We offer a rationale and method for devising expectations needed to answer the question: did a population’s response to intra-pandemic deaths coincide with more non-COVID-19 deaths than expected from the efficacy of its response to all-cause deaths before the pandemic? These new-signal, prior-response expectations led us to answer that, for example, the response by German public health agencies and clinicians, which included impeded human-to-human contact, did not coincide with greater non-COVID-19 deaths than expected from the efficacy of their response to pre-pandemic all-cause deaths.
We acknowledge that deaths shown in Fig. 1 appear to drift below expected during 5 weeks of “shutdown” (i.e., weeks 16 through 20) and above expected later in the year when public resistance to social-distancing policies increased. We note, however, that social-distancing policies, albeit of varying stringency, applied throughout the 42 weeks and that, as our test results imply, the sum of differences between expected and observed non-COVID-19 deaths over the 42 weeks did not differ from expected. We, therefore, would resist the post-hoc suspicion that impeding human-to-human contact reduced non-COVID-19 deaths.
Artifacts of the data we used may have affected our results. Defining COVID-19 deaths remains, as noted above, subject to human judgement and error. We note, however, that accounting policies did not change during our test period implying that systematic errors unlikely affected temporal variation in our series. Our data will also fail to capture non-COVID-19 deaths that occurred after the test period but may have been averted had human to human contact been greater during the pre-vaccine pandemic.
We could repeat our analyses for sub-categories of mortality and would likely find some for which the new-signal, same-response expectations appeared less than the observed values implying that social distancing may have reduced the efficacy of pre-pandemic interventions. We note, however, that reconciling that result with our main finding would logically require discovering causes of death for which the expectation appeared greater than the observed value. Social distancing, in other words, would have decreased the likelihood of some other cause or causes of death.
We used process-control logic and methods to answer the question: did Germany’s social distancing policies coincide with more non-COVID-19 deaths than expected from the efficacy of its response to all-cause deaths before the pandemic? The “pandemic studies” literature includes many attempts to answer a related but fundamentally different question: did the pandemic coincide with more deaths than expected from history ? Answering this question requires estimating deaths that process-control logic would characterize as “same-signal, same-response” expectations because neither deaths nor policies during the pandemic era affect their derivation. Researchers have derived “same-signal, same-response” expectations using several methods, including “stacked calendars” [16, 17] and exponential smoothing , drawn from the forecasting literature. These approaches would not serve our purposes because answering our question requires expectations affected by deaths observed during the pandemic (i.e., that react to a new signal). Unlike Box-Jenkins methods, moreover, neither “stacked calendars” nor exponential smoothing was intended to identify and exploit all forms of autocorrelation. Expectations based on them may not, therefore, reflect the efficacy of pre-pandemic clinical and public health policies in reducing autocorrelation in deaths (i.e., not fully capture the pre-pandemic response).