Meteorological Drivers of Influenza Spread in New South Wales: A Spatial Bayesian Distributed Lag Non-linear Model Approach

Few studies have estimated the nonlinear association of ambient temperature with the risk of influenza. We therefore applied a time-series analysis to explore the short-term effect of ambient temperature on the incidence of influenza in Wuhan, China. Daily influenza cases were collected from Hubei Provincial Center for Disease Control and Prevention (Hubei CDC) from January 1, 2014, to December 31, 2017. The meteorological and daily pollutant data was obtained from the Hubei Meteorological Service Center and National Air Quality Monitoring Stations, respectively. We used a generalized additive model (GAM) coupled with the distributed lag nonlinear model (DLNM) to explore the exposure-lag-response relationship between the short-term risk of influenza and daily average ambient temperature. Analyses were also performed to assess the extreme cold and hot temperature effects. We observed that the ambient temperature was statistically significant, and the exposure-response curve is approximately S-shaped, with a peak observed at 23.57 ℃. The single-day lag curve showed that extreme hot and cold temperatures were both significantly associated with influenza. The extreme hot temperature has an acute effect on influenza, with the most significant effect observed at lag 0-1. The extreme cold temperature has a relatively smaller effect but lasts longer, with the effect exerted continuously during a lag of 2-4days. Our study found significant nonlinear and delayed associations between ambient temperature and the incidence of influenza. Our finding contributes to the establishment of an early warning system for airborne infectious diseases.

BackgroundSeasonal influenza is a highly contagious acute respiratory infection that imposes a considerable global health burden. Although numerous investigations have examined the short-term effects of ambient temperature or humidity on influenza incidence, relatively few have addressed their combined effects. To bridge this gap, the present study sought to conduct a time‐series analysis to examine the combined effects of temperature and relative humidity on influenza incidence in Japan, while accounting for potential confounders.MethodsWeekly time‐series data on influenza incidence and meteorological factors (i.e., mean temperature (°C), relative humidity (%), precipitation (mm), wind speed (m/s) and sunshine duration (hours)) were collected from all 47 prefectures in Japan from 2010 to 2019. A composite exposure metric, humidex, was calculated to capture the combined effects of temperature and relative humidity. We employed an extended two‐stage time-series design. In the first stage, a time‐stratified case‐crossover design was implemented using conditional quasi‐Poisson regression integrated with a distributed lag non‐linear model to characterize the humidex–influenza associations at the prefectural level. In the second stage, a multivariate meta‐analysis was conducted to derive pooled national estimates.ResultsA total of 14,526,346 influenza cases were analyzed. Overall, an inverted J‐shaped association between short‐term exposure to humidex and influenza incidence was observed. Decreases in humidex were associated with an increased risk of influenza, with the maximum relative risk (RR) reaching 10.75 (95% confidence interval [CI]: 8.35–3.82). The elevated risk corresponding to low humidex (5th percentile) became apparent at week 0, persisted until week 4, and peaked at approximately week 1 (RR = 3.31, 95% CI: 2.89–4.31). Furthermore, significant geographical heterogeneity in influenza incidence was detected across prefectures (Q = 343.4, p-value < 0.001; I² = 46.4%).ConclusionsOur findings demonstrates that the combined effects of ambient temperature and relative humidity are significantly associated with an elevated risk of influenza in Japan. These findings underscore the urgent need for bespoke public health interventions tailored to mitigate adverse health outcomes in regions characterized by persistently low humidex values.Supplementary InformationThe online version contains supplementary material available at 10.1007/s44197-025-00474-y.

Latitudes mediate the association between influenza activity and meteorological factors: A nationwide modelling analysis in 45 Japanese prefectures from 2000 to 2018

BackgroundPatients with rheumatoid arthritis (RA) are known to be at increased risk of infection, particularly if they are taking drugs with immunomodulatory effects. There is a need for more information on the risk of influenza in patients with RA.MethodsA retrospective cohort study was carried out using data gathered from a large US commercial health insurance database (Thomson Reuters Medstat MarketScan) from 1 January 2000 to 31 December 2007. Patients were ≥18 years of age, with at least two RA claims diagnoses. The database was scanned for incidence of seasonal influenza and its complications on or up to 30 days after an influenza diagnosis in RA patients and matched controls. Other factors accounted for included medical conditions, use of disease-modifying anti-rheumatic drugs (DMARDs), use of biological agents, influenza vaccination and high- or low-dose corticosteroids. Incidence rate ratios (IRRs) were calculated for influenza and its complications in patients with RA.Results46,030 patients with RA and a matching number of controls had a median age of 57 years. The incidence of influenza was higher in RA patients than in controls (409.33 vs 306.12 cases per 100,000 patient-years), and there was a 2.75-fold increase in incidence of complications in RA. Presence or absence of DMARDs or biologics had no significant effect. The adjusted IRR of influenza was statistically significant in patients aged 60–69 years, and especially among men. A significantly increased rate of influenza complications was observed in women and in both genders combined (but not in men only) when all age groups were combined. In general, the risk of influenza complications was similar in RA patients not receiving DMARDs or biologics to that in all RA patients. Pneumonia rates were significantly higher in women with RA. Rates of stroke/myocardial infarction (MI) were higher in men, although statistical significance was borderline.ConclusionsRA is associated with increased incidence of seasonal influenza and its complications. Gender- and age-specific subgroup data indicate that women generally have a greater rate of complications than men, but that men primarily have an increased rate of stroke and MI complications. Concomitant DMARD or biological use appears not to significantly affect the rate of influenza or its complications.

Analyzing the epidemiological characteristics of influenza cases among children aged 0-17 years in Guangzhou from 2019 to 2022. Assessing the relationships between multiple meteorological factors and influenza, improving the early warning systems for influenza, and providing a scientific basis for influenza prevention and control measures. The influenza data were obtained from the Chinese Center for Disease Control and Prevention. Meteorological data were provided by Guangdong Meteorological Service. Spearman correlation analysis was conducted to examine the relevance between meteorological factors and the number of influenza cases. Distributed lag non-linear models (DLNM) were used to explore the effects of meteorological factors on influenza incidence. The relationship between mean temperature, rainfall, sunshine hours, and influenza cases presented a wavy pattern. The correlation between relative humidity and influenza cases was illustrated by a U-shaped curve. When the temperature dropped below 13°C, Relative risk (RR) increased sharply with decreasing temperature, peaking at 5.7°C with an RR of 83.78 (95% CI: 25.52, 275.09). The RR was increased when the relative humidity was below 66% or above 79%, and the highest RR was 7.50 (95% CI: 22.92, 19.25) at 99%. The RR was increased exponentially when the rainfall exceeded 1,625 mm, reaching a maximum value of 2566.29 (95% CI: 21.85, 3558574.07) at the highest rainfall levels. Both low and high sunshine hours were associated with reduced incidence of influenza, and the lowest RR was 0.20 (95% CI: 20.08, 0.49) at 9.4 h. No significant difference of the meteorological factors on influenza was observed between males and females. The impacts of cumulative extreme low temperature and low relative humidity on influenza among children aged 0-3 presented protective effects and the 0-3 years group had the lowest RRs of cumulative extreme high relative humidity and rainfall. The highest RRs of cumulative extreme effect of all meteorological factors (expect sunshine hours) were observed in the 7-12 years group. Temperature, relative humidity, rainfall, and sunshine hours can be used as important predictors of influenza in children to improve the early warning system of influenza. Extreme weather reduces the risk of influenza in the age group of 0-3 years, but significantly increases the risk for those aged 7-12 years.

Effects and interaction of meteorological factors on influenza: Based on the surveillance data in Shaoyang, China

: The method for calculating warm and cold temperature extremes, described in Part I for the Northern Hemisphere, is used in this report (Part II) for an analogous presentation in the Southern Hemisphere. A bias in the estimates of cold temperature extremes for the Southern Hemisphere is discussed and evaluated in this report, resulting in development of a new set of regression equations to depict cold temperature extremes. The resulting Southern Hemisphere maps of the 1-, 5-, and 10-percent warm temperatures, and the 1-, 5-, 10-, and 20-percent cold temperatures for the warmest and coldest months, respectively, are presented. Parts I and II of this report together provide a global representation of warm and cold surface temperature extremes for use in systems design and operation.

Impact of meteorological factors on the incidence of influenza in Beijing: A 35-year retrospective study based on Yunqi theory

Short-term effects of ambient air pollution on the incidence of influenza in Wuhan, China: A time-series analysis

Interactive effects of meteorological factors and ambient air pollutants on influenza incidences 2019–2022 in Huaian, China

Seasonality and temperature effects on fasting plasma glucose: A population-based longitudinal study in China

Temperature and daily mortality in Suzhou, China: A time series analysis

BackgroundThe effect of temperature and humidity on the incidence of influenza may differ by climate region. In addition, the effect of diurnal temperature range on influenza incidence is unclear, according to previous study findings.ObjectivesThe aim of this study was to analyze the effects of temperature, humidity, and diurnal temperature range on the incidence of influenza in Seoul, Republic of Korea, which is located in a temperate region.MethodsWe used Korean National Health insurance data to assess the weekly influenza incidence between 2010 and 2016, and used meteorological data from Seoul. To investigate the effect of temperature, relative humidity, and diurnal temperature range levels on influenza incidence, we used a distributed lag non‐linear model.ResultsThe risk of influenza incidence was significantly increased with low daily temperatures of 0‐5°C and low (30%–40%) or high (70%) relative humidity. We found a positive significant association between diurnal temperature range and influenza incidence in this study.ConclusionsInfluenza incidence increased with low temperature and low/high humidity in a temperate region. Influenza incidence also increased with high diurnal temperature range, after considering temperature and humidity.

BackgroundResearch is lacking in examining how multiple climate factors affect the incidence of seasonal influenza. We investigated the associations between El Niño Southern Oscillation (ENSO), meteorological factors, and influenza incidence in New York State, United States. MethodWe collected emergency department visit data for influenza from the New York State Department of Health. ENSO index was obtained from the National Oceanic and Atmospheric Administration. Meteorological factors, Google Flu Search Index (GFI), and Influenza-like illness (ILI) data in New York State were also collected. Wavelet analysis was used to quantitatively estimate the coherence and phase difference of ENSO, temperature, precipitation, relative humidity, and absolute humidity with emergency department visits of influenza in New York State. Generalized additive models (GAM) were employed to examine the exposure-response relationships between ENSO, weather, and influenza. GFI and ILI data were used to simulate synchronous influenza visits. ResultsThe influenza epidemic in New York State had multiple periodic and was primarily on the 1-year scale. The incidence of influenza closely followed the low ENSO index by an average of two months, and the lag period of ENSO on influenza was shorter during 2015–2018. Low temperature in the previous 2 weeks and low absolute humidity in the prior week were positively associated with influenza incidence in New York State. We found an l-shaped association between ENSO index and influenza, a parabolic relationship between temperature in the previous two weeks and influenza, and a linear negative association between absolute humidity in the previous week and influenza. The simulation models including GFI and ILI had higher accuracy for influenza visit estimation. ConclusionsLow ENSO index, low temperature, and low absolute humidity may drive the influenza epidemics in New York State. The findings can help us deepen the understanding of the climate-influenza association, and help to develop an influenza forecasting model.

Influenza poses a significant threat to public health, potentially influenced by environmental factors. However, the role of meteorological factors (MFs) on influenza risks in China remains underexplored. This study explored the effect of MFs on laboratory-confirmed influenza (LCI) cases in Anhui, China. We analysed daily meteorological and influenza data between January 2015 and March 2023, to determine the relationship between temperature, relative humidity, wind speed and LCI cases, using two-stage time series analysis. First, we used distributed lag nonlinear models (DLNMs) to construct cross-basis functions capturing the non-linear and lagged effects of MFs, which were then incorporated into a generalized additive quasi-Poisson regression model for each city. Second, we conducted a random-effects meta-analysis to combine city-specific estimates. We further performed sub-group analysis by age and gender and explored effect modifications by population density, median MFs levels, longitude, and latitude through meta-regression. A total of 43,872 LCI cases were recorded in Anhui. A slight, non-significant negative association between temperature and influenza cases was observed at a single-day lag (RR = 0.9778; 95% CI: 0.9468-1.0098), but a positive association was found over cumulative lags (RR = 1.0263; 95% CI: 0.9721-1.0836). Relative humidity showed a positive association with influenza on single-day lag (RR = 1.0056; 95% CI: 0.9899-1.0216), but a slight negative association over cumulative lags (RR = 0.9974; 95% CI: 0.9927-1.0022). Wind speed displayed a slight, non-significant positive association at both single-day (RR = 1.0105; 95% CI: 0.9965-1.0246) and over cumulative lags (RR = 1.0083; 95% CI: 0.9498-1.0704). Temperature negatively associated with LCI cases across all genders and ages, at p = 0.0001, marginally moderated by population density (p = 0.0506). In conclusion, while MFs showed non-significant associations with influenza in general population, sub-group analysis showed statistically significant temperature-LCI cases association. Population density marginally modified this association. Our findings enhance evidence-based knowledge for developing targeted interventions like early warning systems to reduce influenza risks.