“Inferring change points in the spread of COVID-19 reveals the effectiveness of interventions”

J. Dehning et al., Science 369, eabb9789 (2020). DOI: 10.1126/science.abb9789

Source code and data.

Note: This is not a classical approach to assessing strength of interventions using either counterfactuals or other kinds of causal inference. Accordingly, the argument for the effectiveness of interventions is weaker than it might be.

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This entry was posted in American Association for the Advancement of Science, American Statistical Association, Bayesian, Bayesian computational methods, causal inference, causation, changepoint detection, coronavirus, counterfactuals, COVID-19, epidemiology, SARS-CoV-2, state-space models, statistical series, time series. Bookmark the permalink.

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