Dynamic coupling between the COVID-19 epidemic timeline and the behavioral response to PAUSE in New York State counties
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Abstract
Behavioral epidemiology suggests that there is a tight dynamic coupling between the timeline of an epidemic outbreak, and the social response in the affected population (with a typical course involving physical distancing between individuals, avoidance of large gatherings, wearing masks, etc). We study the bidirectional coupling between the epidemic dynamics of COVID-19 and the population social response in the state of New York, between March 1, 2020 (which marks the first confirmed positive diagnosis in the state), until June 20, 2020. This window captures the first state-wide epidemic wave, which peaked to over 11,000 confirmed cases daily in April (making New York one of the US states most severely affected by this first wave), and subsided by the start of June to a count of consistently under 1,500 confirmed cases per day (suggesting temporary state-wide control of the epidemic). In response to the surge in cases, social distancing measures were gradually introduced over two weeks in March, culminating with the PAUSE directive on March 22nd, which mandated statewide shutdown of all nonessential activity. The mandates were then gradually relaxed in stages throughout summer, based on how epidemic benchmarks were met in various New York regions. In our study, we aim to examine on one hand, whether different counties exhibited different responses to the PAUSE centralized measures depending on their epidemic situation immediately preceding PAUSE. On the other hand, we explore whether these different county-wide responses may have contributed in turn to modulating the counties’ epidemic timelines. We used the public domain to extract county-wise epidemic measures (such as cumulative and daily incidence of COVID-19), and social mobility measures for different modalities (driving, walking, public transit) and to different destinations. Our correlation analyses between the epidemic and the mobility time series found significant correlations between the size of the epidemic and the degree of mobility drop after PAUSE, as well as between the mobility comeback patterns and the epidemic recovery timeline. In line with existing literature on the role of the population behavioral response during an epidemic outbreak, our results support the potential importance of the PAUSE measures to the control of the first epidemic wave in New York State.
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SciScore for 10.1101/2020.07.08.20148981: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank…
SciScore for 10.1101/2020.07.08.20148981: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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