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Data-Powered Positive Deviance during the SARS-CoV-2 Pandemic—An Ecological Pilot Study of German Districts

Author

Listed:
  • Joshua Driesen

    (Driesen Data Analytics, 04317 Leipzig, Germany
    Co-first author.)

  • Ziad El-Khatib

    (Department of Global Public Health, Karolinska Institutet, Solna, 17177 Stockholm, Sweden
    Co-first author.)

  • Niklas Wulkow

    (Department of Mathematics and Computer Science, Zuse Institute Berlin, Freie Universität Berlin, 14195 Berlin, Germany)

  • Mitchell Joblin

    (Siemens AG Corporate Technology, 80333 Munich, Germany)

  • Iskriyana Vasileva

    (Iskriyana Vasileva Data Science, 10997 Berlin, Germany)

  • Andreas Glücker

    (Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH, Postfach 5180, 65726 Eschborn, Germany)

  • Valentin Kruspel

    (Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH, Postfach 5180, 65726 Eschborn, Germany
    Co-senior author.)

  • Catherine Vogel

    (Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH, Postfach 5180, 65726 Eschborn, Germany
    Co-senior author.)

Abstract

We introduced the mixed-methods Data-Powered Positive Deviance (DPPD) framework as a potential addition to the set of tools used to search for effective response strategies against the SARS-CoV-2 pandemic. For this purpose, we conducted a DPPD study in the context of the early stages of the German SARS-CoV-2 pandemic. We used a framework of scalable quantitative methods to identify positively deviant German districts that is novel in the scientific literature on DPPD, and subsequently employed qualitative methods to identify factors that might have contributed to their comparatively successful reduction of the forward transmission rate. Our qualitative analysis suggests that quick, proactive, decisive, and flexible/pragmatic actions, the willingness to take risks and deviate from standard procedures, good information flows both in terms of data collection and public communication, alongside the utilization of social network effects were deemed highly important by the interviewed districts. Our study design with its small qualitative sample constitutes an exploratory and illustrative effort and hence does not allow for a clear causal link to be established. Thus, the results cannot necessarily be extrapolated to other districts as is. However, the findings indicate areas for further research to assess these strategies’ effectiveness in a broader study setting. We conclude by stressing DPPD’s strengths regarding replicability, scalability, adaptability, as well as its focus on local solutions, which make it a promising framework to be applied in various contexts, e.g., in the context of the Global South.

Suggested Citation

  • Joshua Driesen & Ziad El-Khatib & Niklas Wulkow & Mitchell Joblin & Iskriyana Vasileva & Andreas Glücker & Valentin Kruspel & Catherine Vogel, 2021. "Data-Powered Positive Deviance during the SARS-CoV-2 Pandemic—An Ecological Pilot Study of German Districts," IJERPH, MDPI, vol. 18(18), pages 1-29, September.
  • Handle: RePEc:gam:jijerp:v:18:y:2021:i:18:p:9765-:d:637190
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    References listed on IDEAS

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    1. Gladwin, Christina H. & Peterson, Jennifer S. & Mwale, Abiud C., 2002. "The Quality of Science in Participatory Research: A Case Study from Eastern Zambia," World Development, Elsevier, vol. 30(4), pages 523-543, April.
    2. Frank Schlosser & Benjamin F. Maier & Olivia Jack & David Hinrichs & Adrian Zachariae & Dirk Brockmann, 2020. "COVID-19 lockdown induces disease-mitigating structural changes in mobility networks," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 117(52), pages 32883-32890, December.
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