About: Symptom-Based Isolation Policies: Evidence from a Mathematical Model of Outbreaks of Influenza and COVID-19

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About: Symptom-Based Isolation Policies: Evidence from a Mathematical Model of Outbreaks of Influenza and COVID-19 Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Symptom-Based Isolation Policies: Evidence from a Mathematical Model of Outbreaks of Influenza and COVID-19
Creator	Burns, Adam Gutfraind, Alexander
Source	MedRxiv; Medline; PMC
abstract	BACKGROUND: Controlling the transmission of respiratory infections such as influenza and COVID-19 is a critical public health priority. Non-pharmaceutical intervention policies such as community quarantines, closures and travel bans are often implemented in emergencies but many of them are disruptive and difficult to maintain for extended periods of time. A promising alternative recommended by the CDC for influenza is requiring individuals showing fever symptoms to remain isolated at home until they are fever-free for at least one day, but there is limited evidence to support the effectiveness of such symptom-based isolation policies. METHODS: Here we introduce a computational model of symptom-based isolation that accounts for the timing of symptoms, viral shedding and the population structure. It was validated on outbreaks of influenza in schools and modified to account for COVID-19. It was then used to estimate the outbreak curves and the attack rates (the proportion of the population infected) under one or more days of fever-based isolation. RESULTS: Using the model we find evidence that symptom-based isolation policies could reduce the attack rates of both influenza and COVID-19 outbreaks, and flatten the outbreak curves. Specifically, we found that across a range of influenza scenarios, a CDC-recommended policy of one day isolation following fever can reduce the attack rate from 27% of the population to 12%, and to 3% if the isolation is extended to two days. In COVID-19 transmission, we estimate that implementing one day post-fever isolation would reduce the attack rate from 79% to 71%, and there is possible benefit from isolation for six days. In both influenza and COVID-19, the policies are predicted to reduce the peak number of infected but not shorten the outbreak duration. CONCLUSIONS: Symptom-based isolation could be an important tool to control influenza and COVID-19 outbreaks in schools, and potentially other settings. We recommend that schools implement a post-fever isolation policy of two days for influenza and six days for COVID-19.
has issue date	2020-03-30(xsd:dateTime)
bibo:doi	10.1101/2020.03.26.20044750
bibo:pmid	32511602
has license	cc-by
sha1sum (hex)	67ca27806a8d9b00ac27ba17a6bc2bd4648eedf8
schema:url	https://doi.org/10.1101/2020.03.26.20044750
resource representing a document's title	Symptom-Based Isolation Policies: Evidence from a Mathematical Model of Outbreaks of Influenza and COVID-19
has PubMed Central identifier	PMC7276029
has PubMed identifier	32511602
schema:publication	medRxiv
resource representing a document's body	covid:67ca27806a8d9b00ac27ba17a6bc2bd4648eedf8#body_text
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