ArticlePLoS currents2016
FLIRT-ing with Zika: A Web Application to Predict the Movement of Infected Travelers Validated Against the Current Zika Virus Epidemic.
Article in PLoS currents, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.
- A systematic review and evaluation of Zika virus forecasting and prediction research during a public health emergency of international concern.PLoS neglected tropical diseases · 2019Pooled it
- Impact of international travel dynamics on domestic spread of 2019-nCoV in India: origin-based risk assessment in importation of infected travelers.Globalization and health · 2020Article
- Passengers' destinations from China: low risk of Novel Coronavirus (2019-nCoV) transmission into Africa and South America.Epidemiology and infection · 2020Article
- Development and validation of influenza forecasting for 64 temperate and tropical countries.PLoS computational biology · 2019Article
- Prediction of Zika-confirmed cases in Brazil and Colombia using Google Trends.Epidemiology and infection · 2018Article
- Assessing the Use of Influenza Forecasts and Epidemiological Modeling in Public Health Decision Making in the United States.Scientific reports · 2018Article
- Identifying Areas at Greatest Risk for Recent Zika Virus Importation - New York City, 2016.PLoS currents · 2018Article
- Zika vaccines and therapeutics: landscape analysis and challenges ahead.BMC medicine · 2018Article
- Big Data's Role in Precision Public Health.Frontiers in public health · 2018Review
- Host outdoor exposure variability affects the transmission and spread of Zika virus: Insights for epidemic control.PLoS neglected tropical diseases · 2017Article
- An outbreak vector-host epidemic model with spatial structure: the 2015-2016 Zika outbreak in Rio De Janeiro.Theoretical biology & medical modelling · 2017Article
- Risk of travel-related cases of Zika virus infection is predicted by transmission intensity in outbreak-affected countries.Parasites & vectors · 2017Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionBeginning in 2015, Zika virus rapidly spread throughout the Americas and has been linked to neurological and autoimmune diseases in adults and babies. Developing accurate tools to anticipate Zika spread is one of the first steps to mitigate further spread of the disease. When combined, air traffic data and network simulations can be used to create tools to predict where infectious disease may spread to and aid in the prevention of infectious diseases. Specific goals were to: 1) predict where travelers infected with the Zika Virus would arrive in the U.S.; and, 2) analyze and validate the open access web application's (i.e., FLIRT) predictions using data collected after the prediction was made.
methodFLIRT was built to predict the flow and likely destinations of infected travelers through the air travel network. FLIRT uses a database of flight schedules from over 800 airlines, and can display direct flight traffic and perform passenger simulations between selected airports. FLIRT was used to analyze flights departing from five selected airports in locations where sustained Zika Virus transmission was occurring. FLIRT's predictions were validated against Zika cases arriving in the U.S. from selected airports during the selected time periods. Kendall's τ and Generalized Linear Models were computed for all permutations of FLIRT and case data to test the accuracy of FLIRT's predictions.
resultsFLIRT was found to be predictive of the final destinations of infected travelers in the U.S. from areas with ongoing transmission of Zika in the Americas from 01 February 2016 - 01 to April 2016, and 11 January 2016 to 11 March 2016 time periods. MIA-FLL, JFK-EWR-LGA, and IAH were top ranked at-risk metro areas, and Florida, Texas and New York were top ranked states at-risk for the future time period analyzed (11 March 2016 - 11 June 2016). For the 11 January 2016 to 11 March 2016 time period, the region-aggregated model indicated 7.24 (95% CI 6.85 - 7.62) imported Zika cases per 100,000 passengers, and the state-aggregated model suggested 11.33 (95% CI 10.80 - 11.90) imported Zika cases per 100,000 passengers. DISCUSSION: The results from 01 February 2016 to 01 April 2016 and 11 January 2016 to 11 March 2016 time periods support that modeling air travel and passenger movement can be a powerful tool in predicting where infectious diseases will spread next. As FLIRT was shown to significantly predict distribution of Zika Virus cases in the past, there should be heightened biosurveillance and educational campaigns to medical service providers and the general public in these states, especially in the large metropolitan areas.
Indexed as
Identifiers
27366587PMC4922883W2418458159What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.