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"Humphreys, John M."
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Epidemiology and economics of foot-and-mouth disease: current understanding and knowledge gaps
Foot-and-mouth disease virus (FMDV) is one of the few veterinary pathogens that defines policy and global trade in animal products. Its prominence necessitates approaches to control that integrate the multiple factors contributing to the disease’s biology and transmission characteristics. Central to this concept is the epidemiological FMD status (endemic or FMD-free, with or without vaccination) of a territory, which defines access to export markets. FMD epidemiology is complex, insufficiently understood, and intertwined with the biology of the virus (multiple serotypes and subtypes), global distribution (distinct regional virus pools), pathogenesis (subclinical infections and species differences), and host range (broad range of susceptible domestic and wild animals). Despite steady advances, critical knowledge gaps persist in FMD epidemiology that undermine the optimal control of FMD. This review summarizes the distinct thematic compartments of FMD epidemiology and presents the critical knowledge gaps that continue to limit the effectiveness of global, regional, and national initiatives to control and eradicate FMD.
Journal Article
Water and chloride as allosteric inhibitors in WNK kinase osmosensing
Osmotic stress and chloride regulate the autophosphorylation and activity of the WNK1 and WNK3 kinase domains. The kinase domain of unphosphorylated WNK1 (uWNK1) is an asymmetric dimer possessing water molecules conserved in multiple uWNK1 crystal structures. Conserved waters are present in two networks, referred to here as conserved water networks 1 and 2 (CWN1 and CWN2). Here, we show that PEG400 applied to crystals of dimeric uWNK1 induces de-dimerization. Both the WNK1 the water networks and the chloride-binding site are disrupted by PEG400. CWN1 is surrounded by a cluster of pan-WNK-conserved charged residues. Here, we mutagenized these charges in WNK3, a highly active WNK isoform kinase domain, and WNK1, the isoform best studied crystallographically. Mutation of E314 in the Activation Loop of WNK3 (WNK3/E314Q and WNK3/E314A, and the homologous WNK1/E388A) enhanced the rate of autophosphorylation, and reduced chloride sensitivity. Other WNK3 mutants reduced the rate of autophosphorylation activity coupled with greater chloride sensitivity than wild-type. The water and chloride regulation thus appear linked. The lower activity of some mutants may reflect effects on catalysis. Crystallography showed that activating mutants introduced conformational changes in similar parts of the structure to those induced by PEG400. WNK activating mutations and crystallography support a role for CWN1 in WNK inhibition consistent with water functioning as an allosteric ligand.
Journal Article
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. We used forecasts submitted to the 2020 WNV Forecasting Challenge, an open challenge organized by the Centers for Disease Control and Prevention, to assess the status of WNV neuroinvasive disease (WNND) prediction and identify avenues for improvement.
Methods
We performed a multi-model comparative assessment of probabilistic forecasts submitted by 15 teams for annual WNND cases in US counties for 2020 and assessed forecast accuracy, calibration, and discriminatory power. In the evaluation, we included forecasts produced by comparison models of varying complexity as benchmarks of forecast performance. We also used regression analysis to identify modeling approaches and contextual factors that were associated with forecast skill.
Results
Simple models based on historical WNND cases generally scored better than more complex models and combined higher discriminatory power with better calibration of uncertainty. Forecast skill improved across updated forecast submissions submitted during the 2020 season. Among models using additional data, inclusion of climate or human demographic data was associated with higher skill, while inclusion of mosquito or land use data was associated with lower skill. We also identified population size, extreme minimum winter temperature, and interannual variation in WNND cases as county-level characteristics associated with variation in forecast skill.
Conclusions
Historical WNND cases were strong predictors of future cases with minimal increase in skill achieved by models that included other factors. Although opportunities might exist to specifically improve predictions for areas with large populations and low or high winter temperatures, areas with high case-count variability are intrinsically more difficult to predict. Also, the prediction of outbreaks, which are outliers relative to typical case numbers, remains difficult. Further improvements to prediction could be obtained with improved calibration of forecast uncertainty and access to real-time data streams (e.g. current weather and preliminary human cases).
Graphical Abstract
Journal Article
Predicting the Landscape Epidemiology of Foot-and-Mouth Disease in Endemic Regions: An Interpretable Machine Learning Approach
Foot-and-mouth disease (FMD) remains a devastating threat to livestock health and food security in the Middle East and North Africa (MENA), where complex interactions among host, environmental, and anthropogenic factors constitute an optimal endemic landscape for virus circulation. Here, we applied an interpretable machine learning (ML) statistical framework to model the epidemiological landscape of FMD between 2005 and 2025. Furthermore, we compared the ecological niche of serotypes O and A in the MENA region. Our ML algorithms demonstrated high predictive performance (accuracies > 85%) in identifying the geographical extent of high-risk areas, including under-reported regions such as the Southern and Northeastern Arabian Peninsula. Sheep density emerged as the dominant predictor for all FMD outbreaks and serotype O, with significant non-linear relationships with wind, temperature, and human population density. In contrast, serotype A risk was primarily influenced by buffalo density and proximity to roads and cropland. Our in-depth interaction and Shapley value analyses provided fine-scale interpretability by interrogating the threshold effects of each feature in shaping the spatial risk of FMD. Further implementation of our analytical pipeline to guide risk-based surveillance programs and intervention efforts will help reduce the economic and public health impacts of this devastating animal pathogen.
Journal Article
Habitat and climatic associations of climate‐sensitive species along a southern range boundary
Climate change and habitat loss are recognized as important drivers of shifts in wildlife species' geographic distributions. While often considered independently, there is considerable overlap between these drivers, and understanding how they contribute to range shifts can predict future species assemblages and inform effective management. Our objective was to evaluate the impacts of habitat, climatic, and anthropogenic effects on the distributions of climate‐sensitive vertebrates along a southern range boundary in Northern Michigan, USA. We combined multiple sources of occurrence data, including harvest and citizen‐science data, then used hierarchical Bayesian spatial models to determine habitat and climatic associations for four climate‐sensitive vertebrate species (American marten [Martes americana], snowshoe hare [Lepus americanus], ruffed grouse [Bonasa umbellus] and moose [Alces alces]). We used total basal area of at‐risk forest types to represent habitat, and temperature and winter habitat indices to represent climate. Marten associated with upland spruce‐fir and lowland riparian forest types, hares with lowland conifer and aspen‐birch, grouse with lowland riparian hardwoods, and moose with upland spruce‐fir. Species differed in climatic drivers with hares positively associated with cooler annual temperatures, moose with cooler summer temperatures and grouse with colder winter temperatures. Contrary to expectations, temperature variables outperformed winter habitat indices. Model performance varied greatly among species, as did predicted distributions along the southern edge of the Northwoods region. As multiple species were associated with lowland riparian and upland spruce‐fir habitats, these results provide potential for efficient prioritization of habitat management. Both direct and indirect effects from climate change are likely to impact the distribution of climate‐sensitive species in the future and the use of multiple data types and sources in the modelling of species distributions can result in more accurate predictions resulting in improved management at policy‐relevant scales. Climate and habitat are important drivers of species' distributions. We used a variety of data sources to fit Bayesian hierarchical models and determine associations between habitat, climatic and anthropogenic conditions for four climate‐sensitive species' in Northern Michigan and predict contemporary distributions. Species were associated with multiple climate‐sensitive habitat classes, while temperature itself was a stronger predictor than more mechanistic variables of snow cover.
Journal Article
Incubation phase transmission of foot-and-mouth disease virus in cattle: experimental evidence and simulated impacts
The capacity of any pathogen to transmit from infected hosts prior to the development of clinical disease substantially impacts the ability to effectively control an outbreak. Foot-and-mouth disease virus (FMDV) is known for its rapid spread and ability to cause severe disease outbreaks amongst susceptible livestock species. In this current investigation, it was demonstrated that cattle infected with FMDV were capable of transmitting infection at least 24 h prior to the development of clinical signs. Additionally, the progression of infection in cattle exposed to infected donors during the early infectious phase was slower than in cattle exposed at later time points, suggesting a dose-dependent effect on infection dynamics in contact-exposed cattle. To quantify the impact, outcomes from the transmission experiment were used to parameterize agent-based simulations at three biological levels, within-host, within-herd, and between-farm. Simulations revealed that outbreaks spread more rapidly and infect more cattle and farms when models account for preclinical transmission. Specifically, including pre-clinical transmission in a between-farm simulation resulted in a 33.7% increase in the number of affected farms, demonstrating that incubation phase infectiousness has important implications for outbreak preparedness and response.
Journal Article
Vector Surveillance, Host Species Richness, and Demographic Factors as West Nile Disease Risk Indicators
West Nile virus (WNV) is the most common arthropod-borne virus (arbovirus) in the United States (US) and is the leading cause of viral encephalitis in the country. The virus has affected tens of thousands of US persons total since its 1999 North America introduction, with thousands of new infections reported annually. Approximately 1% of humans infected with WNV acquire neuroinvasive West Nile Disease (WND) with severe encephalitis and risk of death. Research describing WNV ecology is needed to improve public health surveillance, monitoring, and risk assessment. We applied Bayesian joint-spatiotemporal modeling to assess the association of vector surveillance data, host species richness, and a variety of other environmental and socioeconomic disease risk factors with neuroinvasive WND throughout the conterminous US. Our research revealed that an aging human population was the strongest disease indicator, but climatic and vector-host biotic interactions were also significant in determining risk of neuroinvasive WND. Our analysis also identified a geographic region of disproportionately high neuroinvasive WND disease risk that parallels the Continental Divide, and extends southward from the US–Canada border in the states of Montana, North Dakota, and Wisconsin to the US–Mexico border in western Texas. Our results aid in unraveling complex WNV ecology and can be applied to prioritize disease surveillance locations and risk assessment.
Journal Article
Interrogating Genomes and Geography to Unravel Multiyear Vesicular Stomatitis Epizootics
We conducted an integrative analysis to elucidate the spatial epidemiological patterns of the Vesicular Stomatitis New Jersey virus (VSNJV) during the 2014–15 epizootic cycle in the United States (US). Using georeferenced VSNJV genomics data, confirmed vesicular stomatitis (VS) disease cases from surveillance, and a suite of environmental factors, our study assessed environmental and phylogenetic similarity to compare VS cases reported in 2014 and 2015. Despite uncertainties from incomplete virus sampling and cross-scale spatial processes, patterns suggested multiple independent re-invasion events concurrent with potential viral overwintering between sequential seasons. Our findings pointed to a geographically defined southern virus pool at the US–Mexico interface as the source of VSNJV invasions and overwintering sites. Phylodynamic analysis demonstrated an increase in virus diversity before a rise in case numbers and a pronounced reduction in virus diversity during the winter season, indicative of a genetic bottleneck and a significant narrowing of virus variation between the summer outbreak seasons. Environment–vector interactions underscored the central role of meta-population dynamics in driving disease spread. These insights emphasize the necessity for location- and time-specific management practices, including rapid response, movement restrictions, vector control, and other targeted interventions.
Journal Article
Epidemiologic consequences of preclinical transmission of foot-and-mouth disease virus in cattle
Foot-and-mouth disease virus (FMDV) can be transmitted during the incubation phase, before clinical detection, but the epidemiological consequences of this preclinical infectious period have not been fully assessed in cattle. Using experimental data derived from transmission studies performed in vivo , we parameterized a state-transition model and simulated FMDV outbreaks across three U.S. regions under varying durations of preclinical infectiousness. We evaluated multiple epidemiologic outcomes under both optimal (1 day after clinical onset) and suboptimal (4 days after clinical onset) detection scenarios. The modeled output demonstrated that even a single day of preclinical transmission significantly increased outbreak magnitude, spatial extent, and duration. These effects were magnified under suboptimal detection and when simulating low-virulence virus strains with prolonged preclinical phases. Optimal response consistently reduced outbreak severity, with greater mitigation observed in the Eastern and Central U.S. as the preclinical phase lengthened. Our findings demonstrate that omission of preclinical transmission from FMD models results in systematic underestimation of outbreak impacts. Incorporating incubation phase transmission is essential for realistic epidemic forecasting, effective preparedness planning, and region-specific response prioritization.
Journal Article