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Lloyd-Smith, J. O. et al. Should we expect population thresholds for wildlife disease? Trends Ecol. Evol. 20, 511-519

Department of Environmental Science, Policy and Management, University of California at Berkeley, Berkeley, CA 94720-3114, USA.
Trends in Ecology & Evolution (Impact Factor: 16.2). 10/2005; 20(9):511-9. DOI: 10.1016/j.tree.2005.07.004
Source: PubMed

ABSTRACT

Host population thresholds for the invasion or persistence of infectious disease are core concepts of disease ecology and underlie disease control policies based on culling and vaccination. However, empirical evidence for these thresholds in wildlife populations has been sparse, although recent studies have begun to address this gap. Here, we review the theoretical bases and empirical evidence for disease thresholds in wildlife. We see that, by their nature, these thresholds are rarely abrupt and always difficult to measure, and important facets of wildlife ecology are neglected by current theories. Empirical studies seeking to identify disease thresholds in wildlife encounter recurring obstacles of small sample sizes and confounding factors. Disease control policies based solely on threshold targets are rarely warranted, but management to reduce abundance of susceptible hosts can be effective.

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    • "For instance, we assumed that ND transmission was density dependent in white-winged parakeets. Density-dependent transmission is commonly assumed for wildlife diseases[103,157]. In most cases of wildlife diseases, empirical data are difficult to obtain to confirm transmission, but Hochachka & Dhondt[140]used pre-and post-enzootic data to conclude that mycoplasma conjunctivitis transmission in house finches was density dependent. "
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    • "A fundamental principle of epidemiological theory is that there is a minimum population threshold for pathogen invasion and a critical community size required for disease persistence for diseases with density dependent transmission[40]. While exact thresholds in wildlife populations are difficult to determine, identifying host distribution ranges around these thresholds, as we did here, can improve our understanding of disease dynamics[41]and therefore ability to forecast future outbreak events. For non-infectious diseases, where pathogens are endemic in the population and infection results from an imbalance in the host–pathogen relationship, variables besides host density may be important determinants of disease prevalence[42]. "

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    • "Understanding the mechanisms underpinning the spread of infectious diseases in populations is critical for disease control (Anderson & May 1991; Grenfell & Dobson 1995; Lloyd-Smith et al. 2005; Keeling & Rohani 2008). The contact structure of a population can significantly affect infectious disease transmission, and therefore, knowledge of host contact patterns can be crucial for predicting and controlling disease outbreaks (Keeling 1999; Newman 2002; Keeling & Eames 2005; Craft 2015). "
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