Imperial College London
Alternate

Professor Deirdre Hollingsworth

Faculty of Medicine, School of Public Health

Honorary Lecturer
 
 
 
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Contact

 

d.hollingsworth Website

 
 
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Location

 

Norfolk PlaceSt Mary's Campus

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Summary

 

Publications

Citation

BibTex format

@article{Lucas:2020:10.1016/j.epidem.2020.100425,
author = {Lucas, TCD and Pollington, TM and Davis, EL and Hollingsworth, TD},
doi = {10.1016/j.epidem.2020.100425},
journal = {Epidemics: the journal of infectious disease dynamics},
title = {Responsible modelling: Unit testing for infectious disease epidemiology},
url = {http://dx.doi.org/10.1016/j.epidem.2020.100425},
volume = {33},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Infectious disease epidemiology is increasingly reliant on large-scale computation and inference. Models have guided health policy for epidemics including COVID-19 and Ebola and endemic diseases including malaria and tuberculosis. Yet a coding bug may bias results, yielding incorrect conclusions and actions causing avoidable harm. We are ethically obliged to make our code as free of error as possible. Unit testing is a coding method to avoid such bugs, but it is rarely used in epidemiology. We demonstrate how unit testing can handle the particular quirks of infectious disease models and aim to increase the uptake of this methodology in our field.
AU  - Lucas,TCD
AU  - Pollington,TM
AU  - Davis,EL
AU  - Hollingsworth,TD
DO  - 10.1016/j.epidem.2020.100425
PY  - 2020///
SN  - 1755-4365
TI  - Responsible modelling: Unit testing for infectious disease epidemiology
T2  - Epidemics: the journal of infectious disease dynamics
UR  - http://dx.doi.org/10.1016/j.epidem.2020.100425
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000603368600004&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - http://hdl.handle.net/10044/1/85899
VL  - 33
ER  -
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