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Many studies have reported a relationship between climate factors and malaria. However, results were inconsistent across the areas. We examined associations between climate factors and malaria in two geographically different areas: lowland (lakeside area) and highland in Western Kenya. Associations between climate factors (rainfall, land surface temperature (LST), and lake water level (LWL)) and monthly malaria cases from 2000 to 2013 in six hospitals (two in lowland and four in highland) were analyzed using time-series regression analysis with a distributed lag nonlinear model (DLNM) and multivariate meta-analysis. We found positive rainfall–malaria overall associations in lowland with a peak at 120 mm of monthly rainfall with a relative risk (RR) of 7.32 (95% CI: 2.74, 19.56) (reference 0 mm), whereas similar associations were not found in highland. Positive associations were observed at lags of 2 to 4 months at rainfall around 100–200 mm in both lowland and highland. The RRs at 150 mm rainfall were 1.42 (95% CI: 1.18, 1.71) in lowland and 1.20 (95% CI: 1.07, 1.33) in highland (at a lag of 3 months). LST and LWL did not show significant association with malaria. The results suggest that geographical characteristics can influence climate–malaria relationships.

Relatively few studies investigated the effects of extreme temperatures (both heat and cold) on mental health (ICD-9: 290-319; ICD-10: F00-F99) and the potential effect modifications by individuals’ age, sex, and race. We aimed to explore the effect of extreme temperatures of both heat and cold on the emergency room (ER) visits for mental health disorders, and conducted a stratified analysis to identify possible susceptible population in Erie and Niagara counties, NY, USA. To assess the short-term impacts of daily maximum temperature on ER visits related to mental disorders (2009–2015), we applied a quasi-Poisson generalized linear model combined with a distributed lag non-linear model (DLNM). The model was adjusted for day of the week, precipitation, long-term time trend, and seasonality. We found that there were positive associations between short-term exposure to extreme ambient temperatures and increased ER visits for mental disorders, and the effects can vary by individual factors. We found heat effect (relative risk (RR) = 1.16; 95% confidence intervals (CI), 1.06–1.27) on exacerbated mental disorders became intense in the study region and subgroup of population (the elderly) being more susceptible to extreme heat than any other age group. For extreme cold, we found that there is a substantial delay effect of 14 days (RR = 1.25; 95% CI = 1.08–1.45), which is particularly burdensome to the age group of 50–64 years old and African-Americans. Our findings suggest that there is a positive association between short-term exposure to extreme ambient temperature (heat and cold) and increased ER visits for mental disorders, and the effects vary as a function of individual factors, such as age and race.

Background Tuberculosis (TB) remains a pressing public health issue, posing a significant threat to individuals' well-being and lives. This study delves into the TB incidence in Chinese mainland during 2014–2021, aiming to gain deeper insights into their epidemiological characteristics and explore macro-level factors to enhance control and prevention. Methods TB incidence data in Chinese mainland from 2014 to 2021 were sourced from the National Notifiable Disease Reporting System (NNDRS). A two-stage distributed lag nonlinear model (DLNM) was constructed to evaluate the lag and non-linearity of daily average temperature (℃, Atemp), average relative humidity (%, ARH), average wind speed (m/s, AWS), sunshine duration (h, SD) and precipitation (mm, PRE) on the TB incidence. A spatial panel data model was used to assess the impact of demographic, medical and health resource, and economic factors on TB incidence. Results A total of 6,587,439 TB cases were reported in Chinese mainland during 2014–2021, with an average annual incidence rate of 59.17/100,000. The TB incidence decreased from 67.05/100,000 in 2014 to 46.40/100,000 in 2021, notably declining from 2018 to 2021 (APC = -8.87%, 95% CI : -11.97, -6.85%). TB incidence rates were higher among males, farmers, and individuals aged 65 years and older. Spatiotemporal analysis revealed a significant cluster in Xinjiang, Qinghai, and Xizang from March 2017 to June 2019 ( RR  = 3.94, P  < 0.001). From 2014 to 2021, the proportion of etiologically confirmed cases increased from 31.31% to 56.98%, and the time interval from TB onset to diagnosis shortened from 26 days (IQR: 10–56 days) to 19 days (IQR: 7–44 days). Specific meteorological conditions, including low temperature (< 16.69℃), high relative humidity (> 71.73%), low sunshine duration (< 6.18 h) increased the risk of TB incidence, while extreme low wind speed (< 2.79 m/s) decreased the risk. The spatial Durbin model showed positive associations between TB incidence rates and sex ratio ( β  = 1.98), number of beds in medical and health institutions per 10,000 population ( β  = 0.90), and total health expenses ( β  = 0.55). There were negative associations between TB incidence rates and population ( β  = -1.14), population density ( β  = -0.19), urbanization rate ( β  = -0.62), number of medical and health institutions ( β  = -0.23), and number of health technicians per 10,000 population ( β  = -0.70). Conclusions Significant progress has been made in TB control and prevention in China, but challenges persist among some populations and areas. Varied relationships were observed between TB incidence and factors from meteorological, demographic, medical and health resource, and economic aspects. These findings underscore the importance of ongoing efforts to strengthen TB control and implement digital/intelligent surveillance for early risk detection and comprehensive interventions. Graphical Abstract

As one of the most common complications of early pregnancy, spontaneous abortion is associated with environmental factors, but reports estimating the effect of ambient temperature on spontaneous abortion are still inconclusive. Herein, a case–control study (1002 cases and 2004 controls) in Nanjing, China, from 2017 to 2021 was conducted to evaluate the association between temperature exposure and the risk of spontaneous abortion by using distributed lag nonlinear model (DLNM). As a result, daily mean temperature exposure and early spontaneous abortion showed a nonlinear relationship in 14-day lag periods. Moreover, taking the median temperature (17 °C) as a reference, gradually increased positive effects of high temperature on spontaneous abortion could be found during the 4 days prior to hospitalization, and the highest odds ratio (OR) of 2.07 (95% confidence interval (CI): 1.36, 3.16) at extremely hot temperature (33 °C) was observed at 1 lag day. The results suggested that high-temperature exposure in short times during early pregnancy might increase the risk of SAB. Thus, our findings highlight the potential risk of short-term high-temperature exposure during early pregnancy, and more evidence was given for the effects of climate change on maternal health.

Objective To investigate the epidemiological characteristics and climate-sensitive transmission patterns of rotavirus (RV), adenovirus (AdV), and RV-AdV coinfections among children with acute gastroenteritis in Wuhan, China, during the post-COVID-19 era. Methods We conducted a retrospective time-series study of 53,088 pediatric patients tested for RV and AdV from April 2020 to August 2024. Age-stratified positivity rates were analyzed alongside temporal trends. Daily meteorological data (temperature, relative humidity, wind speed) and air pollutants were incorporated into a generalized additive model (GAM) framework with distributed lag nonlinear models (DLNMs) to assess delayed and nonlinear associations between weather exposures and virus positivity. Results RV was the most frequently detected virus (7.74%), peaking in preschool-aged children (3–6 years), while AdV showed broader age distribution with highest positivity in toddlers (1–3 years). Coinfections were most common in children under 2 years. Significant seasonal and interannual fluctuations were observed, particularly a post-pandemic RV surge in 2024. Spearman analysis revealed inverse correlations between RV/AdV positivity and temperature. DLNMs showed that RV risk increased significantly under low wind (RR = 1.79, lag 0), cold (RR = 1.47, lag 21), and dry conditions (RR = 1.23, lag 15). AdV exhibited a U-shaped humidity-risk curve and increased risk with cold and moderately humid conditions. Coinfection risk was primarily driven by cold temperatures. Significant interactions were found between temperature and wind (RV) and between temperature and humidity (AdV). Season-stratified analysis indicated atypical spring and summer RV peaks. Conclusion This study is the first in China to apply DLNMs in a large pediatric cohort to evaluate climate-driven risk of RV and AdV infections. Findings reveal pathogen-specific, delayed meteorological sensitivities and post-COVID shifts in transmission patterns, providing a foundation for climate-informed surveillance and targeted interventions in pediatric gastroenteritis control.

Objectives Previous studies on the association between temperature and preeclampsia mainly considered temperature on a monthly or seasonal time scale. The objective of this study was to assess the preeclampsia risk associated with short-term temperature exposure using daily data. Study design Daily preeclampsia hospitalization data, daily meteorological data and daily air pollutant data from Nanjing were collected from 2016 to 2017. Both the T test and distributed lag nonlinear model (DLNM) were applied to assess the short-term effect of temperature on preeclampsia risk. Three kinds of daily temperature, including the daily mean temperature, daily minimum temperature and daily maximum temperature, were analysed. Results When the daily number of preeclampsia hospital admissions was divided into two subgroups based on temperature, it was significantly larger on cold days than on hot days. Regarding the mean temperature, a very low level of mean temperature (4.5 °C, lag = 0–20) and a low level of mean temperature (9.1 °C, lag = 0–20) increased the cumulative relative risk of preeclampsia by more than 60%. At the same time, a very high level of mean temperature (28.7 °C, lags = 0–10, 0–15, 0–20) and a high level of mean temperature (24.1 °C, lags = 0–10, 0–15) decreased the cumulative relative risk of preeclampsia by more than 35%. At a minimum temperature, a very low level of minimum temperature (0.9 °C, lag 0–5) and a low level of minimum temperature (5.6 °C, lag 0–5) increased the cumulative relative risk of preeclampsia by more than 55%. At the same time, a high level of mean temperature (20.9 °C, lags = 0, 0–5) decreased the cumulative relative risk of preeclampsia by more than 20%. The maximum temperature result was similar to the mean temperature result. Conclusions Both direct and lag effects of low temperature on preeclampsia were demonstrated to be significant risk factors. These results could be used to help pregnant women and the government reduce preeclampsia risk.

Background Climate change has significantly increased adverse effects on cardiovascular disease (CVD). Ozone (O 3 ) exposure is recognized as a risk factor for CVD mortality. However, few studies have analyzed the modifying effects of climatic factors on O 3 , particularly in subtropical regions. This study analyzed the association between O 3 and CVD mortality in Zhejiang Province, China, while evaluating the modifying effects of temperature and humidity. Methods Using mortality, air pollution, and meteorological data from 11 cities (2019–2023) in Zhejiang Province, China, we employed distributed lag nonlinear models (DLNMs) to assess lagged and cumulative O 3 effects. For effect modification, a general linear model (GLM) was used to quantify the extra effect of temperature and relative humidity on O 3 -related CVD mortality risks. A series of sensitivity analyses were conducted to assess the robustness of the effect modification by temperature–humidity interactions on O 3 -associated cardiovascular mortality. Results Results revealed a nonlinear relationship, with CVD mortality risk peaking at an O 3 concentration of 229.7 µg/m ³ (relative risk (RR) = 1.330, 95% confidence interval (CI): 1.110–1.600) and a delayed maximum effect at a 6.2-day lag. High temperature ( T > P 95 ) and moderate humidity (40% ≤ RH < 70%) amplified O 3 -associated mortality ( β = 0.160, P < 0.001). Sensitivity analyses demonstrated robustness across alternative climate thresholds and COVID-19 adjustments. Conclusions O 3 exposure significantly increases cardiovascular mortality, with risks amplified by high temperature and moderate humidity. These findings highlight the necessity of integrating climate interactions into region-specific air quality policies and public health warnings.

Introduction Evidence remains limited regarding the cumulative multi-system health effects of nitrogen dioxide (NO 2 ) exposure and its lag–response patterns. This study aimed to evaluate the associations between short-term NO₂ exposure and multi-system healthcare utilization, with particular emphasis on lagged effects. Methods Daily data on ambient air pollution, meteorological factors, and healthcare utilization across multiple disease systems were collected from 2023 to 2024 in four subtropical humid monsoon cities in China. Using a time-series design, distributed lag non-linear models (DLNMs) were applied to examine lagged and exposure–response associations between short-term NO 2 exposure (lag 0–7 days) and daily healthcare visits. Stratified analyses by sex, age, healthcare utilization type, and season, as well as sensitivity analyses, were conducted. Results Significant positive associations between NO 2 exposure and healthcare utilization were consistently observed across all four cities, with relative risks (RRs) ranging from 1.016 (95% confidence interval [CI] 1.008–1.084) to 1.290 (1.185–1.404), 1.072 (1.040–1.105) to 1.168 (1.128–1.210), and 1.072 (1.032–1.114) to 1.145 (1.099–1.193), respectively, for mental/behavioral, cardiovascular, and respiratory diseases, associated with a 10 μg/m 3 increase in NO 2 concentration during lag01–lag07. Statistically significant cumulative risks were also observed for neurological and metabolic/endocrine diseases in certain cities. Exposure–response indicated a predominantly non-linear, upward association between NO₂ concentrations and healthcare utilization, with relative risks increasing more sharply at higher concentrations. Further subtype analyses indicated that the cumulative lag effects were mainly concentrated in schizophrenia and delusional disorders, affective disorders, hypertensive diseases, and acute upper respiratory infections. Conclusion Short-term NO₂ exposure was associated with increased healthcare utilization across multiple disease systems, underscoring the need for strengthened NO₂ control to mitigate its broader health impacts.

Climate change is a crucial cause of health issues, as reported in many studies. Temperature is one of the important factors related to extreme weather. Chiang Mai, the center of the north of Thailand, is also affected by temperature changes that have led to many outpatient visits. Better information will help the health service to be well-prepared. This research applied typical meteorological data and solar radiation into the distributed lag nonlinear model and a quasi-Poisson regression model. The “hot effect” and “cold effect” on outpatient visits caused by respiratory diseases, dermatophytosis, and intestinal infectious diseases in a public Chiang Mai hospital between January 2015 and December 2019 were then investigated. Of the 185,202 cases, results showed that all of the diseases mentioned had more than 10% of relative risk (RR) in cold effects. However, the RR of dermatophytosis was found to be 114%, a very high risk. In the case of hot effects, the patients of the age 19–29 have relatively high RR over 20% for respiratory diseases and dermatophytosis. It was also observed that cold effects lasted longer than hot effects.

To characterize the epidemiology of pediatric respiratory infections and evaluate the lagged, nonlinear associations between meteorological factors and pathogen activity in post-COVID-19 Wuhan, China. A total of 28,903 respiratory specimens were collected from pediatric patients at a tertiary hospital between November 2023 and February 2025. Seven pathogens- , adenovirus, respiratory syncytial virus (RSV), influenza A/B, and parainfluenza virus types I/III-were detected using multiplex RT-PCR. Epidemiological patterns were analyzed by age, sex, seasonality, and clinical setting. Daily meteorological data (temperature, relative humidity, wind speed) were aggregated citywide and temporally matched to case data. Spearman correlation and generalized additive models integrated with distributed lag nonlinear models (GAM-DLNMs) were used to assess pathogen-specific climatic sensitivity. (18.9%), adenovirus (14.5%), and RSV (9.1%) were the most prevalent pathogens. Distinct age- and sex-specific distributions were observed, with peaking in school-aged boys and RSV in infants. Seasonal peaks were evident: RSV and influenza A predominated in winter, while peaked in spring. Meteorological analysis revealed pathogen-specific associations: low humidity preceded RSV surges by 7-14 days; influenza B was strongly associated with wind exposure; and extreme climatic conditions showed heterogeneous effects on transmission risk across pathogens. This study demonstrates the utility of GAM-DLNMs in capturing climate-sensitive, time-lagged transmission dynamics for multiple pediatric respiratory pathogens. The findings support the development of localized, climate-informed early warning systems to enhance respiratory disease surveillance and preparedness.