The forecasting of dynamical Ross River virus outbreaks: Victoria, Australia.

Alphavirus Infections / epidemiology Animals Disease Outbreaks Forecasting Humans Models, Theoretical Public Health Ross River virus Victoria
Arboviruses Epidemiology Forecasting Mosquito-borne disease Predicting epidemics Transmission

Journal

Epidemics
ISSN: 1878-0067
Titre abrégé: Epidemics
Pays: Netherlands
ID NLM: 101484711

Informations de publication

Date de publication:
03 2020
Historique:
received: 01 05 2019
revised: 04 11 2019
accepted: 04 11 2019
pubmed: 19 11 2019
medline: 30 1 2021
entrez: 19 11 2019
Statut: ppublish

Résumé

Ross River virus (RRV) is Australia's most epidemiologically important mosquito-borne disease. During RRV epidemics in the State of Victoria (such as 2010/11 and 2016/17) notifications can account for up to 30% of national RRV notifications. However, little is known about factors which can forecast RRV transmission in Victoria. We aimed to understand factors associated with RRV transmission in epidemiologically important regions of Victoria and establish an early warning forecast system. We developed negative binomial regression models to forecast human RRV notifications across 11 Local Government Areas (LGAs) using climatic, environmental, and oceanographic variables. Data were collected from July 2008 to June 2018. Data from July 2008 to June 2012 were used as a training data set, while July 2012 to June 2018 were used as a testing data set. Evapotranspiration and precipitation were found to be common factors for forecasting RRV notifications across sites. Several site-specific factors were also important in forecasting RRV notifications which varied between LGA. From the 11 LGAs examined, nine experienced an outbreak in 2011/12 of which the models for these sites were a good fit. All 11 LGAs experienced an outbreak in 2016/17, however only six LGAs could predict the outbreak using the same model. We document similarities and differences in factors useful for forecasting RRV notifications across Victoria and demonstrate that readily available and inexpensive climate and environmental data can be used to predict epidemic periods in some areas. Furthermore, we highlight in certain regions the complexity of RRV transmission where additional epidemiological information is needed to accurately predict RRV activity. Our findings have been applied to produce a Ross River virus Outbreak Surveillance System (ROSS) to aid in public health decision making in Victoria.

Identifiants

DOI: 10.1016/j.epidem.2019.100377 PMID: 31735585
pubmed: 31735585
pii: S1755-4365(19)30065-9
doi: 10.1016/j.epidem.2019.100377
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

100377

Informations de copyright

Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.

Auteurs

Iain S Koolhof (IS)

College of Health and Medicine, School of Medicine, University of Tasmania, Hobart, Tasmania, Australia; College of Sciences and Engineering, School of Natural Sciences, University of Tasmania, Hobart, Tasmania, Australia. Electronic address: koolhofi@utas.edu.au.

Katherine B Gibney (KB)

Victorian Department of Health and Human Services, Communicable Disease Epidemiology and Surveillance, Health Protection Branch, Melbourne, Victoria, Australia; The Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, Victoria, Australia; Department of Infectious Diseases, Austin Hospital, Melbourne, Victoria, Australia.

Silvana Bettiol (S)

College of Health and Medicine, School of Medicine, University of Tasmania, Hobart, Tasmania, Australia.

Michael Charleston (M)

College of Sciences and Engineering, School of Natural Sciences, University of Tasmania, Hobart, Tasmania, Australia.

Anke Wiethoelter (A)

Melbourne Veterinary School, Faculty of Veterinary and Agricultural Sciences, University of Melbourne, Melbourne, Victoria, Australia.

Anna-Lena Arnold (AL)

Victorian Department of Health and Human Services, Communicable Disease Epidemiology and Surveillance, Health Protection Branch, Melbourne, Victoria, Australia.

Patricia T Campbell (PT)

The Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, Victoria, Australia; Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia.

Peter J Neville (PJ)

Victorian Department of Health and Human Services, Communicable Disease Epidemiology and Surveillance, Health Protection Branch, Melbourne, Victoria, Australia; Department of Health, Western Australia, Public and Aboriginal Health, Environmental Health Directorate, Perth, Western Australia, Australia.

Phyo Aung (P)

The Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, Victoria, Australia.

Tsubasa Shiga (T)

The Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, Victoria, Australia.

Scott Carver (S)

College of Sciences and Engineering, School of Natural Sciences, University of Tasmania, Hobart, Tasmania, Australia.

Simon M Firestone (SM)

Melbourne Veterinary School, Faculty of Veterinary and Agricultural Sciences, University of Melbourne, Melbourne, Victoria, Australia.

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Classifications MeSH

questionsmedicales.fr › Infection › Maladies virales › Infections à virus à ARN › Infections à Togaviridae › Infections à alphavirus › The forecasting of dynamical Ross River virus...
questionsmedicales.fr › Eucaryotes › Animaux › The forecasting of dynamical Ross River virus...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Épidémies de maladies › The forecasting of dynamical Ross River virus...
questionsmedicales.fr › Sciences sociales › Prévision › The forecasting of dynamical Ross River virus...
questionsmedicales.fr › Eucaryotes › Animaux › Chordés › Vertébrés › Mammifères › Eutheria › Primates › Haplorhini › Catarrhini › Hominidae › Humains › The forecasting of dynamical Ross River virus...
questionsmedicales.fr › Techniques d'investigation › Modèles théoriques › The forecasting of dynamical Ross River virus...
questionsmedicales.fr › Environnement et santé publique › Santé publique › The forecasting of dynamical Ross River virus...
questionsmedicales.fr › Virus › Virus à ARN › Virus à ARN à brin positif › Togaviridae › Alphavirus › Virus de la rivière Ross › The forecasting of dynamical Ross River virus...
questionsmedicales.fr › Régions géographiques › Océanie › Australasie › Australie › Victoria › The forecasting of dynamical Ross River virus...