The ambient ozone and COVID-19 transmissibility in China: A data-driven ecological study of 154 cities.
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ABSTRACT:
SUBMITTER: Ran J
PROVIDER: S-EPMC7342057 | biostudies-literature | 2020 Sep
REPOSITORIES: biostudies-literature
Publications
The ambient ozone and COVID-19 transmissibility in China: A data-driven ecological study of 154 cities.
Ran Jinjun J Zhao Shi S Han Lefei L Chen Dieyi D Yang Zuyao Z Yang Lin L Wang Maggie H MH He Daihai D
The Journal of infection 20200708 3
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Project description:BackgroundExisting literatures demonstrated that meteorological factors could be of importance in affecting the spread patterns of the respiratory infectious diseases. However, how ambient temperature may influence the transmissibility of COVID-19 remains unclear.ObjectivesWe explore the association between ambient temperature and transmissibility of COVID-19 in different regions across China.MethodsThe surveillance data on COVID-19 and meteorological factors were collected from 28 provincial level regions in China, and estimated the instantaneous reproductive number (Rt). The generalized additive model was used to assess the relationship between mean temperature and Rt.ResultsThere were 12,745 COVID-19 cases collected in the study areas. We report the associated effect of temperature on Rt is likely to be negative but not of statistical significance, which holds for most Chinese regions.ConclusionsWe found little statistical evidence for that the higher temperature may reduce the transmissibility of COVID-19. Since intensive control measures against the COVID-19 epidemics were implemented in China, we acknowledge this may impact the underlying effect size estimation, and thus cautiousness should be taken when interpreting our findings.
| S-EPMC7713592 | biostudies-literature
Project description:BackgroundCoronavirus disease 2019 (COVID-19) has become a severe public health problem globally. Both epidemiological and laboratory studies have shown that ambient temperature could affect the transmission and survival of coronaviruses. This study aimed to determine whether the temperature is an essential factor in the infection caused by this novel coronavirus.MethodsDaily confirmed cases and meteorological factors in 122 cities were collected between January 23, 2020, to February 29, 2020. A generalized additive model (GAM) was applied to explore the nonlinear relationship between mean temperature and COVID-19 confirmed cases. We also used a piecewise linear regression to determine the relationship in detail.ResultsThe exposure-response curves suggested that the relationship between mean temperature and COVID-19 confirmed cases was approximately linear in the range of <3 °C and became flat above 3 °C. When mean temperature (lag0-14) was below 3 °C, each 1 °C rise was associated with a 4.861% (95% CI: 3.209-6.513) increase in the daily number of COVID-19 confirmed cases. These findings were robust in our sensitivity analyses.ConclusionsOur results indicate that mean temperature has a positive linear relationship with the number of COVID-19 cases with a threshold of 3 °C. There is no evidence supporting that case counts of COVID-19 could decline when the weather becomes warmer, which provides useful implications for policymakers and the public.
| S-EPMC7142675 | biostudies-literature
Project description:BackgroundFew large multicity studies have been conducted in developing countries to address the acute health effects of atmospheric ozone pollution.ObjectiveWe explored the associations between ozone and daily cause-specific mortality in China.MethodsWe performed a nationwide time-series analysis in 272 representative Chinese cities between 2013 and 2015. We used distributed lag models and over-dispersed generalized linear models to estimate the cumulative effects of ozone (lagged over 0-3 d) on mortality in each city, and we used hierarchical Bayesian models to combine the city-specific estimates. Regional, seasonal, and demographic heterogeneity were evaluated by meta-regression.ResultsAt the national-average level, a 10-μg/m3 increase in 8-h maximum ozone concentration was associated with 0.24% [95% posterior interval (PI): 0.13%, 0.35%], 0.27% (95% PI: 0.10%, 0.44%), 0.60% (95% PI: 0.08%, 1.11%), 0.24% (95% PI: 0.02%, 0.46%), and 0.29% (95% PI: 0.07%, 0.50%) higher daily mortality from all nonaccidental causes, cardiovascular diseases, hypertension, coronary diseases, and stroke, respectively. Associations between ozone and daily mortality due to respiratory and chronic obstructive pulmonary disease specifically were positive but imprecise and nonsignificant. There were no statistically significant differences in associations between ozone and nonaccidental mortality according to region, season, age, sex, or educational attainment.ConclusionsOur findings provide robust evidence of higher nonaccidental and cardiovascular mortality in association with short-term exposure to ambient ozone in China. https://doi.org/10.1289/EHP1849.
| S-EPMC5947936 | biostudies-literature
Project description:The effect of lockdown due to coronavirus disease (COVID-19) pandemic on air pollution in four Southern European cities (Nice, Rome, Valencia and Turin) and Wuhan (China) was quantified, with a focus on ozone (O3). Compared to the same period in 2017-2019, the daily O3 mean concentrations increased at urban stations by 24% in Nice, 14% in Rome, 27% in Turin, 2.4% in Valencia and 36% in Wuhan during the lockdown in 2020. This increase in O3 concentrations is mainly explained by an unprecedented reduction in NOx emissions leading to a lower O3 titration by NO. Strong reductions in NO2 mean concentrations were observed in all European cities, ~53% at urban stations, comparable to Wuhan (57%), and ~65% at traffic stations. NO declined even further, ~63% at urban stations and ~78% at traffic stations in Europe. Reductions in PM2.5 and PM10 at urban stations were overall much smaller both in magnitude and relative change in Europe (~8%) than in Wuhan (~42%). The PM reductions due to limiting transportation and fuel combustion in institutional and commercial buildings were partly offset by increases of PM emissions from the activities at home in some of the cities. The NOx concentrations during the lockdown were on average 49% lower than those at weekends of the previous years in all cities. The lockdown effect on O3 production was ~10% higher than the weekend effect in Southern Europe and 38% higher in Wuhan, while for PM the lockdown had the same effect as weekends in Southern Europe (~6% of difference). This study highlights the challenge of reducing the formation of secondary pollutants such as O3 even with strict measures to control primary pollutant emissions. These results are relevant for designing abatement policies of urban pollution.
| S-EPMC7237366 | biostudies-literature
Project description:Although short-term exposure to ambient ozone (O3) can cause poor respiratory health outcomes, the shape of the concentration-response (C-R) between O3 and respiratory morbidity has not been widely investigated. We estimated the effect of daily O3 on emergency department (ED) visits for selected respiratory outcomes in 5 US cities under various model assumptions and assessed model fit. Population-weighted average 8-h maximum O3 concentrations were estimated in each city. Individual-level data on ED visits were obtained from hospitals or hospital associations. Poisson log-linear models were used to estimate city-specific associations between the daily number of respiratory ED visits and 3-day moving average O3 levels controlling for long-term trends and meteorology. Linear, linear-threshold, quadratic, cubic, categorical, and cubic spline O3 C-R models were considered. Using linear C-R models, O3 was significantly and positively associated with respiratory ED visits in each city with rate ratios of 1.02-1.07 per 25 ppb. Models suggested that O3-ED C-R shapes were linear until O3 concentrations of roughly 60 ppb at which point risk continued to increase linearly in some cities for certain outcomes while risk flattened in others. Assessing C-R shape is necessary to identify the most appropriate form of the exposure for each given study setting.
| S-EPMC6301150 | biostudies-literature
Project description:BackgroundAntibiotic resistance leads to longer hospital stays, higher medical costs, and increased mortality. However, research into the relationship between climate change and antibiotic resistance remains inconclusive. This study aims to address the gap in the literature by exploring the association of antibiotic resistance with regional ambient temperature and its changes over time.MethodsData were obtained from the China Antimicrobial Surveillance Network (CHINET), monitoring the prevalence of carbapenem-resistant Acinetobacter baumannii (CRAB), Klebsiella pneumoniae (CRKP) and Pseudomonas aeruginosa (CRPA) in 28 provinces/regions over the period from 2005 to 2019. Log-linear regression models were established to determine the association between ambient temperature and antibiotic resistance after adjustment for variations in socioeconomic, health service, and environmental factors.FindingsA 1 °C increase in average ambient temperature was associated with 1.14-fold increase (95%-CI [1.07-1.23]) in CRKP prevalence and 1.06-fold increase (95%-CI [1.03-1.08]) in CRPA prevalence. There was an accumulative effect of year-by-year changes in ambient temperature, with the four-year sum showing the greatest effect on antibiotic resistance. Higher prevalence of antibiotic resistance was also associated with higher antibiotic consumption, lower density of health facilities, higher density of hospital beds and higher level of corruption.InterpretationHigher prevalence of antibiotic resistance is associated with increased regional ambient temperature. The development of antibiotic resistance under rising ambient temperature differs across various strains of bacteria.FundingThe National Key R&D Program of China (grant number: 2018YFA0606200), National Natural Science Foundation of China (grant number: 72074234), Fundamental Scientific Research Funds for Central Universities, P.R. China (grant number: 22qntd4201), China Medical Board (grant number: CMB-OC-19-337).
| S-EPMC9672962 | biostudies-literature
Project description:BackgroundThe new coronavirus disease COVID-19 began in December 2019 and has spread rapidly by human-to-human transmission. This study evaluated the transmissibility of the infectious disease and analyzed its association with temperature and humidity to study the propagation pattern of COVID-19.MethodsIn this study, we revised the reported data in Wuhan based on several assumptions to estimate the actual number of confirmed cases considering that perhaps not all cases could be detected and reported in the complex situation there. Then we used the equation derived from the Susceptible-Exposed-Infectious-Recovered (SEIR) model to calculate R0 from January 24, 2020 to February 13, 2020 in 11 major cities in China for comparison. With the calculation results, we conducted correlation analysis and regression analysis between R0 and temperature and humidity for four major cities in China to see the association between the transmissibility of COVID-19 and the weather variables.ResultsIt was estimated that the cumulative number of confirmed cases had exceeded 45 000 by February 13, 2020 in Wuhan. The average R0 in Wuhan was 2.7, significantly higher than those in other cities ranging from 1.8 to 2.4. The inflection points in the cities outside Hubei Province were between January 30, 2020 and February 3, 2020, while there had not been an obvious downward trend of R0 in Wuhan. R0 negatively correlated with both temperature and humidity, which was significant at the 0.01 level.ConclusionsThe transmissibility of COVID-19 was strong and importance should be attached to the intervention of its transmission especially in Wuhan. According to the correlation between R0 and weather, the spread of disease will be suppressed as the weather warms.
| S-EPMC7348130 | biostudies-literature
Project description:Land-sea atmosphere interaction (LSAI) is one of the important processes affecting ozone (O3) pollution in coastal areas. The effects of small-scale LSAIs like sea-land breezes have been widely studied. However, it is not fully clear how and to what extent the large-scale LSAIs affect O3 pollution. Here we explored an O3 episode to illuminate the role of large-scale LSAIs in O3 pollution over the Bohai-Yellow Seas and adjacent areas through observations and model simulations. The results show that the northern Bohai Sea's coastal region, influenced by the Mongolian High, initially experienced a typical unimodal diurnal O3 variation for three days, when O3 precursors from Beijing-Tianjin-Hebei, Shandong, and Northeast China were transported to the Bohai-Yellow Seas. Photochemical reactions generated O3 within marine air masses, causing higher O3 levels over the seas than coastal regions. As the Mongolian High shifted eastward and expanded, southerly winds on its western edge transported O3-rich marine air masses toward the coast, prolonging pollution for an additional three days and weakening diurnal variations. Subsequently, emissions from the Korean Peninsula and marine shipping significantly affected O3 levels in the northern Bohai Sea (10.7% and 13.7%, respectively). Notably, Shandong's emissions played a substantial role in both phases (27.5% and 26.1%, respectively). These findings underscore the substantial impact of large-scale LSAIs driven by the Mongolian High on O3 formation and pollution duration in coastal cities. This insight helps understand and manage O3 pollution in northern Bohai Sea cities and broadly applies to temperate coastal cities worldwide.
| S-EPMC10582397 | biostudies-literature
Project description:This study aims to explore the relationship between ambient NO2 levels and the transmission ability (basic reproductive number, R0) of COVID-19 in 63 Chinese cities. After adjustment for temperature and relative humidity, R0 was positively associated with NO2 concentration at city level. The temporal analysis within Hubei province indicated that all the 11 Hubei cities (except Xianning City) had significant positive correlations between NO2 concentration (with 12-day time lag) and R0 (r > 0.51, p < 0.005). Since the association between ambient NO2 and R0 indicated NO2 may increase underlying risk of infection in the transmission process of COVID-19. In addition, NO2 is also an indicator of traffic-related air pollution, the association between NO2 and COVID-19's spreadability suggest that reduced population movement may have reduced the spread of the SARS-CoV-2.
| S-EPMC7524685 | biostudies-literature
Project description:With the implementation of COVID-19 restrictions and consequent improvement in air quality due to the nationwide lockdown, ozone (O3) pollution was generally amplified in China. However, the O3 levels throughout the Guangxi region of South China showed a clear downward trend during the lockdown. To better understand this unusual phenomenon, we investigated the characteristics of conventional pollutants, the influence of meteorological and anthropogenic factors quantified by a multiple linear regression (MLR) model, and the impact of local sources and long-range transport based on a continuous emission monitoring system (CEMS) and the HYSPLIT model. Results show that in Guangxi, the conventional pollutants generally declined during the COVID-19 lockdown period (January 24 to February 9, 2020) compared with their concentrations during 2016-2019, while O3 gradually increased during the resumption (10 February to April 2020) and full operation periods (May and June 2020). Focusing on Beihai, a typical Guangxi region city, the correlations between the daily O3 concentrations and six meteorological parameters (wind speed, visibility, temperature, humidity, precipitation, and atmospheric pressure) and their corresponding regression coefficients indicate that meteorological conditions were generally conducive to O3 pollution mitigation during the lockdown. A 7.84 μg/m3 drop in O3 concentration was driven by meteorology, with other decreases (4.11 μg/m3) explained by reduced anthropogenic emissions of O3 precursors. Taken together, the lower NO2/SO2 ratios (1.25-2.33) and consistencies between real-time monitored primary emissions and ambient concentrations suggest that, with the closure of small-scale industries, residual industrial emissions have become dominant contributors to local primary pollutants. Backward trajectory cluster analyses show that the slump of O3 concentrations in Southern Guangxi could be partly attributed to clean air mass transfer (24-58%) from the South China Sea. Overall, the synergistic effects of the COVID-19 lockdown and meteorological factors intensified O3 reduction in the Guangxi region of South China.
| S-EPMC7588315 | biostudies-literature