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On the interplay of regional mobility, social connectedness and the spread of COVID‐19 in Germany

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  • Cornelius Fritz
  • Göran Kauermann

Abstract

Since the primary mode of respiratory virus transmission is person‐to‐person interaction, we are required to reconsider physical interaction patterns to mitigate the number of people infected with COVID‐19. While research has shown that non‐pharmaceutical interventions (NPI) had an evident impact on national mobility patterns, we investigate the relative regional mobility behaviour to assess the effect of human movement on the spread of COVID‐19. In particular, we explore the impact of human mobility and social connectivity derived from Facebook activities on the weekly rate of new infections in Germany between 3 March and 22 June 2020. Our results confirm that reduced social activity lowers the infection rate, accounting for regional and temporal patterns. The extent of social distancing, quantified by the percentage of people staying put within a federal administrative district, has an overall negative effect on the incidence of infections. Additionally, our results show spatial infection patterns based on geographical as well as social distances.

Suggested Citation

  • Cornelius Fritz & Göran Kauermann, 2022. "On the interplay of regional mobility, social connectedness and the spread of COVID‐19 in Germany," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(1), pages 400-424, January.
    • Handle: RePEc:bla:jorssa:v:185:y:2022:i:1:p:400-424
    DOI: 10.1111/rssa.12753
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    1. Francis Cailliez, 1983. "The analytical solution of the additive constant problem," Psychometrika, Springer;The Psychometric Society, vol. 48(2), pages 305-308, June.
    2. Simon N. Wood, 2003. "Thin plate regression splines," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(1), pages 95-114, February.
    3. Mitze, Timo & Kosfeld, Reinhold & Rode, Johannes & Wälde, Klaus, 2020. "Face masks considerably reduce COVID-19 cases in Germany," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 124587, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    4. Michael Bailey & Rachel Cao & Theresa Kuchler & Johannes Stroebel & Arlene Wong, 2018. "Social Connectedness: Measurement, Determinants, and Effects," Journal of Economic Perspectives, American Economic Association, vol. 32(3), pages 259-280, Summer.
    5. Simon N. Wood, 2011. "Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 73(1), pages 3-36, January.
    6. Gale Young & A. Householder, 1938. "Discussion of a set of points in terms of their mutual distances," Psychometrika, Springer;The Psychometric Society, vol. 3(1), pages 19-22, March.
    7. Christian Kleiber & Achim Zeileis, 2016. "Visualizing Count Data Regressions Using Rootograms," The American Statistician, Taylor & Francis Journals, vol. 70(3), pages 296-303, July.
    8. R. A. Rigby & D. M. Stasinopoulos, 2005. "Generalized additive models for location, scale and shape," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(3), pages 507-554, June.
    9. Simon N. Wood & Natalya Pya & Benjamin Säfken, 2016. "Smoothing Parameter and Model Selection for General Smooth Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1548-1563, October.
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    Cited by:

    1. Beate Jahn & Sarah Friedrich & Joachim Behnke & Joachim Engel & Ursula Garczarek & Ralf Münnich & Markus Pauly & Adalbert Wilhelm & Olaf Wolkenhauer & Markus Zwick & Uwe Siebert & Tim Friede, 2022. "Authors’ response: on the role of data, statistics and decisions in a pandemic," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(3), pages 403-405, September.
    2. Ursula Berger & Göran Kauermann & Helmut Küchenhoff, 2022. "Discussion on On the role of data, statistics and decisions in a pandemic," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(3), pages 387-390, September.
    3. Matthias Flückiger & Markus Ludwig, 2023. "Spatial networks and the spread of COVID-19: results and policy implications from Germany," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 43(1), pages 1-27, April.
    4. Krzysztof Zaremba, 2023. "Opening of hotels and ski facilities: Impact on mobility, spending, and Covid‐19 outcomes," Health Economics, John Wiley & Sons, Ltd., vol. 32(5), pages 1148-1180, May.
    5. Xinming Du, 2023. "Symptom or Culprit? Social Media, Air Pollution, and Violence," CESifo Working Paper Series 10296, CESifo.

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