Assessing the Risk of International Spread of Yellow Fever Virus: A Mathematical Analysis of an Urban Outbreak in Asuncion, 2008

Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico.
The American journal of tropical medicine and hygiene (Impact Factor: 2.7). 02/2012; 86(2):349-58. DOI: 10.4269/ajtmh.2012.11-0432
Source: PubMed


Yellow fever virus (YFV), a mosquito-borne virus endemic to tropical Africa and South America, is capable of causing large urban outbreaks of human disease. With the ease of international travel, urban outbreaks could lead to the rapid spread and subsequent transmission of YFV in distant locations. We designed a stochastic metapopulation model with spatiotemporally explicit transmissibility scenarios to simulate the global spread of YFV from a single urban outbreak by infected airline travelers. In simulations of a 2008 outbreak in Asunción, Paraguay, local outbreaks occurred in 12.8% of simulations and international spread in 2.0%. Using simple probabilistic models, we found that local incidence, travel rates, and basic transmission parameters are sufficient to assess the probability of introduction and autochthonous transmission events. These models could be used to assess the risk of YFV spread during an urban outbreak and identify locations at risk for YFV introduction and subsequent autochthonous transmission.

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    • "Rates and routes of imported malaria have been shown to be significantly related to a combination of numbers of travellers to/from endemic destinations and the prevalence of malaria there [3]. The potential thus exists to construct a model based on global malaria prevalence [40,41], the local spatial interaction and accessibility to an airport within a region [60], transmission models for attack rate estimation [27], and traveller flow data [36], that can be used to forecast imported malaria rates, validated with imported malaria data reported by health facilities/organizations. "
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    ABSTRACT: Air travel has expanded at an unprecedented rate and continues to do so. Its effects have been seen on malaria in rates of imported cases, local outbreaks in non-endemic areas and the global spread of drug resistance. With elimination and global eradication back on the agenda, changing levels and compositions of imported malaria in malaria-free countries, and the threat of artemisinin resistance spreading from Southeast Asia, there is a need to better understand how the modern flow of air passengers connects each Plasmodium falciparum- and Plasmodium vivax-endemic region to the rest of the world. Recently constructed global P. falciparum and P.vivax malaria risk maps, along with data on flight schedules and modelled passenger flows across the air network, were combined to describe and quantify global malaria connectivity through air travel. Network analysis approaches were then utilized to describe and quantify the patterns that exist in passenger flows weighted by malaria prevalence. Finally, the connectivity within and to the Southeast Asia region where the threat of imported artemisinin resistance arising is highest, was examined to highlight risk routes for its spread. The analyses demonstrate the substantial connectivity that now exists between and from malaria-endemic regions through air travel. While the air network provides connections to previously isolated malarious regions, it is clear that great variations exist, with significant regional communities of airports connected by higher rates of flow standing out. The structures of these communities are often not geographically coherent, with historical, economic and cultural ties evident, and variations between P. falciparum and P. vivax clear. Moreover, results highlight how well connected the malaria-endemic areas of Africa are now to Southeast Asia, illustrating the many possible routes that artemisinin-resistant strains could take. The continuing growth in air travel is playing an important role in the global epidemiology of malaria, with the endemic world becoming increasingly connected to both malaria-free areas and other endemic regions. The research presented here provides an initial effort to quantify and analyse the connectivity that exists across the malaria-endemic world through air travel, and provide a basic assessment of the risks it results in for movement of infections.
    Malaria Journal 08/2013; 12(1):269. DOI:10.1186/1475-2875-12-269 · 3.11 Impact Factor
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    • "To study the movement of vector-borne disease on the air travel network, Johansson et al [17], [40] modeled the actual passengers counts between 141 airports worldwide, for origins and destinations that had epidemic significance. Utilizing the air travel itineraries of the United States as a training set, they constructed a generalized linear model with a Poisson link to estimate worldwide passenger flows using nodes and routes characteristics as model covariates. "
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    ABSTRACT: The expanding global air network provides rapid and wide-reaching connections accelerating both domestic and international travel. To understand human movement patterns on the network and their socioeconomic, environmental and epidemiological implications, information on passenger flow is required. However, comprehensive data on global passenger flow remain difficult and expensive to obtain, prompting researchers to rely on scheduled flight seat capacity data or simple models of flow. This study describes the construction of an open-access modeled passenger flow matrix for all airports with a host city-population of more than 100,000 and within two transfers of air travel from various publicly available air travel datasets. Data on network characteristics, city population, and local area GDP amongst others are utilized as covariates in a spatial interaction framework to predict the air transportation flows between airports. Training datasets based on information from various transportation organizations in the United States, Canada and the European Union were assembled. A log-linear model controlling the random effects on origin, destination and the airport hierarchy was then built to predict passenger flows on the network, and compared to the results produced using previously published models. Validation analyses showed that the model presented here produced improved predictive power and accuracy compared to previously published models, yielding the highest successful prediction rate at the global scale. Based on this model, passenger flows between 1,491 airports on 644,406 unique routes were estimated in the prediction dataset. The airport node characteristics and estimated passenger flows are freely available as part of the Vector-Borne Disease Airline Importation Risk (VBD-Air) project at:
    PLoS ONE 05/2013; 8(5):e64317. DOI:10.1371/journal.pone.0064317 · 3.23 Impact Factor
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    • "By simulating risks of importation from literature-derived probability distributions for each variable, improved and more informative model outputs could be produced that would enable the user to better understand and manage the uncertainties inherent in forecasts (e.g. [49]). "
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    ABSTRACT: Background Over the past century, the size and complexity of the air travel network has increased dramatically. Nowadays, there are 29.6 million scheduled flights per year and around 2.7 billion passengers are transported annually. The rapid expansion of the network increasingly connects regions of endemic vector-borne disease with the rest of the world, resulting in challenges to health systems worldwide in terms of vector-borne pathogen importation and disease vector invasion events. Here we describe the development of a user-friendly Web-based GIS tool: the Vector-Borne Disease Airline Importation Risk Tool (VBD-AIR), to help better define the roles of airports and airlines in the transmission and spread of vector-borne diseases. Methods Spatial datasets on modeled global disease and vector distributions, as well as climatic and air network traffic data were assembled. These were combined to derive relative risk metrics via air travel for imported infections, imported vectors and onward transmission, and incorporated into a three-tier server architecture in a Model-View-Controller framework with distributed GIS components. A user-friendly web-portal was built that enables dynamic querying of the spatial databases to provide relevant information. Results The VBD-AIR tool constructed enables the user to explore the interrelationships among modeled global distributions of vector-borne infectious diseases (malaria. dengue, yellow fever and chikungunya) and international air service routes to quantify seasonally changing risks of vector and vector-borne disease importation and spread by air travel, forming an evidence base to help plan mitigation strategies. The VBD-AIR tool is available at Conclusions VBD-AIR supports a data flow that generates analytical results from disparate but complementary datasets into an organized cartographical presentation on a web map for the assessment of vector-borne disease movements on the air travel network. The framework built provides a flexible and robust informatics infrastructure by separating the modules of functionality through an ontological model for vector-borne disease. The VBD‒AIR tool is designed as an evidence base for visualizing the risks of vector-borne disease by air travel for a wide range of users, including planners and decisions makers based in state and local government, and in particular, those at international and domestic airports tasked with planning for health risks and allocating limited resources.
    International Journal of Health Geographics 08/2012; 11(1):33. DOI:10.1186/1476-072X-11-33 · 2.62 Impact Factor
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