%0 Journal Article
%T Modeling approaches to inform travel-related policies for COVID-19 containment: a scoping review and future directions.
%A Koiso S
%A Gulbas E
%A Dike L
%A Mulroy NM
%A Ciaranello AL
%A Freedberg KA
%A Jalali MS
%A Walker AT
%A Ryan ET
%A LaRocque RC
%A Hyle EP
%J Travel Med Infect Dis
%V 0
%N 0
%D 2024 Jun 1
%M 38830442
%F 20.441
%R 10.1016/j.tmaid.2024.102730
%X <B>BACKGROUND: </B>Travel-related strategies to reduce the spread of COVID-19 evolved rapidly in response to changes in the understanding of SARS-CoV-2 and newly available tools for prevention, diagnosis, and treatment. Modeling is an important methodology to investigate the range of outcomes that could occur from different disease containment strategies.<BR><B>METHODS: </B>We examined 43 articles published from December 2019 through September 2022 that used modeling to evaluate travel-related COVID-19 containment strategies. We extracted and synthesized data regarding study objectives, methods, outcomes, populations, settings, strategies, and costs. We used a standardized approach to evaluate each analysis according to 26 criteria for modeling quality and rigor.<BR><B>RESULTS: </B>The most frequent approaches included compartmental modeling to examine quarantine, isolation, or testing. Early in the pandemic, the goal was to prevent travel-related COVID-19 cases with a focus on individual-level outcomes and assessing strategies such as travel restrictions, quarantine without testing, social distancing, and on-arrival PCR testing. After the development of diagnostic tests and vaccines, modeling studies projected population-level outcomes and investigated these tools to limit COVID-19 spread. Very few published studies included rapid antigen screening strategies, costs, explicit model calibration, or critical evaluation of the modeling approaches.<BR><B>CONCLUSIONS: </B>Future modeling analyses should leverage open-source data, improve the transparency of modeling methods, incorporate newly available prevention, diagnostics, and treatments, and include costs and cost-effectiveness so that modeling analyses can be informative to address future SARS-CoV-2 variants of concern and other emerging infectious diseases (e.g., mpox and Ebola) for travel-related health policies.