A Testing and Quarantine Algorithm for Individual International Travelers Using Published Data on WHO-Approved Vaccines and Bayes' Theorem

Policies such as border closures and quarantines have been widely used during the COVID-19 pandemic. Policy modifications and updates, however, must be adjusted as global vaccination rates increase. We calculated the risks of individual travelers based on their expected transmission and benchmarked them against that of an unvaccinated traveler quarantined for 14 days without testing. All individuals with a negative preboarding test can be released with a negative arrival test, when both tests have a sensitivity ≥ 90% and a specificity ≥ 97%, performance characteristics that could be accomplished by rapid antigen tests. This assumption is valid for an incidence rate up to 0.1 (prior to testing) and effective reproduction number (Rt) up to 4 in the arrival country. In a sensitivity analysis scenario where the incidence rate is 0.4 and Rt is 16, a negative preboarding test and a negative arrival test, both with a sensitivity ≥ 98% and a specificity ≥ 97%, can ensure that a traveler has a lower expected transmission than an unvaccinated person who is quarantined for 14 days. In most cases, fully vaccinated travelers (with or without booster) and a negative preboarding test can be released with a negative rapid antigen test upon arrival, allowing travelers to depart the airport within 30 min.

Medienart:

E-Artikel

Erscheinungsjahr:

2022

Erschienen:

2022

Enthalten in:

Zur Gesamtaufnahme - volume:10

Enthalten in:

Vaccines - 10(2022), 6 vom: 06. Juni

Sprache:

Englisch

Beteiligte Personen:

Lee, FuShiuan Whitney [VerfasserIn]
Wang, Jamie [VerfasserIn]
Wang, C Jason [VerfasserIn]

Links:

Volltext

Themen:

COVID-19
Journal Article
Pandemic
Testing and quarantine policy
Travel policy
Vaccinated travelers

Anmerkungen:

Date Revised 16.07.2022

published: Electronic

Citation Status PubMed-not-MEDLINE

doi:

10.3390/vaccines10060902

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM342675931