Table 2 Association between long-term exposure to air pollution and risk, severity, incidence, and lethality for COVID-19 Pandemic

Yao Y et al. [52], June 2020

*Associations between PM and CFR of COVID-19

*49 Chinese cities, spatial analysis

CFR

Pollutants (10 μg/m³ increase in and concentrations)- COVID-19 CFR increased by:

*Long-term (2015–2019):

• PM_2.5: 0.61% (0.09–1.12%) and

• PM₁₀: 0.33% (0.03–0.64%) respectively.

PM pollution distribution and its association with COVID-19 CFR suggests that exposure to such may affect COVID-19 prognosis.

Hendryx M et al. [65], October 2020

Pollution data (PM_2.5, DPM, O₃) from the US Environmental Protection Agency Environmental Justice Screen, May 31, 2020 with 2014–2019

Cumulative prevalence and fatality rates

Estimate (SE), p-value.

(Note: PM_2.5 is one pollutant model.

others, all indictors considered simultaneously)

*Pollutants/ sources and COVID-19 Prevalence

• PM_2.5: 23.5, p = .02

• O₃: 2.36 (3.29) p = .47

• Diesel PM: 237 (55.8) p = .001

• PM_2.5minus DPM: 8.96 (10.8) p = .40

• Traffic: − 0.20 (.06) p = .02

• NPL sites: − 5.59 (113) p = .96

• TSDFs: − 1.75 (4.95) p = .72

• RMP sites: 56.7 (22.6) p = .01

*Pollutants/ sources and COVID-19 Death

• PM_2.5: 1.08 (.54) p = .05

• Ozone: 0.10 (.17) p = .54

• Diesel PM: 18.7 (2.80) p = .001

• PM_2.5 minus DPM: 0.20 (.56) p = .72

• Traffic − 0.01 (.003) p = .001

• NPL sites: 3.76 (5.65) p = .51

• TSDFs: 0.52 (.25) p = .04

• RMP sites: − 0.83 (1.14) p = .47

Areas with worse prior air quality, especially higherconcentrations of diesel exhaust, may be at greater COVID-19 risk, although further studies are needed to confirm these relationships.

Fattorini D et al. [66], September 2020

Data on COVID-19 outbreak in Italian provinces and corresponding long-term air quality evaluations (four years), obtained from Italian and European agencies. Updated April 27, 2020

frequency and severity of cases (spread)

*Pollutants (average)-Incidence of COVID-19

• NO₂: r = 0.4969, p < 0.01, (2016–2017)

• PM_2.5: r = 0.5827, p < 0.01, (2016–2017)

• O₃: r = 0.5142, p < 0.01 (2017–2016)

• PM₁₀: r = 0.4127, p < 0.05.(2017–2017)

• PM₁₀: r = 05168, p < 0.01 (2016–2017)

*Long-term air-quality data significantly correlated with cases of COVID-19 in up to 71 Italian provinces

Atmospheric and environmental pollution should be considered as part of an integrated approach for sustainable development, human health protection and prevention of epidemic spreads but in a long-term

Konstantinoudis G et al. [67], December 2020

Long-term exposure to NO₂ and PM_2.5 (2014–2018 from the Pollution Climate Mapping) on COVID-19 deaths up to June 30, 2020 in England using high geographical resolution.

Death

Pollutants (1 μg/m3 increase)-COVID-19 Mortality rate:

*Unadjusted

• NO₂: 2·6% (95%CrI: 2·4%-2·7%)

• PM_2.5: 4·4% (3·7%-5·1%)

*Adjust for spatial autocorrelation and confounders

• NO₂: 0.5% (95% credible interval: − 0.2-1.2%)

• PM_2.5: 1.4% (− 2.1–5.1%).

some evidence of an effect of long-term NO₂ exposure on COVID-19 mortality, while the effect of PM2.5 remains more uncertain

Liang D et al. [68], October 2020

Cross-sectional nationwide study using zero- inflated negative binomial models to estimate the association between long-term (2010–2016) county-level exposures to NO₂, PM_2.5 and O₃ and county-level COVID-19 in the US.

CFR, Mortality

*Single Pollutant Model (estimate, 95%CI, p-value)

COVID-19 CFR vs Mortality

• NO₂: 1.12, (1.05–1.18), 0.0003 vs 1.17, (1.10 to 1.25), < 0.0001

• PM_2.5: 1.09, (0.96 to 1.23), 0.19 vs 1.19, (1.04 to 1.37), 0.012

• O₃: 0.99, (0.93 to 1.06), 0.74 vs 1.00, (0.93 to 1.08), 0.95

*3- Pollutant Model (estimate, 95%CI, p-value)

COVID-19 CFR vs Mortality

• NO₂: 1.11, (1.05 to 1.18), 0.0005 vs 1.16, (1.09 to 1.24), < 0.0001

• PM_2.5: 1.06, (0.93 to 1.20), 0.39 vs 1.15, (1.00 to 1.32), 0.051

• O₃: 0.98, (0.91 to 1.04), 0.48 vs 0.98, (0.91 to 1.05), 0.55

*Per IQR increase-COVID-19 CFR vs Mortality

• NO₂ (4.6 ppb): increase of 11.3% (95% CI 4.9 to 18.2%) vs 16.2% (95% CI

8.7 to 24.0%)

• PM_2.5 (2.6 μg/m³) marginally associated with 14.9% (95% CI 0.0 to 31.9%)increase mortality rate.

*Long-term exposure to NO₂, which largely arises from urban combustion sources such as traffic, may enhance susceptibility to severe COVID-19 outcomes, independent of long-term PM_2.5 and O₃ exposure.

*The results support targeted public health actions to protect residents from COVID-19 in heavily polluted regions with historically high NO₂ levels.

Wu X et al. [69], November 2020

A nationwide, cross-sectional study using county-level data for long-term average exposure to PM_2.5 and risk of COVID-19 death in the US (≥ 3000 counties, representing 98% of the population) up to April 22, 2020 from Johns Hopkins University

Mortality

PM_2.5-COVID-19 Mortality:

• MRR: 1.11 (1.06, 1.17)

• 1 μg/m³ associated with an 11% (95% CI: 6, 17%) increase in death rate

*A small increase in long-term exposure to PM_2.5leads to a large increase in the COVID-19 death rate. *Despite the ecological study design, importance of continuing to enforce existing air pollution regulations to protect human health both during and after the COVID-19 crisis.

Vasquez-Apestegui et al. [56], July 2020

Levels of PM_2.5 exposure in the previous years (2010–2016) in 24 districts of Lima with the cases, deaths, and case-fatality rates of COVID-19.

Incidence, CFR and mortality

* PM_2.5 (estimate, 95%CI) and COVID-19:

• Case/population density: 0.070**, (0.034–0.107)

• Death/ population density: 0.0014*, (0.0006–0.0023)

• CFR: − 0.022, (− 0.067–0.023)

Note: p < 0.05; **p < 0.01.

The higher rates of COVID-19 in Metropolitan Lima is attributable, among others, to the increased PM_2.5 exposure in the previous years

Coker ES et al. [70], August 2020

Ecologic association between long-term concentrations of area-level of PM_2.5 (2015–2019) and excess deaths in the first quarter of 2020 in municipalities of Northern Italy.

Excess mortality

* PM_2.5 (estimate, SE)-COVID-19 Excess Deaths

• No geographical effects: 0.128*** (0.008)

• Regional fixed effects: 0.085*** (0.009)

• LLS random effects: 0.089*** (0.014)

• Regional fixed effects and LLS: 0.089*** (0.014)

• 1 μg/m³ increase= > 9% (95% CI: 6–12%)*** increase in mortality.

Note: ***p < 0.01, **p < 0.05, *p < 0.1

Positive association of ambient PM_2.5 concentration on excess mortality in Northern Italy related to the COVID-19 epidemic.

Cole et al. [71], August 2020

Ecological association between long-term concentrations of of PM_2.5 NO₂, SO₂ (2015–2019) and COVID-19 in 355 municipalities in Netherlands (National Institute for Public Health and the Environment)

Death, incidence and hospital admission

*Average 5 years (estimate, SE)=>

COVID-19 cases:

• PM_2.5: 0.11*(0.051)

• NO₂: 0.027*(0.012)

• SO₂: 0.11 (0.079)

COVID-19 admissions

• PM_2.5: 0.15*(0.065)

• NO₂: 0.015 (0.013)

• SO₂: 0.055 (0.065)

COVID-19 deaths

• PM_2.5: 0.23**(0.073)

• NO₂: 0.035*(0.016)

• SO₂: 0.18 (0.10)

Note: ***p < 0.001, **p < 0.01, *p < 0.05

Pollutants (1 μg/m3 increase)-COVID-19 Cases:

• PM_2.5: 9.4 (95%CI: 1.1,17.7)

• NO₂: 2.2 (95%CI: 0.2,4.3)

Admissions

• PM_2.5: 3.0 (95%CI: 0.43, 5.6)

Deaths

• PM_2.5: 2.3 (95%CI: 0.87,3.6)

• NO₂: 0.35 (95%CI: 0.042,0.66)

Relationship between COVID-19 and PM_2.5 persists even when a wide

range of control variables are included and a number of different estimation methods used.

Gupta A et al. [72], July 2020

Data related to 9 Asian cities analysed to assess the link between mortality rate in the infected cases and the air pollution (WHO databases 2007–2016)

Mortality

Percentage of mortality per reported COVID-19 cases

• Log10 (PM_2.5): coef, SE, p: 5.747, 2.169, 0.033

• Log10 (PM₁₀): coef, SE, p: 3.226, 1.811, 0.118

Percentage mortality per reported COVID-19 cases

• PM_2.5 (R² = 50.1% and R² Adj = 42.9%)

• PM₁₀ (R² = 31.2% and R² Adj = 24.1%).

Positive correlation indicating air pollution to be an elemental andconcealed factor in aggravating the global burden of deaths related to COVID-19

Pacheco H et al. [73], July 2020

Spatio-temporal variations in NO₂ concentrations in 12 highly populated cities in Ecuador by comparing NO₂ tropospheric concentrations before (March 2019) and after (March 2020) the COVID-19 lockdown.

Incidence, Mortality

NO₂-COVID-19:

• Cases: r = 0.88; p < 0.001

• Deaths: r = 0.91; p < 0.001

• Death per Capita: r = 0.84; p < 0.01

*Reduction in NO₂ of up to 22–23% in the most highly populated cities in Ecuador (Quito and Guayaquil) after the lockdown caused by the outbreak of COVID-19.

*Crucial role played by air quality as regards human health.

Saha J et al. [54], July 2020

Data from the 4th round of the National Family Health Survey 2015–16, and from the Ministry of Health and Family Welfare on 18th May 2020 to assess link between pre-existing morbidity conditions and IAP and COVID-19 among under-five children in India

Risk factor current fatality and recovery rate

Mean (SD) composite risk score of different indicators of indoor domestic smoky environment with COVID-19:

• CFR: 2.5 (2.5)

• Non-Recovery Rate: 47.5 (18.6)

From a research viewpoint, there is a prerequisite need for epidemiological studies to investigate the connection between indoor air pollution and pre-existing morbidity which are associated with COVID-19.

Rodriguez-Diaz CE et al. [74], July 2020

Comparison of predictors of COVID-19 cases and deaths between disproportionally Latino counties (> 17.8% Latino population) and all other counties through May 11, 2020.

Incidence, Death.

* PM_2.5-COVID-19 Rate ratios (third vs. first quartile):

• Cases: RR(95%CI): 1.028 (0.918, 1.151)

• Deaths: RR(95%CI): 1.230 (1.028, 1.471)

Structural factors place Latino populations and particularly monolingual Spanish speakers at elevated risk for COVID-19 acquisition.