# 6446
In 2009, about 6 weeks before news of the outbreak of H1N1 in Mexico was announced, I came across a fascinating video on Youtube which inspired a blog called How The Next Pandemic Will Arrive.
I wrote:
There is a lot we don't currently know about the next pandemic. We don't know when it will arrive. We don't know what virus will cause it. And we don't know how bad it will be.
But there is one thing almost certain.
It will arrive in most countries by airplane.
Not exactly an earth shattering revelation, given that air travel is an obvious mode of viral spread. But my timing was excellent.
By the end of following month the new H1N1 virus was winging its way around the globe in large part due to spring break vacationers returning from Mexico.
While obviously a major factor, the dynamics of disease spread through airports is only partially understood.
We’ve a new study, appearing in PloS One, that looks at the early spread of a pandemic virus through air travel, and through the use of Monte Carlo simulations, finds some airports contributing more to the spread of a pandemic than the number of travelers passing through it might suggest.
The study, conducted by researchers at MIT, is called:
A Metric of Influential Spreading during Contagion Dynamics through the Air Transportation Network
Christos Nicolaides, Luis Cueto-Felgueroso, Marta C. González, Ruben Juanes
Abstract
The spread of infectious diseases at the global scale is mediated by long-range human travel. Our ability to predict the impact of an outbreak on human health requires understanding the spatiotemporal signature of early-time spreading from a specific location.
Here, we show that network topology, geography, traffic structure and individual mobility patterns are all essential for accurate predictions of disease spreading. Specifically, we study contagion dynamics through the air transportation network by means of a stochastic agent-tracking model that accounts for the spatial distribution of airports, detailed air traffic and the correlated nature of mobility patterns and waiting-time distributions of individual agents.
From the simulation results and the empirical air-travel data, we formulate a metric of influential spreading––the geographic spreading centrality––which accounts for spatial organization and the hierarchical structure of the network traffic, and provides an accurate measure of the early-time spreading power of individual nodes.
I would invite those with a better grasp of statistical analysis than I to read the entire study, but for the rest of us, we have the following report from MIT News.
Monday, July 23
New model of disease contagion ranks U.S. airports in terms of their spreading influence
Airports in New York, Los Angeles and Honolulu are judged likeliest to play a significant role in the growth of a pandemic.
Denise Brehm, Civil and Environmental Engineering
World map shows flight routes from the 40 largest U.S. airports.
Image: Christos Nicolaides, Juanes Research GroupPublic health crises of the past decade — such as the 2003 SARS outbreak, which spread to 37 countries and caused about 1,000 deaths, and the 2009 H1N1 flu pandemic that killed about 300,000 people worldwide — have heightened awareness that new viruses or bacteria could spread quickly across the globe, aided by air travel.
<SNIP>
Outsize role for Honolulu
For example, a simplified model using random diffusion might say that half the travelers at the Honolulu airport will go to San Francisco and half to Anchorage, Alaska, taking the disease and spreading it to travelers at those airports, who would randomly travel and continue the contagion.
In fact, while the Honolulu airport gets only 30 percent as much air traffic as New York's Kennedy International Airport, the new model predicts that it is nearly as influential in terms of contagion, because of where it fits in the air transportation network: Its location in the Pacific Ocean and its many connections to distant, large and well-connected hubs gives it a ranking of third in terms of contagion-spreading influence.
Kennedy Airport is ranked first by the model, followed by airports in Los Angeles, Honolulu, San Francisco, Newark, Chicago (O'Hare) and Washington (Dulles). Atlanta's Hartsfield-Jackson International Airport, which is first in number of flights, ranks eighth in contagion influence. Boston's Logan International Airport ranks 15th.
Complicating matters - attempts to identify and quarantine air travelers with fevers, or other signs of illness - have proved notoriously difficult.
Last April, in EID Journal: Airport Screening For Pandemic Flu In New Zealand, we looked at a study that found that the screening methods used at New Zealand’s airport were inadequate to slow the entry of the 2009 pandemic flu into their country, detecting less than 6% of those infected.
Unlike some other countries in 2009, New Zealand did not employ thermal scanners, which look for arriving passengers or crew with elevated temperatures.
(Thermal Imaging for SARS in 2003)
But even countries that employed thermal scanners and far more strict interdiction techniques during the summer of 2009 failed to keep the flu out.
Just as the pandemic was ramping up, in Vietnam Discovers Passengers Beating Thermal Scanners, we saw evidence of flyers taking fever-reducers to beat the airport scanners in order to get home.
In December of 2009, in Travel-Associated H1N1 Influenza in Singapore, I wrote about a NEJM Journal Watch of a new study that has been published, ahead of print, in the CDC’s EID Journal entitled:
Epidemiology of travel-associated pandemic (H1N1) 2009 infection in 116 patients, Singapore. Emerg Infect Dis 2010 Jan; [e-pub ahead of print]. Mukherjee P et al
Travel-Associated H1N1 Influenza in Singapore
Airport thermal scanners detected only 12% of travel-associated flu cases; many travelers boarded flights despite symptoms.
And finally, in June of 2010 CIDRAP carried this piece on a study of thermal scanners in New Zealand in 2008 (before the pandemic) presented at 2010’s ICEID.
Thermal scanners are poor flu predictors
Thermal scanners for screening travelers do moderately well at detecting fever, but do a poor job at flagging influenza, according to researchers from New Zealand who presented their findings today at the International Conference on Emerging Infectious Diseases (ICEID) in Atlanta.
As far as the transmission of the influenza virus aboard an airliner, in May of 2010 we saw a study in the BMJ that looked at that very topic (see BMJ: Flu Transmission Risks On Airplanes)
BMJ 2010;340:c2424
Research
Transmission of pandemic A/H1N1 2009 influenza on passenger aircraft: retrospective cohort study
Conclusions
A low but measurable risk of transmission of pandemic A/H1N1 exists during modern commercial air travel. This risk is concentrated close to infected passengers with symptoms. Follow-up and screening of exposed passengers is slow and difficult once they have left the airport.
Another study, conducted by researchers at UCLA and published in BMC Medicine in late 2009:
Calculating the potential for within-flight transmission of influenza A (H1N1)
Bradley G Wagner, Brian J Coburn and Sally Blower*
Results
The risk of catching H1N1 will essentially be confined to passengers travelling in the same cabin as the source case. Not surprisingly, we find that the longer the flight the greater the number of infections that can be expected. We calculate that H1N1, even during long flights, poses a low to moderate within-flight transmission risk if the source case travels First Class.
While it may prove impossible to halt the spread of a pandemic via airline passengers, knowing which airports are the most likely to contribute to the spread of a new virus could aid in attempts to slow its progress.
Which makes research like what we’ve seen out of MIT today of more than just academic interest.
