The propagation effect of commuting to work in the spatial transmission of COVID-19

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.

Clustering Accelerometer Activity Patterns from the UK Biobank Cohort

“…The period for which we have the COVID-19 testing data (up to March 2021) saw periods between lockdowns where more people returned to work and therefore had greater exposure to possible infections. Their activity pattern is certainly suggestive of activities around commute journeys to a place of work, and such activities may expose people to more contacts in environments that they have little control over [74]. In support of this, Rowlands, Dempsey [75] also found that there was a positive association between total physical activity and higher odds of a non-severe infection, with an odds estimate of 1.10.…”

Spatial patterns of excess mortality in the first year of the COVID-19 pandemic in Germany

“…The influence of mobility (especially commuting) on virus transmission was outlined several times for infectious diseases such as influenza (Charaudeau et al 2014, Charu et al 2017, Dalziel et al 2013, Viboud et al 2006). With respect to SARS-CoV-2, Mitze, Kosfeld (2021) outline the enhancing effect of commuting to work on regional infections in the first pandemic wave in Germany. Regarding the same time period, Wieland (2020) shows that, all other things being equal, growth rates of SARS-CoV-2 infections in German counties increase with increasing intensity of commuting.…”

A Link Mixture Model for Spatio-temporal Infection Data, with Applications to the COVID Epidemic

“…One may add lags to infection counts in spatially close areas to reflect infection spillover from neighbouring areas -due, for example, to social interactions between residents in different areas, or to cross boundary commuting (Mitze and Kosfeld, 2021). Let h ij measure spatial interactions between areas i and j, and w ij = h ij / j h ij be row standardised spatial weights, with j w ij = 1.…”

“…These include considerable time fluctuations (with epidemic phases) in many infectious diseases; spatial diffusion or spillover (e.g. Dalvi and Braga, 2019) related to behaviours such as commuting (Mitze and Kosfeld, 2021), and the occurrence of hotspots for disease propagation early in infectious outbreaks (Dowdy et al, 2012). It is also especially useful in policy terms to be able to extrapolate the infectious disease evolution beyond the observation span, as illustrated in some studies of the COVID epidemic (Vahedi et al, 2021;Rui et al, 2021;Watson et al, 2017;Giuliani et al, 2020).…”