Network Models: An Underutilized Tool in Wildlife Epidemiology?

Craft, Meggan E.; Caillaud, Damien

doi:10.1155/2011/676949

Cited by 116 publications

(144 citation statements)

References 72 publications

Supporting

Mentioning

144

Contrasting

Order By: Relevance

“…In natural systems, it has been demonstrated that these interrelated facets of transmission can vary widely between individuals. In fact, empirical studies suggest that unequal contact rates are the rule rather than the exception (Craft and Caillaud 2011), that contact rates can vary with infection-induced behavioral changes (Croft et al 2011), and that these changes are likely non-uniform across individuals (Lopes et al 2016). Innate and plastic heterogeneity in susceptibility to infection has been documented for several species (Dwyer et al 1997, Beldomenico and Begon 2010, Gibson et al 2016, and variability in infectiousness has also been observed, particularly when concomitant infections are present (Cattadori et al 2007).…”

Section: Introductionmentioning

confidence: 99%

Covariation between the physiological and behavioral components of pathogen transmission: host heterogeneity determines epidemic outcomes

White

Forester

Craft

2017

Oikos

Self Cite

View full text Add to dashboard Cite

Although heterogeneity in contact rate, physiology, and behavioral response to infection have all been empirically demonstrated in host-pathogen systems, little is known about how interactions between individual variation in behavior and physiology scaleup to affect pathogen transmission at a population level. The objective of this study is to evaluate how covariation between the behavioral and physiological components of transmission might affect epidemic outcomes in host populations. We tested the consequences of contact rate covarying with susceptibility, infectiousness, and infection status using an individual-based, dynamic network model where individuals initiate and terminate contacts with conspecifics based on their behavioral predispositions and their infection status. Our results suggest that both heterogeneity in physiology and subsequent covariation of physiology with contact rate could powerfully influence epidemic dynamics. Overall, we found that 1) individual variability in susceptibility and infectiousness can reduce the expected maximum prevalence and increase epidemic variability; 2) when contact rate and susceptibility or infectiousness negatively covary, it takes substantially longer for epidemics to spread throughout the population, and rates of epidemic spread remained suppressed even for highly transmissible pathogens; and 3) reductions in contact rate resulting from infection-induced behavioral changes can prevent the pathogen from reaching most of the population. These effects were strongest for theoretical pathogens with lower transmissibility and for populations where the observed variation in contact rate was higher, suggesting that such heterogeneity may be most important for less infectious, more chronic diseases in wildlife. Understanding when and how variability in pathogen transmission should be modelled is a crucial next step for disease ecology.

show abstract

Section: Introductionmentioning

confidence: 99%

Covariation between the physiological and behavioral components of pathogen transmission: host heterogeneity determines epidemic outcomes

White

Forester

Craft

2017

Oikos

Self Cite

View full text Add to dashboard Cite

show abstract

“…While traditionally applied to human-pathogen systems, network analysis tools have recently gained traction among ecologists studying wildlife disease dynamics [11][12][13]. Here, we present how network epidemiology can be used to develop efficient vaccination strategies for a social wildlife species.…”

Section: Introductionmentioning

confidence: 99%

Network-based vaccination improves prospects for disease control in wild chimpanzees

Rushmore

Caillaud

Hall

et al. 2014

J. R. Soc. Interface.

Self Cite

135

View full text Add to dashboard Cite

Many endangered wildlife populations are vulnerable to infectious diseases for which vaccines exist; yet, pragmatic considerations often preclude largescale vaccination efforts. These barriers could be reduced by focusing on individuals with the highest contact rates. However, the question then becomes whether targeted vaccination is sufficient to prevent large outbreaks. To evaluate the efficacy of targeted wildlife vaccinations, we simulate pathogen transmission and control on monthly association networks informed by behavioural data from a wild chimpanzee community (Kanyawara N ¼ 37, Kibale National Park, Uganda). Despite considerable variation across monthly networks, our simulations indicate that targeting the most connected individuals can prevent large outbreaks with up to 35% fewer vaccines than random vaccination. Transmission heterogeneities might be attributed to biological differences among individuals (e.g. sex, age, dominance and family size). Thus, we also evaluate the effectiveness of a trait-based vaccination strategy, as trait data are often easier to collect than interaction data. Our simulations indicate that a trait-based strategy can prevent large outbreaks with up to 18% fewer vaccines than random vaccination, demonstrating that individual traits can serve as effective estimates of connectivity. Overall, these results suggest that fine-scale behavioural data can help optimize pathogen control efforts for endangered wildlife.

show abstract

“…In addition, it will be essential understand the interactions between genetic diversity and sociality on parasite transmission (Hughes and Boomsma 2006;Walker and Hughes 2009;Baer and Schmid-Hempel 1999;Ugelvig et al 2010). For now, the robust empirical data on the impact of sociality on parasites outside of human diseases is lacking (Craft and Caillaud 2011).…”

Section: Individual Simulationsmentioning

confidence: 99%

The Red Queen Process does not Select for High Recombination Rates in Haplodiploid Hosts

Kidner

Moritz

2013

Evol Biol

View full text Add to dashboard Cite

One of the main competing theories to describe the evolution of recombination is the Red Queen Hypothesis (RQH). Presently, many theoretical analyses of the RQH typically examine fitness interactions in host-parasite frameworks. Less emphasis has been placed on understanding the impact of host ploidy in these systems. In this study, we look to investigate the high observed rates of recombination observed in two common haplodiploid species (Apis mellifera and Bombus terrestris). We compared haplodiploid to diploid host populations under infection with haploid asexual parasites, using a Matching Allele (MAM) model. Results from a simulation analysis showed that the Red Queen does not run in haplodiploid hosts and is therefore, probably not responsible for the high recombination rates observed so far in haplodiploid hosts.

show abstract

Network Models: An Underutilized Tool in Wildlife Epidemiology?

Cited by 116 publications

References 72 publications

Covariation between the physiological and behavioral components of pathogen transmission: host heterogeneity determines epidemic outcomes

Covariation between the physiological and behavioral components of pathogen transmission: host heterogeneity determines epidemic outcomes

Network-based vaccination improves prospects for disease control in wild chimpanzees

The Red Queen Process does not Select for High Recombination Rates in Haplodiploid Hosts

Contact Info

Product

Resources

About