scholarly journals Yearly and Daily Relationship Assessment between Air Pollution and Early-Stage COVID-19 Incidence: Evidence from 231 Countries and Regions

2021 ◽  
Vol 10 (6) ◽  
pp. 401
Author(s):  
Yuan Meng ◽  
Man Sing Wong ◽  
Hanfa Xing ◽  
Mei-Po Kwan ◽  
Rui Zhu
Keyword(s):  
Air Pollution ◽  
Early Stage ◽  
Additive Model ◽  
Global Scale ◽  
Linear Relationships ◽  
Non Linear ◽  
Air Pollutions ◽  
Novel Coronavirus ◽  
Relationship Assessment ◽  
Relationship Of

The novel coronavirus disease 2019 (COVID-19) has caused significantly changes in worldwide environmental and socioeconomics, especially in the early stage. Previous research has found that air pollution is potentially affected by these unprecedented changes and it affects COVID-19 infections. This study aims to explore the non-linear association between yearly and daily global air pollution and the confirmed cases of COVID-19. The concentrations of tropospheric air pollution (CO, NO2, O3, and SO2) and the daily confirmed cases between 23 January 2020 and 31 May 2020 were collected at the global scale. The yearly discrepancies of air pollutions and daily air pollution are associated with total and daily confirmed cases, respectively, based on the generalized additive model. We observed that there are significant spatially and temporally non-stationary variations between air pollution and confirmed cases of COVID-19. For the yearly assessment, the number of confirmed cases is associated with the positive fluctuation of CO, O3, and SO2 discrepancies, while the increasing NO2 discrepancies leads to the significant peak of confirmed cases variation. For the daily assessment, among the selected countries, positive linear or non-linear relationships are found between CO and SO2 concentrations and the daily confirmed cases, whereas NO2 concentrations are negatively correlated with the daily confirmed cases; variations in the ascending/declining associations are identified from the relationship of the O3-confirmed cases. The findings indicate that the non-linear relationships between global air pollution and the confirmed cases of COVID-19 are varied, which implicates the needs as well as the incorporation of our findings in the risk monitoring of public health on local, regional, and global scales.

scholarly journals Non-linear Relationships Between the Built Environment and Walking Frequency Among Older Adults in Zhongshan, China

2021 ◽  
Vol 9 ◽  
Author(s):  
Jiani Wu ◽  
Chunli Zhao ◽  
Chaoyang Li ◽  
Tao Wang ◽  
Lanjing Wang ◽  
...  
Keyword(s):  
Older Adults ◽  
Land Use ◽  
Built Environment ◽  
Green Space ◽  
Additive Model ◽  
Walking Behavior ◽  
Old Adults ◽  
Linear Relationships ◽  
Walking Activity ◽  
Non Linear

Aim: Promoting walking activity is an effective way to improve the health of older adults. Walking frequency is a critical component of walking behavior and an essential determinant of daily walking levels. To decipher the association between the built environment and walking frequency among older adults, this study's aims are as follows: (1) to empirically test whether non-linear relationships between the two exist, and (2) to identify the thresholds of the built environment characteristics that promote walking.Methods: The walking frequency of old adults was derived from the Zhongshan Household Travel Survey (ZHTS) in 2012. The sample size of old adults aged 60 or over was 4784 from 274 urban and rural neighborhoods. A semi-parametric generalized additive model (GAMM) is used to analyze the non-linear or non-monotonic relationships between the built environment and the walking frequency among older adults.Results: We found that non-linear relationships exist among five out of the six built environment characteristics. Within certain thresholds, the population density, sidewalk density, bus stop density, land use mixture, and the percentage of green space are positively related to older adults' walking trips. Furthermore, the land use mixture and the percentage of green space show an inverse “V”-shaped relationship.Conclusions: Built environment features can either support or hinder the walking frequency among older adults. The findings in the current study contribute to effective land use and transport policies for promoting active travel among older adults.

scholarly journals The association between ambient air pollution and scarlet fever in Qingdao, China, 2014-2018: a quantitative analysis

2020 ◽  
Author(s):  
Xiaowen Hu ◽  
Tao Wei ◽  
Yalin Han ◽  
Jing Jia ◽  
Bei Pan ◽  
...  
Keyword(s):  
Air Pollution ◽  
Scarlet Fever ◽  
Mixed Model ◽  
Linear Time ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
Lag Effects ◽  
Distributed Lag ◽  
Non Linear ◽  
Air Pollutions

Abstract Background: We conducted a distributed lag non-linear time series analysis to quantify the association between air pollution and scarlet fever in Qingdao city during 2014-2018. Methods: A generalized additive Mixed Model (GAMM) combined with a distributed lag non-linear model (DLNM) was applied to quantify the distributed lag effects of air pollutions on scarlet fever, with daily incidence of scarlet fever as the dependent variable and air pollutions as the independent variable adjusted for potential confounders. Results: A total of 6,316 cases of scarlet fever were notified, and there were 376 days occurring air pollution during the study period. Scarlet fever was significantly associated with air pollutions at a lag of 7 days with different RRs of air pollution degrees (1.172, 95%CI: 1.038-1.323 in mild air pollution; 1.374, 95%CI: 1.078-1.749 in moderate air pollution; 1.610, 95%CI: 1.163-2.314 in severe air pollution; 1.887, 95%CI: 1.163-3.061 in most severe air pollution). Conclusions: Our findings show that air pollution is positively associated with scarlet fever in Qingdao, and the risk of scarlet fever could be increased along with the degrees of air pollution. It contributes to developing strategies to prevent and reduce health impact from scarlet fever and other non-vaccine-preventable respiratory infectious diseases in air polluted areas.

scholarly journals Repurposing the Natural Compound for Antiviral During an Epidemic -a Case Study on the Drug Repurpose of Natural Compounds to Treat COVID-19

2020 ◽  
Author(s):  
Zhihao Wang ◽  
Chi Xu ◽  
Bing Liu ◽  
Nan Qiao
Keyword(s):  
Molecular Docking ◽  
In Silico ◽  
Natural Compound ◽  
Early Stage ◽  
Drug Repurposing ◽  
The United States ◽  
Natural Compounds ◽  
Global Scale ◽  
Novel Coronavirus ◽  
Approved Drugs

<p>The pandemic caused by the novel coronavirus SARS-CoV-2 is rapidly spreading and infecting the population on the global scale, it is a global health threat due to its high infection rate, high mortality and the lack of clinically approved drugs and vaccines for treating the disease (COVID-19). Utilising the published structures and homologue remodelling for proteins from SARS-CoV-2, an <i>in silico</i> molecular docking based screening was conducted and deposited in the Shennong project database. The results from the screening could be used to explain the clinical observation of repurposing the Ritonavir and Lopinavir to treat patients in the early stage of COVID-19 infection, and the prescription of Remdisivir in the United States as the therapy. Additionally, this molecular docking identified natural compound candidates for drug repurposing. This <i>in silico </i>molecular docking screen may be used for the initatial evaluation and rationalisation for drug repurposing of other potential candidates, especially other natural compounds from traditional Chinese medicines.</p>

scholarly journals Association between COVID-19 lockdown policies and air pollution with associated mortality reduction in Europe

2021 ◽  
Author(s):  
Rochelle Schneider ◽  
Pierre Masselot ◽  
Ana Maria Vicedo-Cabrera ◽  
Francesco Sera ◽  
Marta Blangiardo ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Pollutant ◽  
Linear Mixed Effect Model ◽  
Mixed Effect ◽  
Pollution Levels ◽  
European Cities ◽  
Linear Relationships ◽  
Wide Range ◽  
Non Linear ◽  
Policy Measures

&lt;p&gt;Governments were enforced to respond to SARS-CoV-2 virus spread by taking a wide range of policy measures. Several studies have reported a decrease in air pollution following the enforcement of lockdown measures during the first wave of the COVID-19 pandemic. However, these investigations were mostly based on simple pre-post comparisons using past years as a reference, and did not assess the role of different policy interventions. These responses offered an unprecedented opportunity to assess the effectiveness of several interventions to reduce air pollution levels worldwide. Using an accurate representation of business-as-usual and lockdown air pollution scenarios, provided by Copernicus Atmosphere Monitoring Service (CAMS), we quantitatively evaluated the association between policies responses to the COVID-19 pandemic with changes in NO&lt;sub&gt;2&lt;/sub&gt;, O&lt;sub&gt;3&lt;/sub&gt;, PM&lt;sub&gt;2.5&lt;/sub&gt;, and PM&lt;sub&gt;10&lt;/sub&gt; levels in 47 European cities. We also estimated the short-term mortality in the period of February-July 2020. An advanced spatio-temporal Bayesian non-linear mixed effect model was performed to determine the association between air pollutant levels and stringency indices as well as individual policy measures. The results indicate non-linear relationships, with a stronger decrease in NO&lt;sub&gt;2&lt;/sub&gt; and to a lesser extent PM&lt;sub&gt;10&lt;/sub&gt; and PM&lt;sub&gt;2.5&lt;/sub&gt; at very strict policy levels. Differences across interventions were also identified, actions linked to school/workplace closure, limitations on gatherings, and stay-at-home requirements had strong effects, while restrictions on internal movement and international travels showed little impact. The observed decrease in pollution potentially resulted in hundreds of avoided deaths across the European cities. This project provides information that can help inform future policies on air pollution reduction.&lt;/p&gt;

scholarly journals The association between ambient air pollution and scarlet fever in Qingdao, China, 2014-2018: a quantitative analysis

2020 ◽  
Author(s):  
Xiaowen Hu ◽  
Tao Wei ◽  
Yalin Han ◽  
Jing Jia ◽  
Bei Pan ◽  
...  
Keyword(s):  
Air Pollution ◽  
Scarlet Fever ◽  
Mixed Model ◽  
Linear Time ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
Lag Effects ◽  
Distributed Lag ◽  
Non Linear ◽  
Air Pollutions

Abstract Background: We conducted a distributed lag non-linear time series analysis to quantify the association between air pollution and scarlet fever in Qingdao city during 2014-2018. Methods: A generalized additive Mixed Model (GAMM) combined with a distributed lag non-linear model (DLNM) was applied to quantify the distributed lag effects of air pollutions on scarlet fever, with daily incidence of scarlet fever as the dependent variable and air pollutions as the independent variable adjusted for potential confounders. Results: A total of 6,316 cases of scarlet fever were notified, and there were 376 days occurring air pollution during the study period. Scarlet fever was significantly associated with air pollutions at a lag of 7 days with different RRs of air pollution degrees (1.172, 95%CI: 1.038-1.323 in mild air pollution; 1.374, 95%CI: 1.078-1.749 in moderate air pollution; 1.610, 95%CI: 1.163-2.314 in severe air pollution; 1.887, 95%CI: 1.163-3.061 in most severe air pollution). Conclusions: Our findings show that air pollution is positively associated with scarlet fever in Qingdao, and the risk of scarlet fever could be increased along with the degrees of air pollution. It contributes to developing strategies to prevent and reduce health impact from scarlet fever and other non-vaccine-preventable respiratory infectious diseases in air polluted areas.

scholarly journals Non-linear Relationships Between Density and Demographic Traits of Aedes

2021 ◽  
Author(s):  
Logan A. Sauers ◽  
Kelsey E. Hawes ◽  
Steven A. Juliano
Keyword(s):  
Population Growth ◽  
Empirical Relationship ◽  
Initial Density ◽  
Rate Of Change ◽  
Adult Size ◽  
Linear Relationships ◽  
Non Linear ◽  
Per Capita ◽  
Relationship Of ◽  
The Relationship

Abstract Understanding the relationship of population dynamics to density is central to many ecological investigations. Despite the importance of density-dependence in determining population growth, the empirical relationship between density and per capita growth remains understudied in most systems and is often assumed to be linear. In experimental studies of interspecific competition, investigators often evaluate the predicted outcomes by assuming such linear relationships, fitting linear functions, and estimating parameters of competition models. In this paper, we tested experimentally the shape of the relationship between estimated population rate of change and initial density using laboratory-reared populations of three mosquito species. We estimated per capita growth rate for these experimental populations over a thirty-fold range of larval densities at a standard resource abundance. We then compared fits of linear models and several different nonlinear models for the relationship of estimated rate of change and density. We find that that the relationship between density and per capita growth is strongly non-linear in all three mosquitoes. Components of population growth (survivorship, development time, adult size) are also nonlinearly related to initial density. The causes and consequences of this nonlinearity are likely to be important issues for population and community ecology.

scholarly journals The association between ambient air pollution and scarlet fever in Qingdao, China, 2014–2018: a quantitative analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Fachun Jiang ◽  
Tao Wei ◽  
Xiaowen Hu ◽  
Yalin Han ◽  
Jing Jia ◽  
...  
Keyword(s):  
Air Pollution ◽  
Scarlet Fever ◽  
Mixed Model ◽  
Linear Time ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
Lag Effects ◽  
Distributed Lag ◽  
Non Linear ◽  
Air Pollutions

Abstract Background We conducted a distributed lag non-linear time series analysis to quantify the association between air pollution and scarlet fever in Qingdao city during 2014–2018. Methods A distributed lag non-linear model (DLNM) combined with a generalized additive mixed model (GAMM) was applied to quantify the distributed lag effects of air pollutions on scarlet fever, with daily incidence of scarlet fever as the dependent variable and air pollutions as the independent variable adjusted for potential confounders. Results A total of 6316 cases of scarlet fever were notified, and there were 376 days occurring air pollution during the study period. Scarlet fever was significantly associated with air pollutions at a lag of 7 days with different relative risk (RR) of air pollution degrees [1.172, 95% confidence interval (CI): 1.038–1.323 in mild air pollution; 1.374, 95% CI 1.078–1.749 in moderate air pollution; 1.610, 95% CI 1.163–2.314 in severe air pollution; 1.887, 95% CI 1.163–3.061 in most severe air pollution]. Conclusions Our findings show that air pollution is positively associated with scarlet fever in Qingdao, and the risk of scarlet fever could be increased along with the degrees of air pollution. It contributes to developing strategies to prevent and reduce health impact from scarlet fever and other non-vaccine-preventable respiratory infectious diseases in air polluted areas.

scholarly journals Robust association between short-term ambient PM2.5 exposure and COVID prevalence in India

2020 ◽  
Author(s):  
Prachi Singh ◽  
Sagnik Dey ◽  
Bhavesh Purohit ◽  
Kuldeep Dixit ◽  
Sikim Chakraborty
Keyword(s):  
Air Pollution ◽  
Fine Particulate Matter ◽  
Additive Model ◽  
Positive Association ◽  
Short Term ◽  
Significant Positive Association ◽  
Uncertainty Interval ◽  
Novel Coronavirus ◽  
Particulate Matter Exposure ◽  
Transmission Information

Abstract Novel coronavirus (COVID) outbreak is the deadliest pandemic in our lifetime. The COVID prevalence risk may be enhanced due to comorbidity from other health risk factors like air pollution. However, such evidence is still lacking in India. Using daily confirmed cases, ambient PM2.5 (fine particulate matter) exposure and meteorological parameters from 28 major states of India between March 14-June 9, 2020, in a generalized additive model, we estimate the association between short-term PM2.5 exposure and daily COVID confirmed cases. We find that a 10 mg m-3 increase in ambient PM2.5 exposure (with a lag of 0-14 days) is significantly associated with an increased COVID incidence [relative risk (RR) of 1.135 (95% uncertainty interval: 1.091-1.180)] after adjusting for the meteorological factors. A non-linear association between PM2.5 (lag 0-14) and COVID infection predicts an RR of 4.482 (3.357-5.983) for exposure at 60 mg m-3 relative to 25 mg m-3. Our results indicate a significant positive association between ambient PM2.5 exposure and COVID prevalence in India. As India is easing lockdown measures, higher outdoor air pollution may have implications on COVID transmission, information which can be helpful for general public and policymakers alike.

scholarly journals Repurposing the Natural Compound for Antiviral During an Epidemic -a Case Study on the Drug Repurpose of Natural Compounds to Treat COVID-19

2020 ◽  
Author(s):  
Zhihao Wang ◽  
Chi Xu ◽  
Bing Liu ◽  
Nan Qiao
Keyword(s):  
Molecular Docking ◽  
In Silico ◽  
Natural Compound ◽  
Early Stage ◽  
Drug Repurposing ◽  
The United States ◽  
Natural Compounds ◽  
Global Scale ◽  
Novel Coronavirus ◽  
Approved Drugs

<p>The pandemic caused by the novel coronavirus SARS-CoV-2 is rapidly spreading and infecting the population on the global scale, it is a global health threat due to its high infection rate, high mortality and the lack of clinically approved drugs and vaccines for treating the disease (COVID-19). Utilising the published structures and homologue remodelling for proteins from SARS-CoV-2, an <i>in silico</i> molecular docking based screening was conducted and deposited in the Shennong project database. The results from the screening could be used to explain the clinical observation of repurposing the Ritonavir and Lopinavir to treat patients in the early stage of COVID-19 infection, and the prescription of Remdisivir in the United States as the therapy. Additionally, this molecular docking identified natural compound candidates for drug repurposing. This <i>in silico </i>molecular docking screen may be used for the initatial evaluation and rationalisation for drug repurposing of other potential candidates, especially other natural compounds from traditional Chinese medicines.</p>

scholarly journals The association between ambient air pollution and scarlet fever in Qingdao, China, 2014-2018: a quantitative analysis

2019 ◽  
Author(s):  
Xiaowen Hu ◽  
Tao Wei ◽  
Yalin Han ◽  
Jing Jia ◽  
Bei Pan ◽  
...  
Keyword(s):  
Air Pollution ◽  
Scarlet Fever ◽  
Mixed Model ◽  
Linear Time ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
Lag Effects ◽  
Distributed Lag ◽  
Non Linear ◽  
Air Pollutions

Abstract Background: We conducted a distributed lag non-linear time series analysis to quantify the association between air pollution and scarlet fever in Qingdao city during 2014-2018. Methods: A generalized additive Mixed Model (GAMM) combined with a distributed lag non-linear model (DLNM) was applied to quantify the distributed lag effects of air pollutions on scarlet fever, with daily incidence of scarlet fever as the dependent variable and air pollutions as the independent variable adjusted for potential confounders. Results: A total of 6,316 cases of scarlet fever were notified, and there were 376 days occurring air pollution during the study period. Scarlet fever was significantly associated with air pollutions at lag 7 days with different RRs of air pollution degrees (1.172, 95%CI: 1.038-1.323 in mild air pollution; 1.374, 95%CI: 1.078-1.749 in moderate air pollution; 1.610, 95%CI: 1.163-2.314 in severe air pollution; 1.887, 95%CI: 1.163-3.061 in most severe air pollution). Conclusions: Our findings show that air pollution is positively associated with scarlet fever in Qingdao. Moreover, the risk of scarlet fever could be increased along with the degrees of air pollution. It contributes to developing strategies to prevent and reduce health impact from scarlet fever and other non-vaccine-preventable respiratory infectious diseases in air polluted areas.

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