Seasonal Drivers of the Epidemiology of Arthropod-Borne Viruses in Australia e3325

• Published in: PLoS neglected tropical diseases Vol. 8; no. 11
• Main Authors: Geoghegan, Jemma L, Walker, Peter J, Duchemin, Jean-Bernard, Jeanne, Isabelle, Holmes, Edward C
• Format: Journal Article
• Language: English
• Published: San Francisco Public Library of Science 01-11-2014
• Subjects: Cattle; Disease; Economic impact; Economic importance; Epidemiology; Equator; Fever; Geography; Infections; Latitude; Livestock; Public health; Risk assessment; Seasonal variations; Tropical diseases; Viruses; Australia
• ISSN: 1935-2727; 1935-2735
• DOI: 10.1371/journal.pntd.0003325

Arthropod-borne viruses are a major cause of emerging disease with significant public health and economic impacts. However, the factors that determine their activity and seasonality are not well understood. In Australia, a network of sentinel cattle herds is used to monitor the distribution of several such viruses and to define virus-free regions. Herein, we utilize these serological data to describe the seasonality, and its drivers, of three economically important animal arboviruses: bluetongue virus, Akabane virus and bovine ephemeral fever virus. Through epidemiological time-series analyses of sero-surveillance data of 180 sentinel herds between 2004-2012, we compared seasonal parameters across latitudes, ranging from the tropical north (-10°S) to the more temperate south (-40°S). This analysis revealed marked differences in seasonality between distinct geographic regions and climates: seasonality was most pronounced in southern regions and gradually decreased as latitude decreased toward the Equator. Further, we show that both the timing of epidemics and the average number of seroconversions have a strong geographical component, which likely reflect patterns of vector abundance through co-varying climatic factors, especially temperature and rainfall. Notably, despite their differences in biology, including insect vector species, all three viruses exhibited very similar seasonality. By revealing the factors that shape spatial and temporal distributions, our study provides a more complete understanding of arbovirus seasonality that will enable better risk predictions.