Objective: To analyze the epidemiological characteristics and influencing factors of severe fever with thrombocytopenia syndrome (SFTS) in Zhejiang Province from 2019 to 2023, so as to provide the reference for strengthening SFTS prevention and control. Methods: Data on laboratory-confirmed SFTS cases in Zhejiang Province from 2019 to 2023 were collected through the Infectious Disease Reporting Information System of Chinese Disease Prevention and Control Information System. Meteorological data, geographic environment and socioeconomic factors during the same period were collected from the fifth-generation European Centre for Medium-Range Weather Forecasts, Geospatial Data Cloud, and Zhejiang Statistical Yearbook, respectively. Descriptive epidemiological methods were used to analyze the epidemiological characteristics of SFTS from 2019 to 2023, and a Bayesian spatio-temporal model was constructed to analyze the influencing factors of SFTS incidence. Results: A total of 578 SFTS cases were reported in Zhejiang Province from 2019 to 2023, with an annual average incidence of 0.23/105. The peak period was from May to July, accounting for 52.60%. There were 309 males and 269 females, with a male-to-female ratio of 1.15∶1. The cases were mainly aged 50-<80 years, farmers, and in rural areas, accounting for 82.53%, 77.34%, and 75.43%, respectively. Taizhou City and Shaoxing City reported more SFTS cases, while Shaoxing City and Zhoushan City had higher annual average incidences of SFTS. The Bayesian spatio-temporal interaction model showed good goodness of fit. The results showed that mean temperature (RR=1.626, 95%CI: 1.111-2.378) and mean wind speed (RR=1.814, 95%CI: 1.321-2.492) were positively correlated with SFTS risk, while altitude (RR=0.432, 95%CI: 0.230-0.829) and population density (RR=0.443, 95%CI: 0.207-0.964) were negatively correlated with SFTS risk. Conclusions SFTS in Zhejiang Province peaks from May to July. Middle-aged and elderly people and farmers are high-risk populations. Taizhou City, Shaoxing City, and Zhoushan City are high-incidence areas. Mean temperature, mean wind speed, altitude, and population density can all affect the risk of SFTS incidence.

Objective: To investigate the impact of temperature changes between neighboring days (TCN) on the mortality risk of respiratory diseases, so as to provide the evidence for the study of deaths from respiratory diseases caused by climate change. Methods: The monitoring data of deaths from respiratory diseases in Zibo City from 2015 to 2019 were collected from Shandong Provincial Management Information System for Chronic Diseases and Cause of Death Surveillance. The meteorological and air pollutant data of the same period were collected from China Meteorological Data Website and ChinaHighAirPollutants dataset. The effect of TCN on the risk of deaths from respiratory diseases was examined using a generalized additive model combined with a distributed lag non-linear model, and subgroup analyses for gender and age were conducted. The disease burden attributed to TCN at different intervals was assessed by calculating attributable fraction. Results: Totally 11 767 deaths from respiratory diseases were reported in Zibo City from 2015 to 2019, including 6 648 males (56.50%) and 5 119 females (43.50%). There were 1 307 deaths aged <65 years (11.11%), and 10 460 deaths aged 65 years and older (88.89%). A monotonically increasing exposure-response relationship was observed between TCN and deaths from respiratory diseases in the general population, females, and the population aged 65 years and older. The 95th percentile of TCN (P95, 3.84 ℃) reached the peak at a cumulative lagged of day 11 (RR=2.063, 95%CI: 1.261-3.376). The results of subgroup analyses showed greater impacts on females and the population aged 65 years and older, with cumulative lagged effects peaking at day 12 (RR=3.119, 95%CI: 1.476-6.589) and day 11 (RR=2.107, 95%CI: 1.260-3.523). The results of attributional risk analysis showed that next-day warming might increase the attributable risk of deaths from respiratory diseases, and next-day cooling might decrease the attributable risk. Conclusion Next-day warming may increase the mortality risk of respiratory diseases, and has greater impacts on females and the population aged 65 years and older.

Objective: To examine the impact of heat waves and cold spells on the incidence of hemorrhagic stroke, so as to provide insights into prevention of hemorrhagic stroke. Methods: Data pertaining to the incidence of hemorrhagic stroke in Zibo City from 2015 to 2019 were collected from Shandong Provincial Management Information System for Chronic Diseases and Cause of Death Surveillance, and the meteorological data during the period from 2015 to 2019 were captured from National Meteorological Information Center of China. The air quality index (AQI) was collected from the National Daily Report of Urban Air Quality in China. Heat wave was defined as the highest daily temperature that was no less than the 90th percentile (P90), P92.5, P95 and P97.5 of the highest daily temperature in the warm season for at least 2, 3 or 4 days, and cold spell was defined as the lowest daily temperature that was no more than the P10, P7.5, P5 and P2.5 of the lowest daily temperature in the cold season for at least 2, 3 or 4 days. The effect of heat waves and cold spells on the incidence of hemorrhagic stroke was evaluated using a generalized additive model and described with relative risk (RR) and its 95%CI. Results: A total of 8 844 case with first-onset hemorrhagic stroke were recorded in Zibo City from 2015 to 2019. The lowest daily temperature that was no more than P10, P7.5 or P5 of the lowest daily temperature in the cold season for at least two days, or that was no more than P10 or P7.5 of the lowest daily temperature for at least 3 days resulted a remarkably increased risk of hemorrhagic stroke (lowest RR=1.187, 95%CI: 1.031-1.366; highest RR=1.242, 95%CI: 1.042-1.480), and after adjusting the effect of daily mean temperature, the lowest daily temperature that was no more than P10 or P7.5 of the lowest daily temperature in the cold season for at least two days, or that was no more than P10 of the lowest daily temperature for at least 3 days resulted a remarkably increased risk of hemorrhagic stroke (lowest RR=1.236, 95%CI: 1.009-1.513; highest RR=1.274, 95%CI: 1.023-1.585). However, there was no significant association between heat waves and the risk of hemorrhagic stroke. Conclusion Cold spells may increase the risk of hemorrhagic stroke, while no significant association is examined between heat waves and the risk of hemorrhagic stroke.