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Massive social protests amid the pandemic in selected Colombian cities: Did they increase COVID-19 cases?

Moreno-Montoya, J.; Rodriguez Villamizar, L. A.; Idrovo, A. J.

2021-06-18 epidemiology
10.1101/2021.06.16.21258989 medRxiv
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BackgroundSince April 28, 2021, in Colombia there are social protests with numerous demonstrations in various cities. The aim of this study was to assess the effect of social protests on the number and trend of the confirmed COVID-19 cases in some selected Colombian cities where social protests had more intensity. MethodsWe performed and interrupted time-series analysis (ITSA) and Autoregressive Integrated Moving Average (ARIMA) models, based on the confirmed COVID-19 cases in Colombia, between March 1 and May 15, 2021, for Bogota, Cali, Barranquilla, Medellin, and Bucaramanga. The ITSA models estimated the effect of social demonstrations on the number and trend of cases for each city by using Newey-West standard errors. ARIMA models assessed the overall pattern of the series and effect of the intervention. We considered May 2, 2021, as the intervention date for the analysis, five days after social demonstrations started in the country. FindingsDuring the study period the number of cases by city was 1,014,815 for Bogota, 192,320 for Cali, 175,269 for Barranquilla, 311,904 for Medellin, and 62,512 for Bucaramanga. Heterogeneous results were found among cities. Only for the cities of Cali and Barranquilla statistically significant changes in trend of the number of cases were obtained after the intervention: positive in the first city, negative in the second one. None ARIMA models show evidence of abrupt changes in the trend of the series for any city and intervention effect was only significant for Bucaramanga. InterpretationSocial protests had a heterogeneous effect on the number and trend of COVID-19 cases. Different effects might be related to the epidemiologic moment of the pandemic and the characteristics of the social protests. Assessing the effect of social protests within a pandemic is complex and there are several methodological limitations. Further analyses are required with longer time-series data.

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