@article{603,
  author = {Andrea Bertozzi and Elisa Franco and George Mohler and Martin Short and Daniel Sledge},
  title = {The challenges of modeling and forecasting the spread of COVID-19},
  abstract = {The coronavirus disease 2019 (COVID-19) pandemic has placed epidemic modeling at the forefront of worldwide public policy making. Nonetheless, modeling and forecasting the spread of COVID-19 remains a challenge. Here, we detail three regional-scale models for forecasting and assessing the course of the pandemic. This work demonstrates the utility of parsimonious models for early-time data and provides an accessible framework for generating policy-relevant insights into its course. We show how these models can be connected to each other and to time series data for a particular region. Capable of measuring and forecasting the impacts of social distancing, these models highlight the dangers of relaxing nonpharmaceutical public health interventions in the absence of a vaccine or antiviral therapies.},
  year = {2020},
  journal = {Proceedings of the National Academy of Sciences},
  chapter = {202006520},
  pages = {1},
  month = {01},
  issn = {0027-8424},
  url = {https://par.nsf.gov/biblio/10172956},
  doi = {10.1073/pnas.2006520117},
}