Tree-based Classifiers and GIS for Biological Risk Forecasting

A tree-based classifier of tick presence, developed to estimate the risk of tick-borne diseases, is currently being interfaced and applied with a Geographical Information System (GIS) based on GRASS (USA-CERL Geographic Resources Analysis Support System). Environmental factors (altitude, substratum, vegetation, exposition, etc.) and tick sampling are used to predict occurrence of the parasite Ixodes ricinus on a target territory. A Tcl/Tk interface to GRASS has been developed for regional data from the Sistema Informativo Ambiente Territorio (S.I.A.T.) of the Autonomous Province of Trento. The system predictions are consistent with the current knowledge of tick ecology and can be used for an effective control of tick-borne diseases

A New Bootstrap Method for Risk Assessment ofExposure to Lyme Disease

Lyme borreliosis, now the most common vector-borne illness in North America, may involve cardiac manifestations as atrioventricular block, myopericarditis, and rhythm disturbances. The overall prognosis of Lyme carditis is good, but temporary cardiac pacing may be required and late dilated cardiomyopathy may occur. Borreliosis should be suspected in all patients with unexplained cardiac symptoms (supraventricular tachiarrhythmia and especially in atrioventricular block of unknown origin in young patients) who have been exposed in regions invaded by the epidemic. Risk assessment of exposure to bites of infected ticks is thus needed for prevention and accurate diagnosis of borreliosi

An Application of the Bootstrap 632+ Rule to Ecological Data

We applied the novel bootstrap 632 rule to choose tree-based classifiers trained for modeling the risk of parasite presence in a host population of ungulates. The method is designed to control overfitting: compact classification trees (CART) are selected using a nonlinear combination of the resubstitution error and the standard bootstrap error estimate. Model selection based on the 632 rule offers a gain over cross-validation for CART models. The tree classifier selected by the new rule for this application favourably compared with standard multivariate GLIM models

Ixodes Ricinus (Acari: Ixodidae) Infestation on Roe Deer (Capreolus Capreolus) in Trentino, Italian Alps

The most important tick-deer system potentially supporting the epidemiology of Lyme disease in the Italian Alps is that regarding Ixodes ricinus (L.) and roe deer (Capreolus capreolus L.). In this study, the pattern of tick infestation on 562 male roe deer harvested in Semptember 1994 in 56 game districts of Trentino, Nothern Italy, was assessed. The prevalence and density of infesttiion by I. ricinus were analyzed by a model based on classification and regression trees (CART), using both discrete and continuous variables concerning environmental and host parameters. The model discriminated altitude and host density as the 2 variables having the greatest effect on the prevalence and density of infestation in deer; the levels of infestation were higher at an altitude below 1125 m or at roe deer densietes over 8.5 head per 100 ha. The density of tick infestation tended to be higher in older roe dee

Classification Tree Methods for Analysis of Mesoscale Distribution of Ixodes ricinus (Acari: Ixodidae) in Trentino, Italian Alps

Cases of Lyme disease and tick borne encephalitis were recently recognized in the province of Trento, Italian Alps. Assessment of areas of potential risk for these tick-borne diseases is carried out by a model based on CART (Classification and Regression Trees), using both discrete and continuous variables. Data on Ixodes ricinus (L.) occurrence resulted from samplings carried out by standard methods in 99 sites throughout the province of Trento. A series of environmental parameters were recorded from each site. Mesoscale population densities of roe deer, Capreolus capreolus (L.), were considered. Cross-validation and bootstrap techniques were used in the definition of the model. The CART model discriminates two variables which appear to have the greatest effect on the occurrence of ticks: altitude and a.s.l. or on volcanic substrata. The model seems to be effective in identifying the mesoscale areas at greater potential ris

Pattern of Infestation of Ixodes Ricinus (Acari: Ixodidae) on Roe Deer in the Italian Alps

The interaction between Ixodes ricinus and roe deer (Capreolus capreolus) is one of the most important host-parasite association supporting the epidemiology of Lyme disease in the Italian Alps. The pattern of infestation of ticks on 534 male roe deer harvested in September 1995 in 56 game districts was assessed. Prevalence and abundance of I. ricinus were analyzed by a model based on classification and regression trees (CART), using both discrete and continuous variables concerning environmental and host parameters. This model discriminated three variables which appear to have the greatest effect on the abundance of ticks on roe deer: altitude, host density and host age, with tick abundance decreasing above 1000 m a.s.l. or with roe deer density below 10 head/100 ha and increasing with host ag