ArticleTravel medicine and infectious disease2009
U.S. airport entry screening in response to pandemic influenza: modeling and analysis.
Article in Travel medicine and infectious disease, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 5 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
27 citing papers in PubMed, 5 syntheses or guidelines pooled it, 41 citations in OpenAlex.
- Physical interventions to interrupt or reduce the spread of respiratory viruses.The Cochrane database of systematic reviews · 2023Pooled it
- Physical interventions to interrupt or reduce the spread of respiratory viruses.The Cochrane database of systematic reviews · 2020Pooled it
- Exit and Entry Screening Practices for Infectious Diseases among Travelers at Points of Entry: Looking for Evidence on Public Health Impact.International journal of environmental research and public health · 2019Pooled it
- The use and reporting of airline passenger data for infectious disease modelling: a systematic review.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2019Pooled it
- Physical interventions to interrupt or reduce the spread of respiratory viruses.The Cochrane database of systematic reviews · 2011Pooled it
- Good Practices for Managing Acute Respiratory Viral Infections at Aerial Entry Points: A Scoping Review.Journal of epidemiology and global health · 2026Article
- Article
- Evaluation of a web-based self-reporting method for monitoring international passengers returning from an area of emerging infection.Infectious diseases now · 2021Article
- COVID-19 in comparison with other emerging viral diseases: risk of geographic spread via travel.Tropical diseases, travel medicine and vaccines · 2021Review
- Evaluation of a telethermographic system for temperature screening at a large tertiary-care referral hospital during the coronavirus disease 2019 (COVID-19) pandemic.Infection control and hospital epidemiology · 2021Article
- Visual Analytics for Decision-Making During Pandemics.Computing in science & engineering · 2020Article
- Dominant bee species and floral abundance drive parasite temporal dynamics in plant-pollinator communities.Nature ecology & evolution · 2020Article
- Nonpharmaceutical Measures for Pandemic Influenza in Nonhealthcare Settings-International Travel-Related Measures.Emerging infectious diseases · 2020Article
- Digitizable therapeutics for decentralized mitigation of global pandemics.Scientific reports · 2019Article
- Health screening strategies for international air travelers during an epidemic or pandemic.Journal of air transport management · 2019Article
- Airport Entry and Exit Screening during the Ebola Virus Disease Outbreak in Sierra Leone, 2014 to 2016.BioMed research international · 2019Article
- Parasites in bloom: flowers aid dispersal and transmission of pollinator parasites within and between bee species.Proceedings. Biological sciences · 2015Article
- Article
- Entry screening for infectious diseases in humans.Emerging infectious diseases · 2015Review
- Airport exit and entry screening for Ebola--August-November 10, 2014.MMWR. Morbidity and mortality weekly report · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundA stochastic discrete event simulation model was developed to assess the effectiveness of passenger screening for Pandemic Influenza (PI) at U.S. airport foreign entry.
methodsInternational passengers arriving at 18 U.S. airports from Asia, Europe, South America, and Canada were assigned to one of three states: not infected, infected with PI, infected with other respiratory illness. Passengers passed through layered screening then exited the model. 80% screening effectiveness was assumed for symptomatic passengers; 6% asymptomatic passengers.
resultsIn the first 100 days of a global pandemic, U.S. airport screening would evaluate over 17 M passengers with 800 K secondary screenings. 11,570 PI infected passengers (majority asymptomatic) would enter the U.S. undetected from all 18 airports. Foreign airport departure screening significantly decreased the false negative (infected/undetected) passengers. U.S. attack rates: no screening (26.9%-30.9%); screening (26.4%-30.6%); however airport screening results in 800 K-1.8 M less U.S. PI cases; 16 K-35 K less deaths (2% fatality rate). Antiviral medications for travel contact prophylaxis (10 contacts/PI passenger) were high - 8.8M. False positives from all 18 airports: 100-200/day.
conclusionsForeign shore exit screening greatly reduces numbers of PI infected passengers. U.S. airport screening identifies 50% infected individuals; efficacy is limited by the asymptomatic PI infected. Screening will not significantly delay arrival of PI via international air transport, but will reduce the rate of new US cases and subsequent deaths.
Indexed as
Identifiers
What 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.