Quantifying COVID-19 Pandemic Spread
Metrics, Mathematics, and Models to Guide Effective Responses
Institute for Computational Medicine
Johns Hopkins University
Sponsored by PSW Science Member Tim Thomas
About the Lecture
This lecture will discuss the mathematics of infectious disease spread, its use in modeling the spread of diseases, such as COVID-19, and its application in formulating effective public health policies to curtail epidemics and minimize their effects.
Reading references –
A.L. Hill, The math behind epidemics, Physics Today. 73 (2020) 28–34. https://doi.org/10.1063/PT.3.4614.
A. Vespignani, H. Tian, C. Dye, J.O. Lloyd-Smith, R.M. Eggo, M. Shrestha, S.V. Scarpino, B. Gutierrez, M.U.G. Kraemer, J. Wu, K. Leung, G.M. Leung, Modelling COVID-19, Nature Reviews Physics. 2 (2020) 279–281. https://doi.org/10.1038/s42254-020-0178-4.
N.C. Grassly, C. Fraser, Mathematical models of infectious disease transmission, Nat Rev Micro. 6 (2008) 477–487. https://doi.org/10.1038/nrmicro1845.
About the Speaker
Alison Hill is Assistant Professor in the Institute for Computational Medicine at the Johns Hopkins University. Alison and her team develop mathematical models and computational tools to help understand, predict, and treat infectious diseases, with a particular focus on HIV/AIDS, COVID-19, drug resistant infections, bed bugs infestations, and anti-viral immune responses.
Alison is a recipient of the NIH Director’s Early Independence Award and was selected as one of the World Economic Forum’s Young Scientists. She has written popular science pieces on infectious disease dynamics for PBS Nova and Physics Today, and is a co-chair of the COVID-19 Dynamics & Evolution Meeting and the COVID-19 Data Forum.
Alison earner her BS at Queen’s University, Canada and her PhD jointly through the Harvard-MIT Division of Health Sciences & Technology, Medical Engineering & Medical Physics.