| Literature DB >> 33535889 |
Lyndon P James1, Joshua A Salomon2, Caroline O Buckee3, Nicolas A Menzies4.
Abstract
Mathematical modeling has played a prominent and necessary role in the current coronavirus disease 2019 (COVID-19) pandemic, with an increasing number of models being developed to track and project the spread of the disease, as well as major decisions being made based on the results of these studies. A proliferation of models, often diverging widely in their projections, has been accompanied by criticism of the validity of modeled analyses and uncertainty as to when and to what extent results can be trusted. Drawing on examples from COVID-19 and other infectious diseases of global importance, we review key limitations of mathematical modeling as a tool for interpreting empirical data and informing individual and public decision making. We present several approaches that have been used to strengthen the validity of inferences drawn from these analyses, approaches that will enable better decision making in the current COVID-19 crisis and beyond.Entities:
Keywords: COVID-19; infectious diseases; mathematical modeling; uncertainty; validation
Mesh:
Year: 2021 PMID: 33535889 PMCID: PMC7862917 DOI: 10.1177/0272989X21990391
Source DB: PubMed Journal: Med Decis Making ISSN: 0272-989X Impact factor: 2.583