Tracing and analysis of 288 early SARS-CoV-2 infections outside China: A modeling study


Autoři: Francesco Pinotti aff001;  Laura Di Domenico aff001;  Ernesto Ortega aff002;  Marco Mancastroppa aff003;  Giulia Pullano aff001;  Eugenio Valdano aff001;  Pierre-Yves Boelle aff001;  Chiara Poletto aff001;  Vittoria Colizza aff001
Působiště autorů: INSERM, Sorbonne Université, Pierre Louis Institute of Epidemiology and Public Health, Paris, France aff001;  Facultad de Física, Universidad de la Habana, Cuba aff002;  Dipartimento di Scienze Matematiche, Fisiche e Informatiche, Università degli Studi di Parma, Parco Area delle Scienze, Parma, Italy aff003;  INFN, Gruppo Collegato di Parma, Parco Area delle Scienze, Parma, Italy aff004;  Sociology and Economics of Networks and Services lab at Orange Experience Design Lab (SENSE/XDLab) Chatillion, Paris, France aff005;  Center for Biomedical Modeling, The Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, United States of America aff006
Vyšlo v časopise: Tracing and analysis of 288 early SARS-CoV-2 infections outside China: A modeling study. PLoS Med 17(7): e32767. doi:10.1371/journal.pmed.1003193
Kategorie: Research Article
doi: 10.1371/journal.pmed.1003193

Souhrn

Background

In the early months of 2020, a novel coronavirus disease (COVID-19) spread rapidly from China across multiple countries worldwide. As of March 17, 2020, COVID-19 was officially declared a pandemic by the World Health Organization. We collected data on COVID-19 cases outside China during the early phase of the pandemic and used them to predict trends in importations and quantify the proportion of undetected imported cases.

Methods and findings

Two hundred and eighty-eight cases have been confirmed out of China from January 3 to February 13, 2020. We collected and synthesized all available information on these cases from official sources and media. We analyzed importations that were successfully isolated and those leading to onward transmission. We modeled their number over time, in relation to the origin of travel (Hubei province, other Chinese provinces, other countries) and interventions. We characterized the importation timeline to assess the rapidity of isolation and epidemiologically linked clusters to estimate the rate of detection. We found a rapid exponential growth of importations from Hubei, corresponding to a doubling time of 2.8 days, combined with a slower growth from the other areas. We predicted a rebound of importations from South East Asia in the successive weeks. Time from travel to detection has considerably decreased since first importation, from 14.5 ± 5.5 days on January 5, 2020, to 6 ± 3.5 days on February 1, 2020. However, we estimated 36% of detection of imported cases. This study is restricted to the early phase of the pandemic, when China was the only large epicenter and foreign countries had not discovered extensive local transmission yet. Missing information in case history was accounted for through modeling and imputation.

Conclusions

Our findings indicate that travel bans and containment strategies adopted in China were effective in reducing the exportation growth rate. However, the risk of importation was estimated to increase again from other sources in South East Asia. Surveillance and management of traveling cases represented a priority in the early phase of the epidemic. With the majority of imported cases going undetected (6 out of 10), countries experienced several undetected clusters of chains of local transmissions, fueling silent epidemics in the community. These findings become again critical to prevent second waves, now that countries have reduced their epidemic activity and progressively phase out lockdown.

Klíčová slova:

Asia – Epidemiology – Forecasting – China – Infectious disease control – Iran – Italy – Statistical models


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