The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak

Chinazzi, Matteo; Davis, Jessica T.; Ajelli, Marco; Gioannini, Corrado; Litvinova, Maria; Merler, Stefano; Piontti, Ana Pastore y; Mu, Kunpeng; Rossi, Luca; Sun, Kaiyuan; Viboud, Cécile; Xiong, Xinyue; Yu, Hongjie; Halloran, M. Elizabeth; Longini, Ira M.; Vespignani, Alessandro

doi:10.1126/science.aba9757

Cited by 3,447 publications

(3,233 citation statements)

References 26 publications

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“…The risk of importation of cases of COVID-19 to Africa from China was estimated based on origin-destination air travel flows from January, 2019; 8,11,12 number of cases in Chinese provinces; and the population in each of the Chinese provinces that reported transmission. Air travel flows counts the number of origin-destination tickets and account for any connection at intermediate airports.…”

Section: Methodsmentioning

confidence: 99%

“…An insufficiency of passenger data (eg, reason for travel [tourism vs business], nationality, age, sex, and socioeconomic status) also prevent us from accounting for different risk exposure of travellers to China. Travel flow data to estimate risk have already been validated against confirmed imported cases, 8 indicating that homogeneous assump tions on travellers' profiles and risk of exposure in China are enough to explain the exportations reported so far.…”

Section: Cluster Number 3 (Two Countries)mentioning

confidence: 97%

“…Previous and current evidence indicates that realistic travel restrictions would have a limited effect in containing the epidemic and would delay the risk that the outbreak extends to new countries by only a few weeks. 8,22,23 Travel or trade restrictions are not currently recommended by WHO. 1 Algeria, Ethiopia, South Africa, and Nigeria were part of the 13 top priority countries identified by WHO on the basis of their direct links and volume of travel to China.…”

Section: Cluster Number 3 (Two Countries)mentioning

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%

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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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Section: Methodsmentioning

confidence: 99%

Section: Cluster Number 3 (Two Countries)mentioning

confidence: 97%

Section: Cluster Number 3 (Two Countries)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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“…First, with the exception of Ethiopian airlines, all African airlines have suspended flights to China. Although these measures might delay, but not stop, 5 the importation risk of COVID-19 into Africa, their implementation is still worthwhile. Second, although Beijing, Shanghai, and Fujian do not report the highest number of cases of COVID-19 in China, the volume of travel from these cities to Africa is high, which might increase the risk of exporting cases to Africa.…”

Section: Looming Threat Of Covid-19 Infection In Africa: Act Collectimentioning

confidence: 99%

Looming threat of COVID-19 infection in Africa: act collectively, and fast

2020

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Association of Public Health Interventions With the Epidemiology of the COVID-19 Outbreak in Wuhan, China

Pan

Liu

Wang

et al. 2020

JAMA

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IMPORTANCE Coronavirus disease 2019 (COVID-19) has become a pandemic, and it is unknown whether a combination of public health interventions can improve control of the outbreak. OBJECTIVE To evaluate the association of public health interventions with the epidemiological features of the COVID-19 outbreak in Wuhan by 5 periods according to key events and interventions.DESIGN, SETTING, AND PARTICIPANTS In this cohort study, individual-level data on 32 583 laboratory-confirmed COVID-19 cases reported between December 8, 2019, and March 8, 2020, were extracted from the municipal Notifiable Disease Report System, including patients' age, sex, residential location, occupation, and severity classification. EXPOSURES Nonpharmaceutical public health interventions including cordons sanitaire, traffic restriction, social distancing, home confinement, centralized quarantine, and universal symptom survey. MAIN OUTCOMES AND MEASURESRates of laboratory-confirmed COVID-19 infections (defined as the number of cases per day per million people), across age, sex, and geographic locations were calculated across 5 periods: December 8 to January 9 (no intervention), January 10 to 22 (massive human movement due to the Chinese New Year holiday), January 23 to February 1 (cordons sanitaire, traffic restriction and home quarantine), February 2 to 16 (centralized quarantine and treatment), and February 17 to March 8 (universal symptom survey). The effective reproduction number of SARS-CoV-2 (an indicator of secondary transmission) was also calculated over the periods. RESULTS Among 32 583 laboratory-confirmed COVID-19 cases, the median patient age was 56.7 years (range, 0-103; interquartile range, 43.4-66.8) and 16 817 (51.6%) were women. The daily confirmed case rate peaked in the third period and declined afterward across geographic regions and sex and age groups, except for children and adolescents, whose rate of confirmed cases continued to increase. The daily confirmed case rate over the whole period in local health care workers (130.5 per million people [95% CI, 123.9-137.2]) was higher than that in the general population (41.5 per million people [95% CI, 41.0-41.9]). The proportion of severe and critical cases decreased from 53.1% to 10.3% over the 5 periods. The severity risk increased with age: compared with those aged 20 to 39 years (proportion of severe and critical cases, 12.1%), elderly people (Ն80 years) had a higher risk of having severe or critical disease (proportion, 41.3%; risk ratio, 3.61 [95% CI,) while younger people (<20 years) had a lower risk (proportion, 4.1%; risk ratio, 0.47 [95% CI, 0.31-0.70]). The effective reproduction number fluctuated above 3.0 before January 26, decreased to below 1.0 after February 6, and decreased further to less than 0.3 after March 1. CONCLUSIONS AND RELEVANCEA series of multifaceted public health interventions was temporally associated with improved control of the COVID-19 outbreak in Wuhan, China. These findings may inform public health policy in other countries and regions.

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The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak

Cited by 3,447 publications

References 26 publications

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

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

Looming threat of COVID-19 infection in Africa: act collectively, and fast

Association of Public Health Interventions With the Epidemiology of the COVID-19 Outbreak in Wuhan, China

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