# Importation models for travel-related SARS-CoV-2 cases reported in Newfoundland and Labrador during the COVID-19 pandemic

**Authors:** Zahra Mohammadi, Monica Gabriela Cojocaru, Julien Arino, Amy Hurford

PMC · DOI: 10.1098/rsos.241902 · 2025-11-26

## TL;DR

This study examines how travel measures in Newfoundland and Labrador helped reduce SARS-CoV-2 importation during the pandemic.

## Contribution

The study emphasizes the importance of using region-specific data in importation models for accurate risk assessment.

## Key findings

- Travel to Newfoundland and Labrador decreased by 82% during the pandemic.
- The best model was 135 times more likely to explain travel-related cases when considering origin-specific data.
- Models without travel-related case data performed poorly, highlighting the need for such data in importation models.

## Abstract

During the COVID-19 pandemic, the World Health Organization updated guidelines for travel measure implementation to recommend consideration of a region's specific epidemiological, health system and socioeconomic context. As such, travel measure implementation decisions require region-specific data, analysis and models to support risk assessment frameworks. From May 2020 to May 2021, the Canadian province of Newfoundland and Labrador (NL) implemented travel measures that required self-isolation and testing of individuals returning from out-of-province travel. We found that during the pandemic travel to NL decreased by 82%. Our best model was 135 times more likely to explain reported travel-related cases arriving in NL than a model where travel volume and infection data did not consider the Canadian jurisdiction of origin. To test an approach used in other studies, we formulated a model without considering the travel-related case data and found that this model performed very poorly. We conclude that importation models need to be supported with data describing the daily number of travel-related cases arriving in Canadian jurisdictions and daily travel volumes originating from each country and each Canadian province and territory. While there was some reporting of this information during the COVID-19 pandemic, these data were not consistently reported or easily accessible.

## Linked entities

- **Diseases:** SARS-CoV-2 (MONDO:0100096), COVID-19 (MONDO:0100096)

## Full-text entities

- **Diseases:** COVID-19 (MESH:D000086382), infection (MESH:D007239)
- **Species:** Severe acute respiratory syndrome coronavirus 2 (no rank) [taxon 2697049]

## Figures

2 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12646790/full.md

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Source: https://tomesphere.com/paper/PMC12646790