An inaugural forum on epidemiological modeling for public health stakeholders in Arizona.

Epidemiological models-which help us understand and forecast the spread of infectious disease-can be valuable tools for public health. However, barriers exist that can make it difficult to employ epidemiological models routinely within the repertoire of public health planning. These barriers include technical challenges associated with constructing the models, challenges in obtaining appropriate data for model parameterization, and problems with clear communication of modeling outputs and uncertainty.

Understanding the exposure risk of aerosolized Coccidioides in a Valley fever endemic metropolis.

Coccidioides is the fungal causative agent of Valley fever, a primarily pulmonary disease caused by inhalation of fungal arthroconidia, or spores. Although Coccidioides has been an established pathogen for 120 years and is responsible for hundreds of thousands of infections per year, little is known about when and where infectious Coccidioides arthroconidia are present within the ambient air in endemic regions. Long-term air sampling programs provide a means to investigate these characteristics across space and time.

A sliding window approach to optimize the time-varying parameters of a spatially-explicit and stochastic model of COVID-19.

The implementation of non-pharmaceutical public health interventions can have simultaneous impacts on pathogen transmission rates as well as host mobility rates. For instance, with SARS-CoV-2, masking can influence host-to-host transmission, while stay-at-home orders can influence mobility. Importantly, variations in transmission rates and mobility patterns can influence pathogen-induced hospitalization rates.

SPARSEMODr: Rapidly simulate spatially explicit and stochastic models of COVID-19 and other infectious diseases.

Building realistically complex models of infectious disease transmission that are relevant for informing public health is conceptually challenging and requires knowledge of coding architecture that can implement key modeling conventions. For example, many of the models built to understand COVID-19 dynamics have included stochasticity, transmission dynamics that change throughout the epidemic due to changes in host behavior or public health interventions, and spatial structures that account for important spatio-temporal heterogeneities. Here we introduce an R package, SPARSEMODr, that allows users to simulate disease models that are stochastic and spatially explicit, including a model for COVID-19 that was useful in the early phases of the epidemic.

Quantifying mechanisms of coexistence in disease ecology.

Pathogen coexistence depends on ecological processes operating at both within and between-host scales, making it difficult to quantify which processes may promote or prevent coexistence. Here, we propose that adapting modern coexistence theory-traditionally applied in plant communities-to pathogen systems provides an exciting approach for examining mechanisms of coexistence operating across different spatial scales. We first overview modern coexistence theory and its mechanistic decomposition; we subsequently adapt the framework to quantify how spatial variation in pathogen density, host resources and immunity, and their interaction may promote pathogen coexistence.

PM10 and Other Climatic Variables Are Important Predictors of Seasonal Variability of Coccidioidomycosis in Arizona.

Coccidioidomycosis (Valley fever) is a disease caused by the fungal pathogens Coccidioides immitis and Coccidioides posadasii that are endemic to the southwestern United States and parts of Mexico and South America. Throughout the range where the pathogens are endemic, there are seasonal patterns of infection rates that are associated with certain climatic variables. Previous studies that looked at annual and monthly relationships of coccidioidomycosis and climate suggest that infection numbers are linked with precipitation and temperature fluctuations; however, these analytic methods may miss important nonlinear, nonmonotonic seasonal relationships between the response (Valley fever cases) and explanatory variables (climate) influencing disease outbreaks.

Can Eco-Evo Theory Explain Population Cycles in the Field?

AbstractEfforts to explain animal population cycles often invoke consumer-resource theory, which has shown that consumer-resource interactions alone can drive population cycles. Eco-evo theory instead argues that population cycles are partly driven by fluctuating selection for resistance in the resource, but support for eco-evo theory has come almost entirely from laboratory microcosms. Here we ask, Can eco-evo theory explain population cycles in the field? We compared the ability of eco-evo models and classical "eco-only" models to explain data on cycles in the insect , in which outbreaks of the insect are terminated by a fatal baculovirus.

Leptospira in river and soil in a highly endemic area of Ecuador.

Background: Leptospira are shed into the environment via urine of infected animals. Rivers are thought to be an important risk factor for transmission to humans, though much is unknown about the types of environment or characteristics that favor survival. To address this, we screened for Leptospira DNA in two rivers in rural Ecuador where Leptospirosis is endemic.

Predicting the current and future distribution of the western black-legged tick, Ixodes pacificus, across the Western US using citizen science collections.

In the twenty-first century, ticks and tick-borne diseases have expanded their ranges and impact across the US. With this spread, it has become vital to monitor vector and disease distributions, as these shifts have public health implications. Typically, tick-borne disease surveillance (e.

Use of a mechanistic growth model in evaluating post-restoration habitat quality for juvenile salmonids.

Individual growth data are useful in assessing relative habitat quality, but this approach is less common when evaluating the efficacy of habitat restoration. Furthermore, available models describing growth are infrequently combined with computational approaches capable of handling large data sets. We apply a mechanistic model to evaluate whether selection of restored habitat can affect individual growth.

An Empirical Test of the Role of Small-Scale Transmission in Large-Scale Disease Dynamics.

A key assumption of epidemiological models is that population-scale disease spread is driven by close contact between hosts and pathogens. At larger scales, however, mechanisms such as spatial structure in host and pathogen populations and environmental heterogeneity could alter disease spread. The assumption that small-scale transmission mechanisms are sufficient to explain large-scale infection rates, however, is rarely tested.

Metacommunity theory for transmission of heritable symbionts within insect communities.

Microbial organisms are ubiquitous in nature and often form communities closely associated with their host, referred to as the microbiome. The microbiome has strong influence on species interactions, but microbiome studies rarely take interactions between hosts into account, and network interaction studies rarely consider microbiomes. Here, we propose to use metacommunity theory as a framework to unify research on microbiomes and host communities by considering host insects and their microbes as discretely defined "communities of communities" linked by dispersal (transmission) through biotic interactions.

Fungal infection alters the selection, dispersal and drift processes structuring the amphibian skin microbiome.

Symbiotic microbial communities are important for host health, but the processes shaping these communities are poorly understood. Understanding how community assembly processes jointly affect microbial community composition is limited because inflexible community models rely on rejecting dispersal and drift before considering selection. We developed a flexible community assembly model based on neutral theory to ask: How do dispersal, drift and selection concurrently affect the microbiome across environmental gradients? We applied this approach to examine how a fungal pathogen affected the assembly processes structuring the amphibian skin microbiome.

Do New World pitvipers "scale-down" at high elevations? Macroecological patterns of scale characters and body size.

Bergmann's rule describes the macroecological pattern of increasing body size in response to higher latitudes and elevations. This pattern is extensively documented in endothermic vertebrates, within and among species; however, studies involving ectotherms are less common and suggest no consistent pattern for amphibians and reptiles. Moreover, adaptive traits, such as epidermal features like scales, have not been widely examined in conjunction with Bergmann's rule, even though these traits affect physiological processes, such as thermoregulation, which are hypothesized as underlying mechanisms for the pattern.

Untangling the dynamics of persistence and colonization in microbial communities.

A central goal of community ecology is to infer biotic interactions from observed distributions of co-occurring species. Evidence for biotic interactions, however, can be obscured by shared environmental requirements, posing a challenge for statistical inference. Here, we introduce a dynamic statistical model, based on probit regression, that quantifies the effects of spatial and temporal covariance in longitudinal co-occurrence data.

Evaluating the Within-Host Dynamics of Infection with Mechanistic Disease Models and Experimental Data.

Mechanistic models are critical for our understanding of both within-host dynamics (i.e., pathogen replication and immune system processes) and among-host dynamics (i.

Co-exposure to multiple ranavirus types enhances viral infectivity and replication in a larval amphibian system.

Multiple pathogens commonly co-occur in animal populations, yet few studies demonstrate how co-exposure of individual hosts scales up to affect transmission. Although viruses in the genus Ranavirus are globally widespread, and multiple virus species or strains likely co-occur in nature, no studies have examined how co-exposure affects infection dynamics in larval amphibians. We exposed individual northern red-legged frog Rana aurora larvae to 2 species of ranavirus, namely Ambystoma tigrinum virus (ATV), frog virus 3 (FV3), or an FV3-like strain isolated from a frog-culturing facility in Georgia, USA (RCV-Z2).

Parasite metacommunities: Evaluating the roles of host community composition and environmental gradients in structuring symbiont communities within amphibians.

Ecologists increasingly report the structures of metacommunities for free-living species, yet far less is known about the composition of symbiont communities through space and time. Understanding the drivers of symbiont community patterns has implications ranging from emerging infectious disease to managing host microbiomes. Using symbiont communities from amphibian hosts sampled from wetlands of California, USA, we quantified the effects of spatial structure, habitat filtering and host community components on symbiont occupancy and overall metacommunity structure.

Using multispecies occupancy models to improve the characterization and understanding of metacommunity structure.

Two of the most prominent frameworks to develop in ecology over the past decade are metacommunity ecology, which seeks to characterize multispecies distributions across space, and occupancy modeling, which corrects for imperfect detection in an effort to better understand species occurrence patterns. Although their goals are complementary, metacommunity theory and statistical occupancy modeling methods have developed independently. For instance, the elements of metacommunity structure (EMS) framework uses species occurrence data to classify metacommunity structure and link it to underlying environmental gradients.

The scaling of host density with richness affects the direction, shape, and detectability of diversity-disease relationships.

Pathogen transmission responds differently to host richness and abundance, two unique components of host diversity. However, the heated debate around whether biodiversity generally increases or decreases disease has not considered the relationships between host richness and abundance that may exist in natural systems. Here we use a multi-species model to study how the scaling of total host community abundance with species richness mediates diversity-disease relationships.

Does life history mediate changing disease risk when communities disassemble?

Biodiversity loss sometimes increases disease risk or parasite transmission in humans, wildlife and plants. Some have suggested that this pattern can emerge when host species that persist throughout community disassembly show high host competence - the ability to acquire and transmit infections. Here, we briefly assess the current empirical evidence for covariance between host competence and extirpation risk, and evaluate the consequences for disease dynamics in host communities undergoing disassembly.

Taming wildlife disease: bridging the gap between science and management.

Parasites and pathogens of wildlife can threaten biodiversity, infect humans and domestic animals, and cause significant economic losses, providing incentives to manage wildlife diseases. Recent insights from disease ecology have helped transform our understanding of infectious disease dynamics and yielded new strategies to better manage wildlife diseases. Simultaneously, wildlife disease management (WDM) presents opportunities for large-scale empirical tests of disease ecology theory in diverse natural systems.

Widespread co-occurrence of virulent pathogens within California amphibian communities.

The chytrid fungus Batrachochytrium dendrobatidis, ranaviruses, and trematodes (Ribeiroia ondatrae and echinostomes) are highly virulent pathogens known to infect amphibians, yet the extent to which they co-occur within amphibian communities remains poorly understood. Using field surveillance of 85 wetlands in the East Bay region of California, USA, we found that 68% of wetlands had ≥2 pathogens and 36% had ≥3 pathogens. Wetlands with high pathogen species richness also tended to cluster spatially.

Effects of an invasive plant transcend ecosystem boundaries through a dragonfly-mediated trophic pathway.

Trophic interactions can strongly influence the structure and function of terrestrial and aquatic communities through top-down and bottom-up processes. Species with life stages in both terrestrial and aquatic systems may be particularly likely to link the effects of trophic interactions across ecosystem boundaries. Using experimental wetlands planted with purple loosestrife (Lythrum salicaria), we tested the degree to which the bottom-up effects of floral density of this invasive plant could trigger a chain of interactions, changing the behavior of terrestrial flying insect prey and predators and ultimately cascading through top-down interactions to alter lower trophic levels in the aquatic community.

Linking metacommunity theory and symbiont evolutionary ecology.

Processes that occur both within and between hosts can influence the ecological and evolutionary dynamics of symbionts, a broad term that includes parasitic and disease-causing organisms. Metacommunity theory can integrate these local- and regional-scale dynamics to explore symbiont community composition patterns across space. In this article I emphasize that symbionts should be incorporated into the metacommunity concept.