Please use this identifier to cite or link to this item: https://biore.bio.bg.ac.rs/handle/123456789/4158
Title: PM2.5 as a major predictor of COVID-19 basic reproduction number in the USA
Authors: Milicevic, Ognjen
Salom, Igor
Rodic, Andjela 
Marković Z. Sofija 
Tumbas Z. Marko 
Zigic, Dusan
Djordjevic, Magdalena
Djordjevic, Marko 
Keywords: COVID-19 pollution dependence;Outdoor air pollutants;Basic reproduction number;Principal component analysis;Machine learning
Issue Date: 24-Jun-2021
Rank: M21a
Journal: Environmental Research
Volume: 201
Start page: 111526
Abstract: 
Many studies have proposed a relationship between COVID-19 transmissibility
and ambient pollution levels. However, a major limitation in establishing such
associations is to adequately account for complex disease dynamics, influenced
by e.g. significant differences in control measures and testing policies.
Another difficulty is appropriately controlling the effects of other
potentially important factors, due to both their mutual correlations and a
limited dataset. To overcome these difficulties, we will here use the basic
reproduction number (R_0) that we estimate for USA states using non-linear
dynamics methods. To account for a large number of predictors (many of which
are mutually strongly correlated), combined with a limited dataset, we employ
machine-learning methods. Specifically, to reduce dimensionality without
complicating the variable interpretation, we employ Principal Component
Analysis on subsets of mutually related (and correlated) predictors. Methods
that allow feature (predictor) selection, and ranking their importance, are
then used, including both linear regressions with regularization and feature
selection (Lasso and Elastic Net) and non-parametric methods based on ensembles
of weak-learners (Random Forest and Gradient Boost). Through these
substantially different approaches, we robustly obtain that PM_2.5 is a
major predictor of R_0 in USA states, with corrections from factors such as
other pollutants, prosperity measures, population density, chronic disease
levels, and possibly racial composition. As a rough magnitude estimate, we
obtain that a relative change in R_0, with variations in pollution levels
observed in the USA, is typically ~30%, which further underscores the
importance of pollution in COVID-19 transmissibility.
URI: https://biore.bio.bg.ac.rs/handle/123456789/4158
ISSN: 0013-9351
DOI: 10.1016/j.envres.2021.111526
Appears in Collections:Journal Article

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