Predicting arboviral disease emergence using Bayesian networks: A case study of dengue virus in Western Australia

Epidemiology and Infection

Volumn 145, Issue 1, 2017, Pages 54-66

  Ho, S H ^a   Speldewinde, P ^a   Cook, A ^a  

^a UNIVERSITY OF WESTERN AUSTRALIA   (Australia)

Author keywords

Aedes albopictus; Bayesian Belief Network; dengue virus; Key words Aedes aegypti; risk mapping; risk modelling

Indexed keywords

AEDES AEGYPTI; AEDES ALBOPICTUS; ARBOVIRUS; ARTICLE; AUSTRALIA; CONCEPTUAL FRAMEWORK; DENGUE; DENGUE VIRUS; ECOLOGICAL NICHE; GENE MAPPING; GEOGRAPHIC DISTRIBUTION; HUMAN; HUMIDITY; MATHEMATICAL MODEL; POPULATION DENSITY; PREDICTION; PROBABILITY; RISK ASSESSMENT; RURAL AREA; TEMPERATURE; URBAN AREA; AEDES; ANIMAL; BAYES THEOREM; CLIMATE; FEMALE; FORECASTING; GROWTH, DEVELOPMENT AND AGING; MOSQUITO VECTOR; PROCEDURES; SEASON; WESTERN AUSTRALIA;

AEDES; ANIMALS; BAYES THEOREM; CLIMATE; DENGUE; FEMALE; FORECASTING; HUMANS; MOSQUITO VECTORS; RISK ASSESSMENT; SEASONS; WESTERN AUSTRALIA;

EID: 84987677364     PISSN: 09502688     EISSN: 14694409     Source Type: Journal    
DOI: 10.1017/S0950268816002090     Document Type: Article

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