Modeling the Effects of Reservoir Competence Decay and Demographic Turnover in Lyme Disease Ecology

Lyme disease risk is related to the abundance of infected nymphal ticks, which in turn depends on the abundance and reservoir competence of wild hosts. Reservoir competence of a host (i.e., probability that an infected host will infect a feeding vector) often declines over time after inoculation, and small mammalian reservoirs typically undergo rapid population growth during the period when vector ticks feed. These processes can affect disease risk in the context of site-specific tick abundance and host community composition. We modeled the effects of reservoir decay and host demographic turnover on Lyme disease risk using a simple yearly difference equation model and a more realistic simulation incorporating seasonal dynamics of ticks and hosts. Both reservoir decay and demographic turnover caused (1) specific infectivity (proportion infected 3 reservoir competence) of host populations to vary with host community composition, (2) tick infection prevalence and the specific infectivity of reservoirs to be highly sensitive to the abundance of questing nymphs, and (3) specific infectivity and the infection prevalence of ticks to decrease at high host densities. Reservoir competence decay had similar effects in both model formulations, but host turnover had less effect than reservoir decay in the seasonal model. In general, exponential reservoir decay and abrupt loss of reservoir competence had similar effects, although exponential decay caused greater sensitivity to tick density and host community composition. Reservoir decay may explain the observed variability in published field measurements of reservoir competence of a host species. Our results illuminate mechanisms by which host diversity can dilute the impact of a highly competent reservoir and suggest that management to reduce nymphal tick abundance may reap an added benefit by reducing nymphal infection prevalence

When is a parasite not a parasite? Effects of larval tick burdens on white-footed mouse survival

Many animal species can carry considerable burdens of ectoparasites: parasites living on the outside of a host's body. Ectoparasite infestation can decrease host survival, but the magnitude and even direction of survival effects can vary depending on the type of ectoparasite and the nature and duration of the association. When ectoparasites also serve as vectors of pathogens, the effects of ectoparasite infestation on host survival have the potential to alter disease dynamics by regulating host populations and stabilizing transmission. We quantified the impact of larval Ixodes scapularis tick burdens on both within-season and overwinter survival of white-footed mice (Peromyscus leucopus) using a hierarchical Bayesian capture-mark-recapture model. I. scapularis and P. leucopus are, respectively, vectors and competent reservoirs for the causative agents of Lyme disease, anaplasmosis, and babesiosis. Using a data set of 5587 individual mouse capture histories over sixteen years, we found little evidence for any effect of tick burdens on either within-season or overwinter mouse survival probabilities. In male mice, tick burdens were positively correlated with within-season survival probabilities. Mean maximum tick burdens were also positively correlated with population rates of change during the concurrent breeding season. The apparent indifference of mice to high tick burdens may contribute to their effectiveness as reservoir hosts for several human zoonotic pathogens.Fil: Hersh, Michelle H.. Cary Institute of Ecosystem Studies; Estados Unidos. Bard College. Program in Biology; Estados Unidos. Sarah Lawrence College; Estados UnidosFil: LaDeau, Shannon L.. Cary Institute of Ecosystem Studies; Estados UnidosFil: Previtali, Maria Andrea. Universidad Nacional del Litoral. Facultad de Humanidades y Ciencias. Departamento de Ciencias Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; ArgentinaFil: Ostfeld, Richard S.. Cary Institute of Ecosystem Studies; Estados Unido

What Is the Best Predictor of Annual Lyme Disease Incidence: Weather, Mice, or Acorns?

Predicting fluctuations in annual risk of Lyme disease would be useful in focusing public health efforts. However, several competing hypotheses have been proposed that point to weather variables, acorn production, or mouse abundance as important predictors of Lyme disease risk. We compared the ability of acorn production, mouse density, and four relevant weather variables to predict annual Lyme disease incidence (detrended) between 1992 and 2002 for Dutchess County, New York, and seven states in the northeastern United States. Acorn production and mouse abundance measured in Dutchess County were the strongest predictors (r ≥ 0.78) of Dutchess County Lyme disease incidence, but the increase in mouse abundance from 1991 to 1992 was contrary to a decrease in Lyme disease in the following years. The Palmer Hydrologic Drought Index (PHDI) was a significant positive predictor of Lyme disease incidence two years later for three states (0.58 ≤ r ≤ 0.88), but summer precipitation was generally negatively correlated with Lyme disease incidence the next year (-0.79 ≤ r ≤ 0.02). Mean temperatures for the prior winter or summer showed weak or inconsistent correlations with Lyme disease incidence. In four states, no variable was a statistically significant predictor of Lyme disease incidence. Synchrony in Lyme disease incidence between pairs of states was not significantly concordant with synchrony in any weather variable that we examined (0.02 ≤ r ≤ 0.21). We found that acorns and mice were strong predictors of Dutchess County Lyme disease incidence, but their predictive power appeared to be weaker spatially. Moreover, evidence was weak for causal relationships between Lyme disease incidence and the weather variables that we tested. Reliable prediction of Lyme disease incidence may require the identification of new predictors or combinations of biotic and abiotic predictors and may be limited to local scales

Limited Dispersal and Heterogeneous Predation Risk Synergistically Enhance Persistence of Rare Prey

White-footed mice prey on gypsy moth pupae while foraging for other, more abundant food. Mice appear capable of locally extirpating moths since mice exert high predation pressure on sparse pupae and are numerically decoupled from moth populations. Nevertheless, during 23 years of monitoring, moths persisted at scales .1 ha despite frequent extinctions at smaller spatial scales. We hypothesized that spatially heterogeneous intensity in mouse foraging and/or limited moth dispersal might allow moth persistence. Using a spatially explicit, individual-based, empirically parameterized model, we show that neither spatially heterogeneous predation by mice, nor limited moth dispersal alone allows moth persistence at typical mouse densities. However, synergy between both factors allows moth population persistence at naturally occurring mouse densities. For example, in models with 40 mice/ha, both limited moth dispersal with spatially homogeneous predation risk and spatially heterogeneous predation risk with unlimited moth dispersal had a 0% chance of moth persistence, but the combination of limited dispersal and heterogeneous predation risk resulted in a ~75% chance of moth persistence. Furthermore, both for limited moth dispersal with spatially homogeneous predation risk and for spatially heterogeneous predation risk with unlimited moth dispersal, moth persistence was only guaranteed at very low mouse densities, while the combination of limited moth dispersal with heterogeneous predation guaranteed moth persistence within a broad range of mouse densities. The findings illustrate a novel mechanism of ‘‘spatial selection and satiation’’ that can enhance rare species persistence under intense incidental predation by generalist predators

Spatial selection and inheritance: applying evolutionary concepts to population dynamics in heterogeneous space.

Organisms in highly suitable sites generally produce more offspring, and offspring can inherit this suitability by not dispersing far. This combination of spatial selection and spatial inheritance acts to bias the distribution of organisms toward suitable sites and thereby increase mean fitness (i.e., per capita population increase). Thus, population growth rates in heterogeneous space change over time by a process conceptually analogous to evolution by natural selection, opening avenues for theoretical cross-pollination between evolutionary biology and ecology. We operationally define spatial inheritance and spatial selective differential and then combine these two factors in a modification of the breeder\u27s equation, derived from simple models of population growth in heterogeneous space. The modified breeder\u27s equation yields a conservative criterion for persistence in hostile environments estimable from field measurements. We apply this framework for understanding gypsy moth population persistence amidst abundant predators and find that the predictions of the modified breeder\u27s equation match initial changes in population growth rate in independent simulation output. The analogy between spatial dynamics and natural selection conceptually links ecology and evolution, provides a spatially implicit framework for modeling spatial population dynamics, and represents an important null model for studying habitat selection

It Takes a Community to Raise the Prevalence of a Zoonotic Pathogen

By definition, zoonotic pathogens are not strict host-species specialists in that they infect humans and at least one nonhuman reservoir species. The majority of zoonotic pathogens infect and are amplified by multiple vertebrate species in nature, each of which has a quantitatively different impact on the distribution and abundance of the pathogen and thus on disease risk. Unfortunately, when new zoonotic pathogens emerge, the dominant response by public health scientists is to search for a few, or even the single, most important reservoirs and to ignore other species that might strongly influence transmission. This focus on the single “primary” reservoir host species can delay biological understanding, and potentially public health interventions as species important in either amplifying or regulating the pathogen are overlooked. Investigating the evolutionary and ecological strategy of newly discovered or emerging pathogens within the community of potential and actual host species will be fruitful to both biological understanding and public health

Climate, Deer, Rodents, and Acorns as Determinants of Variation in Lyme-Disease Risk

Risk of human exposure to vector-borne zoonotic pathogens is a function of the abundance and infection prevalence of vectors. We assessed the determinants of Lyme-disease risk (density and Borrelia burgdorferi-infection prevalence of nymphal Ixodes scapularis ticks) over 13 y on several field plots within eastern deciduous forests in the epicenter of US Lyme disease (Dutchess County, New York). We used a model comparison approach to simultaneously test the importance of ambient growing-season temperature, precipitation, two indices of deer (Odocoileus virginianus) abundance, and densities of white-footed mice (Peromyscus leucopus), eastern chipmunks (Tamias striatus), and acorns ( Quercus spp.), in both simple and multiple regression models, in predicting entomological risk. Indices of deer abundance had no predictive power, and precipitation in the current year and temperature in the prior year had only weak effects on entomological risk. The strongest predictors of a current year's risk were the prior year's abundance of mice and chipmunks and abundance of acorns 2 y previously. In no case did inclusion of deer or climate variables improve the predictive power of models based on rodents, acorns, or both. We conclude that interannual variation in entomological risk of exposure to Lyme disease is correlated positively with prior abundance of key hosts for the immature stages of the tick vector and with critical food resources for those hosts

Defining the Risk of Zika and Chikungunya Virus Transmission in Human Population Centers of the Eastern United States

The recent spread of mosquito-transmitted viruses and associated disease to the Americas motivates a new, data-driven evaluation of risk in temperate population centers. Temperate regions are generally expected to pose low risk for significant mosquito-borne disease; however, the spread of the Asian tiger mosquito (Aedes albopictus) across densely populated urban areas has established a new landscape of risk. We use a model informed by field data to assess the conditions likely to facilitate local transmission of chikungunya and Zika viruses from an infected traveler to Ae. albopictus and then to other humans in USA cities with variable human densities and seasonality. Mosquito-borne disease occurs when specific combinations of conditions maximize virus-to-mosquito and mosquito-to-human contact rates. We develop a mathematical model that captures the epidemiology and is informed by current data on vector ecology from urban sites. The model demonstrates that under specific but realistic conditions, fifty-percent of introductions by infectious travelers to a high human, high mosquito density city could initiate local transmission and 10% of the introductions could result in 100 or more people infected. Despite the propensity for Ae. albopictus to bite non-human vertebrates, we also demonstrate that local virus transmission and human outbreaks may occur when vectors feed from humans even just 40% of the time. Inclusion of human behavioral changes and mitigations were not incorporated into the models and would likely reduce predicted infections. This work demonstrates how a conditional series of non-average events can result in local arbovirus transmission and outbreaks of human disease, even in temperate cities