| 11. |
- Gilbertson, Kendra, et al.
(författare)
-
The Importance of Livestock Demography and Infrastructure in Driving Foot and Mouth Disease Dynamics
- 2022
-
Ingår i: Life. - : MDPI. - 2075-1729. ; 12:10
-
Tidskriftsartikel (refereegranskat)abstract
- Transboundary animal diseases, such as foot and mouth disease (FMD) pose a significant and ongoing threat to global food security. Such diseases can produce large, spatially complex outbreaks. Mathematical models are often used to understand the spatio-temporal dynamics and create response plans for possible disease introductions. Model assumptions regarding transmission behavior of premises and movement patterns of livestock directly impact our understanding of the ecological drivers of outbreaks and how to best control them. Here, we investigate the impact that these assumptions have on model predictions of FMD outbreaks in the U.S. using models of livestock shipment networks and disease spread. We explore the impact of changing assumptions about premises transmission behavior, both by including within-herd dynamics, and by accounting for premises type and increasing the accuracy of shipment predictions. We find that the impact these assumptions have on outbreak predictions is less than the impact of the underlying livestock demography, but that they are important for investigating some response objectives, such as the impact on trade. These results suggest that demography is a key ecological driver of outbreaks and is critical for making robust predictions but that understanding management objectives is also important when making choices about model assumptions.
|
|
| 12. |
- Gorsich, Erin E., et al.
(författare)
-
Model-guided suggestions for targeted surveillance based on cattle shipments in the US
- 2018
-
Ingår i: Preventive Veterinary Medicine. - : ELSEVIER SCIENCE BV. - 0167-5877 .- 1873-1716. ; 150, s. 52-59
-
Tidskriftsartikel (refereegranskat)abstract
- Risk-based sampling is an essential component of livestock health surveillance because it targets resources towards sub-populations with a higher risk of infection. Risk-based surveillance in U.S. livestock is limited because the locations of high-risk herds are often unknown and data to identify high-risk herds based on shipments are often unavailable. In this study, we use a novel, data-driven network model for the shipments of cattle in the U.S. (the U.S. Animal Movement Model, USAMM) to provide surveillance suggestions for cattle imported into the U.S. from Mexico. We describe the volume and locations where cattle are imported and analyze their predicted shipment patterns to identify counties that are most likely to receive shipments of imported cattle. Our results suggest that most imported cattle are sent to relatively few counties. Surveillance at 10 counties is predicted to sample 22-34% of imported cattle while surveillance at 50 counties is predicted to sample 43%-61% of imported cattle. These findings are based on the assumption that USAMM accurately describes the shipments of imported cattle because their shipments are not tracked separately from the remainder of the U.S. herd. However, we analyze two additional datasets - Interstate Certificates of Veterinary Inspection and brand inspection data - to ensure that the characteristics of potential post-import shipments do not change on an annual scale and are not dependent on the dataset informing our analyses. Overall, these results highlight the utility of USAMM to inform targeted surveillance strategies when complete shipment information is unavailable.
|
|
| 13. |
- Lindström, Tom, et al.
(författare)
-
A Bayesian Approach for Modeling Cattle Movements in the United States: Scaling up a Partially Observed Network
- 2013
-
Ingår i: PLOS ONE. - : Public Library of Science. - 1932-6203. ; 8:1
-
Tidskriftsartikel (refereegranskat)abstract
- Networks are rarely completely observed and prediction of unobserved edges is an important problem, especially in disease spread modeling where networks are used to represent the pattern of contacts. We focus on a partially observed cattle movement network in the U.S. and present a method for scaling up to a full network based on Bayesian inference, with the aim of informing epidemic disease spread models in the United States. The observed network is a 10% state stratified sample of Interstate Certificates of Veterinary Inspection that are required for interstate movement; describing approximately 20,000 movements from 47 of the contiguous states, with origins and destinations aggregated at the county level. We address how to scale up the 10% sample and predict unobserved intrastate movements based on observed movement distances. Edge prediction based on a distance kernel is not straightforward because the probability of movement does not always decline monotonically with distance due to underlying industry infrastructure. Hence, we propose a spatially explicit model where the probability of movement depends on distance, number of premises per county and historical imports of animals. Our model performs well in recapturing overall metrics of the observed network at the node level (U.S. counties), including degree centrality and betweenness; and performs better compared to randomized networks. Kernel generated movement networks also recapture observed global network metrics, including network size, transitivity, reciprocity, and assortativity better than randomized networks. In addition, predicted movements are similar to observed when aggregated at the state level (a broader geographic level relevant for policy) and are concentrated around states where key infrastructures, such as feedlots, are common. We conclude that the method generally performs well in predicting both coarse geographical patterns and network structure and is a promising method to generate full networks that incorporate the uncertainty of sampled and unobserved contacts.
|
|
| 14. |
- Pasquini, Luca, et al.
(författare)
-
Magnesium- and intermetallic alloys-based hydrides for energy storage : modelling, synthesis and properties
- 2022
-
Ingår i: Progress in Energy. - : Institute of Physics Publishing (IOPP). - 2516-1083. ; 4:3
-
Forskningsöversikt (refereegranskat)abstract
- Hydrides based on magnesium and intermetallic compounds provide a viable solution to the challenge of energy storage from renewable sources, thanks to their ability to absorb and desorb hydrogen in a reversible way with a proper tuning of pressure and temperature conditions. Therefore, they are expected to play an important role in the clean energy transition and in the deployment of hydrogen as an efficient energy vector. This review, by experts of Task 40 'Energy Storage and Conversion based on Hydrogen' of the Hydrogen Technology Collaboration Programme of the International Energy Agency, reports on the latest activities of the working group 'Magnesium- and Intermetallic alloys-based Hydrides for Energy Storage'. The following topics are covered by the review: multiscale modelling of hydrides and hydrogen sorption mechanisms; synthesis and processing techniques; catalysts for hydrogen sorption in Mg; Mg-based nanostructures and new compounds; hydrides based on intermetallic TiFe alloys, high entropy alloys, Laves phases, and Pd-containing alloys. Finally, an outlook is presented on current worldwide investments and future research directions for hydrogen-based energy storage.
|
|
| 15. |
- Sawalha, Amr H., et al.
(författare)
-
Common variants within MECP2 confer risk of systemic lupus erythematosus
- 2008
-
Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 3:3, s. e1727-
-
Tidskriftsartikel (refereegranskat)abstract
- Systemic lupus erythematosus (SLE) is a predominantly female autoimmune disease that affects multiple organ systems. Herein, we report on an X-chromosome gene association with SLE. Methyl-CpG-binding protein 2 (MECP2) is located on chromosome Xq28 and encodes for a protein that plays a critical role in epigenetic transcriptional regulation of methylation-sensitive genes. Utilizing a candidate gene association approach, we genotyped 21 SNPs within and around MECP2 in SLE patients and controls. We identify and replicate association between SLE and the genomic element containing MECP2 in two independent SLE cohorts from two ethnically divergent populations. These findings are potentially related to the overexpression of methylation-sensitive genes in SLE.
|
|
| 16. |
- Sellman, Stefan, et al.
(författare)
-
Modeling nation-wide US swine movement networks at the resolution of the individual premises
- 2022
-
Ingår i: Epidemics. - : Elsevier. - 1755-4365 .- 1878-0067. ; 41
-
Tidskriftsartikel (refereegranskat)abstract
- The spread of infectious livestock diseases is a major cause for concern in modern agricultural systems. In the dynamics of the transmission of such diseases, movements of livestock between herds play an important role. When constructing mathematical models used for activities such as forecasting epidemic development, evaluating mitigation strategies, or determining important targets for disease surveillance, including between -premises shipments is often a necessity. In the United States (U.S.), livestock shipment data is not routinely collected, and when it is, it is not readily available and mostly concerned with between-state shipments. To bridge this gap in knowledge and provide insight into the complete livestock shipment network structure, we have developed the U.S. Animal Movement Model (USAMM). Previously, USAMM has only existed for cattle shipments, but here we present a version for domestic swine. This new version of USAMM consists of a Bayesian model fit to premises demography, county-level livestock industry variables, and two limited data sets of between-state swine movements. The model scales up the data to simulate nation-wide networks of both within-and between-state shipments at the level of individual premises. Here we describe this shipment model in detail and subsequently explore its usefulness with a rudimentary predictive model of the prevalence of porcine epidemic diarrhea virus (PEDv) across the U.S. Additionally, in order to promote further research on livestock disease and other topics involving the movements of swine in the U.S., we also make 250 synthetic premises-level swine shipment networks with complete coverage of the entire conterminous U.S. freely available to the research community as a useful surrogate for the absent shipment data.
|
|
| 17. |
- Sellman, Stefan, et al.
(författare)
-
Modeling US cattle movements until the cows come home: Who ships to whom and how many?
- 2022
-
Ingår i: Computers and Electronics in Agriculture. - : ELSEVIER SCI LTD. - 0168-1699 .- 1872-7107. ; 203
-
Tidskriftsartikel (refereegranskat)abstract
- Livestock movements between agricultural premises is an important pathway for the spread of infectious disease. Data providing details about the origin and destination of shipments, as well as information about the shipment size is an important component of computer models used to formulate mitigation strategies and design surveillance programs. The United States (U.S.) currently lacks a comprehensive database of farm animal shipments, which hinders such efforts. With the U.S. Animal Movement Model (USAMM), earlier work has successfully scaled up from limited data based on interstate certificates of veterinary inspection (CVI) to comprehensive county-level shipment networks at the national scale. In this work, we present three major improvements to earlier versions of USAMM: (1) increased resolution of the model and simulated networks to the level of individual premises; (2) predictions of shipment sizes; (3) taking into account the types and herd sizes of the premises. We fitted parameters in a Bayesian framework to two sets of CVI data consisting of sub-samples of one years between-state beef and dairy shipments. Through posterior predictive simulation, we then created 1,000 synthetic beef and dairy networks, which we make publicly available to support livestock disease modeling. The simulated networks were validated against summary statistics of the training data as well as out-of-sample CVI data from subsequent years. This new development opens up the possibility of using USAMM in a broader spectrum of applications where information about shipment size and premises identity is necessary and gives novel insights into the U.S. cattle shipment network.
|
|
| 18. |
- Sellman, Stefan, et al.
(författare)
-
Realistic assumptions about spatial locations and clustering of premises matter for models of foot-and-mouth disease spread in the United States
- 2020
-
Ingår i: PloS Computational Biology. - : PUBLIC LIBRARY SCIENCE. - 1553-734X .- 1553-7358. ; 16:2
-
Tidskriftsartikel (refereegranskat)abstract
- Spatially explicit livestock disease models require demographic data for individual farms or premises. In the U.S., demographic data are only available aggregated at county or coarser scales, so disease models must rely on assumptions about how individual premises are distributed within counties. Here, we addressed the importance of realistic assumptions for this purpose. We compared modeling of foot and mouth disease (FMD) outbreaks using simple randomization of locations to premises configurations predicted by the Farm Location and Agricultural Production Simulator (FLAPS), which infers location based on features such as topography, land-cover, climate, and roads. We focused on three premises-level Susceptible-Exposed-Infectious-Removed models available from the literature, all using the same kernel approach but with different parameterizations and functional forms. By computing the basic reproductive number of the infection (R-0) for both FLAPS and randomized configurations, we investigated how spatial locations and clustering of premises affects outbreak predictions. Further, we performed stochastic simulations to evaluate if identified differences were consistent for later stages of an outbreak. Using Ripleys K to quantify clustering, we found that FLAPS configurations were substantially more clustered at the scales relevant for the implemented models, leading to a higher frequency of nearby premises compared to randomized configurations. As a result, R-0 was typically higher in FLAPS configurations, and the simulation study corroborated the pattern for later stages of outbreaks. Further, both R-0 and simulations exhibited substantial spatial heterogeneity in terms of differences between configurations. Thus, using realistic assumptions when de-aggregating locations based on available data can have a pronounced effect on epidemiological predictions, affecting if, where, and to what extent FMD may invade the population. We conclude that methods such as FLAPS should be preferred over randomization approaches.
|
|
| 19. |
|
|
| 20. |
- Webb, Ryan, et al.
(författare)
-
A polymorphism within IL21R confers risk for systemic lupus erythematosus
- 2009
-
Ingår i: Arthritis and Rheumatism. - : Wiley. - 0004-3591 .- 1529-0131. ; 60:8, s. 2402-2407
-
Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: Interleukin-21 (IL-21) is a member of the type I cytokine superfamily that has a variety of effects on the immune system, including B cell activation, plasma cell differentiation, and immunoglobulin production. The expression of IL-21 receptor (IL-21R) is reduced in the B cells of patients with systemic lupus erythematosus (SLE), while serum IL-21 levels are increased both in lupus patients and in some murine lupus models. We recently reported that polymorphisms within the IL21 gene are associated with increased susceptibility to SLE. The aim of this study was to examine the genetic association between single-nucleotide polymorphisms (SNPs) within IL21R and SLE. METHODS: We genotyped 17 SNPs in the IL21R gene in 2 large cohorts of lupus patients (a European-derived cohort and a Hispanic cohort) and in ethnically matched healthy controls. RESULTS: We identified and confirmed the association between rs3093301 within the IL21R gene and SLE in the 2 cohorts (meta-analysis odds ratio 1.16 [95% confidence interval 1.08-1.25], P=1.0x10(-4)). CONCLUSION: Our findings indicate that IL21R is a novel susceptibility gene for SLE.
|
|
