Imperial College London
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DrAdaYan

Faculty of Medicine, Department of Infectious Disease

Imperial College Research Fellow
 
 
 
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Contact

 

a.yan Website

 
 
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Location

 

421Praed StreetSt Mary's Campus

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Summary

 

Publications

Citation

BibTex format

@article{Alahmadi:2020:10.1016/j.epidem.2020.100393,
author = {Alahmadi, A and Belet, S and Black, A and Cromer, D and Flegg, JA and House, T and Jayasundara, P and Keith, JM and McCaw, JM and Moss, R and Ross, JV and Shearer, FM and Tun, STT and Walker, J and White, L and Whyte, JM and Yan, AWC and Zarebski, AE},
doi = {10.1016/j.epidem.2020.100393},
journal = {Epidemics: the journal of infectious disease dynamics},
title = {Influencing public health policy with data-informed mathematical models of infectious diseases: Recent developments and new challenges},
url = {http://dx.doi.org/10.1016/j.epidem.2020.100393},
volume = {32},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Modern data and computational resources, coupled with algorithmic and theoretical advances to exploit these, allow disease dynamic models to be parameterised with increasing detail and accuracy. While this enhances models' usefulness in prediction and policy, major challenges remain. In particular, lack of identifiability of a model's parameters may limit the usefulness of the model. While lack of parameter identifiability may be resolved through incorporation into an inference procedure of prior knowledge, formulating such knowledge is often difficult. Furthermore, there are practical challenges associated with acquiring data of sufficient quantity and quality. Here, we discuss recent progress on these issues.
AU  - Alahmadi,A
AU  - Belet,S
AU  - Black,A
AU  - Cromer,D
AU  - Flegg,JA
AU  - House,T
AU  - Jayasundara,P
AU  - Keith,JM
AU  - McCaw,JM
AU  - Moss,R
AU  - Ross,JV
AU  - Shearer,FM
AU  - Tun,STT
AU  - Walker,J
AU  - White,L
AU  - Whyte,JM
AU  - Yan,AWC
AU  - Zarebski,AE
DO  - 10.1016/j.epidem.2020.100393
PY  - 2020///
SN  - 1755-4365
TI  - Influencing public health policy with data-informed mathematical models of infectious diseases: Recent developments and new challenges
T2  - Epidemics: the journal of infectious disease dynamics
UR  - http://dx.doi.org/10.1016/j.epidem.2020.100393
UR  - https://www.ncbi.nlm.nih.gov/pubmed/32674025
UR  - http://hdl.handle.net/10044/1/82507
VL  - 32
ER  -
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