key: cord-0939267-zcizdc7s
authors: Thompson, Hayley A; Imai, Natsuko; Dighe, Amy; Ainslie, Kylie E C; Baguelin, Marc; Bhatia, Sangeeta; Bhatt, Samir; Boonyasiri, Adhiratha; Boyd, Olivia; Brazeau, Nicholas F; Cattarino, Lorenzo; Cooper, Laura V; Coupland, Helen; Cucunuba, Zulma; Cuomo-Dannenburg, Gina; Djaafara, Bimandra; Dorigatti, Ilaria; Elsland, Sabine; FitzJohn, Richard; Fu, Han; Gaythorpe, Katy A M; Green, Will; Hallett, Timothy; Hamlet, Arran; Haw, David; Hayes, Sarah; Hinsley, Wes; Jeffrey, Benjamin; Knock, Edward; Laydon, Daniel J; Lees, John; Mangal, Tara D; Mellan, Thomas; Mishra, Swapnil; Mousa, Andria; Nedjati-Gilani, Gemma; Nouvellet, Pierre; Okell, Lucy; Parag, Kris V; Ragonnet-Cronin, Manon; Riley, Steven; Unwin, H Juliette T; Verity, Robert; Vollmer, Michaela; Volz, Erik; Walker, Patrick G T; Walters, Caroline; Wang, Haowei; Wang, Yuanrong; Watson, Oliver J; Whittaker, Charles; Whittles, Lilith K; Winskill, Peter; Xi, Xiaoyue; Donnelly, Christl A; Ferguson, Neil M
title: SARS-CoV-2 infection prevalence on repatriation flights from Wuhan City, China
date: 2020-08-24
journal: J Travel Med
DOI: 10.1093/jtm/taaa135
sha: 2829e6bbc739aa32cc4a677ef530525729af4aa8
doc_id: 939267
cord_uid: zcizdc7s

We estimated SARS-CoV-2 infection prevalence in cohorts of repatriated citizens from Wuhan to be 0.44% (95% CI: 0.19%–1.03%). Although not representative of the wider population we believe these estimates are helpful in providing a conservative estimate of infection prevalence in Wuhan City, China, in the absence of large-scale population testing early in the epidemic.

Highlight: We estimated SARS-CoV-2 infection prevalence in cohorts of repatriated citizens from Wuhan to be 0.44% (95% CI: 0.19%-1.03%). Although not representative of the wider population we believe these estimates are helpful in providing a conservative estimate of infection prevalence in Wuhan City, China, in the absence of large-scale population testing early in the epidemic.

The World Health Organization declared COVID-19 a global pandemic on 11 th March 2020. 1 Cases of atypical pneumonia caused by the SARS-CoV-2 virus were first detected in Wuhan City, China in late 2019. The growing scale of the outbreak and the strict travel and movement restrictions implemented in January 2020 prompted foreign governments to repatriate citizens from the then epicentre of transmission. 2 Between January 29 th and February 27 th , 56 flights repatriated a total of 8,597 individuals from Wuhan to 55 countries. This letter details SARS-CoV-2 infection prevalence over these repatriation flights. Estimating infection prevalence in repatriated individuals is useful especially early in an outbreak of a novel pathogen when local case ascertainment at the origin is low and relies on symptomatic testing. For example, if infection prevalence in repatriates is high this could indicate a highly transmissible and widely circulating pathogen.

Repatriation flights were identified from international and local news outlets and government press releases. We tracked the total number of repatriates per flight, final destinations, number tested on arrival, during and before release from quarantine, and of those who tested positive, the number symptomatic or asymptomatic where available (for downloadable data table of identified flights see our public GitHub repository: https://github.com/mrc-ide/repatriationcovid-19).

As testing protocols differed by country, we present the infection prevalence only for the 17 repatriation flights where all individuals (N=2,433) were tested upon arrival regardless of symptoms. As transmission during the flight itself could not be ruled out, we did not consider individuals who later tested positive during the quarantine period. By focusing on flights where all passengers were tested for SARS-CoV-2 infection with real-time Reverse Transcription Polymerase Chain Reaction (RT-PCR), regardless of symptoms, a more accurate estimate of infection prevalence can be obtained compared to relying on symptomatic surveillance testing alone. We calculated the infection point prevalence per flight as the number of positive RT-PCR test results on arrival divided by the total population tested and the corresponding exact 95% binomial confidence intervals. We used a binomial mixed-effects model to obtain a pooled estimate of infection prevalence over this time frame, accounting for the heterogeneity between different repatriated populations. 3, 4 Per flight infection prevalence ranged from 0 to 1.9% and of the 2,433 passengers tested immediately upon arrival, 13 individuals tested positive, resulting in a pooled infection prevalence in repatriates of 0.44% (95% CI: 0.19%-1.03%) (Figure 1 ). Over the 5 flights leaving Wuhan between 30 th January and 1 st February inclusive (flights closest to the reported peak of the epidemic in Wuhan) where everyone was tested on arrival, the pooled infection prevalence was 0.88% (6/685, 95% CI: 0.39%-1.93%). The infection risk for foreign nationals and tourists could differ from the general population due to socio-economic status, living and/or working conditions, and exposure patterns. In addition, following the travel ban on January 23 rd

symptomatic individuals may have been prevented from boarding these flights. Therefore, prevalence from repatriated flights can be considered a conservative estimate of infection prevalence in the wider population. Compared to the estimated infection prevalence of 3.6% (95% CI: 2.0-6.1%) and 6.3% (95% CI: 0.8-20.8%) amongst repatriates from European countries to Greece in late March, our estimates of prevalence in repatriates from Wuhan suggest relatively low levels of community transmission in Wuhan during this period despite flights occurring close to the reported peak of the epidemic. 5 More accurately than PCR positivity in repatriated populations, or symptomatic surveillance in local communities, retrospective local serological surveys can provide an insight into the scale of an outbreak as seroprevalence can be used as a measure of the cumulative incidence of infection. Several serological surveys have been conducted since the epidemic subsided in Wuhan. A survey conducted between March 15 th and April 28 th measured a seroprevalence of 3.27% (95% CI: 3.02-3.52%) in asymptomatic individuals visiting a general hospital in the Jianghan District, Wuhan, when adjusted for age and sex, and 2.72% (95% CI: 2.49-2.95) when adjusted for assay sensitivity and specificity. 6 Another survey conducted between March 30 th and April 10 th measured seroprevalence to be 3.8% (95% CI: 2.6-5.4%) in healthcare workers (HCWs), 3.8% (95% CI 2.2-6.3%) in hotel staff, and 3.2% (95% CI: 1.6-6.4%) in family members of HCWs. 7 However, it should be noted that these are high-risk populations and not necessarily representative of the general population of Wuhan. In addition, there is evidence that antibodies to SARS-CoV-2 wane quickly and so serosurveys may not capture all past infections within a population. 8 The repatriation flights we considered represent a globally diverse population of foreign nationals who were residing in Wuhan City leading up to the outbreak for variable periods of time and for a variety of reasons: students, work-related travel, visiting friends and families and tourism. It is important to note that it is unclear how the risk of infection posed to these individuals compared to the risk of infection within the general population in Wuhan City. We assume the infection prevalence in repatriated individuals can be used as a lower bound for infection prevalence in the general population. While this assumption is hard to quantify and validate it does impact the interpretation of our results and should be borne in mind. Despite this, characterising infection prevalence from repatriated cohorts highlights a way to help bridge the gap between symptom-based surveillance which may under-estimate true infection prevalence and seroprevalence surveys which are difficult to conduct during epidemic peaks.

Author contributions: HAT, NI, CAD, NMF conceived the study; HAT, NI, AD, WG, GCD, KAMG, HF collected and extracted the international flight data and information on testing strategies; HAT and NI carried out the analysis; HAT wrote the first draft with input from NI and AD; all authors contributed to the final draft.

Funding: This work was supported by joint Centre funding from the UK Medical Research Council and Department for International Development.

The authors have declared no conflicts of interest. 

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Random effects meta-analysis of event outcome in the framework of the generalized linear mixed model with applications in sparse data

The binomial distribution of meta-analysis was preferred to model within-study variability

High prevalence of SARS-CoV-2 infection in repatriation flights to Greece from three European countries

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