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Estimating front-wave velocity of infectious diseases: a simple, efficient method applied to bluetongue
Authors:Pioz Maryline  Guis Hélène  Calavas Didier  Durand Benoît  Abrial David  Ducrot Christian
Affiliation:1Institut National de la Recherche Agronomique, Centre de Clermont-Ferrand Theix, Unité d''Epidémiologie Animale, St Genès Champanelle, France;2CIRAD, UMR Contrôle des maladies, F-34398 Montpellier, France;3French Agency for Food, Environnemental and Occupational Health Safety, Lyon, France;4French Agency for Food, Environnemental and Occupational Health Safety, Maisons-Alfort, France
Abstract:ABSTRACT: Understanding the spatial dynamics of an infectious disease is critical when attempting to predict where and how fast the disease will spread. We illustrate an approach using a trend-surface analysis (TSA) model combined with a spatial error simultaneous autoregressive model (SARerr model) to estimate the speed of diffusion of bluetongue (BT), an infectious disease of ruminants caused by bluetongue virus (BTV) and transmitted by Culicoides. In a first step to gain further insight into the spatial transmission characteristics of BTV serotype 8, we used 2007-2008 clinical case reports in France and TSA modelling to identify the major directions and speed of disease diffusion. We accounted for spatial autocorrelation by combining TSA with a SARerr model, which led to a trend SARerr model. Overall, BT spread from north-eastern to south-western France. The average trend SARerr-estimated velocity across the country was 5.6 km/day. However, velocities differed between areas and time periods, varying between 2.1 and 9.3 km/day. For more than 83% of the contaminated municipalities, the trend SARerr-estimated velocity was less than 7 km/day. Our study was a first step in describing the diffusion process for BT in France. To our knowledge, it is the first to show that BT spread in France was primarily local and consistent with the active flight of Culicoides and local movements of farm animals. Models such as the trend SARerr models are powerful tools to provide information on direction and speed of disease diffusion when the only data available are date and location of cases.
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