Novel coronavirus (2019-nCoV) early-stage importation risk to Europe, January 2020

Pullano, Giulia; Pinotti, Francesco; Valdano, Eugenio; Boëlle, Pierre‐Yves; Poletto, Chiara; Colizza, Vittoria

doi:10.2807/1560-7917.es.2020.25.4.2000057

Cited by 134 publications

(115 citation statements)

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“…Furthermore, we used publicly available connectivity and risk estimates based on international travel data to predict the number of cases exported into each country. These estimates have shown good correspondence with the distribution of exported cases to date, 22 and are similar to another risk assessment for COVID-19 with different data. 23 We also assumed that the latent period is equal to the incubation period (ie, individuals become infectious and symptomatic at the same time) and all infected individuals will eventually become symptomatic.…”

Section: E Discussionsupporting

confidence: 79%

Early dynamics of transmission and control of COVID-19: a mathematical modelling study

Kucharski

Russell

Diamond

et al. 2020

The Lancet Infectious Diseases

2,533

2,422

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Background An outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to 95 333 confirmed cases as of March 5, 2020. Understanding the early transmission dynamics of the infection and evaluating the effectiveness of control measures is crucial for assessing the potential for sustained transmission to occur in new areas. Combining a mathematical model of severe SARS-CoV-2 transmission with four datasets from within and outside Wuhan, we estimated how transmission in Wuhan varied between December, 2019, and February, 2020. We used these estimates to assess the potential for sustained human-to-human transmission to occur in locations outside Wuhan if cases were introduced. Methods We combined a stochastic transmission model with data on cases of coronavirus disease 2019 (COVID-19) inWuhan and international cases that originated in Wuhan to estimate how transmission had varied over time during January, 2020, and February, 2020. Based on these estimates, we then calculated the probability that newly introduced cases might generate outbreaks in other areas. To estimate the early dynamics of transmission in Wuhan, we fitted a stochastic transmission dynamic model to multiple publicly available datasets on cases in Wuhan and internationally exported cases from Wuhan. The four datasets we fitted to were: daily number of new internationally exported cases (or lack thereof), by date of onset, as of Jan 26, 2020; daily number of new cases in Wuhan with no market exposure, by date of onset, between Dec 1, 2019, and Jan 1, 2020; daily number of new cases in China, by date of onset, between Dec 29, 2019, and Jan 23, 2020; and proportion of infected passengers on evacuation flights between Jan 29, 2020, and Feb 4, 2020. We used an additional two datasets for comparison with model outputs: daily number of new exported cases from Wuhan (or lack thereof) in countries with high connectivity to Wuhan (ie, top 20 most at-risk countries), by date of confirmation, as of Feb 10, 2020; and data on new confirmed cases reported in Wuhan between Jan 16, 2020, and Feb 11, 2020.Findings We estimated that the median daily reproduction number (R t ) in Wuhan declined from 2·35 (95% CI 1·15-4·77) 1 week before travel restrictions were introduced on Jan 23, 2020, to 1·05 (0·41-2·39) 1 week after. Based on our estimates of R t , assuming SARS-like variation, we calculated that in locations with similar transmission potential to Wuhan in early January, once there are at least four independently introduced cases, there is a more than 50% chance the infection will establish within that population.Interpretation Our results show that COVID-19 transmission probably declined in Wuhan during late January, 2020, coinciding with the introduction of travel control measures. As more cases arrive in international locations with similar transmission potential to Wuhan before these control measures, it is likely many chains of transmission will fail to establish initially, but might lead to new outbreaks eventually.

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Section: E Discussionsupporting

confidence: 79%

Early dynamics of transmission and control of COVID-19: a mathematical modelling study

Kucharski

Russell

Diamond

et al. 2020

The Lancet Infectious Diseases

2,533

2,422

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“…12 The province of Hubei was not included among the possible locations able to export the virus, given the travel ban introduced by Chinese authorities on Jan 23 and 24, 2020. 5 The importation risk per country in Africa was measured as the probability of importing a case from the infected provinces in China, accounting for the origindestination travel flows originated from such provinces and for their different epidemic levels (appendix p 2).…”

Section: Methodsmentioning

confidence: 99%

“…We assessed the risk of importation of cases of COVID-19 to Africa from affected provinces in China, and contextualised this risk with each country's vulnerability to epidemic emergencies and capacity to respond. Importation risk was determined by the volume of air traffic connections [5][6][7][8][9] from areas where the virus currently circulates in China. Each country's functional capacity to manage health security issues is based on WHO International Health Regulations (IHR) Monitoring and Evaluation Framework (MEF), 10 and on an indicator of vulnerability to emerging epidemics.…”

Section: Introductionmentioning

confidence: 99%

Preparedness and vulnerability of African countries against importations of COVID-19: a modelling study

et al. 2020

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Background The novel coronavirus disease 2019 (COVID-19) epidemic has spread from China to 25 countries. Local cycles of transmission have already occurred in 12 countries after case importation. In Africa, Egypt has so far confirmed one case. The management and control of COVID-19 importations heavily rely on a country's health capacity. Here we evaluate the preparedness and vulnerability of African countries against their risk of importation of COVID-19. MethodsWe used data on the volume of air travel departing from airports in the infected provinces in China and directed to Africa to estimate the risk of importation per country. We determined the country's capacity to detect and respond to cases with two indicators: preparedness, using the WHO International Health Regulations Monitoring and Evaluation Framework; and vulnerability, using the Infectious Disease Vulnerability Index. Countries were clustered according to the Chinese regions contributing most to their risk.Findings Countries with the highest importation risk (ie, Egypt, Algeria, and South Africa) have moderate to high capacity to respond to outbreaks. Countries at moderate risk (ie, and Kenya) have variable capacity and high vulnerability. We identified three clusters of countries that share the same exposure to the risk originating from the provinces of Guangdong, Fujian, and the city of Beijing, respectively.Interpretation Many countries in Africa are stepping up their preparedness to detect and cope with COVID-19 importations. Resources, intensified surveillance, and capacity building should be urgently prioritised in countries with moderate risk that might be ill-prepared to detect imported cases and to limit onward transmission.

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“…In Spain, this risk is around 5-10%, according to some estimates. 17 Imported cases have already been detected in Germany, Spain, France, Finland, Italy, the United Kingdom and Sweden, with some secondary cases.…”

Section: W Edwards Demingmentioning

confidence: 99%

One world, one health: The novel coronavirus COVID-19 epidemic

Trilla

2020

Medicina Clínica (English Edition)

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Novel coronavirus (2019-nCoV) early-stage importation risk to Europe, January 2020

Cited by 134 publications

References 1 publication

Early dynamics of transmission and control of COVID-19: a mathematical modelling study

Early dynamics of transmission and control of COVID-19: a mathematical modelling study

Preparedness and vulnerability of African countries against importations of COVID-19: a modelling study

One world, one health: The novel coronavirus COVID-19 epidemic

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