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Comparing Data Collection Strategies via Input Uncertainty When Simulating Testing Policies Using Viral Load Profiles

Research output: Contribution to conference - Without ISBN/ISSN Conference paperpeer-review

Forthcoming
Publication date18/06/2021
<mark>Original language</mark>English
EventWinter Simulation Conference 2021 - Online
Duration: 13/12/202116/12/2021

Conference

ConferenceWinter Simulation Conference 2021
Abbreviated titleWSC '21
Period13/12/2116/12/21

Abstract

Temporal profiles of viral load have individual variability and are used to determine whether individuals are infected based on some limit of detection. Modelling and simulating viral load profiles allows for the performance of testing policies to be estimated, however viral load behaviour can be very uncertain. We describe an approach for studying the input uncertainty passed to simulated policy performance when viral load profiles are estimated from different data collection strategies. Our example shows that comparing the strategies solely based on input uncertainty is inappropriate due to the differences in confidence interval coverage caused by negatively biased simulation outputs.