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. 2020 Jul 20:727:138761.
doi: 10.1016/j.scitotenv.2020.138761. Epub 2020 Apr 18.

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

Marc Saez  1 , Aurelio Tobias  2 , Diego Varga  3 , Maria Antònia Barceló  4
Affiliations

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

Marc Saez et al. Sci Total Environ. .

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.

Keywords: COVID-19; Generalized linear mixed models; Mitigation; Physical distancing; R-INLA.

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Conflict of interest statement

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Unlabelled Image
Graphical abstract
Fig. 1
Fig. 1
Accumulated confirmed cases of COVID 19 and seasonal influenza, Spain Source: COVID-19: ECDC (https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide), Seasonal influenza: Influenza Surveillance System in Spain [in Spanish] (http://vgripe.isciii.es/inicio.do) Day 0 corresponds to the epidemic outbreak: Coronavirus: The day that 20 cases were registered for the first time; Seasonal influenza: The week in which the global incidence rate of influenza was >54.6 cases per 100,000 inhabitants.
Fig. 2
Fig. 2
(a) Accumulated confirmed cases of COVID 19 Source: COVID-19: ECDC (https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide) (b) Rate of variation of accumulated confirmed cases of COVID 19 Source: COVID-19: ECDC (https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide).
Fig. 3
Fig. 3
(a). Prediction of the variation rates of the cumulative cases of COVID-19 in Spain (%). Origin March 11 (before the intervention) (b). Prediction of the variation rates of the cumulative cases of COVID-19 in Spain (%). Origin March 18 (after the intervention).
Fig. 4
Fig. 4
Reduction of the rate of variation of cumulative cases of COVID-19 in Spain (percentage points).
See this image and copyright information in PMC

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