Projections updated on:
Weekly Deaths in USA
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Hospital Beds in USA
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About
To study the spatiotemporal COVID-19 spread, we use the Global Epidemic and Mobility Model (GLEAM), an individual-based, stochastic, and spatial epidemic model [1, 2, 3, 4]. GLEAM uses real-world data to perform in-silico simulations of the spatial spread of infectious diseases at the global level. We use the model to analyze the spatiotemporal spread and magnitude of the COVID-19 epidemic in the continental US. The model generates an ensemble of possible epidemic projections described by the number of newly generated infections, times of disease arrival in different regions, and the number of traveling infection carriers. Approximate Bayesian Computation is used to estimate the posterior distribution of the basic parameters of the model. The calibration of the global model for COVID-19 is reported in Science. The US model considers the timeline of mitigation interventions that are integrated as detailed in the model description published here. The projections will be regularly updated as new data and information about mitigation policies become available. Sensitivity analysis on the basic parameters is routinely performed along with the baseline projections considered. In order to calculate the number of deaths the model uses estimates of COVID-19 severity from available data [5, 6].
Disclaimer: There are large uncertainties around the transmission of COVID-19, the effectiveness of different policies and the extent to which the population is compliant to social distancing measures. The presented material is based on modeling scenario assumptions informed by current knowledge of the disease and subject to change as more data become available. Future decisions on when and for how long to relax mitigation policies will be informed by ongoing surveillance. Additional modeling and data studies are required to assess the level and effectiveness of additional non-pharmaceuticals interventions required to lift current social distancing measures.
Team
Northeastern University
- Alessandro Vespignani
(to whom correspondence should be addressed) - Matteo Chinazzi
- Jessica T. Davis
- Kunpeng Mu
- Ana Pastore y Piontti
- Nicole Samay
- Xinyue Xiong
Fred Hutchinson Cancer Research Center
University of Florida
NIH Fogarty Center
- Cécile Viboud
- Kaiyuan Sun
ISI Foundation
Indiana University
- Marco Ajelli
University of Greenwich
- Nicola Perra
Acknowledgments
We thank Agastya Mondal and Robel Kassa for the development of this dashboard.