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A dynamic data-based model describing nephropathia epidemica in Belgium

S Amirpour Haredasht, JM Barrios, P Maes, WW Verstraeten, J Clement, G Ducoffre, K Lagrou, M Van Ranst, P Coppin, D Berckmans, JM Aerts

Nephropathia epidemica (NE) is a human infection caused by Puumala virus (PUUV), which is naturally carried and shed by bank voles (Myodes glareolus). Population dynamics and infectious diseases in general, such as NE, have often been modelled with mechanistic SIR (Susceptible, Infective and Remove with immunity) models. Precipitation and temperature have been found to be indicators of NE, however most SIR models do not take them into account. The objective of this paper was to develop a dynamic model of incidences of NE in Belgium by taking into account climatological data. A multiple input, single-output (MISO) transfer function was used to model the incidence of NE. In a first step, the NE cases were modelled based on data from 1996 until 2003 with an R2 of 0.68. In the next step the MISO model was validated for incidences of NE in Belgium from 2003 to 2008 (R2 of 0.54). The output of the MISO models was the number of NE cases in Belgium over the time period 1996 until 2008 and the inputs were average measured monthly precipitation (mm), and temperature as well as estimated carrying capacity (vole ha-1).
The monthly values of carrying capacity (K ) were estimated for the whole period by using an existing mechanistic SIR model. K is related to the variation in seed production in Northern Europe, which has an effect on the population of bank voles.
In the future, such modelling approaches may be used to predict and monitor forthcoming NE cases based on climate and vegetation data as a tool for prevention of NE cases.

Bibliografische gegevens

S Amirpour Haredasht, JM Barrios, P Maes, WW Verstraeten, J Clement, G Ducoffre, K Lagrou, M Van Ranst, P Coppin, D Berckmans, JM Aerts. A dynamic data-based model describing nephropathia epidemica in Belgium
Status: published, Journal: Biosystems engineering, Year: 2011, First page: 77, Last page: 89, doi: 10.1016/j.biosystemseng.2011.02.004

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