In this section
@inbook{Imai:2024:10.1007/978-3-031-48408-7_37,
author = {Imai, N and Baguelin, M and Ferguson, NM},
booktitle = {Principles and Practice of Emergency Research Response},
doi = {10.1007/978-3-031-48408-7_37},
pages = {669--685},
title = {Models in the COVID-19 pandemic},
url = {http://dx.doi.org/10.1007/978-3-031-48408-7_37},
year = {2024}
}
TY - CHAP
AB - The scale and impact of the COVID-19 pandemic have challenged policymakers globally. Decisions on implementing socially and economically disruptive control measures have often had to be made on limited quantitative evidence. Epidemiological analysis and mathematical modeling are powerful tools for systematically synthesizing the knowns and unknowns to highlight key knowledge gaps and provide quantitative insights into potential policy options. The pandemic has reinforced the role of modeling and advanced analytics in informing policy responses. This chapter explores the advanced analytics and mathematical modeling used during the COVID-19 pandemic, focusing on key retrospective analyses and prospective modeling approaches.
AU - Imai,N
AU - Baguelin,M
AU - Ferguson,NM
DO - 10.1007/978-3-031-48408-7_37
EP - 685
PY - 2024///
SP - 669
TI - Models in the COVID-19 pandemic
T1 - Principles and Practice of Emergency Research Response
UR - http://dx.doi.org/10.1007/978-3-031-48408-7_37
ER -
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