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• W4200043220 abstract "This research aims to look at the link between environmental pollutants and the coronavirus disease (COVID-19) outbreak in California. To illustrate the COVID-19 outbreak, weather, and environmental pollution, we used daily confirmed cases of COVID-19 patients, average daily temperature, and air quality Index, respectively. To evaluate the data from March 1 to May 24, 2020, we used continuous wavelet transform and then applied partial wavelet coherence (PWC), wavelet transform coherence (WTC), and multiple wavelet coherence (MWC). Empirical estimates disclose a significant association between these series at different time-frequency spaces. The COVID-19 outbreak in California and average daily temperature show a negative (out phase) coherence. Similarly, the air quality index and COVID-19 also show a negative association circle during the second week of the observed period. Our findings will serve as policy implications for state and health officials and regulators to combat the COVID-19 outbreak." @default.
• W4200043220 created "2021-12-31" @default.
• W4200043220 creator A5051306160 @default.
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• W4200043220 date "2021-12-23" @default.
• W4200043220 modified "2023-10-11" @default.
• W4200043220 title "Investigating the Co-movement Nexus Between Air Quality, Temperature, and COVID-19 in California: Implications for Public Health" @default.
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• W4200043220 doi "https://doi.org/10.3389/fpubh.2021.815248" @default.
• W4200043220 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35004602" @default.
• W4200043220 hasPublicationYear "2021" @default.
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