Biology subjects

Greenhalgh, S.

Publications and source records attributed to Greenhalgh, S..

3 recordsLinked to original sources

bioRxiv2025

Temporal effects on the abundance of lethal fungal pathogens of amphibians

Fungal pathogens greatly threaten amphibian diversity, bringing many species near extinction. Consequently, informing on the abundance and ecological characteristics of fungal pathogens, such as Batrachochytrium dendrobatidis (Bd), through tools such as mathematical models is of the utmost importance with respect to current conservation efforts. While traditional mathematical models, such as the logistic growth model, can infer basic details on Bd abundance, the models simplistic nature renders it unable to account for myriad external factors. So, to inform on some of these factors, namely temporal fluctuations in the Bd growth rate, and carrying capacity, we extended the logistic growth model to consider combinations of time-varying coefficients. For our new models, we estimated model parameters from publicly available data on Bd zoospore density across multiple temperature ranges and geographies, assessing the quality of model fit relative to complexity by Akaike Information Criterion, and Akaike weights, in addition to characterizing potential long-term behaviors through stability analysis. Our work shows that our time-varying growth rate and carrying capacity model was at least 1.4 times more likely to reflect Bd abundance at optimal temperature ranges. This suggests a multi-pronged approach for hindering Bd, namely at non-optimal temperatures, conservation efforts such as tadpole removal and water disinfection should be utilized consistently, and at optimal temperatures, they should be timed to when they generate the greatest benefit with respect to the elimination of Bd zoospores.

evolutionary biology↗

bioRxiv2019

Novel compartmental models of infectious disease transmission

For decades, mathematical models of disease transmission have provided researchers and public health officials with critical insights into the progression, control, and prevention of disease spread. Of these models, one of most fundamental is the SIR differential equation model. However, this ubiquitous model has one significant and rarely acknowledged shortcoming: it is unable to account for a diseases true infectious period distribution. As the misspecification of such a biological characteristic is known to significantly affect model behavior, there is a need to develop new modeling approaches that capture such information. Therefore, we illustrate an innovative take on compartmental models, derived from their general formulation as systems of nonlinear Volterra integral equations, to capture a broader range of infectious period distributions, yet maintain the desirable formulation as systems of differential equations. Our work illustrates a compartmental model that captures any Erlang distributed duration of infection with only 3 differential equations, instead of the typical inflated model sizes required by differential equation compartmental models, and a compartmental model that capture any mean, standard deviation, skewness, and kurtosis of an infectious period distribution with merely 4 differential equations. The significance of our work is that it opens up a new class of easy-to-use compartmental models to predict disease outbreaks that does not require a complete overhaul of existing theory, and thus provides a starting point for multiple research avenues of investigation under the contexts of mathematics, public health, and evolutionary biology.

microbiology↗

bioRxiv2018

Managing Marek’s disease in the egg industry

The industrialization of farming has had an enormous impact. To most, this impact is viewed solely in the context of productivity, but the denser living conditions and shorter rearing periods of industrial livestock farms provide pathogens with an ideal opportunity to spread and evolve. For example, the industrialization of poultry farms drove the Mareks disease virus (MDV) to evolve from causing a mild paralytic syndrome to causing a highly contagious, globally prevalent, disease that can have up to a 100% mortality rate. Fortunately, the economic catastrophe that would occur from MDV evolution has been prevented through widespread use of live imperfect vaccines that limit disease symptoms, but fail to prevent transmission. Unfortunately, the continued rollout of such imperfect vaccines is steering the evolution of MDV towards an even greater virulence and an ability to evade vaccine protection. Thus, there is a need to investigate alternative economically viable control measures for their ability to inhibit MDV spread and evolution. In what follows we examine the economic viability of standard husbandry practices for their ability to inhibit the spread of both virulent MDV and very virulent MDV throughout an industrialized egg farm. To do this, we parameterized a dynamic MDV transmission model and calculate the loss in egg production due to disease. We find that the MDV strain as well as the cohort duration had the greatest influence on disease burden and hence egg production. Additionally, we find that the standard husbandry practice involving conventional cages, often referred to as \"battery cages\", results in the least per capita loss in egg production due to MDV infection when compared to alternative enriched or aviary (free-run) systems for virulent MDV, but not very virulent MDV, in which case the Aviary system performs the best. These results highlight an important cost that managers will face when implementing new hen husbandry practices.

epidemiology↗