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Assessing the risk of international spread of yellow fever virus: a mathematical analysis of an urban outbreak in Asuncion, 2008.

ABSTRACT: 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.

SUBMITTER: Johansson MA

PROVIDER: S-EPMC3269406 | biostudies-literature | 2012 Feb

REPOSITORIES: biostudies-literature

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Assessing the risk of international spread of yellow fever virus: a mathematical analysis of an urban outbreak in Asuncion, 2008.

Johansson Michael A MA Arana-Vizcarrondo Neysarí N Biggerstaff Brad J BJ Gallagher Nancy N Marano Nina N Staples J Erin JE

The American journal of tropical medicine and hygiene 20120201 2

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. ...[more]

PMID: 22302873

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Project description:The recent reemergence of yellow fever virus (YFV) in Brazil has raised serious concerns due to the rapid dissemination of the virus in the southeastern region. To better understand YFV genetic diversity and dynamics during the recent outbreak in southeastern Brazil, we generated 18 complete and nearly complete genomes from the peak of the epidemic curve from nonhuman primates (NHPs) and human infected cases across the Espírito Santo and Rio de Janeiro states. Genomic sequencing of 18 YFV genomes revealed the estimated timing, source, and likely routes of yellow fever virus transmission and dispersion during one of the largest outbreaks ever registered in Brazil. We showed that during the recent epidemic, YFV was reintroduced from Minas Gerais to the Espírito Santo and Rio de Janeiro states multiple times between 2016 and 2019. The analysis of data from portable sequencing could identify the corridor of spread of YFV. These findings reinforce the idea that continued genomic surveillance strategies can provide information on virus genetic diversity and transmission dynamics that might assist in understanding arbovirus epidemics.IMPORTANCE Arbovirus infections in Brazil, including yellow fever, dengue, zika, and chikungunya, result in considerable morbidity and mortality and are pressing public health concerns. However, our understanding of these outbreaks is hampered by the limited availability of genomic data. In this study, we investigated the genetic diversity and spatial distribution of YFV during the current outbreak by analyzing genomic data from areas in southeastern Brazil not covered by other previous studies. To gain insights into the routes of YFV introduction and dispersion, we tracked the virus by sequencing YFV genomes sampled from nonhuman primates and infected patients from the southeastern region. Our study provides an understanding of how YFV initiates transmission in new Brazilian regions and illustrates that genomics in the field can augment traditional approaches to infectious disease surveillance and control.

Project description:BackgroundSince late 2015, an epidemic of yellow fever has caused more than 7334 suspected cases in Angola and the Democratic Republic of the Congo, including 393 deaths. We sought to understand the spatial spread of this outbreak to optimise the use of the limited available vaccine stock.MethodsWe jointly analysed datasets describing the epidemic of yellow fever, vector suitability, human demography, and mobility in central Africa to understand and predict the spread of yellow fever virus. We used a standard logistic model to infer the district-specific yellow fever virus infection risk during the course of the epidemic in the region.FindingsThe early spread of yellow fever virus was characterised by fast exponential growth (doubling time of 5-7 days) and fast spatial expansion (49 districts reported cases after only 3 months) from Luanda, the capital of Angola. Early invasion was positively correlated with high population density (Pearson's r 0·52, 95% CI 0·34-0·66). The further away locations were from Luanda, the later the date of invasion (Pearson's r 0·60, 95% CI 0·52-0·66). In a Cox model, we noted that districts with higher population densities also had higher risks of sustained transmission (the hazard ratio for cases ceasing was 0·74, 95% CI 0·13-0·92 per log-unit increase in the population size of a district). A model that captured human mobility and vector suitability successfully discriminated districts with high risk of invasion from others with a lower risk (area under the curve 0·94, 95% CI 0·92-0·97). If at the start of the epidemic, sufficient vaccines had been available to target 50 out of 313 districts in the area, our model would have correctly identified 27 (84%) of the 32 districts that were eventually affected.InterpretationOur findings show the contributions of ecological and demographic factors to the ongoing spread of the yellow fever outbreak and provide estimates of the areas that could be prioritised for vaccination, although other constraints such as vaccine supply and delivery need to be accounted for before such insights can be translated into policy.FundingWellcome Trust.

Dataset Information

Assessing the risk of international spread of yellow fever virus: a mathematical analysis of an urban outbreak in Asuncion, 2008.

Publications

Assessing the risk of international spread of yellow fever virus: a mathematical analysis of an urban outbreak in Asuncion, 2008.

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