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How have COVID-19 stringency measures changed scholarly activity?

ABSTRACT: Government restrictions to the movement of people due to the COVID-19 pandemic have had a wide range of effects on scientific activity. Here, we show that during the pandemic there has been a reduction in the number of registered non-COVID-19 clinical trials. Furthermore, using the Oxford COVID-19 Government Response Tracker Stringency Index (SI) as an indicator of COVID-19-related workplace adjustment (e.g., restrictions on gatherings, workplace closures, and stay-at-home orders), we demonstrate that this drop in clinical trial registration has been greater in countries with a higher SI. This could have significant consequences for the discovery of treatments that are required to reduce the global burden of disease.

SUBMITTER: Caudwell KM

PROVIDER: S-EPMC9115337 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundHow effective have lockdowns been at reducing the covid-19 infection and mortality rates? Lockdowns influence contact among persons within or between populations including restricting travel, closing schools, prohibiting public gatherings, requiring workplace closures, all designed to slow the contagion of the virus. The purpose of the present study was to assess the impact of lockdown measures on the spread of covid-19 and test a theoretical model of the covid-19 pandemic employing structural equation modelling.MethodsLockdown variables, population demographics, mortality rates, infection rates, and health were obtained for eight countries: Austria, Belgium, France, Germany, Italy, Netherlands, Spain, and the United Kingdom. The dataset, owid-covid-data.csv, was downloaded on 06/01/2020 from: https://github.com/owid/covid-19-data/tree/master/public/data. Infection spread and mortality data were depicted as logistic growth and analyzed with stepwise multiple regression. The overall structure of the covid-19 data was explored through factor analyses leading to a theoretical model that was tested using latent variable path analysis.ResultsMultiple regression indicated that the time from lockdown had a small but significant effect (β = 0.112, p< 0.01) on reducing the number of cases per million. The stringency index produced the most important effect for mortality and infection rates (β = 0.588,β = 0.702, β = 0.518, β = 0.681; p< 0.01). Exploratory and confirmatory analyses resulted in meaningful and cohesive latent variables: 1) Mortality, 2) Infection Spread, 3) Pop Health Risk, and 4) Health Vulnerability (Comparative Fit Index = 0.91; Standardized Root Mean Square Residual = 0.08).DiscussionThe stringency index had a large impact on the growth of covid-19 infection and mortality rates as did percentage of population aged over 65, median age, per capita GDP, diabetes prevalence, cardiovascular death rates, and ICU hospital beds per 100K. The overall Latent Variable Path Analysis is theoretically meaningful and coherent with acceptable fit indices as a model of the covid-19 pandemic.

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How have COVID-19 stringency measures changed scholarly activity?

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