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At least 127 records · Page 7Linked to original sources

USGS2011

Modelling the distribution of chickens, ducks, and geese in China

Global concerns over the emergence of zoonotic pandemics emphasize the need for high-resolution population distribution mapping and spatial modelling. Ongoing efforts to model disease risk in China have been hindered by a lack of available species level distribution maps for poultry. The goal of this study was to develop 1 km resolution population density models for China's chickens, ducks, and geese. We used an information theoretic approach to predict poultry densities based on statistical relationships between poultry census data and high-resolution agro-ecological predictor variables. Model predictions were validated by comparing goodness of fit measures (root mean square error and correlation coefficient) for observed and predicted values for 1/4 of the sample data which were not used for model training. Final output included mean and coefficient of variation maps for each species. We tested the quality of models produced using three predictor datasets and 4 regional stratification methods. For predictor variables, a combination of traditional predictors for livestock mapping and land use predictors produced the best goodness of fit scores. Comparison of regional stratifications indicated that for chickens and ducks, a stratification based on livestock production systems produced the best results; for geese, an agro-ecological stratification produced best results. However, for all species, each method of regional stratification produced significantly better goodness of fit scores than the global model. Here we provide descriptive methods, analytical comparisons, and model output for China's first high resolution, species level poultry distribution maps. Output will be made available to the scientific and public community for use in a wide range of applications from epidemiological studies to livestock policy and management initiatives.

Agriculture, Ecosystems and Environment↗

USGS2011

Modelling the distribution of domestic ducks in Monsoon Asia

Domestic ducks are considered to be an important reservoir of highly pathogenic avian influenza (HPAI), as shown by a number of geospatial studies in which they have been identified as a significant risk factor associated with disease presence. Despite their importance in HPAI epidemiology, their large-scale distribution in Monsoon Asia is poorly understood. In this study, we created a spatial database of domestic duck census data in Asia and used it to train statistical distribution models for domestic duck distributions at a spatial resolution of 1 km. The method was based on a modelling framework used by the Food and Agriculture Organisation to produce the Gridded Livestock of the World (GLW) database, and relies on stratified regression models between domestic duck densities and a set of agro-ecological explanatory variables. We evaluated different ways of stratifying the analysis and of combining the prediction to optimize the goodness of fit of the predictions. We found that domestic duck density could be predicted with reasonable accuracy (mean RMSE and correlation coefficient between log-transformed observed and predicted densities being 0.58 and 0.80, respectively), using a stratification based on livestock production systems. We tested the use of artificially degraded data on duck distributions in Thailand and Vietnam as training data, and compared the modelled outputs with the original high-resolution data. This showed, for these two countries at least, that these approaches could be used to accurately disaggregate provincial level (administrative level 1) statistical data to provide high resolution model distributions.

Agriculture, Ecosystems and Environment↗

USGS2024

Vaccination of endangered wildlife as a conservation tool: Hindsights and new horizons in the pandemic era

Vaccines are an established conservation tool that can reduce the threat of infectious disease in endangered wildlife populations. Vaccines exist for many infectious pathogens, and at a time of rapid technological advances in vaccinology, developing vaccines and vaccination programs for free-living endangered wildlife could help efforts to prevent extinctions from disease threats. Vaccination efforts could focus on protecting members of the target species or could be directed at reservoir populations to prevent pathogen spillover. Vaccination strategies need to be substantiated by research on safety and effectiveness, include risk and feasibility assessments, account for differences in host biology and disease epidemiology, and align with relevant regulatory frameworks. Engagement with stakeholders and the public is important to ensure the success of endangered species vaccination programs. Challenges such as funding, regulation, and societal acceptance are barriers to progress in vaccination programs for some species and geographic regions. We recommend the development of scientifically based international guidelines and a transdisciplinary forum with a specific emphasis on endangered wildlife vaccination. New technologies could be used collaboratively to prevent transmission of diseases for which vaccines are not currently available. Careful approaches and enhanced collaborations could help ensure the successful development of wildlife vaccination programs and promote resilience of endangered wildlife populations to increasing anthropogenic and environmental stressors on biodiversity.

Biological Conservation↗

USGS2004

An automated approach to mapping corn from Landsat imagery

Most land cover maps generated from Landsat imagery involve classification of a wide variety of land cover types, whereas some studies may only need spatial information on a single cover type. For example, we required a map of corn in order to estimate exposure to agricultural chemicals for an environmental epidemiology study. Traditional classification techniques, which require the collection and processing of costly ground reference data, were not feasible for our application because of the large number of images to be analyzed. We present a new method that has the potential to automate the classification of corn from Landsat satellite imagery, resulting in a more timely product for applications covering large geographical regions. Our approach uses readily available agricultural areal estimates to enable automation of the classification process resulting in a map identifying land cover as ‘highly likely corn,’ ‘likely corn’ or ‘unlikely corn.’ To demonstrate the feasibility of this approach, we produced a map consisting of the three corn likelihood classes using a Landsat image in south central Nebraska. Overall classification accuracy of the map was 92.2% when compared to ground reference data.

Computers and Electronics in Agriculture↗

USGS2012

Viral fitness: definitions, measurement, and current insights

Viral fitness is an active area of research, with recent work involving an expanded number of human, non-human vertebrate, invertebrate, plant, and bacterial viruses. Many publications deal with RNA viruses associated with major disease emergence events, such as HIV-1, influenza virus, and Dengue virus. Study topics include drug resistance, immune escape, viral emergence, host jumps, mutation effects, quasispecies diversity, and mathematical models of viral fitness. Important recent trends include increasing use of in vivo systems to assess vertebrate virus fitness, and a broadening of research beyond replicative fitness to also investigate transmission fitness and epidemiologic fitness. This is essential for a more integrated understanding of overall viral fitness, with implications for disease management in the future.

Current Opinion in Virology↗

USGS2017

The practice of prediction: What can ecologists learn from applied, ecology-related fields?

The pervasive influence of human induced global environmental change affects biodiversity across the globe, and there is great uncertainty as to how the biosphere will react on short and longer time scales. To adapt to what the future holds and to manage the impacts of global change, scientists need to predict the expected effects with some confidence and communicate these predictions to policy makers. However, recent reviews found that we currently lack a clear understanding of how predictable ecology is, with views seeing it as mostly unpredictable to potentially predictable, at least over short time frames. However, in applied, ecology-related fields predictions are more commonly formulated and reported, as well as evaluated in hindsight, potentially allowing one to define baselines of predictive proficiency in these fields. We searched the literature for representative case studies in these fields and collected information about modeling approaches, target variables of prediction, predictive proficiency achieved, as well as the availability of data to parameterize predictive models. We find that some fields such as epidemiology achieve high predictive proficiency, but even in the more predictive fields proficiency is evaluated in different ways. Both phenomenological and mechanistic approaches are used in most fields, but differences are often small, with no clear superiority of one approach over the other. Data availability is limiting in most fields, with long-term studies being rare and detailed data for parameterizing mechanistic models being in short supply. We suggest that ecologists adopt a more rigorous approach to report and assess predictive proficiency, and embrace the challenges of real world decision making to strengthen the practice of prediction in ecology.

Ecological Complexity↗

USGS2021

Exploring relationships among stream health, human well-being, and demographics in Virginia, USA

Quantification of empirical relationships between ecosystem health and human well-being is uncommon at broad spatial scales. We used public data for Virginia (USA) counties to examine pairwise correlations among two indicators of stream health, thirteen indicators of human well-being, and four demographic metrics. Our indicators of stream health included the Virginia Stream Condition Index (VSCI) and the percentage of stream kilometers with a fish consumption advisory (%FCA); these measures are inversely related. VSCI and %FCA were correlated with some indicators of human health, safety and security, and living standards, as well as with some demographic metrics. VSCI was most strongly correlated (positively) with the percentage of a county’s population self-identifying as White; %FCA was most strongly correlated (positively) with overall mortality rate (number of deaths per 100,000 people). This exploratory study highlights the need for future multidisciplinary, multiscale studies to characterize toxicological, epidemiological, socioeconomic, and political linkages – including causal mechanisms – between ecosystem health and human well-being.

Virginia↗

USGS2006

Assessing vaccination as a control strategy in an ongoing epidemic: Bovine tuberculosis in African buffalo

Bovine tuberculosis (BTB) is an exotic disease invading the buffalo population ( Syncerus caffer ) of the Kruger National Park (KNP), South Africa. We used a sex and age-structured epidemiological model to assess the effectiveness of a vaccination program and define important research directions. The model allows for dispersal between a focal herd and background population and was parameterized with a combination of published data and analyses of over 130 radio-collared buffalo in the central region of the KNP. Radio-tracking data indicated that all sex and age categories move between mixed herds, and males over 8 years old had higher mortality and dispersal rates than any other sex or age category. In part due to the high dispersal rates of buffalo, sensitivity analyses indicate that disease prevalence in the background population accounts for the most variability in the BTB prevalence and quasi-eradication within the focal herd. Vaccination rate and the transmission coefficient were the second and third most important parameters of the sensitivity analyses. Further analyses of the model without dispersal suggest that the amount of vaccination necessary for quasi-eradication (i.e. prevalence < 5%) depends upon the duration that a vaccine grants protection. Vaccination programs are more efficient (i.e. fewer wasted doses) when they focus on younger individuals. However, even with a lifelong vaccine and a closed population, the model suggests that >70% of the calf population would have to be vaccinated every year to reduce the prevalence to less than 1%. If the half-life of the vaccine is less than 5 years, even vaccinating every calf for 50 years may not eradicate BTB. Thus, although vaccination provides a means of controlling BTB prevalence it should be combined with other control measures if eradication is the objective.

Kruger National Park↗

USGS2022

Informing surveillance through the characterization of outbreak potential of chronic wasting disease in white-tailed deer

Understanding the role that an environmental prion reservoir plays in the outbreak dynamics of chronic wasting disease (CWD) in free ranging white-tailed deer ( Odocoileus virginianus ) is critical for the allocation of disease surveillance resources by state and provincial wildlife agencies. We hypothesized that demographic, ecological, and epidemiological configurations naturally attenuate epidemic risk despite the introduction of infectious prions into a susceptible population of deer, but the magnitude of infectious prions in the environmental prion reservoir complicate outbreak expectations. We developed a Susceptible-Latent-Exposed-Infective (SLEI) compartment model to represent the dynamics of CWD epidemics in free-ranging white-tailed deer, then used the basic reproductive ratio ( R 0 "> R0 ) to pinpoint counties under which pathogenic introduction (transport of infectious bodily fluids, tissues, and carcasses through natural or anthropogenic means) naturally produced (or failed to produce) an epidemic. We found that the outlook for an epidemic hinged on transmission rates, the magnitude of environmental contamination, and system type (density-, frequency-, or density/frequency-dependent). CWD can persistently infect individuals living in a contaminated environment even if direct transmission is insufficient to sustain circulation. Theoretical results show that transmission of CWD cannot be exclusively density dependent, and must behave as either a mix between frequency and density dependent, or strictly frequency dependent. While the compartment model is a simplistic representation of reality and did not contain many complicating biological considerations, it was immediately useful in hypothesis generation, motivating the collection of additional data for use in more biologically detailed models, and in the allocation of finite surveillance resources to place emphasis on data collection in areas where an introduction of infectious prions is comparatively more likely to result in an epidemic.

Ecological Modelling↗

USGS2022

Arsenic in private well water and birth outcomes in the United States

Background Prenatal exposure to drinking water with arsenic concentrations >50 μg/L is associated with adverse birth outcomes, with inconclusive evidence for concentrations ≤50 μg/L. In a collaborative effort by public health experts, hydrologists, and geologists, we used published machine learning model estimates to characterize arsenic concentrations in private wells—federally unregulated for drinking water contaminants—and evaluated associations with birth outcomes throughout the conterminous U.S. Methods Using several machine learning models, including boosted regression trees (BRT) and random forest classification (RFC), developed from measured groundwater arsenic concentrations of ∼20,000 private wells, we characterized the probability that arsenic concentrations occurred within specific ranges in groundwater. Probabilistic model estimates and private well usage data were linked by county to all live birth certificates from 2016 (n = 3.6 million). We evaluated associations with gestational age and term birth weight using mixed-effects models, adjusted for potential confounders and incorporated random intercepts for spatial clustering. Results We generally observed inverse associations with term birth weight. For instance, when using BRT estimates, a 10-percentage point increase in the probability that private well arsenic concentrations exceeded 5 μg/L was associated with a −1.83 g (95% CI: −3.30, −0.38) lower term birth weight after adjusting for covariates. Similarly, a 10-percentage point increase in the probability that private well arsenic concentrations exceeded 10 μg/L was associated with a −2.79 g (95% CI: −4.99, −0.58) lower term birth weight. Associations with gestational age were null. Conclusion In this largest epidemiologic study of arsenic and birth outcomes to date, we did not observe associations of modeled arsenic estimates in private wells with gestational age and found modest inverse associations with term birth weight. Study limitations may have obscured true associations, including measurement error stemming from a lack of individual-level information on primary water sources, water arsenic concentrations, and water consumption patterns.

Environment International↗

USGS2026

Drinking water arsenic, urinary arsenic biomarkers, and cognitive impairment in the REGARDS study

Background There are several pathways by which inorganic arsenic (iAs) exposure can affect cognition among adults. Few epidemiologic studies evaluate iAs in water and inter-individual differences in urinary arsenic toxicokinetics. We aimed to estimate the association between individual-level urinary arsenic biomarkers, county-level iAs in drinking water, and cognitive impairment in a cohort of Black and White Americans. Methods We evaluated the association between county-level iAs in water and urinary iAs metabolites with incident cognitive impairment in REasons for Geographic and Racial Differences in Stroke (REGARDS). Participants were linked to county-level concentrations of arsenic in public water (n = 15,516) and county-level probabilities of private well arsenic exceeding 10 μg/L (n = 20,448). In addition, urinary concentrations of iAs, monomethylarsonic acid (MMA) and dimethylarsinic acid (DMA) were measured in a subset of participants (n = 1,013). Cognitive impairment was determined by the Six Item Screener (SIS) and the Enhanced Cognitive Battery (ECB). We used multivariable logistic regression to estimate odds ratios. Results Approximately 9 % of participants in REGARDS developed incident cognitive impairment on the SIS over 10 years of follow-up. County-level public water iAs concentrations and private well iAs probabilities were not associated with increased odds of cognitive impairment. Higher concentrations of MMA (OR: 1.74 [95 % CI: 1.22, 2.49]) and iAs (OR: 1.58 [95 % CI: 1.12, 2.22]) in urine were associated with greater odds of cognitive impairment on the SIS. Results for the ECB were similar. Conclusions iAs exposure may be associated with cognitive impairment. Our findings highlight the importance of considering multiple measures of iAs exposure.

Environmental Research↗

USGS2016

Predicting recreational water quality advisories: A comparison of statistical methods

Epidemiological studies indicate that fecal indicator bacteria (FIB) in beach water are associated with illnesses among people having contact with the water. In order to mitigate public health impacts, many beaches are posted with an advisory when the concentration of FIB exceeds a beach action value. The most commonly used method of measuring FIB concentration takes 18–24 h before returning a result. In order to avoid the 24 h lag, it has become common to ”nowcast” the FIB concentration using statistical regressions on environmental surrogate variables. Most commonly, nowcast models are estimated using ordinary least squares regression, but other regression methods from the statistical and machine learning literature are sometimes used. This study compares 14 regression methods across 7 Wisconsin beaches to identify which consistently produces the most accurate predictions. A random forest model is identified as the most accurate, followed by multiple regression fit using the adaptive LASSO.

Environmental Modelling and Software↗

USGS2008

Biomedical and veterinary science can increase our understanding of coral disease

A balanced approach to coral disease investigation is critical for understanding the global decline of corals. Such an approach should involve the proper use of biomedical concepts, tools, and terminology to address confusion and promote clarity in the coral disease literature. Investigating disease in corals should follow a logical series of steps including identification of disease, systematic morphologic descriptions of lesions at the gross and cellular levels, measurement of health indices, and experiments to understand disease pathogenesis and the complex interactions between host, pathogen, and the environment. This model for disease investigation is widely accepted in the medical, veterinary and invertebrate pathology disciplines. We present standard biomedical rationale behind the detection, description, and naming of diseases and offer examples of the application of Koch's postulates to elucidate the etiology of some infectious diseases. Basic epidemiologic concepts are introduced to help investigators think systematically about the cause(s) of complex diseases. A major goal of disease investigation in corals and other organisms is to gather data that will enable the establishment of standardized case definitions to distinguish among diseases. Concepts and facts amassed from empirical studies over the centuries by medical and veterinary pathologists have standardized disease investigation and are invaluable to coral researchers because of the robust comparisons they enable; examples of these are given throughout this paper. Arguments over whether coral diseases are caused by primary versus opportunistic pathogens reflect the lack of data available to prove or refute such hypotheses and emphasize the need for coral disease investigations that focus on: characterizing the normal microbiota and physiology of the healthy host; defining ecological interactions within the microbial community associated with the host; and investigating host immunity, host-agent interactions, pathology, pathogenesis, and factors that promote the pathogenicity of the causative agent(s) of disease.

Journal of Experimental Marine Biology and Ecology↗

USGS2017

Coupling ecological and social network models to assess “transmission” and “contagion” of an aquatic invasive species

Network analysis is used to address diverse ecological, social, economic, and epidemiological questions, but few efforts have been made to combine these field-specific analyses into interdisciplinary approaches that effectively address how complex systems are interdependent and connected to one another. Identifying and understanding these cross-boundary connections improves natural resource management and promotes proactive, rather than reactive, decisions. This research had two main objectives; first, adapt the framework and approach of infectious disease network modeling so that it may be applied to the socio-ecological problem of spreading aquatic invasive species, and second, use this new coupled model to simulate the spread of the invasive Chinese mystery snail ( Bellamya chinensis ) in a reservoir network in Southeastern Nebraska, USA. The coupled model integrates an existing social network model of how anglers move on the landscape with new reservoir-specific ecological network models. This approach allowed us to identify 1) how angler movement among reservoirs aids in the spread of B . chinensis , 2) how B . chinensis alters energy flows within individual-reservoir food webs, and 3) a new method for assessing the spread of any number of non-native or invasive species within complex, social-ecological systems.

Journal of Environmental Management↗

USGS2021

Genomic comparison of carbapenem-resistant Enterobacteriaceae from humans and gulls in Alaska

Objectives Wildlife may harbor clinically important antimicrobial resistant (AMR) bacteria, but the role of wildlife in the epidemiology of AMR bacterial infections in humans is largely unknown. In this study, we aimed to assess dissemination of the bla KPC carbapenemase gene among humans and gulls in Alaska. Methods We performed whole genome sequencing to determine the genetic context of bla KPC in bacterial isolates from all four human carbapenemase-producing Enterobacteriaceae (CPE) infections reported in Alaska between 2013–2018 and to compare sequences to seven previously reported CPE isolates from gull feces within the same region and time period. Results Genomic analysis of CPE isolates suggested independent acquisition events among humans with no evidence for direct transmission of bla KPC between people and gulls. However, some isolates shared conserved genetic elements surrounding bla KPC , suggesting possible exchange between species. Conclusions Our results highlight the genomic plasticity associated with bla KPC and demonstrate that sampling of wildlife may be useful for identifying clinically relevant antimicrobial resistance not observed through local passive surveillance in humans.

Alaska↗

USGS2023

Environmental antimicrobial resistance gene detection from wild bird habitats using two methods: A commercially available culture-independent qPCR assay and culture of indicator bacteria followed by whole-genome sequencing

Objectives A variety of methods have been developed to detect antimicrobial resistance (AMR) in different environments to better understand the evolution and dissemination of this public health threat. Comparisons of results generated using different AMR detection methods, such as quantitative PCR (qPCR) and whole-genome sequencing (WGS), are often imperfect, and few studies have analysed samples in parallel to evaluate differences. In this study, we compared bacterial culture and WGS to a culture-independent commercially available qPCR assay to evaluate the concordance between methods and the utility of each in answering research questions regarding the presence and epidemiology of AMR in wild bird habitats. Methods We first assessed AMR gene detection using qPCR in 45 bacterial isolates from which we had existing WGS data. We then analysed 52 wild bird faecal samples and 9 spatiotemporally collected water samples using culture-independent qPCR and WGS of phenotypically resistant indicator bacterial isolates. Results Overall concordance was strong between qPCR and WGS of bacterial isolates, although concordance differed among antibiotic classes. Analysis of wild bird faecal and water samples revealed that more samples were determined to be positive for AMR via qPCR than via culture and WGS of bacterial isolates, although qPCR did not detect AMR genes in two samples from which phenotypically resistant isolates were found. Conclusions Both qPCR and culture followed by sequencing may be effective approaches for characterising AMR genes harboured by wild birds, although data streams produced using these different tools may have advantages and disadvantages that should be considered given the application and sample matrix.

Journal of Global Antimicrobial Resistance↗

USGS2014

Beach science in the Great Lakes

Monitoring beach waters for human health has led to an increase and evolution of science in the Great Lakes, which includes microbiology, limnology, hydrology, meteorology, epidemiology, and metagenomics, among others. In recent years, concerns over the accuracy of water quality standards at protecting human health have led to a significant interest in understanding the risk associated with water contact in both freshwater and marine environments. Historically, surface waters have been monitored for fecal indicator bacteria (fecal coliforms, Escherichia coli , enterococci), but shortcomings of the analytical test (lengthy assay) have resulted in a re-focusing of scientific efforts to improve public health protection. Research has led to the discovery of widespread populations of fecal indicator bacteria present in natural habitats such as soils, beach sand, and stranded algae. Microbial source tracking has been used to identify the source of these bacteria and subsequently assess their impact on human health. As a result of many findings, attempts have been made to improve monitoring efficiency and efficacy with the use of empirical predictive models and molecular rapid tests. All along, beach managers have actively incorporated new findings into their monitoring programs. With the abundance of research conducted and information gained over the last 25 years, “Beach Science” has emerged, and the Great Lakes have been a focal point for much of the ground-breaking work. Here, we review the accumulated research on microbiological water quality of Great Lakes beaches and provide a historic context to the collaborative efforts that have advanced this emerging science.

Great Lakes↗

USGS2014

Sapronosis: a distinctive type of infectious agent

Sapronotic disease agents have evolutionary and epidemiological properties unlike other infectious organisms. Their essential saprophagic existence prevents coevolution, and no host–parasite virulence trade-off can evolve. However, the host may evolve defenses. Models of pathogens show that sapronoses, lacking a threshold of transmission, cannot regulate host populations, although they can reduce host abundance and even extirpate their hosts. Immunocompromised hosts are relatively susceptible to sapronoses. Some particularly important sapronoses, such as cholera and anthrax, can sustain an epidemic in a host population. However, these microbes ultimately persist as saprophages. One-third of human infectious disease agents are sapronotic, including nearly all fungal diseases. Recognition that an infectious disease is sapronotic illuminates a need for effective environmental control strategies.

Trends in Parasitology↗