The effectiveness of government measures during the first wave of the outbreak.

María Celeste Ratto, Juan Manuel Cabrera, Daniela Zacharías, Juan Martín Azerrat
Author Information
  1. María Celeste Ratto: Research Institute on Cultural Diversity and Changing Process National University of Río Negro, National Council for Scientific and Technical Research San Carlos de Bariloche Río Negro Argentina. ORCID
  2. Juan Manuel Cabrera: Chemistry Department National University of Comahue San Carlos de Bariloche Río Negro Argentina. ORCID
  3. Daniela Zacharías: Department of Statistics National University of Comahue San Carlos de Bariloche Río Negro Argentina. ORCID
  4. Juan Martín Azerrat: Research Institute on Cultural Diversity and Changing Process National University of Río Negro, National Council for Scientific and Technical Research San Carlos de Bariloche Río Negro Argentina. ORCID

Abstract

OBJECTIVES: The Covid-19 pandemic changed the humanity life. Millions of deaths and infections that spread rapidly around the world made all countries take measures to stop the outbreaks and assume the enormous consequences that the Coronavirus is leaving behind. The challenge has been enormous; governments across the world have implemented a wide span of nonpharmaceutical interventions to mitigate the Coronavirus pandemic (SARS-CoV-2) and its consequences in economic terms. The aim of this article is to analyze the effects that different kinds of measures taken by Latin American governments had on the daily new infections. The countries analyzed were Argentina, Bolivia, Chile, Colombia, Costa Rica, El Salvador, Guatemala, Honduras, México, Panamá, Peru, Paraguay, Dominican Republic, Uruguay and Venezuela.
METHODS: A time series cross-section analysis was performed, which allows studying the evolution of the number of daily cases over time and by country. The timeframe of this study was from the day the first case of coronavirus was registered in a country, until September 14, 2020. We used data from Covid-19 Dashboard database of Johns Hopkins University and the Oxford Covid-19 Government Response Tracker data set.
RESULTS: The Stringency Index did not have a significant influence at the beginning of the pandemic but turned out to be significant and inversely related to DNI during Phases 2 and 3. On the contrary, the Economic and the Sanitary Containment Index was not statistically significant for any of the phases. Furthermore, the level of wealthfare of a country, measured from its GDP per capita, exerts a substantive conditional influence on the management of the Covid-19 crisis.
CONCLUSIONS: The scenarios have been changing and strategies had to change as well in order to be successful because they lose effectiveness and have increased social costs with time. Therefore, understanding the relative effectiveness of such measures had on the disease spreading during the first wave of the outbreak, could help governments to make more informed decisions about how to control future outbreaks of the Covid-19 pandemic.

Keywords

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Word Cloud

Created with Highcharts 10.0.0Covid-19pandemicmeasuresgovernmentstimecountryfirstsignificanteffectivenessinfectionsworldcountriesoutbreaksenormousconsequencesCoronavirusnonpharmaceuticalinterventionsLatindailycoronavirusdataIndexinfluencewaveoutbreakgovernmentOBJECTIVES:changedhumanitylifeMillionsdeathsspreadrapidlyaroundmadetakestopassumeleavingbehindchallengeacrossimplementedwidespanmitigateSARS-CoV-2economictermsaimarticleanalyzeeffectsdifferentkindstakenAmericannewanalyzedArgentinaBoliviaChileColombiaCostaRicaElSalvadorGuatemalaHondurasMéxicoPanamáPeruParaguayDominicanRepublicUruguayVenezuelaMETHODS:seriescross-sectionanalysisperformedallowsstudyingevolutionnumbercasestimeframestudydaycaseregisteredSeptember142020usedDashboarddatabaseJohnsHopkinsUniversityOxfordGovernmentResponseTrackersetRESULTS:StringencybeginningturnedinverselyrelatedDNIPhases23contraryEconomicSanitaryContainmentstatisticallyphasesFurthermorelevelwealthfaremeasuredGDPpercapitaexertssubstantiveconditionalmanagementcrisisCONCLUSIONS:scenarioschangingstrategieschangewellordersuccessfulloseincreasedsocialcostsThereforeunderstandingrelativediseasespreadinghelpmakeinformeddecisionscontrolfutureCovid‐19Americacomparativepoliticsresponsespublicpolicies

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