• Energy Research

AbstractScrub typhus is a climate‐sensitive and life‐threatening vector‐borne disease that poses a growing public health threat. Although the climate‐epidemic associations of many vector‐borne diseases have been studied for decades, the impacts of climate on scrub typhus remain poorly understood, especially in the context of global warming. Here we incorporate Chinese national surveillance data on scrub typhus from 2010 to 2019 into a climate‐driven generalized additive mixed model to explain the spatiotemporal dynamics of this disease and predict how it may be affected by climate change under various representative concentration pathways (RCPs) for three future time periods (the 2030s, 2050s, and 2080s). Our results demonstrate that temperature, precipitation, and relative humidity play key roles in driving the seasonal epidemic of scrub typhus in mainland China with a 2‐month lag. Our findings show that the change of projected spatiotemporal dynamics of scrub typhus will be heterogeneous and will depend on specific combinations of regional climate conditions in future climate scenarios. Our results contribute to a better understanding of spatiotemporal dynamics of scrub typhus, which can help public health authorities refine their prevention and control measures to reduce the risks resulting from climate change.

AbstractSevere fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease with increasing incidence and geographic extent. The extent to which global climate change affects the incidence of SFTS disease remains obscure. We use an integrated multi‐model, multi‐scenario framework to assess the impact of global climate change on SFTS disease in China. The spatial distribution of habitat suitability for the tick Haemaphysalis longicornis was predicted by applying a boosted regression tree model under four alternative climate change scenarios (RCP2.6, RCP4.5, RCP6.0, and RCP8.5) for the periods 2030–2039, 2050–2059, and 2080–2089. We incorporate the SFTS cases in the mainland of China from 2010 to 2019 with environmental variables and the projected distribution of H. longicornis into a generalized additive model to explore the current and future spatiotemporal dynamics of SFTS. Our results demonstrate an expanded geographic distribution of H. longicornis toward Northern and Northwestern China, showing a more pronounced change under the RCP8.5 scenario. In contrast, the environmental suitability of H. longicornis is predicted to be reduced in Central and Eastern China. The SFTS incidence in three time periods (2030–2039, 2050–2059, and 2080–2089) is predicted to be increased as compared to the 2010s in the context of various RCPs. A heterogeneous trend across provinces, however, was observed, when an increased incidence in Liaoning and Shandong provinces, while decreased incidence in Henan province is predicted. Notably, we predict possible outbreaks in Xinjiang and Yunnan in the future, where only sporadic cases have been reported previously. These findings highlight the need for tick control and population awareness of SFTS in endemic regions, and enhanced monitoring in potential risk areas.

This dataset is the data used in the paper of Global change biology entitled "Climate drives the spatiotemporal dynamics of scrub typhus in China". We incorporate Chinese national surveillance data on scrub typhus from 2010 to 2019 into a climate-driven generalized additive mixed model to explain the spatiotemporal dynamics of this disease and predict how it may be affected by climate change under various representative concentration pathways (RCPs) for three future time periods (the 2030s, 2050s, and 2080s). This dataset provides important information on the projected cases of scrub typhus in mainland China under various RCPs (RCP4.5, RCP6.0, and RCP8.5) for three future time periods, which can help public health authorities refine their prevention and control measures to reduce the disease risk. See the Materials and methods section in the original paper. Microsoft Excel are required to open the data files.

Résumé Objectifs Comprendre si et comment la pandémie de COVID-19 affecte le risque de différents types de conflits dans le monde dans le contexte du changement climatique. Méthodologie Sur la base de la base de données des conflits armés, de la COVID-19, des données climatiques détaillées et des données non climatiques couvrant la période 2020–2021, nous avons appliqué la modélisation des équations structurelles spécifiquement pour réorganiser les liens entre le climat, la COVID-19 et le risque de conflit. De plus, nous avons utilisé la méthode de l'arbre de régression boosté pour simuler le risque de conflit sous l'influence de multiples facteurs. Résultats Le risque de transmission de la COVID-19 semble diminuer à mesure que la température augmente. En outre, la COVID-19 a un impact mondial important sur le risque de conflit, bien qu'il existe des variations régionales et de risque de conflit. De plus, lorsque nous testons un effet différé d'un mois, nous constatons une cohérence entre les régions, indiquant une influence positive de la COVID-19 sur les manifestations (manifestations et émeutes) et une relation négative avec le risque de conflit non étatique et violent. Conclusion La COVID-19 a un effet complexe sur le risque de conflit dans le monde entier dans le contexte du changement climatique. Implications Jeter les bases théoriques de la façon dont la COVID-19 affecte le risque de conflit et fournir une certaine inspiration pour la mise en œuvre des politiques pertinentes. Resumen Objetivos Comprender si y cómo la pandemia de COVID-19 afecta el riesgo de diferentes tipos de conflictos en todo el mundo en el contexto del cambio climático. Metodología Con base en la base de datos de conflictos armados, COVID-19, clima detallado y datos no climáticos que cubren el período 2020–2021, aplicamos el Modelado de Ecuaciones Estructurales específicamente para reorganizar los vínculos entre el clima, COVID-19 y el riesgo de conflicto. Además, utilizamos el método del Árbol de Regresión Impulsado para simular el riesgo de conflicto bajo la influencia de múltiples factores. Hallazgos El riesgo de transmisión de COVID-19 parece disminuir a medida que aumenta la temperatura. Además, la COVID-19 tiene un impacto mundial sustancial en el riesgo de conflicto, aunque existen variaciones regionales y de riesgo de conflicto. Además, al probar un efecto rezagado de un mes, encontramos coherencia entre las regiones, lo que indica una influencia positiva de COVID-19 en las manifestaciones (protestas y disturbios) y una relación negativa con el riesgo de conflictos no estatales y violentos. Conclusión El COVID-19 tiene un efecto complejo sobre el riesgo de conflicto en todo el mundo bajo el cambio climático. Implicaciones Sentar las bases teóricas de cómo la COVID-19 afecta el riesgo de conflicto y proporcionar algo de inspiración para la implementación de políticas relevantes. Abstract Objectives Understand whether and how the COVID-19 pandemic affects the risk of different types of conflict worldwide in the context of climate change. Methodology Based on the database of armed conflict, COVID-19, detailed climate, and non-climate data covering the period 2020–2021, we applied Structural Equation Modeling specifically to reorganize the links between climate, COVID-19, and conflict risk. Moreover, we used the Boosted Regression Tree method to simulate conflict risk under the influence of multiple factors. Findings The transmission risk of COVID-19 seems to decrease as the temperature rises. Additionally, COVID-19 has a substantial worldwide impact on conflict risk, albeit regional and conflict risk variations exist. Moreover, when testing a one-month lagged effect, we find consistency across regions, indicating a positive influence of COVID-19 on demonstrations (protests and riots) and a negative relationship with non-state and violent conflict risk. Conclusion COVID-19 has a complex effect on conflict risk worldwide under climate change. Implications Laying the theoretical foundation of how COVID-19 affects conflict risk and providing some inspiration for the implementation of relevant policies. الملخص الأهداف فهم ما إذا كانت جائحة كوفيد-19 تؤثر على مخاطر أنواع مختلفة من النزاعات في جميع أنحاء العالم في سياق تغير المناخ وكيفية تأثيرها. المنهجية استنادًا إلى قاعدة بيانات النزاع المسلح وكوفيد-19 والمناخ التفصيلي والبيانات غير المناخية التي تغطي الفترة 2020–2021، طبقنا نمذجة المعادلة الهيكلية على وجه التحديد لإعادة تنظيم الروابط بين المناخ وكوفيد-19 ومخاطر النزاع. علاوة على ذلك، استخدمنا طريقة شجرة الانحدار المعزز لمحاكاة مخاطر النزاع تحت تأثير عوامل متعددة. النتائج يبدو أن خطر انتقال COVID -19 ينخفض مع ارتفاع درجة الحرارة. بالإضافة إلى ذلك، فإن COVID -19 له تأثير كبير في جميع أنحاء العالم على مخاطر النزاع، على الرغم من وجود اختلافات إقليمية ومخاطر النزاع. علاوة على ذلك، عند اختبار تأثير متأخر لمدة شهر واحد، نجد الاتساق عبر المناطق، مما يشير إلى التأثير الإيجابي لـ COVID -19 على المظاهرات (الاحتجاجات وأعمال الشغب) والعلاقة السلبية مع مخاطر النزاع العنيف وغير الحكومي. الخاتمة كوفيد-19 له تأثير معقد على مخاطر النزاع في جميع أنحاء العالم في ظل تغير المناخ. الآثار وضع الأساس النظري لكيفية تأثير كوفيد-19 على مخاطر النزاع وتوفير بعض الإلهام لتنفيذ السياسات ذات الصلة.