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Social Restrictions versus Testing Campaigns in the COVID-19 Crisis: A Predictive Model Based on the Spanish Case.

ABSTRACT: The global COVID-19 spread has forced countries to implement non-pharmacological interventions (NPI) (i.e., mobility restrictions and testing campaigns) to preserve health systems. Spain is one of the most severely impacted countries, both clinically and economically. In an effort to support policy decision-making, we aimed to assess the impacts of different NPI on COVID-19 epidemiology, healthcare costs and Gross Domestic Product (GDP). A modified Susceptible-Exposed-Infectious-Removed epidemiological model was created to simulate the pandemic evolution. Its output was used to populate an economic model to quantify healthcare costs and GDP variation through a regression model which correlates NPI and GDP change from 42 countries. Thirteen scenarios combining different NPI were consecutively simulated in the epidemiological and economic models. Both increased testing and stringency could reduce cases, hospitalizations and deaths. While policies based on increased testing rates lead to higher healthcare costs, increased stringency is correlated with greater GDP declines, with differences of up to 4.4% points. Increased test sensitivity may lead to a reduction of cases, hospitalizations and deaths and to the implementation of pooling techniques that can increase throughput testing capacity. Alternative strategies to control COVID-19 spread entail differing economic outcomes. Decision-makers may utilize this tool to identify the most suitable strategy considering epidemiological and economic outcomes.

SUBMITTER: Candel FJ

PROVIDER: S-EPMC8157049 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Early in the pandemic, slowing the spread of novel coronavirus disease 2019 (COVID-19) relied on non-pharmaceutical interventions. All U.S. states adopted social-distancing restrictions in March and April of 2020, though policies varied both in timing and scope. Compared to states with Democratic governors, those with Republican governors often adopted measures for shorter durations and with greater resistance from their residents. In Kentucky, an extremely close gubernatorial election immediately prior to the discovery of SARS-CoV-2 replaced a Republican incumbent with a Democrat, despite Republicans easily winning all other statewide races. This chance election result offers a unique opportunity to examine the impact of early social distancing policies in a relatively conservative, rural, white-working-class state. Our study begins by estimating an event-study model to link adoption of several common social distancing measures-public school closures, bans on large gatherings, closures of entertainment-related businesses such as restaurants, and shelter-in-place orders (SIPOs)-to the growth rate of cases across counties in the Midwest and South in the early stages of the pandemic. These policies combined to slow the daily growth rate of COVID-19 cases by 9 percentage points after 16 days, with SIPOs and entertainment establishment closures accounting for the entire effect. In order to obtain results with more direct applicability to Kentucky, we then estimate a model that interacts the policy variables with a "white working class" index characterized by political conservatism, rurality, and high percentages of white, evangelical Christian residents without college degrees. We find that the effectiveness of early social distancing measures decreased with higher values of this index. The results imply that the restrictions combined to slow the spread of COVID-19 by 12 percentage points per day in Kentucky's two largest urban counties but had no statistically detectable effect across the rest of the state.

Project description:IntroductionIncreased mortality has been reported in the Latin American population. The objective is to compare the clinical characteristics and outcome of Latin American and Spanish populations in a cohort of patients hospitalized with COVID-19 during the first year of the pandemic.MethodsWe retrospectively analysed all the Latin American patients (born in South or Central America) hospitalized in our centre from February 2020 to February 2021 and compared them with an age- and gender-matched group of Spanish subjects. Variables included were demographics, co-morbidities, clinical and analytical parameters at admission and treatment received. The primary outcomes were ICU admission and mortality at 60 days. A conditional regression analysis was performed to evaluate the independent baseline predictors of both outcomes.ResultsFrom the 3216 patients in the whole cohort, 216 pairs of case-controls (Latin American and Spanish patients, respectively) with same age and gender were analysed. COPD was more frequent in the Spanish group, while HIV was more prevalent in the Latin American group. Other co-morbidities showed no significant difference. Both groups presented with similar numbers of days from symptom onset, but the Latin American population had a higher respiratory rate (21 vs. 20 bpm, P = 0.041), CRP (9.13 vs. 6.22 mg/dl, P = 0.001), ferritin (571 vs. 383 ng/ml, P = 0.012) and procalcitonin (0.10 vs. 0.07 ng/ml, P = 0.020) at admission and lower cycle threshold of PCR (27 vs. 28.8, P = 0.045). While ICU admission and IVM were higher in the Latin American group (17.1% vs. 13% and 9.7% vs. 5.1%, respectively), this was not statistically significant. Latin American patients received remdesivir and anti-inflammatory therapies more often, and no difference in the 60-day mortality rate was found (3.2% for both groups).ConclusionLatin American patients with COVID-19 have more severe disease than Spanish patients, requiring ICU admission, antiviral and anti-inflammatory therapies more frequently. However, the mortality rate was similar in both groups.

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Social Restrictions versus Testing Campaigns in the COVID-19 Crisis: A Predictive Model Based on the Spanish Case.

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