ABSTRACT
This work is concerned with the spatiotemporal dynamics of the coronavirus disease 2019 (COVID-19) in Germany. Our goal is twofold: first, we propose a novel spatial econometric model of the epidemic spread across NUTS-3 regions to identify the role played by commuting-to-work patterns for spatial disease transmission. Second, we explore if the imposed containment (lockdown) measures during the first pandemic wave in spring 2020 have affected the strength of this transmission channel. Our results from a spatial panel error correction model indicate that, without containment measures in place, commuting-to-work patterns were the first factor to significantly determine the spatial dynamics of daily COVID-19 cases in Germany. This indicates that job commuting, particularly during the initial phase of a pandemic wave, should be regarded and accordingly monitored as a relevant spatial transmission channel of COVID-19 in a system of economically interconnected regions. Our estimation results also provide evidence for the triggering role of local hot spots in disease transmission and point to the effectiveness of containment measures in mitigating the spread of the virus across German regions through reduced job commuting and other forms of mobility. Supplementary Information: The online version contains supplementary material available at 10.1007/s10109-021-00349-3.
ABSTRACT
The paper studies the containment effects of public health measures to curb the spread of Covid-19 during the first wave of the pandemic in spring 2020 in Germany. To identify the effects of six compound sets of public health measures, we employ a spatial difference-in-differences approach. We find that contact restrictions, mandatory wearing of face masks and closure of schools substantially contributed to flattening the infection curve. The significance of the impact of restaurant closure does not prove to be robust. No incremental effect is evidenced for closure of establishments and the shutdown of nonessential retail stores.
ABSTRACT
We use the synthetic control method to analyze the effect of face masks on the spread of COVID-19 in Germany. Our identification approach exploits regional variation in the point in time when wearing of face masks became mandatory in public transport and shops. Depending on the region we consider, we find that face masks reduced the number of newly registered severe acute respiratory syndrome coronavirus 2 infections between 15% and 75% over a period of 20 days after their mandatory introduction. Assessing the credibility of the various estimates, we conclude that face masks reduce the daily growth rate of reported infections by around 47%.