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

Joshua Driesen, Ziad El-Khatib, Niklas Wulkow, Mitchell Joblin, Iskriyana Vasileva, Andreas Glücker, Valentin Kruspel and Catherine Vogel
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Joshua Driesen: Driesen Data Analytics, 04317 Leipzig, Germany
Ziad El-Khatib: Department of Global Public Health, Karolinska Institutet, Solna, 17177 Stockholm, Sweden
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
Catherine Vogel: Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH, Postfach 5180, 65726 Eschborn, Germany

IJERPH, 2021, vol. 18, issue 18, 1-29

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.

Keywords: Data-Powered Positive Deviance; pandemic response; SARS-CoV-2; mixed methods (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
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