Dataset Information

Airborne particulate matter, population mobility and COVID-19: a multi-city study in China.

ABSTRACT:

Background

Coronavirus disease 2019 (COVID-19) is an emerging infectious disease, which has caused numerous deaths and health problems worldwide. This study aims to examine the effects of airborne particulate matter (PM) pollution and population mobility on COVID-19 across China.

Methods

We obtained daily confirmed cases of COVID-19, air particulate matter (PM_2.5, PM₁₀), weather parameters such as ambient temperature (AT) and absolute humidity (AH), and population mobility scale index (MSI) in 63 cities of China on a daily basis (excluding Wuhan) from January 01 to March 02, 2020. Then, the Generalized additive models (GAM) with a quasi-Poisson distribution were fitted to estimate the effects of PM₁₀, PM_2.5 and MSI on daily confirmed COVID-19 cases.

Results

We found each 1 unit increase in daily MSI was significantly positively associated with daily confirmed cases of COVID-19 in all lag days and the strongest estimated RR (1.21, 95% CIs:1.14 ~ 1.28) was observed at lag 014. In PM analysis, we found each 10 μg/m³ increase in the concentration of PM₁₀ and PM_2.5 was positively associated with the confirmed cases of COVID-19, and the estimated strongest RRs (both at lag 7) were 1.05 (95% CIs: 1.04, 1.07) and 1.06 (95% CIs: 1.04, 1.07), respectively. A similar trend was also found in all cumulative lag periods (from lag 01 to lag 014). The strongest effects for both PM₁₀ and PM_2.5 were at lag 014, and the RRs of each 10 μg/m³ increase were 1.18 (95% CIs:1.14, 1.22) and 1.23 (95% CIs:1.18, 1.29), respectively.

Conclusions

Population mobility and airborne particulate matter may be associated with an increased risk of COVID-19 transmission.

SUBMITTER: Wang B

PROVIDER: S-EPMC7576551 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background: In classrooms high concentrations of particulate matter PM10 were measured. It is unknown whether the hazard of indoor particles is similar to that of the better studied outdoor particles. This study therefore analyzed adverse biological effects of classroom in comparison to outdoor PM10. Methods: Samples were taken from six schools during teaching hours. Genome-wide gene expression in human bronchial BEAS-2B epithelial cells was analyzed, and regulated genes were verified by quantitative PCR. Polycyclic aromatic hydrocarbons (PAH), endotoxin, and cat allergen Fel d 1 were analyzed with standard methods. Enhancement of allergic reactivity by PM10 was confirmed with CD63 upregulation in human primary basophils. Acceleration of human blood coagulation was determined with supernatants of PM10-exposed human peripheral blood monocytes. Results: Indoor PM10 induced SERPINB2 (involved in blood coagulation) and inflammatory genes (like CXCL6, CXCL1, IL6, IL8, all p<0.001). Outdoor PM10 induced xenobiotic metabolizing enzymes (CYP1A1, CYP1B1, TIPARP, all p<0.001). The induction of inflammatory genes by indoor PM10 could be explained by endotoxin (indoor 128.5±42.2EU/mg versus outdoor 13.4±21.5EU/mg, p<0.001), the induction of CYP by outdoor PAH (indoor 8.3±4.9ng/mg versus outdoor 16.7±15.2ng/mg, p<0.01). The induction of SERPINB2 was confirmed by a more rapid human blood coagulation (p<0.05). Indoor PM10 had no effect on the allergic reactivity from human primary basophils, except in cat allergic individuals. This was explained by varying Fel d 1 concentrations in indoor PM10 (p<0.001). Conclusions: Indoor PM10, compared to outdoor PM10, was 6 times higher, had a different composition, and on an equal weight basis induced more inflammatory and allergenic reactions, and accelerated blood coagulation. Outdoor PM10 had significantly lower effects, but induced detoxifying enzymes. Therefore, preliminary interventions for the reduction of classroom PM10 seem reasonable, perhaps by intensified ventilation.

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