About: Predictive Power of Air Travel and Socio-Economic Data for Early Pandemic Spread

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Predictive Power of Air Travel and Socio-Economic Data for Early Pandemic Spread
Creator	Daszak, Peter Hosseini, Parviez Kilpatrick, A Sokolow, Susanne Vandegrift, Kurt
Source	PMC
abstract	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. METHODOLOGY/PRINCIPAL FINDINGS: 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/SIGNIFICANCE: 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.
has issue date	2010-09-15(xsd:dateTime)
bibo:doi	10.1371/journal.pone.0012763
bibo:pmid	20856678
has license	cc-by
sha1sum (hex)	22f1e46f69ea11771ee26f499b234bd3ff1bb88b
schema:url	https://doi.org/10.1371/journal.pone.0012763
resource representing a document's title	Predictive Power of Air Travel and Socio-Economic Data for Early Pandemic Spread
has PubMed Central identifier	PMC2939898
has PubMed identifier	20856678
schema:publication	PLoS One
resource representing a document's body	covid:22f1e46f69ea11771ee26f499b234bd3ff1bb88b#body_text
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