Effectiveness of the measures to flatten the epidemic curve of COVID-19. The case of Spain

Abstract

After the cases of COVID-19 skyrocketed, showing that it was no longer possible to contain the spread of the disease, the governments of many countries launched mitigation strategies, trying to slow the spread of the epidemic and flatten its curve. The Spanish Government adopted physical distancing measures on March 14; 13 days after the epidemic outbreak started its exponential growth. Our objective in this paper was to evaluate ex-ante (before the flattening of the curve) the effectiveness of the measures adopted by the Spanish Government to mitigate the COVID-19 epidemic. Our hypothesis was that the behavior of the epidemic curve is very similar in all countries. We employed a time series design, using information from January 17 to April 5, 2020 on the new daily COVID-19 cases from Spain, China and Italy. We specified two generalized linear mixed models (GLMM) with variable response from the Gaussian family (i.e. linear mixed models): one to explain the shape of the epidemic curve of accumulated cases and the other to estimate the effect of the intervention. Just one day after implementing the measures, the variation rate of accumulated cases decreased daily, on average, by 3.059 percentage points, (95% credibility interval: −5.371, −0.879). This reduction will be greater as time passes. The reduction in the variation rate of the accumulated cases, on the last day for which we have data, has reached 5.11 percentage points. The measures taken by the Spanish Government on March 14, 2020 to mitigate the epidemic curve of COVID-19 managed to flatten the curve and although they have not (yet) managed to enter the decrease phase, they are on the way to do so.

Scaling effect in COVID-19 spreading: The role of heterogeneity in a hybrid ODE-network model with restrictions on the inter-cities flow

“…Saez et al. [21] identified a reduction in the rate of infection in Spain after different measures of physical distance, including travel flow. With the advance of the outbreak, local interventions such as lockdown, hygiene, curfew, mass examinations of the population are more efficient.…”

Forecast predictions for the COVID-19 pandemic in Brazil by statistical modeling using the Weibull distribution for daily new cases and deaths

“…COVID-19 is a global health emergency that is going to change the way in which people, institutions and governments manage their lives and duties. The fact that there is no known specific drugs or vaccines for COVID-19 until now raises the importance of behavioral strategies, such as social distancing, lockdowns [2][3][4][5][6][7] and mass testing [8,19,20] in the fight against the pandemic. Our results show that the LR of COVID-19 in Brazil raised since the beginning of pandemic and reach a percentual value of 7.0 ± 0.2 %.…”

Use of wearable sensors to assess compliance of asthmatic children in response to lockdown measures for the COVID-19 epidemic

“…During the rst peak of the pandemic, affected countries chose different levels of interventions based, among others, on national risk assessments of estimated number of patients and capacity for hospitalization and critical care support [8,9]. The evolution of the pandemic over the last months demonstrated that timely interventions were effective to delay the spread of COVID-19 [10,11], as it was also shown in previous u and SARS epidemics [12][13][14].…”