The burden of influenza and pneumonia mortality attributable to absolute humidity among elderly people in Chongqing, China, 2012–2018

Li, Qi; Gao, Yuan; Yang, Jun; Ding, Xianbin; Xiong, Yingfei; Su, Kun; Liu, Tian; Li, Qin; Tang, Wenge; Liu, Qiyong

doi:10.1016/j.scitotenv.2020.136682

Cited by 27 publications

(20 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…With the latitude of 29.6°N and a subtropical climate with four distinct seasons, Chongqing is the largest municipality with over 30 million registered inhabitants in China. Our previous studies demonstrated a substantial in uenza mortality burden in Chongqing 4 , and absolute humidity has a signi cant impact on in uenza and pneumonia mortality among elderly people 5 . However, it remains unclear whether other meteorological factors such as temperature, relative humidity, precipitation, wind speed and sunshine affect the activity of in uenza.…”

Section: Introductionmentioning

confidence: 93%

Effect of meteorological factors on the activity of influenza in Chongqing, China, 2012–2019

Liu

Gao

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

Background: The effects of multiple meteorological factors on influenza activity remain unclear in Chongqing, the largest municipality in China. We aimed to fix this gap in this study.Methods: Weekly meteorological data and influenza surveillance data in Chongqing were collected from 2012 to 2019. Distributed lag nonlinear models (DLNMs) were conducted to estimate the effects of multiple meteorological factors on influenza activity.Results: Inverted J-shaped nonlinear associations between mean temperature, wind speed, sunshine and influenza activity were found. The relative risks (RRs) of influenza activity increased as weekly average mean temperature fell below 18.18℃, average wind speed fell below 1.55 m/s and average sunshine fell below 2.36 hours. Taking the median values as the references, lower temperature and windless could significantly increase the risks of influenza activity and last for 4 weeks. A J-shaped nonlinear association was observed between relative humidity and influenza activity; the risk of influenza activity increased with rising relative humidity with 78.26% as the break point. Taking the median value as the reference, high relative humidity could increase the risk of influenza activity and last for 3 weeks. In addition, we found the relationship between aggregate rainfall and influenza activity could be described with a U-shaped curve. Rainfall effect has significantly higher RR than rainless effect.Conclusions: Our study shows that multiple meteorological factors have strong associations with influenza activity in Chongqing, providing evidence for developing a meteorology-based early warning system for influenza to facilitate timely response to upsurge of influenza activity.

show abstract

Section: Introductionmentioning

confidence: 93%

Effect of meteorological factors on the activity of influenza in Chongqing, China, 2012–2019

Liu

Gao

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…3 which depicted the maximum, minimum, 1 st quartile, median and 3 rd quartile values. Absolute humidity (AH, g/m 3 ), which is considered as the mass of water in a unit volume of air, was estimated through dry bulb temperature, dew point temperature and relative humidity using the derived equation with the assumptions of standard atmospheric pressure of the study area (Qi et al, 2020;H. Xu et al, 2014 .…”

Section: Data Collectionmentioning

confidence: 99%

“…The impact of air pollutants and meteorological factors have been demonstrated to evaluate human-to-human contact, which could rise the risk of COVID-19 infections (Auler et al, 2020;Bashir et al, 2020;Briz-redón and Serranoaroca, 2020;Chan et al, 2020). Besides, the droplets transmission from human to human has a significant effect on increase in number of COVID -9 infected cases, association of air pollutants and meteorological parameters have shown significant correlations with COVID-19 infections (Fattorini and Regoli, 2020;Frontera et al, 2020;Muhammad et al, 2020;Ogen, 2020;Qi et al, 2020;Wang and Su, 2020;Xie and Zhu, 2020). The impact of air pollution in increasing number of COVID-19 cases lacks careful attention and research.…”

Section: Introductionmentioning

confidence: 99%

Significance between Air pollutants, Meteorological Factors and COVID-19 Infections: Probable Evidences in India

Sahoo

2020

Preprint

View full text Add to dashboard Cite

SARS-CoV-2 (Coronavirus) disease represents the causative agent with a potentially fatal risk which is having great global human health concern. Earlier studies suggested that air pollutants and meteorological factors were considered as the risk factors for acute respiratory infection, which carries harmful pathogens and affects the immunity. The study intended to explore the correlation between air pollutants, meteorological factors and the daily reported infection cases caused by novel coronavirus in India. The daily positive infected cases, air pollution and meteorological factors in 288 districts were collected from January 30, 2020 to April 23, 2020 in India. Speraman’s correlation and generalised additive model were applied to investigate the correlations of four air pollutants (PM2.5, PM10, NO2 and SO2) and eight meteorological factors (Temp, DTR, RH, AH, AP, RF, WS and WD) with COVID-19 infected cases. The study indicated that a 10 µg/m3 increase during (Lag0-14) in PM2.5, PM10 and NO2 was resulted in 2.21% (95%CI: 1.13 to 3.29), 2.67% (95% CI: 0.33 to 5.01) and 4.56 (95% CI: 2.22 to 6.90) increase in daily counts of COVID 19 infected cases respectively. However, only 1 unit increase in meteorological factor levels in case of daily mean temperature and DTR during (Lag0-14) associated with 3.78% (95%CI: 1.81 to 5.75) and 1.82% (95% CI: -1.74 to 5.38) rise of COVID-19 infected cases respectively. In addition, SO2 and relative humidity were negatively associated with COVID-19 infected cases at Lag0-14 with decrease of 7.23% (95% CI: -10.99 to -3.47) and 1.11% (95% CI: -3.45 to 1.23) for SO2 and for relative humidity respectively. The study recommended that there is significant relationship between air pollutants and meteorological factors with COVID-19 infected cases, which substantially explain the effect of national lockdown and suggested positive implications for control and prevention of the spread of SARS-CoV-2 disease.

show abstract

“…A 1 °C increase in temperature and a 1% increase in RH is related to 3.08% death rate reduction and 0.85% reduction of daily new cases of COVID-19 infection (Wu et al 2020 ). Qi et al ( 2020b ) used the generalized additive model (GAM) to compute the province-specific relations among climatological factors and daily cases of COVID-19 in China. The study found that temperature and humidity presented negative associations with COVID-19, while a significant association between temperature and humidity existed.…”

Section: Introductionmentioning

confidence: 99%

“…The study found that temperature and humidity presented negative associations with COVID-19, while a significant association between temperature and humidity existed. Temperate countries and regions with low humidity should be taken more considerate (Qi et al 2020b ). Ma et al ( 2020 ) established a daily number of COVID-19 death with meteorological variables and air pollutant datasets in Wuhan, China, which was the starting point of the global pandemic.…”

Section: Introductionmentioning

confidence: 99%

Are meteorological factors enhancing COVID-19 transmission in Bangladesh? Novel findings from a compound Poisson generalized linear modeling approach

Islam

Hasanuzzaman

Shammi

et al. 2020

Environ Sci Pollut Res

View full text Add to dashboard Cite

Novel coronavirus (SARS-CoV-2) causing COVID-19 disease has arisen to be a pandemic. Since there is a close association between other viral infection cases by epidemics and environmental factors, this study intends to unveil meteorological effects on the outbreak of COVID-19 across eight divisions of Bangladesh from March to April 2020. A compound Poisson generalized linear modeling (CPGLM), along with a Monte-Carlo method and random forest (RF) model, was employed to explore how meteorological factors affecting the COVID-19 transmission in Bangladesh. Results showed that subtropical climate (mean temperature about 26.6 °C, mean relative humidity (MRH) 64%, and rainfall approximately 3 mm) enhanced COVD-19 onset. The CPGLM model revealed that every 1 mm increase in rainfall elevated by 30.99% (95% CI 77.18%, − 15.20%) COVID-19 cases, while an increase of 1 °C of diurnal temperature (TDN) declined the confirmed cases by − 14.2% (95% CI 9.73%, − 38.13%) on the lag 1 and lag 2, respectively. In addition, NRH and MRH had the highest increase (17.98% (95% CI 22.5%, 13.42%) and 19.92% (95% CI: 25.71%, 14.13%)) of COVID-19 cased in lag 4. The results of the RF model indicated that TDN and AH (absolute humidity) influence the COVID-19 cases most. In the Dhaka division, MRH is the most vital meteorological factor that affects COVID-19 deaths. This study indicates the humidity and rainfall are crucial factors affecting the COVID-19 case, which is contrary to many previous studies in other countries. These outcomes can have policy formulation for the suppression of the COVID-19 outbreak in Bangladesh.

show abstract

The burden of influenza and pneumonia mortality attributable to absolute humidity among elderly people in Chongqing, China, 2012–2018

Cited by 27 publications

References 29 publications

Effect of meteorological factors on the activity of influenza in Chongqing, China, 2012–2019

Effect of meteorological factors on the activity of influenza in Chongqing, China, 2012–2019

Significance between Air pollutants, Meteorological Factors and COVID-19 Infections: Probable Evidences in India

Are meteorological factors enhancing COVID-19 transmission in Bangladesh? Novel findings from a compound Poisson generalized linear modeling approach

Contact Info

Product

Resources

About