Independent and interactive effects of disease and methylmercury on demographic rates across multiple amphibian populations.

Disease, alone or combined with other stressors such as habitat loss and contaminants, affects wildlife populations worldwide. However, interactions among stressors and how they affect demography and populations remain poorly understood. The amphibian chytrid fungus (Batrachochytrium dendrobatidis; Bd) is a sometimes-lethal pathogen linked with population declines and extirpations of amphibians globally.

Rethinking statistical approaches for serological data analysis for viral surveillance.

A robust serological surveillance system for zoonotic pathogens is imperative for both early detection and advancing knowledge of emerging diseases. A statistical analysis plan that is aligned to research and epidemiological goals requires a purposeful choice among alternative methods for differentiating seronegative from seropositive samples, estimating seroprevalence, and estimating risk factors associated with seropositivity. The common standard deviation-based cutoff (e.

Gastrointestinal Shedding of Rubulaviruses from Egyptian Rousette Bats: Temporal Dynamics and Spillover Implications.

Bats are recognized as reservoirs for diverse paramyxoviruses, some of which are closely related to known human pathogens or directly implicated in zoonotic transmission. The emergence of the zoonotic Sosuga virus (SOSV) from Egyptian rousette bats (ERBs), which caused an acute febrile illness in a reported human case in Africa, has increased the focus on the zoonotic potential of the subfamily. Previous studies identified human parainfluenza virus 2 (HPIV2)- and mumps (MuV)-related viruses in ERBs from South Africa, with HPIV2-related viruses restricted to gastrointestinal samples, an underexplored target for rubulavirus biosurveillance, suggesting that sample-type bias may have led to their oversight.

Evaluation of an open forecasting challenge to assess skill of West Nile virus neuroinvasive disease prediction.

Background: West Nile virus (WNV) is the leading cause of mosquito-borne illness in the continental USA. WNV occurrence has high spatiotemporal variation, and current approaches to targeted control of the virus are limited, making forecasting a public health priority. However, little research has been done to compare strengths and weaknesses of WNV disease forecasting approaches on the national scale.

Not all mosquitoes are created equal: A synthesis of vector competence experiments reinforces virus associations of Australian mosquitoes.

The globalization of mosquito-borne arboviral diseases has placed more than half of the human population at risk. Understanding arbovirus ecology, including the role individual mosquito species play in virus transmission cycles, is critical for limiting disease. Canonical virus-vector groupings, such as Aedes- or Culex-associated flaviviruses, have historically been defined using virus detection in field-collected mosquitoes, mosquito feeding patterns, and vector competence, which quantifies the intrinsic ability of a mosquito to become infected with and transmit a virus during a subsequent blood feed.

Human-mediated impacts on biodiversity and the consequences for zoonotic disease spillover.

Human-mediated changes to natural ecosystems have consequences for both ecosystem and human health. Historically, efforts to preserve or restore 'biodiversity' can seem to be in opposition to human interests. However, the integration of biodiversity conservation and public health has gained significant traction in recent years, and new efforts to identify solutions that benefit both environmental and human health are ongoing.

The impact of long-term non-pharmaceutical interventions on COVID-19 epidemic dynamics and control: the value and limitations of early models.

Mathematical models of epidemics are important tools for predicting epidemic dynamics and evaluating interventions. Yet, because early models are built on limited information, it is unclear how long they will accurately capture epidemic dynamics. Using a stochastic SEIR model of COVID-19 fitted to reported deaths, we estimated transmission parameters at different time points during the first wave of the epidemic (March-June, 2020) in Santa Clara County, California.

Physiology and ecology combine to determine host and vector importance for Ross River virus.

Identifying the key vector and host species that drive the transmission of zoonotic pathogens is notoriously difficult but critical for disease control. We present a nested approach for quantifying the importance of host and vectors that integrates species' physiological competence with their ecological traits. We apply this framework to a medically important arbovirus, Ross River virus (RRV), in Brisbane, Australia.

Chopping the tail: How preventing superspreading can help to maintain COVID-19 control.

Disease transmission is notoriously heterogeneous, and SARS-CoV-2 is no exception. A skewed distribution where few individuals or events are responsible for the majority of transmission can result in explosive, superspreading events, which produce rapid and volatile epidemic dynamics, especially early or late in epidemics. Anticipating and preventing superspreading events can produce large reductions in overall transmission rates.

Chopping the tail: how preventing superspreading can help to maintain COVID-19 control.

Disease transmission is notoriously heterogeneous, and SARS-CoV-2 is no exception. A skewed distribution where few individuals or events are responsible for the majority of transmission can result in explosive, superspreading events, which produce rapid and volatile epidemic dynamics, especially early or late in epidemics. Anticipating and preventing superspreading events can produce large reductions in overall transmission rates.

The impact of long-term non-pharmaceutical interventions on COVID-19 epidemic dynamics and control.

Non-pharmaceutical interventions to combat COVID-19 transmission have worked to slow the spread of the epidemic but can have high socio-economic costs. It is critical we understand the efficacy of non-pharmaceutical interventions to choose a safe exit strategy. Many current models are not suitable for assessing exit strategies because they do not account for epidemic resurgence when social distancing ends prematurely (e.

Predicting West Nile virus transmission in North American bird communities using phylogenetic mixed effects models and eBird citizen science data.

Background: West Nile virus (WNV) is a mosquito-transmitted disease of birds that has caused bird population declines and can spill over into human populations. Previous research has identified bird species that infect a large fraction of the total pool of infected mosquitoes and correlate with human infection risk; however, these analyses cover small spatial regions and cannot be used to predict transmission in bird communities in which these species are rare or absent. Here we present a mechanistic model for WNV transmission that predicts WNV spread (R) in any bird community in North America by scaling up from the physiological responses of individual birds to transmission at the level of the community.

Anti-predator behavioral variation among Physa acuta in response to temporally fluctuating predation risk by Procambarus.

Research in behavioral ecology routinely quantifies individual variation in behavior using transitions between discrete environments, for example prey moving from a no predator to predator treatment. This research often ignores behavioral variation in response to temporal fluctuations in environmental conditions around an unchanging mean environment. In this study we evaluate the effects of temporal fluctuations in predation risk (predator cue concentration of Procambarus spp.

A practical guide and power analysis for GLMMs: detecting among treatment variation in random effects.

In ecology and evolution generalized linear mixed models (GLMMs) are becoming increasingly used to test for differences in variation by treatment at multiple hierarchical levels. Yet, the specific sampling schemes that optimize the power of an experiment to detect differences in random effects by treatment/group remain unknown. In this paper we develop a blueprint for conducting power analyses for GLMMs focusing on detecting differences in variance by treatment.