Effects of ambient temperature on influenza-like illness: A multicity analysis in Shandong Province, China, 2014-2017

Association between ambient temperature and risk of notifiable infectious diseases in China from 2011 to 2019

Previous studies on temperature and infectious diseases primarily focused on individual disease types, yielding inconsistent conclusions. This study collected monthly data on notifiable infectious disease cases and meteorological variables across 7 provinces in China from 2011 to 2019. A distributed lag nonlinear model was used to evaluate the association between ambient temperature and infectious diseases within each province, and random meta-analysis was applied to evaluate the pooled effect. Extreme hot temperature (the 97.5th percentile) was positively associated with the risk of respiratory infectious diseases with the relative risk (RR) of 1.45 (95%CI: 1.01-2.08). Conversely, extreme cold temperature (the 2.5th percentile) was negatively associated with intestinal infectious diseases and zoonotic diseases and vector-borne diseases, reporting RRs of 0.43 (95%CI: 0.30-0.60) and 0.46 (95%CI: 0.38-0.57), respectively. This study described the nonlinear association between ambient temperature and infectious diseases with different transmission routes, informing comprehensive prevention and control strategies for temperature-related infectious diseases.

Estimating the prevalence of six common respiratory viral infections in Zhangzhou, China using nasopharyngeal swabs in adults and throat swabs in Children

Acute respiratory viral infections are a major public health concern worldwide, causing significant morbidity and economic burden. Understanding the epidemiological characteristics of these infections is crucial for effective control and prevention measures. The study aimed to investigate the epidemiology of six common respiratory viral infections in Zhangzhou, Fujian Province, China. Clinical and demographic information, along with throat swabs from children and nasopharyngeal swabs from adults, were collected from 19,523 patients from Jan 2023 to Aug 2024 in Zhangzhou, Fujian Province, China. Multiplex RT-PCR was performed to detected six respiratory viral pathogens. At least one virus was detected in 6911 cases, the positivity rate was 35.40%. A total of 440 cases of mixed infection with two or more viruses were detected, and the positivity rate of co-infection was 2.25%. Age-specific analysis revealed that RSV predominantly affected children aged 0-3 years, while FluA had a broader age distribution, with significant incidences in elderly (≥ 60 years old). Seasonal peaks in viral detection were observed in Mar and Jul 2023, as well as Apr 2024. Overall, there was no statistically significant difference in viral detection rates between sexes, with the exception of the 6-14 years age group, where males exhibited a higher rate. Co-infections were more prevalent during the summer months and were particularly common among children aged 1-3 years. The study highlights the distinct age, sex, and seasonal patterns of six common respiratory viral infections in Zhangzhou, China. These findings emphasize the need for targeted age-specific and seasonal public health interventions to effectively prevent and control these infections.

The role of meteorological factors on influenza incidence among children in Guangzhou China, 2019-2022

Objective

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.

Methods

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.

Results

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.

Conclusion

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.

Spatial distribution and driving factors of the associations between temperature and influenza-like illness in the United States: a time-stratified case-crossover study

BACKGROUND

Several previous studies investigated the associations between temperature and influenza in a single city or region without a national picture. The attributable risk of influenza due to temperature and the corresponding driving factors were unclear. This study aimed to evaluate the spatial distribution characteristics of attributable risk of Influenza-like illness (ILI) caused by adverse temperatures and explore the related driving factors in the United States.

METHODS

ILI, meteorological factors, and PM_2.5 of 48 states in the United States were collected during 2011-2019. The time-stratified case-crossover design with a distributed lag non-linear model was carried out to evaluate the association between temperature and ILI at the state level. The multivariate meta-analysis was performed to obtain the combined effects at the national level. The attributable fraction (AF) was calculated to assess the ILI burden ascribed to adverse temperatures. The ordinary least square model (OLS), spatial lag model (SLM), and spatial error model (SEM) were utilized to identify driving factors.

RESULTS

A total of 7,716,115 ILI cases were included in this study. Overall, the temperature was negatively associated with ILI risk, and lower temperature gave rise to a higher risk of ILI. AF ascribed to adverse temperatures differed across states, from 49.44% (95% eCI: 36.47% ~ 58.68%) in Montana to 6.51% (95% eCI: -6.49% ~ 16.46%) in Wisconsin. At the national level, 29.08% (95% eCI: 27.60% ~ 30.24%) of ILI was attributable to cold. Per 10,000 dollars increase in per-capita income was associated with the increment in AF (OLS: β = -6.110, P = 0.021; SLM: β = -5.496, P = 0.022; SEM: β = -6.150, P = 0.022).

CONCLUSION

The cold could enhance the risk of ILI and result in a considerable proportion of ILI disease burden. The ILI burden attributed to cold varied across states and was higher in those states with lower economic status. Targeted prevention programs should be considered to lower the burden of influenza.