Modelling COVID-19

Alessandro Vespignani; Huaiyu Tian; Christopher Dye; James O Lloyd-Smith; Rosalind M Eggo; Munik Shrestha; Samuel V Scarpino; Bernardo Gutierrez; Moritz U G Kraemer; Joseph Wu; Kathy Leung; Gabriel M Leung

doi:10.1038/s42254-020-0178-4

Modelling COVID-19

Nat Rev Phys. 2020;2(6):279-281. doi: 10.1038/s42254-020-0178-4. Epub 2020 May 6.

Authors

Alessandro Vespignani^{1

2}, Huaiyu Tian³, Christopher Dye⁴, James O Lloyd-Smith⁵, Rosalind M Eggo⁶, Munik Shrestha¹, Samuel V Scarpino¹, Bernardo Gutierrez^{4

7}, Moritz U G Kraemer^{4

8

9}, Joseph Wu¹⁰, Kathy Leung¹⁰, Gabriel M Leung¹⁰

Affiliations

¹ Network Science Institute, Northeastern University, Boston, MA USA.
² ISI Foundation, Turin, Italy.
³ State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China.
⁴ Department of Zoology, University of Oxford, Oxford, UK.
⁵ Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA USA.
⁶ Centre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
⁷ School of Biological and Environmental Sciences, Universidad San Francisco de Quito USFQ, Quito, Ecuador.
⁸ Harvard Medical School, Harvard University, Boston, MA USA.
⁹ Boston Children's Hospital, Boston, MA USA.
¹⁰ WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.

Abstract

As the COVID-19 pandemic continues, mathematical epidemiologists share their views on what models reveal about how the disease has spread, the current state of play and what work still needs to be done.

Keywords: Applied mathematics; Complex networks.

Publication types

Review