A Literature Review and Meta Analysis of the Effects of Lockdowns on COVID 19 Mortality

<strong>the</strong> effect <strong>of</strong> lockdowns in <strong>the</strong>se studies might contain time-dependent shifts, such as seasonality.
This excludes studies like Bakolis et al. (2021) <strong>and</strong> Siedner et al. (2020).
Given our criteria, we exclude <strong>the</strong> much-cited paper by Flaxman et al. (2020), which claimed
that lockdowns saved three million lives in Europe. Flaxman et al. assume that <strong>the</strong> p<strong>and</strong>emic
would follow an epidemiological curve unless countries locked down. However, this assumption
means that <strong>the</strong> only interpretation possible for <strong>the</strong> empirical results is that lockdowns are <strong>the</strong> only
thing that matters, even if o<strong>the</strong>r factors like season, behavior etc. caused <strong>the</strong> observed change in
<strong>the</strong> reproduction rate, Rt. Flaxman et al. are aware <strong>of</strong> this <strong>and</strong> state that “our parametric form <strong>of</strong>
Rt assumes that changes in Rt are an immediate response to interventions ra<strong>the</strong>r than gradual
changes in behavior.” Flaxman et al. illustrate how problematic it is to force data to fit a certain
model if you want to infer <strong>the</strong> effect <strong>of</strong> lockdowns on COVID-19 mortality. 16
The counterfactual difference-in-difference studies in this review generally exploit variation
across countries, U.S. states, or o<strong>the</strong>r geographical jurisdictions to infer <strong>the</strong> effect <strong>of</strong> lockdowns
on COVID-19 fatalities. Preferably, <strong>the</strong> effect <strong>of</strong> lockdowns should be tested using r<strong>and</strong>omized
control trials, natural experiments, or <strong>the</strong> like. However, <strong>the</strong>re are very few studies <strong>of</strong> this type. 17
Syn<strong>the</strong>tic control studies
The syn<strong>the</strong>tic control method is a statistical method used to evaluate <strong>the</strong> effect <strong>of</strong> an intervention
in comparative case studies. It involves <strong>the</strong> construction <strong>of</strong> a syn<strong>the</strong>tic control which functions as
<strong>the</strong> counter factual <strong>and</strong> is constructed as an (optimal) weighted combination <strong>of</strong> a pool <strong>of</strong> donors.
For example, Born et al. (2021) create a syn<strong>the</strong>tic control for Sweden which consists <strong>of</strong> 30.0%
Denmark, 25.3% Finl<strong>and</strong>, 25.8% Ne<strong>the</strong>rl<strong>and</strong>s, 15.0% Norway, <strong>and</strong> 3.9% Sweden. The effect <strong>of</strong>
<strong>the</strong> intervention is derived by comparing <strong>the</strong> actual developments to those contained in <strong>the</strong>
syn<strong>the</strong>tic control.
We exclude syn<strong>the</strong>tic control studies because <strong>of</strong> <strong>the</strong>ir inherent empirical problems as discussed
by Bjørnskov (2021b). He finds that <strong>the</strong> syn<strong>the</strong>tic control version <strong>of</strong> Sweden in Born et al. (2021)
deviates substantially from “actual Sweden,” when looking at <strong>the</strong> period before mid-March 2020,
when Sweden decided not to lock down. Bjørnskov estimates that actual Sweden experienced
16
Several scholars have criticized Flaxman et al. (2020), e.g. see Homburg <strong>and</strong> Kuhb<strong>and</strong>ner (2020), Lewis (2020),
<strong>and</strong> Lemoine (2020).
17
Kepp <strong>and</strong> Bjørnskov (2021) is one such study. They use evidence from a quasi-natural experiment in <strong>the</strong> Danish
region <strong>of</strong> Nor<strong>the</strong>rn Jutl<strong>and</strong>. After <strong>the</strong> discovery <strong>of</strong> mutations <strong>of</strong> Sars-CoV-2 in mink – a major Danish export –
seven <strong>of</strong> <strong>the</strong> 11 municipalities <strong>of</strong> <strong>the</strong> region went into extreme lockdown in early November, while <strong>the</strong> four o<strong>the</strong>r
municipalities retained <strong>the</strong> moderate restrictions <strong>of</strong> <strong>the</strong> remaining country. Their analysis shows that while
infection levels decreased, <strong>the</strong>y did so before lockdown was in effect, <strong>and</strong> infection numbers also decreased in
neighbor municipalities without m<strong>and</strong>ates. They conclude that efficient infection surveillance <strong>and</strong> voluntary
compliance make full lockdowns unnecessary, at least in some circumstances. Kepp <strong>and</strong> Bjørnskov (2021) is not
included in our review, because <strong>the</strong>y focus on cases <strong>and</strong> not COVID-19 mortality. Dave et al. (2020) is ano<strong>the</strong>r
such study. They see <strong>the</strong> Wisconsin Supreme Court abolishment <strong>of</strong> Wisconsin’s “Safer at Home” order (a SIPO)
as a natural experiment <strong>and</strong> find that “<strong>the</strong> repeal <strong>of</strong> <strong>the</strong> state SIPO impacted social distancing, COVID-19 cases, or
COVID-19-related mortality during <strong>the</strong> fortnight following enactment.” Dave et al. (2020) is not included in our
review, because <strong>the</strong>y use a syn<strong>the</strong>tic control method.
9