23 Oct 2014

Assessing the #impact of #travel #restrictions on #international #spread of the 2014 West African #Ebola epidemic (@Eurosurveillanc, edited)

[Source: Eurosurveillance, full page: (LINK). Edited.]

Eurosurveillance, Volume 19, Issue 42, 23 October 2014  / Rapid communications

Assessing the impact of travel restrictions on international spread of the 2014 West African Ebola epidemic [      ]

C Poletto1,2, M F Gomes3, A Pastore y Piontti3, L Rossi4, L Bioglio1,2, D L Chao5, I M Longini6, M E Halloran5, V Colizza 1,2,4, A Vespignani3

1INSERM, UMR-S 1136, Institut Pierre Louis d’Epidémiologie et de Santé Publique, Paris, France  - 2 Sorbonne Universités, UPMC Univ Paris 06, UMR-S 1136, Institut Pierre Louis d’Epidémiologie et de Santé Publique, Paris, France – 3 Laboratory for the Modeling of Biological and Socio-Technical Systems, Northeastern University, Boston, Massachusetts, United States – 4 Institute for Scientific Interchange (ISI), Turin, Italy  - 5 Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States  - 6 Department of Biostatistics, University of Florida, Gainesville, Florida, United States


Citation style for this article: Poletto C, Gomes MF, Pastore y Piontti A, Rossi L, Bioglio L, Chao DL, Longini IM, Halloran ME, Colizza V, Vespignani A. Assessing the impact of travel restrictions on international spread of the 2014 West African Ebola epidemic. Euro Surveill. 2014;19(42):pii=20936. Available online: http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=20936

Date of submission: 26 September 2014



The quick spread of an Ebola outbreak in West Africa has led a number of countries and airline companies to issue travel bans to the affected areas. Considering data up to 31 Aug 2014, we assess the impact of the resulting traffic reductions with detailed numerical simulations of the international spread of the epidemic. Traffic reductions are shown to delay by only a few weeks the risk that the outbreak extends to new countries.



The 2014 Ebola outbreak currently involves three countries with widespread and intense transmission in the West African region (Guinea, Liberia and Sierra Leone) and four others where initial case(s) or localised transmission have been reported (Nigeria, Senegal, Spain and the United States), reaching a total of 8,997 cases and 4,493 deaths in the official report of 15 October 2014 [1].

With the number of cases exponentially increasing in the affected area, several agencies and governments are calling for massive coordinated interventions aimed at the surveillance and containment of the epidemic [2]. Scaling up the international response appears necessary for providing financial support, supply of technical resources and expertise, and delivery of essential services to the affected area [2]. The need to consider an international framework lies also in the possible further international spread of the epidemic [3]. In response to such concerns and in an attempt to reduce the risk of case importation, several countries and airlines have adopted travel restrictions to and from the affected area. These include the suspension of flights by a number of carriers, air/sea/land border closures, restrictions for non-residents, suspension of visa issuance, and entry screening. Travel bans could potentially hamper the delivery of medical supplies and the deployment of specialised personnel to manage the epidemic [4]. Although international public health and relief agencies and representatives have been urgently calling for lifting such travel bans [4-6], these disease-avoidance mechanisms remain in place at the time of writing, and more are being considered. In light of their potentially harmful effects, the benefits of travel restrictions need to be carefully evaluated.

Air travel data is a critical source of information that has been recently analysed to characterise the degree of connectivity of the affected area to the rest of the world [7,8]. Air travel and human mobility data have also been integrated in large-scale computer microsimulations that, taking explicitly into account the local evolution of the epidemic in the affected countries, quantify the risk for international spread of Ebola virus disease (EVD) out of Africa in the short term [9]. Hypothetical simulation scenarios considering an 80% reduction of passenger traffic flow out of the region indicate that further international spread is delayed by only a few weeks. Here, we use the model to quantify the effect that the travel restrictions implemented during August 2014 by countries and airlines have on the global spread of Ebola. By comparing the differences between simulations with and without travel restrictions, we can make quantitative estimates of the effectiveness of such restrictions on reducing the importation of new Ebola cases to countries outside of West Africa. Our goal is to inform the debate over the utility of travel bans to slow the spread of Ebola.



We used 2013 flight itinerary data providing travel volumes of passengers flying between any origin–destination pair of commercial airports in the world (International Air Transport Association (IATA), www.iata.org; Official Airline Guide (OAG), www.oag.com). Starting from the airport of origin, each itinerary reports all connecting airports to reach the final destination and the airline companies handling the connecting flights along the given route. We collected publicly available information on the travel restrictions related to Ebola-affected regions up to 31 August 2014. We considered both travel bans implemented by national authorities and flight discontinuations by individual airlines (Table). Restrictions are heterogeneous in terms of start date and target country in the affected area (e.g. some concern the entire Western Africa area and others just one of its countries). Flight suspensions by airline company A targeting the set of countries C were considered by removing from the flight database all itineraries (and associated travel volumes) to C where A was the dominant airline. Then, travel bans and border closures implemented by country B targeting the set of countries C were considered by singling out all itineraries connecting B with C (in both directions) and reducing by a factor r the associated travel volumes, with rneighbours = 80% for the affected area’s neighbouring countries and rothers = 90% for all other countries, to model residual human mobility and non-compliance to policies. The resulting overall traffic reduction for each country was obtained by combining the effect of flight discontinuation and country level travel bans. We further required that the overall reduction could not be larger than r. This additional constraint is meant to model additional types of possible movements not captured by the air travel data (e.g. cross-border ground movement) and also adaptation to the restrictions (e.g. rearrangements of flight itineraries to other airline companies) for which detailed data are not currently available.


Table. Travel restrictions to and from Ebola-affected areas implemented by authorities and companies as of 31 August 2014


We used the Global Epidemic and Mobility model [10,11] applied to the EVD outbreak [9] to simulate case importation events in 220 countries around the world. The model [9] accounts for EVD transmission in the general community, in hospital settings, and during funeral rites [12]. Basic reproductive numbers for each of these settings were inferred through a Monte Carlo likelihood analysis considering more than 3,500,000 simulations that sampled the disease model parameter space and the case data on the EVD outbreak up to 27 August 2014. Other epidemiological parameters were taken from the literature [9,12,13]. The spatio-temporal epidemic evolution is modelled using individual-level dynamics where transitions are mathematically defined by chain binomial and multinomial processes to preserve the discrete and stochastic nature of the processes. Individuals in the latent state are allowed to follow the same mobility patterns and international travel behaviour as those who are not infected. Travel probabilities are calculated based on the integrated flight database and mechanistically simulated travel and commuting patterns. More details on the model and on the parameters’ inference procedure are provided in [9] and in the supplementary information* (http://www.mobs-lab.org/ebola-eurosurvsup.html).

To assess the effect of current travel restrictions on the risk of case importation, we compared the international spread of the EVD epidemic obtained from numerical simulations of the model with and without the travel reductions. We focus on short-term projections and calculate the probability of case importation per country (and per continent) predicted for 30 September 2014 in the baseline scenario without travel restrictions. The probability of importation at that date is still relatively small for most of the countries and detailed values for different dates can be found in [9]. We then compute the time delay needed to reach the same value of case importation probability per country (or continent) once the travel restrictions shown in the Table are implemented.



The modelled travel restrictions impacted airline passenger volume to countries worldwide in a very heterogeneous manner (Figure 1, reporting results for countries with a case importation probability larger than 0.5% as of 30 September 2014). Notably, flight suppressions and border closures did not affect solely the countries implementing such measures but they also had considerable repercussions on others (e.g. India and the Philippines following the suppression of Emirates Airline flights). With few exceptions, African countries were predicted to experience traffic reductions greater than 70% due to generalised travel bans.


Figure 1. Modelled effect of travel restrictions on the risk of Ebola case importation for individual countries


The total estimated reduction of 60% of airline passenger traffic connecting the West Africa region currently most affected by Ebola to the rest of the world was shown to be insufficient to prevent the exportation of Ebola cases. The observed traffic reductions were shown to delay the risk of case importation per country from a few days to a few weeks (Figure 1). The majority of the countries (56%, mainly in Central Europe, Asia and the Americas) would not experience a delay longer than one month. At the continental level, the delay was predicted to be negligible for the Americas, and at most one month for the African continent (Figure 2). Results confirmed previous empirical evidence from past epidemics of other infectious diseases and were in agreement with mathematical modelling studies of the relationship between the exponential growth rate of an epidemic in a source region and the exportation to other regions [14-18]. Those can be summarised with the simple rule of thumb that a 50% travel reduction produces a delay equal to the doubling time of the number of cases.


Figure 2. Modelled overall delays predicted for Ebola case importation by continent, following the application of the travel restrictions




Although the current travel restrictions postpone the spread of EVD to other continents by at most a few weeks, they can impose heavy logistical constraints on the management of the epidemic in the countries severely hit by the disease and ill-equipped to cope with its alarming rapid spread [4-6]. If not offset by massive humanitarian operations, they can cause major shortages of food, energy and essential resources, with the potential to severely compromise local economies [19].

Similar to what happened during the severe acute respiratory syndrome (SARS) outbreak in 2003 [20], adverse effects on local economies of the same countries implementing the bans may also occur, as a reduced connectivity and the increased apprehension may induce a considerable reduction in the demand for service industries (business travel, tourism and associated services).

International agencies suggest that currently unaffected countries should invest in health system preparedness, strengthening their own capacity to detect and contain newly imported cases [21]. These measures are expected to substantially reduce the risk of importation. Indeed, while the relatively long latency period of EVD may allow exposed individuals to travel long distances, infectiousness occurs at symptom onset only, so that potentially infectious individuals can be clinically recognised. The mode of transmission is expected to minimise the risk of spread during a flight [21].

It is also worth mentioning that delays in the global spread of the outbreak may have to be evaluated with respect to the development timeline of pharmaceutical interventions. For instance, Ebola vaccines are being fast-tracked, and field trials are planned, probably in healthcare workers at high risk of exposure to the virus in the affected areas [22].

The results presented here need to be considered in light of the assumptions and limitations of the modelling approach used. We considered all travel restrictions obtained from publicly available sources that were implemented up to the end of August 2014, but this list may not be complete and not all information could be verified with the original sources. In the presence of uncertainty (e.g. vague information or inconsistency between different news) we assumed the scenario with the strongest traffic reduction in order to provide the best-case scenario in terms of resulting delay. An additional world-wide fear-induced decrease of tourist and business travel to the region has been observed [23,24] in September and has probably further increased the delay in case importation, although only logarithmically with the magnitude of the traffic reduction [15,16].

The simulation presented was based on the study of the current West African outbreak described in Gomes et al. [9], which contains estimates of the incubation period and generation time based on past Ebola outbreaks. Recent estimates for the current outbreak have been published by Hollingsworth et al., and Althaus et al. [13,25]. Updated results on the risk of the epidemic spread are regularly posted on our website http://www.mobs-lab.org/ebola.html to account for the most recently published epidemiological information. We note that, although these parameters affect the absolute value of the probability of importation, they do not affect the relative delay depending on the epidemic growth rate [15,16].

Detailed data on unmeasured movements during the epidemic and on possible rearrangements of air travel volumes following decisions of airline companies to suspend flights are not available to be implemented directly into the model. For this reason, we took these aspects into account by considering a maximum of 90% overall traffic reduction (80% for countries bordering the currently affected area), representing the maximum ability of a country to implement the border closures. A sensitivity analysis exploring smaller values of these upper bounds (70% for neighbouring countries and 80% for the others) yielded delays in the risk of case importations reduced to five weeks for the African countries with the largest overall reductions (supplementary information*).



This study indicates that travel bans are only delaying the further international spread of the Ebola outbreak in West Africa for a limited time, at the risk of compromising connectivity to the region, mobilisation of resources to the affected area and sustained response operations, all actions of critical value for the immediate local control of EVD and for preventing its further geographical spread. Any decision making process on this issue must take into account complex cost-benefit analyses of travel bans.



Supplementary information made available by the authors on an independent website is not edited by Eurosurveillance, and Eurosurveillance is not responsible for the content. The material can be accessed at: http://www.mobs-lab.org/ebola-eurosurvsup.html



This work has been partially supported by the EC-Health contract no. 278433 (PREDEMICS) and the ANR contract no. ANR- 12-MONU-0018 (HARMSFLU). We acknowledge also funding from DTRA-1-0910039 and MIDAS-National Institute of General Medical Sciences U54GM111274. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.


Conflict of interest

None declared.


Authors’ contributions

CP, VC, MG, AP, AV provided the data. CP, LR performed the computational experiments. CP VC AV conceived and designed the study. All authors discussed the results, edited and commented the manuscript draft. All authors read and approved the final manuscript.



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Continued #seasonal #circulation of #enterovirus D68 in the #Netherlands, 2011–2014 (@Eurosurveillanc, abstract, edited)

[Source: Eurosurveillance, full page: (LINK). Abstract, edited.]

Eurosurveillance, Volume 19, Issue 42, 23 October 2014  / Rapid communications

Continued seasonal circulation of enterovirus D68 in the Netherlands, 2011–2014 [      ]

A Meijer 1, K S Benschop1, G A Donker2, H G van der Avoort1

1Centre for Infectious Disease Research, Diagnostics and Screening, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands  - 2 NIVEL Primary Care Database, Sentinel Practices, Utrecht, The Netherlands

Citation style for this article: Meijer A, Benschop KS, Donker GA, van der Avoort HG. Continued seasonal circulation of enterovirus D68 in the Netherlands, 2011–2014. Euro Surveill. 2014;19(42):pii=20935. Available online: http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=20935

Date of submission: 17 October 2014



Enterovirus D68 (EV-D68) continued to circulate in a seasonal pattern in the Netherlands, after the outbreak in 2010. Outpatient EV-D68 cases, mainly in the under 20 and 50–59 years age groups, presented with relatively mild respiratory disease. Hospital-based enterovirus surveillance identified more severe cases, mainly in children under 10 years of age. Dutch partial VP1 genomic region sequences from 2012 through 2014 were distributed over three sublineages similar to EV-D68 from the outbreak in the US in 2014.



#Chikungunya – #France (@WHO, October 23 2014)

[Source: World Health Organization, full page: (LINK).]

Chikungunya – France [      ]

Disease outbreak news / 23 October 2014

On 21 October 2014, WHO was notified by the National IHR Focal Point for France of 4 cases of chikungunya locally-acquired infection in Montpellier, France.

The cases were confirmed by tests conducted by the French National Reference Laboratory for arboviruses on 20 October 2014.

This is the first time that locally-acquired transmission of chikungunya has been detected in France since 2010.

The 4 cases of chikungunya infection occurred within the same family, with symptoms onset between 20 September and 12 October.

The cases live in Montpellier in the vicinity of a chikungunya case imported from Cameroon.

The cases have no history of travel out of their district of residence in the 15 days prior to the onset of symptoms.

French public health authorities have implemented the following public health measures:

  • Vector control aimed at preventing local transmission.
  • Provision of information about the awareness of the cluster, the signs and symptoms of the disease, when and where to seek care, and how to prevent infection.
  • Advice to health care practitioners on clinical case management.
  • Assessment of the risk of infection through blood and tissues donations.

Chikungunya is a viral disease that is rarely fatal and is transmitted to humans by infected mosquitoes.

Symptoms of chikungunya include high fever and headache, with significant pains in the joints (ankles, wrists), which can persist for several weeks.

The symptoms appear between 4 and 7 days after the patient has been bitten by an infected mosquito.

The name, chikungunya derives from a word in Makonde language roughly meaning “that which bends up”, reflecting the physique of a person suffering from the disease.



#OHIO DAILY #EBOLA #CONTACT #REPORT, 10-23-14, 11 a.m. (DoH, edited)

[Source: State of Ohio Department of Health, full PDF document: (LINK). Edited.]

FOR IMMEDIATE RELEASE / October 23, 2014 / Contact: State Joint Information Center, (614) 799-6480

OHIO DAILY EBOLA CONTACT REPORT, 10-23-14, 11 a.m. [      ]

COLUMBUS – The Ohio Department of Health reported this morning in its Daily Ebola Contact Report that there are currently:

  • 0 confirmed cases of Ebola in Ohio;
  • 3 people under quarantine;
  • 163 contacts statewide;

ODH’s Daily Ebola Contact Report is issued at approximately 11 a.m. and is compiled from the local health districts, ODH officials and Centers for Disease Control and Prevention (CDC) Ohio team members who are working together to identify anyone who may have had contact of some type with the Dallas nurse who was in Northeast Ohio, Oct. 10-13.

Symptoms may appear anywhere from 2-21 days after exposure to Ebola, but the average is 8-10 days.

It is anticipated that contacts will be removed from the contact list between October 31, and November 4, 2014.

The figures may change daily based on the information officials learn from contacts and the type of exposure they may have had.

The report is below and also found on ODH’s website here: http://www.odh.ohio.gov/odhprograms/dis/orbitdis/ebola/Ebola.aspx


OHIO EBOLA DAILY CONTACT REPORT 10/23/14 (as of 11 AM, EST of date of issuance)






  • Cuyahoga – 1 – 3 – 35 – 17 – 1 – 56
  • Medina – 0 – 1 – 4 – 5 – 0 – 10
  • Portage – 0 – 0 – 4 – 5 – 1 – 9
  • Summit  - 2 – 8 – 15 – 16 – 0 – 41
  • All Other Counties * – 0 – 5 – 35 – 7 – 0 – 47
  • TOTAL – 3 – 17 – 93 – 50 – 2 – 163


* 15 counties have seven or less contacts and those figures are not being broken out by county in order to protect the privacy of individual contacts. (Belmont, Erie, Franklin, Geauga, Hamilton, Hardin, Lake, Lorain, Mahoning, Putnam, Seneca, Stark, Trumbull, Tuscarawas, Wayne)




Extra powers to tackle deadly #bat #lyssavirus in #Australia (Channel NewsAsia, October 23 2014)

[Source: Channel News Asia, full page: (LINK).]

Extra powers to tackle deadly bat virus in Australia [      ]

Australia's New South Wales state is set to unveil tougher measures to tackle bats after three flying foxes were found to be carrying the deadly lyssavirus. Three people in Australia have died from the bat-borne virus, which has no effective treatment. 




#Cão de #enfermeira americana infectada com #ebola está livre do vírus (O GLOBO, October 23 2014)

[Source: Globo, full page: (LINK).]

Cão de enfermeira americana infectada com ebola está livre do vírus [      ]

RIO - A Prefeitura de Dallas, no Texas, informou que o canhorro da enfermeira Nina Pham, infectada com ebola no início do mês, está livre do vírus. Após sua dona contrair a doença, o pequenho Bentley, um chihuahua de um ano de idade, havia sido isolado em uma base naval no estado.




Virus del #Ebola: Cinco #contactos de la auxiliar han sido dados de alta este jueves (RTVE.es, October 23 2014)

[Source: RTVE, full page: (LINK).]

La auxiliar de enfermería pide justicia: "Me siento atropellada" [      ]

RTVE.es / EFE 23.10.2014 - 15:26h

La auxiliar de enfermería Teresa R., que ya está curada de la infección del virus del Ébola, ha pedido justicia por todo lo ocurrido a raíz de su contagio, incluido el sacrificio de su perro Excálibur, y ha afirmado: "Me siento atropellada".




#Mali found a suspected case of #Ebola (EN NEWS 163, October 23 2014)

[Source: EN News, full page: (LINK).]

Mali found a suspected case of Ebola [      ]

International online news: According to Xinhua News Agency , the western city of Kayes in Mali 22 found a suspected Ebola patients , currently this patient has been isolated for treatment to a local hospital . It is reported that the patient was a 3 -year-old girl with relatives recently returned from Guinea , Mali . This part of the girl ‘s relatives have also been isolated.




Hubris: The Recurring #Pandemic. (Disaster Med Public Health Prep., abstract, edited)

[Source: US National Library of Medicine, full page: (LINK). Abstract, edited.]

Disaster Med Public Health Prep. 2014 Oct 22:1-6. [Epub ahead of print]

Hubris: The Recurring Pandemic. [      ]

Koch T.

Author information: Department of Geography (Medical),University of British Columbia,1984 West Mall,Vancouver,BC,British Columbia,Canada.



The 2014 Ebola outbreak has been seen by many as a "perfect storm" and an "unprecedented" public health calamity. This article attempts to place this most current of epidemics, one currently struggling for pandemic status, in an historical frame. At least since the 1600s protocols and programs for the containment of epidemic disease have been known, and mapped. And yet it was almost six months after warnings about this epidemic were first sounded that incomplete programs of control and surveillance were instituted. In effect, we have forgotten the basics of what was once common knowledge in public health. Having placed our faith in bacteriology, virology, and pharmacology, we have forgotten the lessons learned, long ago. (Disaster Med Public Health Preparedness. 2014;0:1-6).

PMID: 25335430 [PubMed - as supplied by publisher]



#Macau, Serviços de Saúde apresentaram aos #profissionais de #Saúde da RAEM as novas #medidas de #prevenção sobre o vírus #Ebola (DoH, October 23 2014)

[Source: Department of Health, Macau PRC SAR, full page: (LINK).]

Serviços de Saúde apresentaram aos profissionais de Saúde da RAEM as novas medidas de prevenção sobre o vírus Ébola [      ]

Os Serviços de Saúde, no âmbito do plano de contigência previsto para a prevenção do Vírus Ébola e de modo a reforçar a consciência de alerta dos profissionais de saúde da primeira linha da RAEM, no que concerne à sensibilização e alerta para casos suspeitos e ao domínio do uso de equipamento de protecção individual contra a infecção, organizaram durante esta quinta-feira, 23 de Outubro, a primeira de duas reuniões de esclarecimento sobre a prevenção de doença por vírus Ébola que decorreram no Auditório do Edifício da Administração dos Serviços de Saúde.