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Background: Effective Coronavirus Disease 2019 (COVID-19) response relies on good knowledge of population infection dynamics, but owing to under-ascertainment and delays in symptom-based reporting, obtaining reliable infection data has typically required large dedicated local population studies. Although many countries implemented Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) testing among travellers, it remains unclear how accurately arrival testing data can capture international patterns of infection, because those arrival testing data were rarely reported systematically, and predeparture testing was often in place as well, leading to nonrepresentative infection status among arrivals. Methods and findings: In French Polynesia, testing data were reported systematically with enforced predeparture testing type and timing, making it possible to adjust for nonrepresentative infection status among arrivals. Combining statistical models of polymerase chain reaction (PCR) positivity with data on international travel protocols, we reconstructed estimates of prevalence at departure using only testing data from arrivals. We then applied this estimation approach to the United States of America and France, using data from over 220,000 tests from travellers arriving into French Polynesia between July 2020 and March 2022. We estimated a peak infection prevalence at departure of 2.1% (95% credible interval: 1.7, 2.6%) in France and 1% (95% CrI: 0.63, 1.4%) in the USA in late 2020/early 2021, with prevalence of 4.6% (95% CrI: 3.9, 5.2%) and 4.3% (95% CrI: 3.6, 5%), respectively, estimated for the Omicron BA.1 waves in early 2022. We found that our infection estimates were a leading indicator of later reported case dynamics, as well as being consistent with subsequent observed changes in seroprevalence over time. We did not have linked data on traveller demography or unbiased domestic infection estimates (e.g., from random community infection surveys) in the USA and France. However, our methodology would allow for the incorporation of prior data from additional sources if available in future. Conclusions: As well as elucidating previously unmeasured infection dynamics in these countries, our analysis provides a proof-of-concept for scalable and accurate leading indicator of global infections during future pandemics. Using travel testing data for SARS-CoV-2 infection obtained from international arrivals and departures, Adam J. Kucharski and colleagues estimate SARS-CoV-2 prevalence in multiple countries. Author summary: Why was this study done?: • During the Coronavirus Disease 2019 (COVID-19) pandemic, the true dynamics of infections have been poorly understood globally. • Although community infection surveys sampling individuals regardless of symptoms have provided crucial insights to inform policy in countries like the United Kingdom, expense and logistical challenges have prevented similar roll-out elsewhere. What did the researchers do and find?: • We identified an alternative source of routine information that can provide comparable insights on infection dynamics: Our analysis demonstrates that travel testing data among international arrivals can be used to reconstruct Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) prevalence in multiple countries. • Applying our method to more than 222,000 arrival tests conducted in French Polynesia between July 2020 and March 2022, we estimated a peak infection prevalence at departure of around 2% in France and 1% in the USA in late 2020/early 2021, with a median prevalence of around 5% and 4%, respectively, estimated for the Omicron BA.1 waves in early 2022. • We found that our infection estimates were a leading indicator of the later observed case dynamics in these countries and were consistent with subsequent observed changes in seroprevalence over time in France and the USA. What do these findings mean?: • Our results suggest that systematic collection of traveller testing data can enable real-time estimation of underlying epidemic dynamics in multiple countries. • In our study, personal data about travellers—such as age and address—was not available for analysis. In future, linking traveller tests to demographic characteristics most relevant to infection status could enable a more detailed understanding of risk. [ABSTRACT FROM AUTHOR]

In French Polynesia, the first case of SARS-CoV-2 infection was detected on March 10th, 2020, in a resident returning from France. Between March 28th and July 14th, international air traffic was interrupted and local transmission of SARS-CoV-2 was brought under control, with only 62 cases recorded. The main challenge for reopening the air border without requiring travelers to quarantine on arrival was to limit the risk of re-introducing SARS-CoV-2. Specific measures were implemented, including the obligation for all travelers to have a negative RT-PCR test for SARS-CoV-2 carried out within 3 days before departure, and to perform another RT-PCR testing 4 days after arrival. Because of limitation in available medical staff, travelers were provided a kit allowing self-collection of oral and nasal swabs. In addition to increase our testing capacity, self-collected samples from up to 10 travelers were pooled before RNA extraction and RT-PCR testing. When a pool tested positive, RNA extraction and RT-PCR were performed on each individual sample. We report here the results of COVID-19 surveillance (COV-CHECK PORINETIA) conducted between July 15th, 2020, and February 15th, 2021, in travelers using self-collection and pooling approaches. We tested 5,982 pools comprising 59,490 individual samples, and detected 273 (0.46%) travelers positive for SARS-CoV-2. A mean difference of 1.17 Ct (CI 95% 0.93-1.41) was found between positive individual samples and pools (N = 50), probably related to the volume of samples used for RNA extraction (200 μL versus 50 μL, respectively). Retrospective testing of positive samples self-collected from October 20th, 2020, using variants-specific amplification kit and spike gene sequencing, found at least 6 residents infected by the Alpha variant. Self-collection and pooling approaches allowed large-scale screening for SARS-CoV-2 using less human, material and financial resources. Moreover, this strategy allowed detecting the introduction of SARS-CoV-2 variants of concern in French Polynesia., Competing Interests: The authors have declared that no competing interests exist.