Business Shutdowns and COVID-19 Mortality

Ciminelli, Gabriele; Garcia-Mandicó, Sílvia

doi:10.2139/ssrn.3683324

Cited by 4 publications

(5 citation statements)

References 29 publications

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“…Miscounting is present also for official fatality counts, but to a reduced extent [26]. It is possible to estimate the extent to which the history of fatalities and infections trace each other in phase space, by comparing the functional dependence of ( X , Δ X ) and ( F , Δ F ):…”

Section: Resultsmentioning

confidence: 99%

Predicting the cumulative medical load of COVID-19 outbreaks after the peak in daily fatalities

Gros

Valentí

Schneider

et al. 2020

Preprint

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The distinct ways the COVID-19 pandemics has been unfolding in different countries and regions suggest that local societal and governmental structures play an essential role both for the baseline infection rate and the short-term and long-term reaction to the outbreak. Here we investigate how societies as a whole, and governments, in particular, modulate the dynamics of a novel epidemic using a generalisation of the SIR model, the controlled SIR model. We posit that containment measures correspond to feedback between the status of the outbreak (the daily or the cumulative number of cases and fatalities) and the reproduction factor. We present the exact phase space solution of the controlled SIR model and use it to quantify containment policies for a large number of countries in terms of short- and long-term control parameters. Furthermore, we identified for numerous countries a relationship between the number of fatalities within a fixed period before and after the peak in daily fatalities. As the number of fatalities corresponds to the number of hospitalised patients, the relationship can be used to predict the cumulative medical load, once the effectiveness of outbreak suppression policies is established with sufficient certainty.

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Section: Resultsmentioning

confidence: 99%

Predicting the cumulative medical load of COVID-19 outbreaks after the peak in daily fatalities

Gros

Valentí

Schneider

et al. 2020

Preprint

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show abstract

“…To do so, we follow closely the methodology that we developed in two companion papers. 10,15 Specifically, we rely on a differences-in-differences approach to estimate the dynamic effects on the mortality rate, using the year 2016 as counterfactual of what mortality would have been in absence of Covid-19. The choice of using the year 2016 follows from a visual inspection of the data (see Appendix Figure A1), but the results are robust to using mean 2015-2019 mortality as alternative counterfactual.…”

Section: Empirical Methodologymentioning

confidence: 99%

How Healthcare Congestion Increases Covid-19 Mortality: Evidence from Lombardy, Italy*

Ciminelli

Garcia-Mandicó

2020

Preprint

Self Cite

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BACKGROUND: The Covid-19 pandemic has caused generous and well-developed healthcare systems to collapse. This paper quantifies how much system congestion may have increased mortality rates, using distance to the ICU as a proxy for access to emergency care. METHODS: We match daily death registry data for almost 1,500 municipalities in Lombardy, Italy, to data on geographical location of all ICU beds in the region. We then analyze how system congestion increases mortality in municipalities that are far from the ICU through a differences-in-differences regression model. FINDINGS: We find that Covid-19 mortality is up to 60% higher in the average municipality -- which is 15 minutes driving away from the closest ICU -- than in a municipality with an ICU in town. This difference is larger in areas and in days characterized by an abnormal number of calls to the emergency line. INTERPRETATION: We interpret these results as suggesting that a sudden surge of critical patients may have congested the healthcare system, forcing emergency medical services to prioritize patients in the most proximate communities in order to maximize the number of lives saved. Through some back-of-the-envelope calculations, we estimate that Lombardy's death toll from the first Covid-19 outbreak could have been 25% lower had all municipalities had ready access to the ICU. Drawing a lesson from Lombardy's tale, governments should strengthen the emergency care response and palliate geographical inequalities to ensure that everyone in need can receive critical care on time during new outbreaks.

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“…The effect of the business shut down on COVID-19 deaths in Italy is investigated in [4]. They gather a substantial dataset across 4,000 Italian municipalities, which covers 222 local labor markets.…”

Section: Brief Literature Review and Some Historymentioning

confidence: 99%

“…Thirds, we examine how socio-economic factors such as density of population, average years of adults' education, income inequality, international tourism arrivals, health care workers, and institutional quality affect the risk of infection. There have been many excellent contributions to this line of research examining the effects of individual variables, including income inequality (eg, [1]), governance quality [2], tourism flows [3], business closures [4], health care infrastructure [5], population density [6], government interventions [7,8] and many others. Rather than emphasizing individual variables of interest and then focusing on issues of causality pertaining to that specific variable, we take a data-driven approach by examining many covariates to uncover the most important potential determinants of infection rate.…”

Section: Introductionmentioning

confidence: 99%

The effect of nonpharmaceutical interventions on COVID-19 infections for lower and middle-income countries: A debiased LASSO approach

Zamanzadeh

Cavoli²

2022

PLoS ONE

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This paper investigates the determinants of COVID-19 infection in the first 100 days of government actions. Using a debiased LASSO estimator, we explore how different measures of government nonpharmaceutical interventions affect new infections of COVID-19 for 37 lower and middle-income countries (LMCs). We find that closing schools, stay-at-home restrictions, and contact tracing reduce the growth of new infections, as do economic support to households and the number of health care workers. Notably, we find no significant effects of business closures. Finally, infections become higher in countries with greater income inequality, higher tourist inflows, poorly educated adults, and weak governance quality. We conclude that several policy interventions reduce infection rates for poorer countries. Further, economic and institutional factors are important; thereby justifying the use, and ultimately success, of economic support to households during the initial infection period.

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Business Shutdowns and COVID-19 Mortality

Cited by 4 publications

References 29 publications

Predicting the cumulative medical load of COVID-19 outbreaks after the peak in daily fatalities

Predicting the cumulative medical load of COVID-19 outbreaks after the peak in daily fatalities

How Healthcare Congestion Increases Covid-19 Mortality: Evidence from Lombardy, Italy*

The effect of nonpharmaceutical interventions on COVID-19 infections for lower and middle-income countries: A debiased LASSO approach

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