Climate change is frequently invoked as an important cause of geographic expansions of tick-borne diseases. Environmental variables such as temperature and precipitation have an important impact on the geographical distribution of disease vectors. We used the maximum entropy model to project the potential geographic distribution and future trends of I. scapularis. The main climatic variables affecting the distribution of potential suitable areas were screened by the jackknife method. Arc Map 10.5 was used to visualize the projection results to better present the distribution of potential suitable areas. Under climate change scenarios, the potential suitable area of I. scapularis is dynamically changing. The largest suitable area of I. scapularis is under SSP3-7.0 from 2081 to 2100, while the smallest is under SSP5-8.5 from 2081 to 2100, even smaller than the current suitable area. Precipitation in May and September are the main contributing factors affecting the potential suitable areas of I. scapularis. With the opportunity to spread to more potential suitable areas, it is critical to strengthen surveillance to prevent the possible invasion of I. scapularis.

China, with its growing population and economic development, faces increasing risks to health from climate change, but also opportunities to address these risks and protect health for generations to come. Without a timely and adequate response, climate change will impact lives and livelihoods at an accelerated rate. In 2020, the Lancet Countdown Regional Centre in Asia, led by Tsinghua University, built on the work of the global Lancet Countdown and began its assessment of the health profile of climate change in China with the aim of triggering rapid and health-responsive actions.This 2021 report is the first annual update, presenting 25 indicators within five domains: climate change impacts, exposures, and vulnerability; adaptation, planning, and resilience for health; mitigation actions and health co-benefits; economics and finance; and public and political engagement. The report represents the contributions of 88 experts from 25 leading institutions in, and outside of, China. From 2020 to 2021, five new indicators have been added and methods have been improved for many indicators. Where possible, the indicator results are presented at national and provincial levels to facilitate local understanding and policy making. In a year marked by COVID-19, this report also endeavours to reflect on China's pathway for a green recovery, ensuring it aligns with the carbon neutrality goal, for the health of the current and future generations.

Climatic factors are closely associated with the occurrence of vector-borne diseases, and they also influence the distribution of vectors. The occurrence of plague is closely related to the population dynamics of fleas and their host animals, as well as climatic conditions. This study focused on Xilingol League, utilizing climatic and flea index data from 2012 to 2021. Spearman correlation and "Boruta" importance analysis were conducted to screen for climatic variables. A generalized additive model (GAM) was employed to investigate the influence of climatic factors and rodent density on the flea index. GAM analysis revealed distinct trends in flea index among different rodent hosts. For Meriones unguiculatus, the flea index declined with increased density and with higher humidity, yet rose with greater lagged sunshine duration. For Spermophilus dauricus, an initial increase in flea index with density was observed, followed by a decrease, and a rise in the index was noted when ground temperatures were low. This study reveals the nonlinear interactions and lag effects among climatic factors, density, and flea index. Climatic factors and density variably influence the flea index of two Yersinia pestis hosts. This research advances the prediction and early warning efforts for plague control, providing a theoretical basis for rodent and flea eradication strategies.

Rising temperatures can increase the risk of mental disorders. As climate change intensifies, the future disease burden due to mental disorders may be underestimated. Using data on the number of daily emergency department visits for mental disorders at 30 hospitals in Beijing, China during 2016-2018, the relationship between daily mean temperature and such visits was assessed using a quasi-Poisson model integrated with a distributed lag nonlinear model. Emergency department visits for mental disorders attributed to temperature changes were projected using 26 general circulation models under four climate change scenarios. Stratification analyses were then conducted by disease subtype, sex, and age. The results indicate that the temperature-related health burden from mental disorders was projected to increase consistently throughout the 21st century, mainly driven by high temperatures. The future temperature-related health burden was higher for patients with mental disorders due to the use of psychoactive substances and schizophrenia as well as for women and those aged <65 years. These findings enhance our knowledge of how climate change could affect mental well-being and can be used to advance and refine targeted approaches to mitigating and adapting to climate change with a view on addressing mental disorders.