Chasing the ghost of infection past: identifying thresholds of change during the COVID-19 infection in Spain

Abstract

One of the largest nationwide bursts of the first COVID-19 outbreak occurred in Spain, where infection expanded in densely populated areas through March 2020. We analyse the cumulative growth curves of reported cases and deaths in all Spain and two highly populated regions, Madrid and Catalonia, identifying changes and sudden shifts in their exponential growth rate through segmented Poisson regressions. We associate these breakpoints with a timeline of key events and containment measures, and data on policy stringency and citizen mobility. Results were largely consistent for infections and deaths in all territories, showing four major shifts involving 19-71% reductions in growth rates originating from infections before 3 March and on 5-8, 10-12 and 14-18 March, but no identifiable effect of the strengthened lockdown of 29-30 March. Changes in stringency and mobility were only associated to the latter two shifts, evidencing an early deceleration in COVID-19 spread associated to personal hygiene and social distancing recommendations, followed by a stronger decrease when lockdown was enforced, leading to the contention of the outbreak by mid-April. This highlights the importance of combining public health communication strategies and hard confinement measures to contain epidemics.

Risk Perception of COVID−19 Community Transmission among the Spanish Population

“…The first cases of COVID−19 in Spain occurred in February 2020 [11], in March, Europe became the epicentre of the pandemic [12]. France, Italy and Spain were the most affected countries with mortality rates of 15%, 13% and 11%, respectively.…”

Change points in the spread of COVID-19 question the effectiveness of nonpharmaceutical interventions in Germany

“…By using official case data [19], true dates of infection are estimated. Inspired by the methodical approach in previous studies [2][3][4]11], change points in time series of three indicators (daily and cumulative infections as well as reproduction numbers, all of which were calculated based on the estimated infection dates) were detected. The data covers infections from February 15 to May 31, 2020, which means that also possible effects of the easing of measures (from April 20) and the introduction of face masks (from April 27) can be assessed.…”

“…In simple terms, the time between infection and reporting consists of two time periods: a) the time between infection and onset of symptoms (incubation period), and b) the time between onset of symptoms and the date of report (reporting delay). Thus, to estimate the date of infection, both periods must be subtracted from the date of report [1][2][3][4][5]8,11]. There are several estimations of the SARS-CoV-2/COVID-19 incubation period, ranging from median values of 5.0 to 6.4 days [21,22].…”

“…Assessing the effectiveness of nonpharmaceutical interventions (NPIs) in the SARS-CoV-2/COVID-19 context is a topic of growing relevance. Nevertheless, findings documenting the impact of these measures have not been homogeneous within the literature; whether with respect to single countries [1][2][3][4][5][6][7][8][9][10][11], or in terms of international comparisons [12][13][14][15][16][17]. The question of whether "lockdowns"including contact bans, curfews or closures of schools and child day care facilitiessucceed or fail in reducing infections is a key concern for policymakers, as such measures are accompanied by consequences in terms of economic, social and psychological effects on societies.…”

“…Exponential growth models for infections and reproduction numbers were estimated and investigated with respect to change points in the time series. Results: A significant decline of daily and cumulative infections as well as reproduction numbers is found at March 8 (CI [7,9]), March 10 (CI [9,11] and March 3 (CI [2, 4]), respectively. Further declines and stabilizations are found in the end of March.…”