Competition, facilitation, and predation offer alternative explanations for successional patterns of migratory herbivores. However, these interactions are difficult to measure, leaving uncertainty about the mechanisms underlying body-size-dependent grazing-and even whether succession occurs at all. We used data from an 8-year camera-trap survey, GPS-collared herbivores, fecal DNA metabarcoding analyze timing, arrival order, among grazers in Serengeti National Park. Temporal grazing is...

Abstract An important challenge to addressing the opioid overdose crisis is lack of information on size population people who misuse opioids (PWMO) in local areas. This estimate needed for better resource allocation, estimation treatment and outcome rates using appropriate denominators (ie, at risk), proper evaluation intervention effects. In this study, we used a bayesian hierarchical spatiotemporal integrated abundance model that integrates multiple types county-level surveillance data,...

Missing data is a common challenge when analyzing epidemiological data, and imputation often used to address this issue. Here, we investigate the scenario where covariate in an analysis has missingness will be imputed. There are recommendations include outcome from model for missing covariates, but it not necessarily clear if recommendation always holds why sometimes true. We examine deterministic (i.e. single with fixed values) stochastic or multiple random methods their implications...

Background: The overdose epidemic remains largely driven by opioids, but county-level prevalence of opioid misuse is unknown. Without this information, public health and policy responses are limited a lack knowledge on the scope problem. Methods: Using an integrated abundance model, we estimate annual for counties in North Carolina from 2016 to 2021. model integrates observed counts illicit deaths, people receiving prescriptions buprenorphine, served treatment programs. It also incorporates...

ABSTRACT Healthy foods are essential for a healthy life, but accessing food can be more challenging some people than others. This disparity in access may lead to disparities well‐being, potentially with disproportionate rates of diseases communities that face challenges (i.e., low‐access communities). Identifying low‐access, high‐risk targeted interventions is public health priority, current methods quantify rely on distance measures either computationally simple (like the length shortest...

Opioid misuse is a national epidemic and significant drug related threat to the United States. While scale of problem undeniable, estimates local prevalence opioid are lacking, despite their importance policy-making resource allocation. This due, in part, challenge directly measuring at level. In this paper, we develop Bayesian hierarchical spatio-temporal abundance model that integrates indirect county-level data on opioid-related outcomes with state-level survey estimate latent counts...

Objectives. To examine the state-level history of US overdose deaths involving stimulants with and without opioids from 1999 to 2020. Methods. We used death certificate data National Center for Health Statistics categorize into 4 groups interest: cocaine opioids, psychostimulants opioids. a Bayesian multiple change point model describe timing magnitude changes in rates each state year. Results. There was little Death sharply increased around 2015, particularly Northeast Mid-Atlantic. also...

Abstract Background Over the past decade in USA, increases overdose rates of cocaine and psychostimulants with opioids were highest among Black, compared to White, populations. Whether fentanyl has contributed rise psychostimulant overdoses Ohio is unknown. We sought measure impact on death by race Ohio. Methods conducted time series spatiotemporal analyses using data from Public Health Information Warehouse. Primary outcomes state- county-level 2010 2020 for Black White Measures interest...

Background: In the United States, true geographic distribution of environmental fungus Histoplasma capsulatum remains poorly understood but appears to have changed since it was first characterized. Histoplasmosis is caused by inhalation and can range in severity from asymptomatic life threatening. Due limited public health surveillance under detection infections, challenging directly use reported case data characterize spatial risk. Methods: Using monthly yearly county-level various...

Background: The opioid epidemic continues to be an ongoing public health crisis in the United States. Initially, large increases overdose death rates were observed largely rural, White communities, leading initial perception that was primarily a problem for population. Recent findings have shown increasing of among Blacks. We compare between Blacks and Whites explore county-level spatiotemporal heterogeneity Ohio. Methods: obtained counts from 2007 2018 fit Bayesian multivariate spatial...

Abstract Occupancy models are widely used in camera trap studies to analyze species presence, abundance, and geographic distribution, among other important ecological quantities. These account for imperfect detection using a latent variable distinguish between true presence/absence observed of species. Under certain experimental setups, parameter estimation framework can be challenging. Several have issued guidelines on the number independent replicated observations (surveys) needed each...

Spatio-temporal occupancy models are used to model the presence or absence of a species at particular locations and times, while accounting for dependence in both space time. Multivariate extensions can be simultaneously multiple species, which introduces another dimension structure data. In this paper we introduce multiocc, an `R` package fitting multivariate spatio-temporal models. We demonstrate use multi-species data on six birds from Swiss MHB Breeding Bird Survey.

We examined a natural history of opioid overdose deaths from 1999-2021 in the United States to describe state-level spatio-temporal heterogeneity waves epidemic. obtained death counts by state 1999-2021, categorized as involving prescription opioids, heroin, synthetic or unspecified drugs. developed Bayesian multivariate multiple change point model flexibly estimate timing and magnitude state-specific changes rates each drug type. found substantial variability around severity wave across...

Abstract We present a multivariate occupancy model to simultaneously the presence/absence of multiple species, and demonstrate its use with goal estimating parameters related occupancy. The proposed accounts for both spatial temporal dependence within each as well across all species. These dependencies are addressed through random effects, defined so there is no confounding covariate effects. Data augmentation specific choices effects permit Gibbs updates in Markov chain Monte Carlo...

Opioid misuse is a major public health issue in the United States and particular state of Ohio. However, burden epidemic challenging to quantify as surveillance measures capture different aspects problem. Here, we synthesize county-level death treatment counts compare relative across counties assess associations with social environmental covariates.We construct generalized spatial factor model jointly rates for each county. For outcome, specify parameterization Poisson regression spatially...

Ohio is one of the states most impacted by opioid epidemic and experienced second highest age-adjusted fatal drug overdose rate in 2017. Initially it was believed prescription opioids were driving crisis Ohio. However, as evolved, deaths due to fentanyl have drastically increased. In this work we develop a Bayesian multivariate spatiotemporal model for county death rates from 2007 2018 different types opioids. The log-odds are assumed follow spatially varying change point regression model....

Abstract Quantifying the opioid epidemic at local level is a challenging problem that has important consequences on resource allocation. Adults and adolescents may exhibit different spatial trends require interventions resources so it to examine for each age group. In Ohio, surveillance data are collected county group measurable outcomes of epidemic, overdose deaths, treatment admissions. However, our interest lies in quantifying unmeasurable construct, representing burden which drives rates...

Abstract We present a novel data set for drought in the continental US (CONUS) built to enable computationally efficient spatio-temporal statistical and probabilistic models of drought. converted obtained from widely-used Drought Monitor (USDM) its native geo-referenced polygon format 0.5 degree regular grid. merged known environmental drivers drought, including those North American Land Data Assimilation System (NLDAS-2), Geological Survey (USGS) streamflow data, National Oceanic...

Healthy foods are essential for a healthy life, but accessing food can be more challenging some people than others. This disparity in access may lead to disparities well-being, potentially with disproportionate rates of diseases communities that face challenges (i.e., low-access communities). Identifying low-access, high-risk targeted interventions is public health priority, current methods quantify rely on distance measures either computationally simple (like the length shortest...

Abstract The US Drought Monitor is the leading drought monitoring tool in United States. Updated weekly and freely distributed, it records conditions as geo-referenced polygons showing one of six ordered levels. These levels are determined by a mixture quantitative environmental measurements local expert opinion across entire At present, forecasts only convey expected direction development (i.e. worsen, persist, subside) do not communicate any uncertainty. This limits utility forecasts. In...

Coccidioidomycosis, or Valley fever, is an infectious disease caused by inhaling Coccidioides fungal spores. Incidence has risen in recent years, and it believed the endemic region for expanding response to climate change. While fever case data can help us understand trends risk, using as a proxy endemicity not ideal because suffers from imperfect detection, including false positives (e.g., travel-related cases reported outside of area) negatives misdiagnosis underreporting). We proposed...