TABLE 4.
Author | Country | Period | Analysis method | Quantified results |
---|---|---|---|---|
Liu et al 2 | 9 countries (China, Japan, Korea, Canada, America, Russia, England, Germany, France) | 21 Jan to 20 May 2020 | Discontinuous linear regression | O3 presents a more pronounced positive effect on COVID‐19 infection in more countries (such as Japan, Canada, America, Russia, France, etc). |
Zhu et al 49 | China (120 cities) | 23 Jan to 29 Feb 2020 | Generalized additive model | Per 10 mg/m3 increase in O3 was associated with 4.76% (95% CI: 1.99‐7.52) increase in the daily counts of confirmed cases, respectively. |
Fronza et al 53 | Europe (47 regional capitals and 107 major Italian)cities) | 10 Feb to 10 Apr 2020 | Artificial neural network | O3 was negatively associated with number of COVID‐19 cases per million (r = −0.44). |
Travaglio et al 56 | UK | 2018‐2019 | Generalized linear models, negative binomial regression analyses | O3 was significantly associated with COVID‐19 deaths and cases at the sub regional level. |
Jiang et al 64 | China (Wuhan, Xiaogan, and Huanggang) | 25 Jan to 29 Feb 2020 | Multivariate Poisson's regression | O3 was negatively associated with daily COVID‐19 incidence in Wuhan (0.99, 95%CI: 0.989‐0.991) and Xiaogan (0.991, 95%CI: 0.989‐0.993) and positively associated with daily COVID‐19 incidence in Huanggang (1.016, 95%CI: 1.012‐1.02). |
Liang et al 70 | USA (3 122 US counties) | 22 Jan to 29 Apr 2020 | Zero‐inflated negative binomial models | No significant associations between O3 and COVID‐19 cases. |
Adhikari et al 79 | New York, USA | 1 Mar to 20 Apr 2020 | Negative binomial regression mode | A one‐unit increase in O3 was associated with a 10.51% (95%CI: 7.47‐13.63) increase in the daily new COVID‐19 cases. |
Zoran et al 71 | Milan, Italy | 1 Jan to 30 Apr 2020 | Time series analysis | COVID‐19 infections showed a positive correlation with ground level O3. |
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