Estimating the extent of spatial association of Mycobacterium bovis infection in badgers in Ireland

Mycobacterium bovis infects the wildlife species badgers Meles meles who are linked with the spread of the associated disease tuberculosis (TB) in cattle. Control of livestock infections depends in part on the spatial and social structure of the wildlife host. Here we describe spatial association of M. bovis infection in a badger population using data from the first year of the Four Area Project in Ireland. Using second-order intensity functions, we show there is strong evidence of clustering of TB cases in each the four areas, i.e. a global tendency for infected cases to occur near other infected cases. Using estimated intensity functions, we identify locations where particular strains of TB cluster. Generalized linear geostatistical models are used to assess the practical range at which spatial correlation occurs and is found to exceed 6 in all areas. The study is of relevance concerning the scale of localized badger culling in the control of the disease in cattle.

Spatial Management of Wildlife Disease

The spread of wildlife diseases is a major threat to livestock, human health, resource-based recreation, and biodiversity conservation (Cleaveland, Laurenson, and Taylor). The development of economically sound wildlife disease-management strategies requires an understanding of the links between ecological functions (e.g., disease transmission and wildlife dispersal) and economic choices, and the associated tradeoffs. Spatial linkages are particularly relevant. Yet while ecologists have long-argued that space is important (Hudson et al.), prior economic work has largely ignored spatial issues. For instance, Horan and Wolf analyzed a case study of bovine tuberculosis (bTB) in Michigan deer, a problem where the disease appears to be confined to a single, spatially confined, wildlife population—an island. But wildlife disease matters generally are not spatially confined. Barlow, in analyzing bTB in possums in New Zealand, accounted for immigration of susceptible possums into a disease reservoir. However, he modeled immigration as fixed and unaffected by management. Bicknell, Wilen, and Howitt, also focusing on possums in New Zealand, developed a model that incorporates simple density-dependent net migration. This allowed the authors to account for endogenous immigration when deriving optimal culling strategies.

Spatial and Temporal Spread of Bovine Tuberculosis in Wild White-Tailed Deer in Michigan

In 1975, a wild white-tailed deer infected with bovine tuberculosis was shot in the northeastern Lower Peninsula, Michigan. The shooting of a second infected deer in the same area in 1994 triggered ongoing disease surveillance in the region. By 2002, bovine tuberculosis had been confirmed in 12 Michigan counties: from 449 deer; two elk; 41 non-cervid wildlife; one captive cervid facility and 28 cattle herds. We analyzed geographic spread of disease since the surveillance began and investigated factors influencing the prevalence of disease within the infected area. These analyses reveal that 78 percent of tuberculous deer came from within a 1560 km2 'core' area, within which the prevalence of apparent disease averaged 2.5 percent. Prevalence declined dramatically outside of the core and was an order of magnitude lower 30 km from its boundary. This prevalence gradient was highly significant (P<0.0001) and did not alter over the 6 year surveillance period (P= 0.98). Within the core, deer density and supplemental feeding by hunters were positively and independently correlated with tuberculosis prevalence in deer. Together, these two factors explained 55 percent of the variation in prevalence. We conclude that bovine tuberculosis was already well established in the deer population in 1994, that the infected area has not expanded significantly since that time, and that deer over-abundance and food supplementation have both contributed to ongoing transmission of disease. Managers are currently enforcing prohibitions on deer feeding in the core and are working to lower deer numbers there through increased hunting pressure.

Spatio-Temporal Event Model for Cyber-Physical Systems

The emerging Cyber-Physical Systems (CPSs) are envisioned to integrate computation, communication and control with the physical world. Therefore, CPS requires close interactions between the cyber and physical worlds both in time and space. These interactions are usually governed by events, which occur in the physical world and should autonomously be reflected in the cyber-world, and actions, which are taken by the CPS as a result of detection of events and certain decision mechanisms. Both event detection and action decision operations should be performed accurately and timely to guarantee temporal and spatial correctness. This calls for a flexible architecture and task representation framework to analyze CP operations. In this paper, we explore the temporal and spatial properties of events, define a novel CPS architecture, and develop a layered spatiotemporal event model for CPS. The event is represented as a function of attribute-based, temporal, and spatial event conditions. Moreover, logical operators are used to combine different types of event conditions to capture composite events. To the best of our knowledge, this is the first event model that captures the heterogeneous characteristics of CPS for formal temporal and spatial analysis.