Processed Data for “Projecting long-term excess risks of major infectious diseases associated with future extreme weather events in Thailand”

Climate change is postulated to impact infectious disease transmission, yet few studies have characterised the excess risks of infectious diseases associated with extreme weather events. To address this, we conducted a study estimating and projecting the impacts of extreme heat and precipitation on the incidence of major infectious diseases in Thailand.We developed, fitted and validated an analytical framework to model province-level disease cases and their relationship with extreme weather indicators based on historical data. We used generalised additive models to delineate the relationship between monthly extreme heat days, standardised precipitation index and incidence rates of seven infectious diseases (dengue, malaria, Japanese encephalitis, melioidosis, leptospirosis, pneumonia, influenza) across Thailand’s provinces. Disease-specific models were fitted to historical surveillance data and used to project future disease incidence across 4 Shared Socioeconomic Pathways (SSP) based on MIROC6 climate projections.Historically, extreme heat was associated with an increase in all infectious disease incidences except malaria and leptospirosis. We projected that dengue risk declines in most future climate change scenarios, except SSP245 where extreme heat drives a significant rise in Northern and Central Thailand from 2021–2060. Nationwide dengue risk is expected to decrease by 24.9% (95%CI:9.68%,40.0%) during future periods of extreme weather from 2061–2080 compared to historical baselines. Influenced by heat and dry weather in Northeastern and Central regions, influenza risk is expected to increase under SSP245 in 2021–2060, then decrease with extreme precipitation. Influenza risk in Nakhon Ratchasima is expected to increase by 36.8% (95%CI:9.83%,63.8%) in 2021–2040 under SSP245. Through isolating periods of concurrent extreme heat and extreme dry or wet weather respectively, we found that excess risks estimated during periods of extreme heat may result from a combination of extreme heat and extreme dry or wet weather. Localised public health interventions are necessary to address climate change impacts.

气候变化被认为会对传染病传播产生影响，但目前鲜有研究针对极端天气事件关联的传染病超额风险开展系统性刻画。为填补这一研究空白，本研究针对泰国主要传染病的发病情况，估算并预测极端高温与降水事件的影响效应。本研究基于历史数据，构建、拟合并验证了一套分析框架，用于建模省级层面的传染病病例数及其与极端天气指标的关联关系。本研究采用广义相加模型（Generalized Additive Models），刻画了泰国各省级行政区月度极端高温日数、标准化降水指数（Standardized Precipitation Index）与7种传染病（登革热、疟疾、日本脑炎、类鼻疽、钩端螺旋体病、肺炎、流感）发病率之间的关联关系。研究针对每种传染病分别基于历史监测数据拟合专属模型，并基于MIROC6气候预测结果，在4种共享社会经济路径（Shared Socioeconomic Pathways, SSPs）框架下开展未来传染病发病情况的预测。历史数据显示，除疟疾与钩端螺旋体病外，极端高温与其余所有传染病的发病率上升存在显著关联。预测结果显示，在多数未来气候变化情景下，登革热发病风险将呈下降趋势；但在SSP245情景中，2021-2060年泰国北部与中部地区的极端高温将推动登革热风险显著上升。相较于历史基线期，2061-2080年全国范围内极端天气事件期间的登革热发病风险预计将下降24.9%（95%置信区间：9.68%，40.0%）。受泰国东北部与中部地区的高温及干旱天气影响，2021-2060年SSP245情景下的流感发病风险预计将上升，随后随极端降水事件增多而下降。在SSP245情景下，2021-2040年呵叻府（Nakhon Ratchasima）的流感发病风险预计将上升36.8%（95%置信区间：9.83%，63.8%）。本研究通过分别分离出同时发生极端高温与极端干旱/极端降水的时段，发现极端高温时段估算出的超额风险，可能由极端高温与极端干旱或极端降水共同作用导致。为应对气候变化带来的公共卫生影响，需制定针对性的本地化干预措施。