Real-time surveillance of international SARS-CoV-2 prevalence using systematic traveller arrival screening (preprint)

ABSTRACT

Background: Effective COVID-19 response relies on good knowledge of 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 SARS-CoV-2 testing among travellers, interpretation of arrival testing data has typically been challenging because arrival testing data were rarely reported systematically, and pre-departure testing was often in place as well, leading to non-representative infection status among arrivals. Methods: In French Polynesia, testing data were reported systematically with enforced pre-departure testing type and timing, making it possible to adjust for non-representative infection status among arrivals. Combining statistical models of 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 USA and France, using data from over 220,000 tests from travellers arriving into French Polynesia between July 2020 and March 2022. Findings: We estimated a peak infection prevalence at departure of 2.8% (2.3-3.6%) in France and 1.1% (0.81-3.1%) in the USA in late 2020/early 2021, with prevalence of 5.4% (4.8-6.1%) and 5.5% (4.6-6.6%) 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. Interpretation: As well as elucidating previously unmeasured infection dynamics in these countries, our analysis provides a proof-of-concept for scalable tracking of global infections during future pandemics.