An Italian individual-level data study investigating on the association between air pollution exposure and Covid-19 severity in primary-care setting

Pégoraro, V.; Heiman, Franca; Levante, Antonella; Urbinati, D.; Peduto, I.

doi:10.21203/rs.3.rs-244278/v1

Cited by 6 publications

(9 citation statements)

References 13 publications

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“…Daily residential air quality data at the census tract level was further averaged to assign exposure levels during shorter- and longer-term periods prior to the month of COVID-19 diagnosis. 1-month averaged exposures were used as representative of shorter-term exposure ( Chen et al, 2016 ; Fouladi et al, 2020 ; Pegoraro et al, 2021 ) and 1-year averaged exposures were used as longer-term exposures.…”

Section: Methodsmentioning

confidence: 99%

Ambient air pollution and COVID-19 incidence during four 2020–2021 case surges

Sidell

Chen

Huang

et al. 2022

Environmental Research

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Background Air pollution exposure may make people more vulnerable to COVID-19 infection. However, previous studies in this area mostly focused on infection before May 2020 and long-term exposure. Objective To assess both long-term and short-term exposure to air pollution and COVID-19 incidence across four case surges from 03/1/2020 to 02/28/2021. Methods The cohort included 4.6 million members from a large integrated health care system in southern California with comprehensive electronic medical records (EMR). COVID-19 cases were identified from EMR. Incidence of COVID-19 was computed at the census tract-level among members. Prior 1-month and 1-year averaged air pollutant levels (PM 2.5 , NO 2 , and O 3 ) at the census tract-level were estimated based on hourly and daily air quality data. Data analyses were conducted by each wave: 3/1/2020–5/31/2020, 6/1/202–9/30/2020, 10/1/2020–12/31/2020, and 1/1/2021–2/28/2021 and pooled across waves using meta-analysis. Generalized linear mixed effects models with Poisson distribution and spatial autocorrelation were used with adjustment for meteorological factors and census tract-level social and health characteristics. Results were expressed as relative risk (RR) per 1 standard deviation. Results The cohort included 446,440 COVID-19 cases covering 4609 census tracts. The pooled RRs (95% CI) of COVID-19 incidence associated with 1-year exposures to PM 2.5 , NO 2 , and O 3 were 1.11 (1.04, 1.18) per 2.3 μg/m 3 ,1.09 (1.02, 1.17) per 3.2 ppb, and 1.06 (1.00, 1.12) per 5.5 ppb respectively. The corresponding RRs (95% CI) associated with prior 1-month exposures were 1.11 (1.03, 1.20) per 5.2 μg/m 3 for PM 2.5 , 1.09 (1.01, 1.17) per 6.0 ppb for NO 2 and 0.96 (0.85, 1.08) per 12.0 ppb for O 3 . Conclusion Long-term PM 2.5 and NO 2 exposures were associated with increased risk of COVID-19 incidence across all case surges before February 2021. Short-term PM 2.5 and NO 2 exposures were also associated. Our findings suggest that air pollution may play a role in increasing the risk of COVID-19 infection.

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Section: Methodsmentioning

confidence: 99%

Ambient air pollution and COVID-19 incidence during four 2020–2021 case surges

Sidell

Chen

Huang

et al. 2022

Environmental Research

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“… Pegoraro et al (2021) , citing Setti et al (2020a , c) [47,26] and Martelletti L, Martelletti P [5]: “One of the ideas underneath the potential relationship between airborne PM and Covid-19 diffusion is that the atmospheric PM might exercise a carrier action along with the virus [5, 26]. Setti and colleagues recently demonstrated the presence of the SARS-CoV-2 RNA on PM [47].”…”

Section: Citation Networkmentioning

confidence: 99%

“…54 were involved in spreading the misconception ( Al Huraimel et al, 2020 ; Amoatey et al, 2020 ; Arslan et al, 2020 ; Baron, 2021 ; Borak, 2020 ; Cao et al, 2021 ; Carraturo et al, 2020 ; Chen et al, 2021 ; Coccia, 2020a , b ; Comunian et al, 2020 ; Copat et al, 2020 ; Dettori et al, 2020 ; Domingo and Rovira, 2020 ; Dunker et al, 2021 ; Gaddi and Capello, 2020 ; He and Han, 2021 ; Ho et al, 2021 ; Ingram et al, 2021 ; Kayalar et al, 2021 ; Kumar et al, 2021 ; Linillos-Pradillo et al, 2021 ; Lorenzo et al, 2021 ; Maleki et al, 2021 ; Marquès et al, 2021 ; Martelletti and Martelletti, 2020 ; Mehmood et al, 2021 ; Mukherjee et al, 2021 ; Nor et al, 2021 ; Pegoraro et al, 2021 ; Poyraz et al, 2021 ; Prather et al, 2020 ; Qu et al, 2020 ; Ram et al, 2021 ; Sanità di Toppi et al, 2020 ; Shao et al, 2021 ; Sharma et al, 2020 ; Senatore et al, 2021 ; Setti et al, 2020a -f; Tang et al, 2020 ; Trancossi et al, 2021 ; Tretiakow et al, 2021 ; Tung et al, 2021 ; van der Valk and In 't Veen, 2021 ; Varotsos et al, 2021 ; Wang et al, 2020a , b ; Xu et al, 2020 ; Zhang et al, 2020a , c ; Zhu et al, 2021 ; Zoran et al, 2020 );…”

Section: Citation Networkmentioning

confidence: 99%

“SARS-CoV-2 is transmitted by particulate air pollution”: Misinterpretations of statistical data, skewed citation practices, and misuse of specific terminology spreading the misconception

Ishmatov

2022

Environmental Research

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In epidemiology, there are still outdated myths associated with the spread of respiratory infections. Recently, we have witnessed the origination of a new misconception, to the effect that SARS-CoV-2 is transmitted in the open air by way of particulate air pollution (atmospheric particulate matter (PM)). There is no evidence to support the idea behind this misconception. Nevertheless, more and more people are involved in animated debate and the number of studies concerning atmospheric PM as a carrier of SARS-CoV-2 is growing rapidly. In this work, the origin of the misconception was investigated, and the published papers which have contributed to the spread of this myth were analyzed. The results show that the following factors lie behind the origin and spread of the misconception: a) The specific terminology is not always clearly defined or consistently used by scientists. In particular, the terms ‘particulate matter’, ‘atmospheric aerosol particles’, ‘air pollutants’, and ‘atmospheric aerosols’ need to be clarified, and besides they are often equated to ‘infectious aerosols’, ‘virus-bearing aerosols’, ‘bio-aerosols’, ‘virus-laden particles’, ‘respiratory aerosol/droplets’, and ‘droplet nuclei’. b) Authors misinterpret statistical data and information from other sources. Interpretation of the correlation between PM levels and the increasing incidence and severity of COVID-19 infection, is often changed from “PM may reflect the indirect action of certain atmospheric conditions that maintain infectious nuclei suspended for prolonged periods, parameters that also act on atmospheric pollutants” to “PM could cause an increase in infectious droplets/aerosols containing SARS-CoV-2.” This is a dramatic change to the meaning. Moreover, it is often not taken into account that PM may reflect activities in areas with high population density and this population density at the same time contributes to the spread COVID-19. c) Skewed citation practices. Many authors cite a hypothetical conclusion from an original study, then other authors cite the papers of these authors as primary sources. This practice leads to the effect that there are many witnesses to a ‘phenomenon’ that did not ever occur. Thus, the terminology used in interdisciplinary communications should be more nuanced and defined precisely. Authors should be more careful when citing unconfirmed data (and hypotheses) as well as in interpreting statistical data so as to avoid confusion and spreading false information. This is especially important now in the era of the COVID-19 pandemic.

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“…By analyzing the regional trends one by one, it can be observed that the "byoblu" web interest has increased over time except for Basilicata and Molise (Figure 2). Although a growing trend was already present, the novel coronavirus seems to have strongly impacted RSVs in Campania (𝛥 20…”

Section: Web Interest In Pre-existing Fake Newsmentioning

confidence: 99%

“…Conspiracy hypotheses, inadequate risk perception, and unjustified fears have already undermined non-pharmacological containment measures and can reduce the effectiveness of pharmacological ones [18]. Furthermore, these factors can compromise the management of equally serious problems such as pollution and climate change (often linked to COVID-19 incidence and mortality) [19][20][21]. Therefore, such a scenario requires careful surveillance of the online information flow as well as thoughtful communication.…”

Section: Introductionmentioning

confidence: 99%

The Impact of COVID-19 on Conspiracy Attitudes and Risk Perception in Italy: an Infodemiological Survey through Google Trends.

Rovetta¹

2021

Preprint

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Background: The novel coronavirus disease (COVID-19) caused the worst international crisis since World War II. Italy was one of the countries most affected by both the pandemic and the related infodemic. The success of anti-COVID-19 strategies and future public health policies in Italy cannot prescind from containment of fake news and divulgation of correct information.Objective: The aim of this paper is to analyze the impact of COVID-19 on conspiracy attitudes and risk perception of Italian web users.Methods: Google Trends was used to monitor users' web interest in specific topics, such as conspiracy hypotheses, vaccine side effects, and pollution/climate change. The keywords adopted to represent these topics were mined from Bufale.net – an Italian website specialized in detecting online hoaxes – and Google Trends suggestions (i.e., related topics and related queries). Relative search volumes of the timelapse 2016-2020 (pre-COVID-19) and 2020-2021 (post-COVID-19) were compared through percentage difference (∆_%) and Welch’s t-test (t). When data series were not stationary, other ad-hoc criteria were used. The trend slopes were assessed through Sen's Slope (SS). The significance thresholds have been indicatively set at P=.05 and t=1.9.Results: The COVID-19 pandemic drastically enforced Italian netizens' conspiracy attitudes (Δ_%∈[60,288],t∈[6,12]). The regional web interest towards conspiracy-related queries has increased and become more homogeneous compared to the pre-COVID-19 period ((RSV) ̅=80±2.8,t_min=1.8,Δ_(min%)=+12.4,min ∆_(SD%)=-25.8). Besides, a growing trend in web interest in the infodemic YouTube channel "ByoBlu" has been highlighted. The web interest in fake news has increased more than that in anti-hoax services (t_1=11.3 vs t_2=4.5,Δ_1=+157.6 vs Δ_2=+84.7). Equivalently, the web interest in vaccine side effects exceeded that in pollution/climate change (SS_vac=0.22,P<.001 vs SS_pol=0.05,P<.001,∆_%=+296.4).Conclusions: COVID-19 has given a significant boost to online conspiracy attitudes in Italy. In particular, the average web interest in conspiracy hypotheses has increased and become more uniform across regions. The pandemic accelerated an already growing trend in users' interest towards some fake news sources, including the 500,000 subscribers YouTube channel "ByoBlu" (canceled for disinformation in March 2021). The risk perception related to COVID-19 vaccines has been so distorted that vaccine side effects-related queries outweighed those relating to pollution and climate change, which are much more urgent issues. Based on these findings, it is necessary that the Italian authorities implement more effective infoveillance systems and communication by the mass media is less sensationalistic and more consistent with the available scientific evidence. In this context, Google Trends can be used to monitor the users' response to specific infodemiological countermeasures. Further research is needed to understand the psychological mechanisms that regulate risk perceptionKeywords: COVID-19, fake news, Google Trends, infodemiology, Italy, risk perception

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An Italian individual-level data study investigating on the association between air pollution exposure and Covid-19 severity in primary-care setting

Cited by 6 publications

References 13 publications

Ambient air pollution and COVID-19 incidence during four 2020–2021 case surges

Ambient air pollution and COVID-19 incidence during four 2020–2021 case surges

“SARS-CoV-2 is transmitted by particulate air pollution”: Misinterpretations of statistical data, skewed citation practices, and misuse of specific terminology spreading the misconception

The Impact of COVID-19 on Conspiracy Attitudes and Risk Perception in Italy: an Infodemiological Survey through Google Trends.

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