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Discovering Spatio‐Temporal Models of the Spread of West Nile Virus
Author(s) -
OrmeZavaleta Jennifer,
Jorgensen Jane,
D'Ambrosio Bruce,
Altendorf Eric,
Rossignol Philippe A.
Publication year - 2006
Publication title -
risk analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.972
H-Index - 130
eISSN - 1539-6924
pISSN - 0272-4332
DOI - 10.1111/j.1539-6924.2006.00738.x
Subject(s) - west nile virus , wildlife , geography , context (archaeology) , emerging infectious disease , public health , outbreak , environmental resource management , environmental planning , data science , environmental health , cartography , virology , ecology , computer science , biology , virus , environmental science , medicine , nursing , archaeology
Emerging infectious diseases are characterized by complex interactions among disease agents, vectors, wildlife, humans, and the environment. ( 1–3 ) Since the appearance of West Nile virus (WNV) in New York City in 1999, it has infected over 8,000 people in the United States, resulting in several hundred deaths in 46 contiguous states. ( 4 ) The virus is transmitted by mosquitoes and maintained in various bird reservoir hosts. ( 5 ) Its unexpected introduction, high morbidity, and rapid spread have left public health agencies facing severe time constraints in a theory‐poor environment, dependent largely on observational data collected by independent survey efforts and much uncertainty. Current knowledge may be expressed as a priori constraints on models learned from data. Accordingly, we applied a Bayesian probabilistic relational approach to generate spatially and temporally linked models from heterogeneous data sources. Using data collected from multiple independent sources in Maryland, we discovered the integrated context in which infected birds are plausible indicators for positive mosquito pools and human cases for 2001 and 2002.