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Passengers' destinations from China: low risk of Novel Coronavirus (2019-nCoV) transmission into Africa and South America

Identifieur interne : 001951 ( Pmc/Checkpoint ); précédent : 001950; suivant : 001952

Passengers' destinations from China: low risk of Novel Coronavirus (2019-nCoV) transmission into Africa and South America

Auteurs : Najmul Haider ; Alexei Yavlinsky [Royaume-Uni] ; David Simons ; Abdinasir Yusuf Osman ; Francine Ntoumi [Allemagne] ; Alimuddin Zumla [Royaume-Uni] ; Richard Kock

Source :

RBID : PMC:7058650

Abstract

Novel Coronavirus (2019-nCoV [SARS-COV-2]) was detected in humans during the last week of December 2019 at Wuhan city in China, and caused 24 554 cases in 27 countries and territories as of 5 February 2020. The objective of this study was to estimate the risk of transmission of 2019-nCoV through human passenger air flight from four major cities of China (Wuhan, Beijing, Shanghai and Guangzhou) to the passengers' destination countries. We extracted the weekly simulated passengers' end destination data for the period of 1–31 January 2020 from FLIRT, an online air travel dataset that uses information from 800 airlines to show the direct flight and passengers' end destination. We estimated a risk index of 2019-nCoV transmission based on the number of travellers to destination countries, weighted by the number of confirmed cases of the departed city reported by the World Health Organization (WHO). We ranked each country based on the risk index in four quantiles (4th quantile being the highest risk and 1st quantile being the lowest risk). During the period, 388 287 passengers were destined for 1297 airports in 168 countries or territories across the world. The risk index of 2019-nCoV among the countries had a very high correlation with the WHO-reported confirmed cases (0.97). According to our risk score classification, of the countries that reported at least one Coronavirus-infected pneumonia (COVID-19) case as of 5 February 2020, 24 countries were in the 4th quantile of the risk index, two in the 3rd quantile, one in the 2nd quantile and none in the 1st quantile. Outside China, countries with a higher risk of 2019-nCoV transmission are Thailand, Cambodia, Malaysia, Canada and the USA, all of which reported at least one case. In pan-Europe, UK, France, Russia, Germany and Italy; in North America, USA and Canada; in Oceania, Australia had high risk, all of them reported at least one case. In Africa and South America, the risk of transmission is very low with Ethiopia, South Africa, Egypt, Mauritius and Brazil showing a similar risk of transmission compared to the risk of any of the countries where at least one case is detected. The risk of transmission on 31 January 2020 was very high in neighbouring Asian countries, followed by Europe (UK, France, Russia and Germany), Oceania (Australia) and North America (USA and Canada). Increased public health response including early case recognition, isolation of identified case, contract tracing and targeted airport screening, public awareness and vigilance of health workers will help mitigate the force of further spread to naïve countries.


Url:
DOI: 10.1017/S0950268820000424
PubMed: 32100667
PubMed Central: 7058650


Affiliations:


Links toward previous steps (curation, corpus...)


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PMC:7058650

Le document en format XML

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,
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<p>Novel Coronavirus (2019-nCoV [SARS-COV-2]) was detected in humans during the last week of December 2019 at Wuhan city in China, and caused 24 554 cases in 27 countries and territories as of 5 February 2020. The objective of this study was to estimate the risk of transmission of 2019-nCoV through human passenger air flight from four major cities of China (Wuhan, Beijing, Shanghai and Guangzhou) to the passengers' destination countries. We extracted the weekly simulated passengers' end destination data for the period of 1–31 January 2020 from FLIRT, an online air travel dataset that uses information from 800 airlines to show the direct flight and passengers' end destination. We estimated a risk index of 2019-nCoV transmission based on the number of travellers to destination countries, weighted by the number of confirmed cases of the departed city reported by the World Health Organization (WHO). We ranked each country based on the risk index in four quantiles (4
<sup>th</sup>
quantile being the highest risk and 1
<sup>st</sup>
quantile being the lowest risk). During the period, 388 287 passengers were destined for 1297 airports in 168 countries or territories across the world. The risk index of 2019-nCoV among the countries had a very high correlation with the WHO-reported confirmed cases (0.97). According to our risk score classification, of the countries that reported at least one Coronavirus-infected pneumonia (COVID-19) case as of 5 February 2020, 24 countries were in the 4
<sup>th</sup>
quantile of the risk index, two in the 3
<sup>rd</sup>
quantile, one in the 2
<sup>nd</sup>
quantile and none in the 1
<sup>st</sup>
quantile. Outside China, countries with a higher risk of 2019-nCoV transmission are Thailand, Cambodia, Malaysia, Canada and the USA, all of which reported at least one case. In pan-Europe, UK, France, Russia, Germany and Italy; in North America, USA and Canada; in Oceania, Australia had high risk, all of them reported at least one case. In Africa and South America, the risk of transmission is very low with Ethiopia, South Africa, Egypt, Mauritius and Brazil showing a similar risk of transmission compared to the risk of any of the countries where at least one case is detected. The risk of transmission on 31 January 2020 was very high in neighbouring Asian countries, followed by Europe (UK, France, Russia and Germany), Oceania (Australia) and North America (USA and Canada). Increased public health response including early case recognition, isolation of identified case, contract tracing and targeted airport screening, public awareness and vigilance of health workers will help mitigate the force of further spread to naïve countries.</p>
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<contrib contrib-type="author">
<contrib-id contrib-id-type="orcid" authenticated="true">https://orcid.org/0000-0002-5980-3460</contrib-id>
<name>
<surname>Haider</surname>
<given-names>Najmul</given-names>
</name>
<xref ref-type="aff" rid="aff1">1</xref>
<xref ref-type="corresp" rid="cor1"></xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Yavlinsky</surname>
<given-names>Alexei</given-names>
</name>
<xref ref-type="aff" rid="aff2">2</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Simons</surname>
<given-names>David</given-names>
</name>
<xref ref-type="aff" rid="aff1">1</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Osman</surname>
<given-names>Abdinasir Yusuf</given-names>
</name>
<xref ref-type="aff" rid="aff1">1</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Ntoumi</surname>
<given-names>Francine</given-names>
</name>
<xref ref-type="aff" rid="aff3">3</xref>
<xref ref-type="aff" rid="aff4">4</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zumla</surname>
<given-names>Alimuddin</given-names>
</name>
<xref ref-type="aff" rid="aff5">5</xref>
<xref ref-type="aff" rid="aff6">6</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Kock</surname>
<given-names>Richard</given-names>
</name>
<xref ref-type="aff" rid="aff1">1</xref>
</contrib>
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The Royal Veterinary College,
<institution>University of London</institution>
, Hawkshead Lane, North Mymms,
<city>Hatfield</city>
,
<country>Hertfordshire</country>
</aff>
<aff id="aff2">
<label>2</label>
Institute of Health Informatics,
<institution>University College London</institution>
,
<city>London</city>
,
<country>UK</country>
</aff>
<aff id="aff3">
<label>3</label>
<institution>Fondation Congolaise pour la Recherche Médicale (FCRM)</institution>
,
<city>Brazzaville</city>
,
<country>Republic of Congo</country>
</aff>
<aff id="aff4">
<label>4</label>
<institution>Institute for Tropical Medicine/University of Tübingen</institution>
,
<city>Tubingen</city>
,
<country>Germany</country>
</aff>
<aff id="aff5">
<label>5</label>
Department of Infection, Division of Infection and Immunity,
<institution>UCL Centre for Clinical Microbiology</institution>
, Royal Free campus,
<city>London</city>
,
<country>UK</country>
</aff>
<aff id="aff6">
<label>6</label>
NIHR Biomedical Research Centre,
<institution>UCL Hospitals NHS Foundation Trust</institution>
,
<city>London</city>
,
<country>UK</country>
</aff>
<author-notes>
<corresp id="cor1">
<bold>Author for correspondence:</bold>
Najmul Haider, E-mail:
<email>nhaider@rvc.ac.uk</email>
</corresp>
</author-notes>
<pub-date publication-format="electronic" date-type="collection" iso-8601-date="2020">
<year>2020</year>
</pub-date>
<pub-date publication-format="electronic" date-type="pub">
<day>26</day>
<month>2</month>
<year>2020</year>
</pub-date>
<volume>148</volume>
<elocation-id>e41</elocation-id>
<history>
<date date-type="received">
<day>07</day>
<month>2</month>
<year>2020</year>
</date>
<date date-type="accepted">
<day>09</day>
<month>2</month>
<year>2020</year>
</date>
</history>
<permissions>
<copyright-statement>© The Author(s) 2020</copyright-statement>
<copyright-year>2020</copyright-year>
<copyright-holder>The Author(s)</copyright-holder>
<license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/4.0/">
<ali:license_ref>http://creativecommons.org/licenses/by/4.0/</ali:license_ref>
<license-p>This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (
<uri xlink:href="http://creativecommons.org/licenses/by/4.0/">http://creativecommons.org/licenses/by/4.0/</uri>
), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
</license>
</permissions>
<self-uri xlink:title="pdf" xlink:href="S0950268820000424a.pdf"></self-uri>
<abstract abstract-type="normal">
<p>Novel Coronavirus (2019-nCoV [SARS-COV-2]) was detected in humans during the last week of December 2019 at Wuhan city in China, and caused 24 554 cases in 27 countries and territories as of 5 February 2020. The objective of this study was to estimate the risk of transmission of 2019-nCoV through human passenger air flight from four major cities of China (Wuhan, Beijing, Shanghai and Guangzhou) to the passengers' destination countries. We extracted the weekly simulated passengers' end destination data for the period of 1–31 January 2020 from FLIRT, an online air travel dataset that uses information from 800 airlines to show the direct flight and passengers' end destination. We estimated a risk index of 2019-nCoV transmission based on the number of travellers to destination countries, weighted by the number of confirmed cases of the departed city reported by the World Health Organization (WHO). We ranked each country based on the risk index in four quantiles (4
<sup>th</sup>
quantile being the highest risk and 1
<sup>st</sup>
quantile being the lowest risk). During the period, 388 287 passengers were destined for 1297 airports in 168 countries or territories across the world. The risk index of 2019-nCoV among the countries had a very high correlation with the WHO-reported confirmed cases (0.97). According to our risk score classification, of the countries that reported at least one Coronavirus-infected pneumonia (COVID-19) case as of 5 February 2020, 24 countries were in the 4
<sup>th</sup>
quantile of the risk index, two in the 3
<sup>rd</sup>
quantile, one in the 2
<sup>nd</sup>
quantile and none in the 1
<sup>st</sup>
quantile. Outside China, countries with a higher risk of 2019-nCoV transmission are Thailand, Cambodia, Malaysia, Canada and the USA, all of which reported at least one case. In pan-Europe, UK, France, Russia, Germany and Italy; in North America, USA and Canada; in Oceania, Australia had high risk, all of them reported at least one case. In Africa and South America, the risk of transmission is very low with Ethiopia, South Africa, Egypt, Mauritius and Brazil showing a similar risk of transmission compared to the risk of any of the countries where at least one case is detected. The risk of transmission on 31 January 2020 was very high in neighbouring Asian countries, followed by Europe (UK, France, Russia and Germany), Oceania (Australia) and North America (USA and Canada). Increased public health response including early case recognition, isolation of identified case, contract tracing and targeted airport screening, public awareness and vigilance of health workers will help mitigate the force of further spread to naïve countries.</p>
</abstract>
<kwd-group>
<title>Key words</title>
<kwd>2019-nCoV</kwd>
<kwd>Africa</kwd>
<kwd>China</kwd>
<kwd>risk map</kwd>
<kwd>transmission</kwd>
<kwd>Wuhan</kwd>
<kwd>COVID-19</kwd>
<kwd>SARS-COV-2</kwd>
</kwd-group>
<counts>
<fig-count count="2"></fig-count>
<table-count count="1"></table-count>
<ref-count count="17"></ref-count>
<page-count count="7"></page-count>
</counts>
</article-meta>
</front>
</pmc>
<affiliations>
<list>
<country>
<li>Allemagne</li>
<li>Royaume-Uni</li>
</country>
</list>
<tree>
<noCountry>
<name sortKey="Haider, Najmul" sort="Haider, Najmul" uniqKey="Haider N" first="Najmul" last="Haider">Najmul Haider</name>
<name sortKey="Kock, Richard" sort="Kock, Richard" uniqKey="Kock R" first="Richard" last="Kock">Richard Kock</name>
<name sortKey="Osman, Abdinasir Yusuf" sort="Osman, Abdinasir Yusuf" uniqKey="Osman A" first="Abdinasir Yusuf" last="Osman">Abdinasir Yusuf Osman</name>
<name sortKey="Simons, David" sort="Simons, David" uniqKey="Simons D" first="David" last="Simons">David Simons</name>
</noCountry>
<country name="Royaume-Uni">
<noRegion>
<name sortKey="Yavlinsky, Alexei" sort="Yavlinsky, Alexei" uniqKey="Yavlinsky A" first="Alexei" last="Yavlinsky">Alexei Yavlinsky</name>
</noRegion>
<name sortKey="Zumla, Alimuddin" sort="Zumla, Alimuddin" uniqKey="Zumla A" first="Alimuddin" last="Zumla">Alimuddin Zumla</name>
<name sortKey="Zumla, Alimuddin" sort="Zumla, Alimuddin" uniqKey="Zumla A" first="Alimuddin" last="Zumla">Alimuddin Zumla</name>
</country>
<country name="Allemagne">
<noRegion>
<name sortKey="Ntoumi, Francine" sort="Ntoumi, Francine" uniqKey="Ntoumi F" first="Francine" last="Ntoumi">Francine Ntoumi</name>
</noRegion>
</country>
</tree>
</affiliations>
</record>

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