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Expectations of non-COVID-19 deaths during the pre-vaccine pandemic: a process-control approach
Ralph Catalano1, Joan A Casey2, Alison Gemmill3
1School of Public Health, University of California, Berkeley, CA, 94720, USA. rayc@berkeley.edu.
Background:
Debate over "social distancing" as a response to the pandemic includes the claim that disrupting clinical and public health programming dependent on human-to-human contact increased non-COVID-19 deaths. This claim warrants testing because novel pathogens will continue to emerge. Tests, however, appear frustrated by lack of a convention for estimating non-COVID-19 deaths that would have occurred had clinical and public health programming during the pre-vaccine pandemic remained as efficacious as in the pre-pandemic era. Intending to hasten the emergence of such a convention, we describe and demonstrate "new-signal, prior-response expectations" suggested by research and methods at the intersection of epidemiology and process control engineering.
Methods:
Using German data, we estimate pre-pandemic public health efficacy by applying Box-Jenkins methods to 271 weekly counts of all-cause deaths from December 29 2014 through March 8 2020. We devise new-signal, prior-response expectations by applying the model to weekly non-COVID-19 deaths from March 9 2020 through December 26 2020.
Results:
The COVID-19 pandemic did not coincide with more non-COVID-19 deaths than expected from the efficacy of responses to pre-pandemic all-cause deaths.
Conclusions:
New-signal, prior-response estimates can contribute to evaluating the efficacy of public health programming in reducing non-COVID-19 deaths during the pre-vaccine pandemic.
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