Fig. 6: Time-varying causal graphs highlighting how the causal relationships between air pollutants, COVID-19 infection, and other key variables (in particular, public health policy interventions) change before and after the peak in infections during each pandemic wave. | Humanities and Social Sciences Communications

Fig. 6: Time-varying causal graphs highlighting how the causal relationships between air pollutants, COVID-19 infection, and other key variables (in particular, public health policy interventions) change before and after the peak in infections during each pandemic wave.

From: Interpretable AI-driven causal inference to uncover the time-varying effects of PM2.5 and public health interventions on COVID-19 infection rates

Fig. 6

a Time-varying causal graphs highlighting PM2.5. b Time-varying causal graphs highlighting NO2. c Time-varying causal graphs highlighting O3. d Time-varying causal graphs highlighting school closure. e Time-varying causal graphs highlighting public transport closure.

Back to article page