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A Compartment Model of Human Mobility and Early Covid-19 Dynamics in NYC

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 نشر من قبل Ian Frankenburg
 تاريخ النشر 2021
  مجال البحث الاحصاء الرياضي
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In this paper, we build a mechanistic system to understand the relation between a reduction in human mobility and Covid-19 spread dynamics within New York City. To this end, we propose a multivariate compartmental model that jointly models smartphone mobility data and case counts during the first 90 days of the epidemic. Parameter calibration is achieved through the formulation of a general Bayesian hierarchical model to provide uncertainty quantification of resulting estimates. The open-source probabilistic programming language Stan is used for the requisite computation. Through sensitivity analysis and out-of-sample forecasting, we find our simple and interpretable model provides evidence that reductions in human mobility altered case dynamics.



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