Estimating front-wave velocity of infectious diseases: a simple, efficient method applied to bluetongue View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2011-04-20

AUTHORS

Maryline Pioz, Hélène Guis, Didier Calavas, Benoît Durand, David Abrial, Christian Ducrot

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. More... »

PAGES

60

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/1297-9716-42-60

DOI

http://dx.doi.org/10.1186/1297-9716-42-60

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1048686664

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/21507221


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