Predictive power of air travel and socio-economic data for early pandemic spread.
BACKGROUND
Controlling the pandemic spread of newly emerging diseases requires rapid, targeted allocation of limited resources among nations. Critical, early control steps would be greatly enhanced if the key risk factors can be identified that accurately predict early disease spread immediately after emergence.


RESULTS
Here, we examine the role of travel, trade, and national healthcare resources in predicting the emergence and initial spread of 2009 A/H1N1 influenza. We find that incorporating national healthcare resource data into our analyses allowed a much greater capacity to predict the international spread of this virus. In countries with lower healthcare resources, the reporting of 2009 A/H1N1 cases was significantly delayed, likely reflecting a lower capacity for testing and reporting, as well as other socio-political issues. We also report substantial international trade in live swine and poultry in the decade preceding the pandemic which may have contributed to the emergence and mixed genotype of this pandemic strain. However, the lack of knowledge of recent evolution of each H1N1 viral gene segment precludes the use of this approach to determine viral origins.


CONCLUSIONS
We conclude that strategies to prevent pandemic influenza virus emergence and spread in the future should include: 1) enhanced surveillance for strains resulting from reassortment in traded livestock; 2) rapid deployment of control measures in the initial spreading phase to countries where travel data predict the pathogen will reach and to countries where lower healthcare resources will likely cause delays in reporting. Our results highlight the benefits, for all parties, when higher income countries provide additional healthcare resources for lower income countries, particularly those that have high air traffic volumes. In particular, international authorities should prioritize aid to those poorest countries where both the risk of emerging infectious diseases and air traffic volume is highest. This strategy will result in earlier detection of pathogens and a reduction in the impact of future pandemics.
Hosseini
Parviez
P
EcoHealth Alliance, New York, New York, United States of America. hosseini@ecohealthalliance.org
Sokolow
Susanne H
SH
Vandegrift
Kurt J
KJ
Kilpatrick
A Marm
AM
Daszak
Peter
P
D003132:Commerce; D014943:Global Health; D006801:Humans; D053118:Influenza A Virus, H1N1 Subtype / Q000235:genetics / Q000502:physiology; D007251:Influenza, Human / Q000191:economics* / Q000453:epidemiology / Q000635:transmission* / Q000821:virology; D015233:Models, Statistical; D058873:Pandemics / Q000191:economics*; D014195:Travel