Interpretable AI-driven causal inference to uncover the time-varying effects of PM2.5 and public health interventions on COVID-19 infection rates
Abstract Although COVID-19 appears to be better controlled since its initial outbreak in 2020, it continues to threaten citizens in different communities due to the unpredictability of new strains. The global viral pandemic has resulted in over 700 million infections and 7 million deaths worldwide,...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer Nature
2024-12-01
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| Series: | Humanities & Social Sciences Communications |
| Online Access: | https://doi.org/10.1057/s41599-024-04202-y |
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