Dataset Information

Independent association between meteorological factors, PM2.5, and seasonal influenza activity in Hangzhou, Zhejiang province, China.

ABSTRACT:

Background

Due to variations in climatic conditions, the effects of meteorological factors and PM_2.5 on influenza activity, particularly in subtropical regions, vary in existing literature. In this study, we examined the relationship between influenza activity, meteorological parameters, and PM_2.5 .

Methods

A total of 20 165 laboratory-confirmed influenza cases in Hangzhou, Zhejiang province, were documented in our dataset and aggregated into weekly counts for downstream analysis. We employed a combination of the quasi-Poisson-generalized additive model and the distributed lag non-linear model to examine the relationship of interest, controlling for long-term trends, seasonal trends, and holidays.

Results

A hockey-stick association was found between absolute humidity and the risk of influenza infections. The overall cumulative adjusted relative risk (ARR) was statistically significant when weekly mean absolute humidity was low (<10 µg/m³ ) and high (>17.5 µg/m³ ). A slightly higher ARR was observed when weekly mean temperature reached over 30.5°C. A statistically significantly higher ARR was observed when weekly mean relative humidity dropped below 67%. ARR increased statistically significantly with increasing rainfall. For PM_2.5 , the ARR was marginally statistically insignificant. In brief, high temperature, wet and dry conditions, and heavy rainfall were the major risk factors associated with a higher risk of influenza infections.

Conclusions

The present study contributes additional knowledge to the understanding of the effects of various environmental factors on influenza activities. Our findings shall be useful and important for the development of influenza surveillance and early warning systems.

SUBMITTER: Lau SY

PROVIDER: S-EPMC8189232 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:The interactions between PM2.5 and meteorological factors play a crucial role in air pollution analysis. However, previous studies that have researched the relationships between PM2.5 concentration and meteorological conditions have been mainly confined to a certain city or district, and the correlation over the whole of China remains unclear. Whether spatial and seasonal variations exist deserves further research. In this study, the relationships between PM2.5 concentration and meteorological factors were investigated in 68 major cities in China for a continuous period of 22 months from February 2013 to November 2014, at season, year, city, and regional scales, and the spatial and seasonal variations were analyzed. The meteorological factors were relative humidity (RH), temperature (TEM), wind speed (WS), and surface pressure (PS). We found that spatial and seasonal variations of their relationships with PM2.5 exist. Spatially, RH is positively correlated with PM2.5 concentration in north China and Urumqi, but the relationship turns to negative in other areas of China. WS is negatively correlated with PM2.5 everywhere except for Hainan Island. PS has a strong positive relationship with PM2.5 concentration in northeast China and mid-south China, and in other areas the correlation is weak. Seasonally, the positive correlation between PM2.5 concentration and RH is stronger in winter and spring. TEM has a negative relationship with PM2.5 in autumn and the opposite in winter. PS is more positively correlated with PM2.5 in autumn than in other seasons. Our study investigated the relationships between PM2.5 and meteorological factors in terms of spatial and seasonal variations, and the conclusions about the relationships between PM2.5 and meteorological factors are more comprehensive and precise than before. We suggest that the variations could be considered in PM2.5 concentration prediction and haze control to improve the prediction accuracy and policy efficiency.

Project description:BackgroundHand-foot-mouth disease (HFMD) is caused by a group of enteroviruses (EVs) and has a high incidence in children; some subtypes had high mortalities in children. The subtypes of HFMD had a different incidence across seasons. Thereby, we suspect that the infection of HFMD is varied by meteorological factors. However, studies examining serotype-specific associations between meteorological factors and HFMD incidence were rare.MethodsWe obtained all HFMD cases that occurred from 1 January 2010 to 31 December 2018 in Zhejiang province from the China Information System for Disease Control and Prevention (CISDCP). Daily meteorological data for Zhejiang province were provided by the China Methodological Data Sharing Service System and linked to HFMD cases based on residential addresses and dates of onset. The associations between meteorological factors and HFMDs were examined using distributed lag non-linear models (DLNMs) for each serotype.ResultsOverall, the incidences of all HFMD cases were increasing in study years, while the number of severe and fatality cases were decreasing. The dominant serotypes varied by study year. The association between temperature and incidence of both CVA16 and EV71 serotypes showed an inverted U shape. The risk ratio for CVA16 was increasing when temperature is 11-25°C, reaching the maximum RR at 18°C and humidity above 77% can promote the occurrence with CVA16, and temperature between 11 and 32°C with the maximum RR at 21°C and relative humidity above 77% are risk conditions of the occurrence of HFMD associated with EV71. For other enteroviruses causing HFMD, temperature above 11°C and humidity above 76% have a risk effect. CVA16, EV71, and all enteroviruses of HFMD have a maximum effect on lag day 0, and temperature is 35, 34, and 33°C respectively, while the enteroviruses of HFMD other than EV71 and CVA16 has a maximum effect when the temperature is 33°C and the lag time is 7 days.ConclusionThis study shows that meteorological factors have an effect on the occurrence of different HFMD serotypes. Local control strategies for public health should be taken in time to prevent and reduce the risk of HFMD while the weather is getting warmer and wetter.

Project description:BACKGROUND:Zhejiang Province has the fifth-highest incidence of severe fever with thrombocytopenia syndrome (SFTS) in China. While the top four provinces are all located in northern and central China, only Zhejiang Province is located in the Yangtze River Delta region of southeast China. This study was undertaken to identify the epidemiological characteristics of SFTS in Zhejiang from 2011 to 2018. METHODS:The epidemic data from SFTS cases in Zhejiang Province from January 2011 to December 2018 were obtained from the China Information Network System of Disease Prevention and Control. Meteorological data were collected from the China Meteorological Data Sharing Service System. A multivariate time series model was used to analyze the heterogeneity of spatial-temporal transmission of the disease. Random forest analysis was performed to detect the importance of meteorological factors and the dose-response association of the incidence of SFTS with these factors. RESULTS:In total, 412 SFTS cases (49 fatal) were reported from January 2011 to December 2018 in Zhejiang Province, China. The number of SFTS cases and the number of affected counties increased year by year. The case fatality rate in Zhejiang Province was 11.89%, which was the highest in China. Elderly patients and farmers were the most affected. The total effect values of the autoregressive component, spatiotemporal component and endemic component of the model in all ranges were 0.4580, 0.0377 and 0.0137, respectively. There was obvious heterogeneity across counties for the mean values of the spatiotemporal component and the autoregressive component. The autoregressive component was obviously the main factor driving the occurrence of SFTS, followed by the spatiotemporal component. The importance scores of the monthly mean pressure, mean temperature, mean relative humidity, mean two-minute wind speed, duration of sunshine and precipitation were 10.64, 8.34, 8.16, 6.37, 5.35 and 2.81, respectively. The relationship between these factors and the incidence of SFTS is complicated and nonlinear. A suitable range of meteorological factors for this disease was also detected. CONCLUSIONS:The autoregressive and spatiotemporal components played an important role in driving the transmission of SFTS. Targeted preventive efforts should be made in different areas based on the main component contributing to the epidemic. For most areas, early measures several months ahead of the suitable season for the occurrence of SFTS should be implemented. The level of reporting and diagnosis of this disease should be further improved.