Quantifying SARS-CoV-2 Infection Risk Within the Google/Apple Exposure Notification Framework to Inform Quarantine Recommendations.
Risk Anal
; 42(1): 162-176, 2022 01.
Article
in English
| MEDLINE | ID: covidwho-1961875
ABSTRACT
Most early Bluetooth-based exposure notification apps use three binary classifications to recommend quarantine following SARS-CoV-2 exposure a window of infectiousness in the transmitter, ≥15 minutes duration, and Bluetooth attenuation below a threshold. However, Bluetooth attenuation is not a reliable measure of distance, and infection risk is not a binary function of distance, nor duration, nor timing. We model uncertainty in the shape and orientation of an exhaled virus-containing plume and in inhalation parameters, and measure uncertainty in distance as a function of Bluetooth attenuation. We calculate expected dose by combining this with estimated infectiousness based on timing relative to symptom onset. We calibrate an exponential dose-response curve based on infection probabilities of household contacts. The probability of current or future infectiousness, conditioned on how long postexposure an exposed individual has been symptom-free, decreases during quarantine, with shape determined by incubation periods, proportion of asymptomatic cases, and asymptomatic shedding durations. It can be adjusted for negative test results using Bayes' theorem. We capture a 10-fold range of risk using six infectiousness values, 11-fold range using three Bluetooth attenuation bins, â¼sixfold range from exposure duration given the 30 minute duration cap imposed by the Google/Apple v1.1, and â¼11-fold between the beginning and end of 14 day quarantine. Public health authorities can either set a threshold on initial infection risk to determine 14-day quarantine onset, or on the conditional probability of current and future infectiousness conditions to determine both quarantine and duration.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Quarantine
/
Contact Tracing
/
Disease Notification
/
Search Engine
/
SARS-CoV-2
/
COVID-19
Type of study:
Observational study
/
Prognostic study
Topics:
Long Covid
Limits:
Humans
Country/Region as subject:
North America
Language:
English
Journal:
Risk Anal
Year:
2022
Document Type:
Article
Affiliation country:
Risa.13768
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