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Lindström, T., Tildesley, M. & Webb, C. (2015). A Bayesian Ensemble Approach for Epidemiological Projections. PloS Computational Biology, 11(4), e1004187
Open this publication in new window or tab >>A Bayesian Ensemble Approach for Epidemiological Projections
2015 (English)In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 11, no 4, p. e1004187-Article in journal (Refereed) Published
Abstract [en]

Mathematical models are powerful tools for epidemiology and can be used to compare control actions. However, different models and model parameterizations may provide different prediction of outcomes. In other fields of research, ensemble modeling has been used to combine multiple projections. We explore the possibility of applying such methods to epidemiology by adapting Bayesian techniques developed for climate forecasting. We exemplify the implementation with single model ensembles based on different parameterizations of the Warwick model run for the 2001 United Kingdom foot and mouth disease outbreak and compare the efficacy of different control actions. This allows us to investigate the effect that discrepancy among projections based on different modeling assumptions has on the ensemble prediction. A sensitivity analysis showed that the choice of prior can have a pronounced effect on the posterior estimates of quantities of interest, in particular for ensembles with large discrepancy among projections. However, by using a hierarchical extension of the method we show that prior sensitivity can be circumvented. We further extend the method to include a priori beliefs about different modeling assumptions and demonstrate that the effect of this can have different consequences depending on the discrepancy among projections. We propose that the method is a promising analytical tool for ensemble modeling of disease outbreaks.

Place, publisher, year, edition, pages
Public Library of Science, 2015
National Category
Biological Sciences
Identifiers
urn:nbn:se:liu:diva-119264 (URN)10.1371/journal.pcbi.1004187 (DOI)000354517600035 ()25927892 (PubMedID)
Note

Funding Agencies|RAPIDD program of the Science and Technology Directorate; Fogarty International Center, National Institutes of Health

Available from: 2015-06-12 Created: 2015-06-12 Last updated: 2017-12-04
Österman, H., Lindgren, I., Lindström, T. & Altimiras, J. (2015). Chronic hypoxia during development does not trigger pathologic remodeling of the chicken embryonic heart but reduces cardiomyocyte number. American Journal of Physiology. Regulatory Integrative and Comparative Physiology, 309(10), R1204-R1214
Open this publication in new window or tab >>Chronic hypoxia during development does not trigger pathologic remodeling of the chicken embryonic heart but reduces cardiomyocyte number
2015 (English)In: American Journal of Physiology. Regulatory Integrative and Comparative Physiology, ISSN 0363-6119, E-ISSN 1522-1490, Vol. 309, no 10, p. R1204-R1214Article in journal (Refereed) Published
Abstract [en]

Fetal growth restriction programs an increased risk of cardiovascular disease in adulthood, but the actual mechanisms of this developmental programming are not fully understood. Previous studies in mammalian models suggest that hearts of growth-restricted fetuses have reduced cardiomyocyte number due to reduced proliferation and premature cardiomyocyte maturation. Chicken embryos incubated under chronic hypoxia are also growth-restricted, have smaller hearts, and show signs of cardiac insufficiency posthatching. The aim of the present study was to investigate how chronic hypoxia (14% O-2) during development affects cardiomyocyte mass and how myocardial structure is altered. Hypoxic incubation reproduced the well-characterized embryonic growth restriction and an increased ventricle-to-body mass ratio (at E11, E15, E17, and E19) with reduced absolute heart mass only at E19. Cell density, apoptosis, and cardiomyocyte size were insensitive to hypoxia at E15 and E19, and no signs of ventricular wall remodeling or myocardial fibrosis were detected. Bayesian modeling provided strong support for hypoxia affecting absolute mass and proliferation rates at E15, indicating that the growth impairment, at least partly, occurs earlier in development. Neither E15 nor E19 hearts contained binucleated cardiomyocytes, indicating that fetal hypoxia does not trigger early maturation of cardiomyocytes in the chicken, which contrasts with previous results from hypoxic rat pups. In conclusion, prenatal hypoxia in the chick embryo results in a reduction in the number of cardiomyocytes without inducing ventricular remodeling, cell hypertrophy, or premature cardiomyocyte maturation.

Place, publisher, year, edition, pages
AMER PHYSIOLOGICAL SOC, 2015
Keywords
prenatal hypoxia; cardiomyocyte endowment; heart growth; hyperplasia; hypertrophy
National Category
Biological Sciences
Identifiers
urn:nbn:se:liu:diva-123806 (URN)10.1152/ajpregu.00499.2014 (DOI)000365878700002 ()26423711 (PubMedID)
Note

Funding Agencies|FORMAS Centre of Excellence in Animal Welfare Science; Linkoping university

Available from: 2016-01-11 Created: 2016-01-11 Last updated: 2017-11-30
Lindström, T., Phillips, B. L., Brown, G. P. & Shine, R. (2015). Identifying the time scale of synchronousmovement: a study on tropical snakes. Movement Ecology, 3(12), 1-9
Open this publication in new window or tab >>Identifying the time scale of synchronousmovement: a study on tropical snakes
2015 (English)In: Movement Ecology, E-ISSN 2051-3933, ISSN 2051-3933, Vol. 3, no 12, p. 1-9Article in journal (Refereed) Published
Abstract [en]

BACKGROUND:

Individual movement is critical to organismal fitness and also influences broader population processes such as demographic stochasticity and gene flow. Climatic change and habitat fragmentation render the drivers of individual movement especially critical to understand. Rates of movement of free-ranging animals through the landscape are influenced both by intrinsic attributes of an organism (e.g., size, body condition, age), and by external forces (e.g., weather, predation risk). Statistical modelling can clarify the relative importance of those processes, because externally-imposed pressures should generate synchronous displacements among individuals within a population, whereas intrinsic factors should generate consistency through time within each individual. External and intrinsic factors may vary in importance at different time scales.

RESULTS:

In this study we focused on daily displacement of an ambush-foraging snake from tropical Australia (the Northern Death Adder Acanthophis praelongus), based on a radiotelemetric study. We used a mixture of spectral representation and Bayesian inference to study synchrony in snake displacement by phase shift analysis. We further studied autocorrelation in fluctuations of displacement distances as "one over f noise". Displacement distances were positively autocorrelated with all considered noise colour parameters estimated as >0. We show how the methodology can reveal time scales of particular interest for synchrony and found that for the analysed data, synchrony was only present at time scales above approximately three weeks.

CONCLUSION:

We conclude that the spectral representation combined with Bayesian inference is a promising approach for analysis of movement data. Applying the framework to telemetry data of A. praelongus, we were able to identify a cut-off time scale above which we found support for synchrony, thus revealing a time scale where global external drivers have a larger impact on the movement behaviour. Our results suggest that for the considered study period, movement at shorter time scales was primarily driven by factors at the individual level; daily fluctuations in weather conditions had little effect on snake movement.

Keywords
Periodogram, Hierarchical Bayes, Relocation data, Elapidae, Ectotherms
National Category
Ecology
Identifiers
urn:nbn:se:liu:diva-128121 (URN)10.1186/s40462-015-0038-5 (DOI)25941572 (PubMedID)
Funder
Swedish Research Council
Available from: 2016-05-18 Created: 2016-05-18 Last updated: 2017-11-30
Amiel, J. J., Lindström, T. & Shine, R. (2014). Egg incubation effects generate positive correlations between size, speed and learning ability in young lizards. Animal Cognition, 17(2), 337-347
Open this publication in new window or tab >>Egg incubation effects generate positive correlations between size, speed and learning ability in young lizards
2014 (English)In: Animal Cognition, ISSN 1435-9448, E-ISSN 1435-9456, Vol. 17, no 2, p. 337-347Article in journal (Refereed) Published
Abstract [en]

Previous studies have suggested that body size and locomotor performance are targets of Darwinian selection in reptiles. However, much of the variation in these traits may derive from phenotypically plastic responses to incubation temperature, rather than from underlying genetic variation. Intriguingly, incubation temperature may also influence cognitive traits such as learning ability. Therefore, we might expect correlations between a reptiles size, locomotor speed and learning ability either due to selection on all of these traits or due to environmental effects during egg incubation. In the present study, we incubated lizard eggs (Scincidae: Bassiana duperreyi) under hot and cold thermal regimes and then assessed differences in hatchling body size, running speed and learning ability. We measured learning ability using a Y-maze and a food reward. We found high correlations between size, speed and learning ability, using two different metrics to quantify learning (time to solution, and directness of route), and showed that environmental effects (incubation temperature) cause these correlations. If widespread, such correlations challenge any simple interpretation of fitness advantages due to body size or speed within a population; for example, survivors may be larger and faster than nonsurvivors because of differences in learning ability, not because of their size or speed.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2014
Keywords
Body size; Cognition; Correlations; Locomotor performance
National Category
Biological Sciences
Identifiers
urn:nbn:se:liu:diva-110528 (URN)10.1007/s10071-013-0665-4 (DOI)000330955800017 ()23922118 (PubMedID)2-s2.0-84893792219 (Scopus ID)
Note

Funding Agencies|ARC, Australian Research Council; NSERC, Natural Sciences and Engineering Research Council of Canada; University of Sydney

Available from: 2014-09-18 Created: 2014-09-12 Last updated: 2017-12-05Bibliographically approved
Buhnerkempe, M. G., Tildesley, M. J., Lindström, T., Grear, D. A., Portacci, K., Miller, R. S., . . . Webb, C. T. (2014). The Impact of Movements and Animal Density on Continental Scale Cattle Disease Outbreaks in the United States. PLoS ONE, 9(3), 0091724
Open this publication in new window or tab >>The Impact of Movements and Animal Density on Continental Scale Cattle Disease Outbreaks in the United States
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2014 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 9, no 3, p. 0091724-Article in journal (Refereed) Published
Abstract [en]

Globalization has increased the potential for the introduction and spread of novel pathogens over large spatial scales necessitating continental-scale disease models to guide emergency preparedness. Livestock disease spread models, such as those for the 2001 foot-and-mouth disease (FMD) epidemic in the United Kingdom, represent some of the best case studies of large-scale disease spread. However, generalization of these models to explore disease outcomes in other systems, such as the United Statess cattle industry, has been hampered by differences in system size and complexity and the absence of suitable livestock movement data. Here, a unique database of US cattle shipments allows estimation of synthetic movement networks that inform a near-continental scale disease model of a potential FMD-like (i.e., rapidly spreading) epidemic in US cattle. The largest epidemics may affect over one-third of the US and 120,000 cattle premises, but cattle movement restrictions from infected counties, as opposed to national movement moratoriums, are found to effectively contain outbreaks. Slow detection or weak compliance may necessitate more severe state-level bans for similar control. Such results highlight the role of large-scale disease models in emergency preparedness, particularly for systems lacking comprehensive movement and outbreak data, and the need to rapidly implement multi-scale contingency plans during a potential US outbreak.

Place, publisher, year, edition, pages
Public Library of Science, 2014
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-106685 (URN)10.1371/journal.pone.0091724 (DOI)000333677000026 ()
Available from: 2014-05-21 Created: 2014-05-19 Last updated: 2017-12-05
Lindström, T., Grear, D. A., Buhnerkempe, M., Webb, C. T., Miller, R. S., Portacci, K. & Wennergren, U. (2013). A Bayesian Approach for Modeling Cattle Movements in the United States: Scaling up a Partially Observed Network. PLoS ONE, 8(1)
Open this publication in new window or tab >>A Bayesian Approach for Modeling Cattle Movements in the United States: Scaling up a Partially Observed Network
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2013 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 8, no 1Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Public Library of Science, 2013
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-88666 (URN)10.1371/journal.pone.0053432 (DOI)000313670100042 ()
Note

Funding Agencies|Research and Policy for Infectious Disease Dynamics (RAPIDD) Program, Science and Technology Directorate, U.S. Department of Homeland Security||Fogarty International Center, National Institutes of Health||Foreign Animal Disease Modeling Program, Science and Technology Directorate, U.S. Department of Homeland Security|ST-108-000017|USDA|11-9208-0269-CA11-109-9208-0235-CA|U.S. Department of Agriculture, Animal and Plant Health Inspection Service, Veterinary Services||NIH||

Available from: 2013-02-14 Created: 2013-02-14 Last updated: 2017-12-06
Lindström, T., Brown, G. P., Sisson, S. A., Phillips, B. L. & Shine, R. (2013). Rapid shifts in dispersal behavior on an expanding range edge. Proceedings of the National Academy of Sciences of the United States of America, 110(33), 13452-13456
Open this publication in new window or tab >>Rapid shifts in dispersal behavior on an expanding range edge
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2013 (English)In: Proceedings of the National Academy of Sciences of the United States of America, ISSN 0027-8424, E-ISSN 1091-6490, Vol. 110, no 33, p. 13452-13456Article in journal (Refereed) Published
Abstract [en]

Dispersal biology at an invasion front differs from that of populations within the range core, because novel evolutionary and ecological processes come into play in the nonequilibrium conditions at expanding range edges. In a world where species range limits are changing rapidly, we need to understand how individuals disperse at an invasion front. We analyzed an extensive dataset from radio-tracking invasive cane toads (Rhinella marina) over the first 8 y since they arrived at a site in tropical Australia. Movement patterns of toads in the invasion vanguard differed from those of individuals in the same area postcolonization. Our model discriminated encamped versus dispersive phases within each toads movements and demonstrated that pioneer toads spent longer periods in dispersive mode and displayed longer, more directed movements while they were in dispersive mode. These analyses predict that overall displacement per year is more than twice as far for toads at the invasion front compared with those tracked a few years later at the same site. Studies on established populations (or even those a few years postestablishment) thus may massively underestimate dispersal rates at the leading edge of an expanding population. This, in turn, will cause us to underpredict the rates at which invasive organisms move into new territory and at which native taxa can expand into newly available habitat under climate change.

Place, publisher, year, edition, pages
National Academy of Sciences, 2013
Keywords
hierarchical Bayes, shift, spatial sorting, relocation data, hidden states
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-97238 (URN)10.1073/pnas.1303157110 (DOI)000323069200058 ()
Note

Funding Agencies|Swedish Research Council||Australian Research Council||

Available from: 2013-09-05 Created: 2013-09-05 Last updated: 2017-12-06
Lindström, T., Sisson, S. A., Hakansson, N., Bergman, K.-O. & Wennergren, U. (2012). A spectral and Bayesian approach for analysis of fluctuations and synchrony in ecological datasets. Methods in Ecology and Evolution, 3(6), 1019-1027
Open this publication in new window or tab >>A spectral and Bayesian approach for analysis of fluctuations and synchrony in ecological datasets
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2012 (English)In: Methods in Ecology and Evolution, ISSN 2041-210X, E-ISSN 2041-210X, Vol. 3, no 6, p. 1019-1027Article in journal (Refereed) Published
Abstract [en]

Autocorrelation within ecological time series and synchrony between them may provide insight into the main drivers of observed dynamics. We here present methods that analyse autocorrelation and synchrony in ecological datasets using a spectral approach combined with Bayesian inference. To exemplify, we implement the method on dendrochronological data of the pedunculate oak (Quercus robur). The data consist of 110 years of growth of 10 live trees and seven trees that died during a synchronized oak death in Sweden in c. 2002-2007. We find that the highest posterior density is found for a noise colour of tree growth of gamma approximate to 0.95 (i.e. pink noise) with little difference between trees, suggesting climatic variation as a driving factor. This is further supported by the presence of synchrony, which we estimate based on phase-shift analysis. We conclude that the synchrony is time-scale dependent with higher synchrony at larger time-scales. We further show that there is no difference between the growth patterns of the alive and dead tree groups. This suggests that the trees were driven by the same factors prior to the synchronized death. We argue that this method is a promising approach for linking theoretical models with empirical data.

Place, publisher, year, edition, pages
Wiley-Blackwell, 2012
Keywords
1/f noise; co-fluctuation; environmental fluctuations; Flicker noise; hierarchical Bayesian modelling; periodogram
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-88346 (URN)10.1111/j.2041-210X.2012.00240.x (DOI)000312462000008 ()
Available from: 2013-02-04 Created: 2013-02-04 Last updated: 2017-12-06
Lindström, T., Sternberg Lewerin, S. & Wennergren, U. (2012). Influence on disease spread dynamics of herd characteristics in a structured livestock industry. Journal of the Royal Society Interface, 9(71), 1287-1294
Open this publication in new window or tab >>Influence on disease spread dynamics of herd characteristics in a structured livestock industry
2012 (English)In: Journal of the Royal Society Interface, ISSN 1742-5689, E-ISSN 1742-5662, Vol. 9, no 71, p. 1287-1294Article in journal (Refereed) Published
Abstract [en]

Studies of between-herd contacts may provide important insight to disease transmission dynamics. By comparing the result from models with different levels of detail in the description of animal movement, we studied how factors influence the final epidemic size as well as the dynamic behaviour of an outbreak. We investigated the effect of contact heterogeneity of pig herds in Sweden due to herd size, between-herd distance and production type. Our comparative study suggests that the production-type structure is the most influential factor. Hence, our results imply that production type is the most important factor to obtain valid data for and include when modelling and analysing this system. The study also revealed that all included factors reduce the final epidemic size and also have yet more diverse effects on initial rate of disease spread. This implies that a large set of factors ought to be included to assess relevant predictions when modelling disease spread between herds. Furthermore, our results show that a more detailed model changes predictions regarding the variability in the outbreak dynamics and conclude that this is an important factor to consider in risk assessment.

Place, publisher, year, edition, pages
ROYAL SOC, 6-9 CARLTON HOUSE TERRACE, LONDON SW1Y 5AG, ENGLAND, 2012
Keywords
disease spread modelling, heterogeneous contact structure, animal movement
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-77518 (URN)10.1098/rsif.2011.0625 (DOI)000303108400018 ()
Note

Funding Agencies|Science and Technology Directorate, Department of Homeland Security|ST-108-000017|

Available from: 2012-05-28 Created: 2012-05-22 Last updated: 2017-12-07
Lindström, T., Sisson, S. A., Stenberg Lewerin, S. & Wennergren, U. (2011). Bayesian analysis of animal movements related to factors at herdand between herd levels: Implications for disease spread modeling. Preventive Veterinary Medicine, 98(4), 230-242
Open this publication in new window or tab >>Bayesian analysis of animal movements related to factors at herdand between herd levels: Implications for disease spread modeling
2011 (English)In: Preventive Veterinary Medicine, ISSN 0167-5877, E-ISSN 1873-1716, Vol. 98, no 4, p. 230-242Article in journal (Other academic) Published
Abstract [en]

A method to assess the influence of between herd distances, production types and herd sizes on patterns of between herd contacts is presented. It was applied on pig movement data from a central database of Swedish Board of Agriculture. To determine the influence of these factors on the contact between holdings we used a Bayesian model and Markov chain Monte Carlo (MCMC) methods to estimate the posterior distribution of model parameters. The analysis showed that the contact pattern via animal movements is highly heterogeneous and influenced by all three factors, production type, herd size, and distance between farms. Most production types showed a positive relationship between maximum capacity and the probability of both incoming and outgoing movements. In agreement with previous studies, holdings also differed in both the number of contacts as well as with what holding types contact occurred with. Also, the scale and shape of distance dependence in contact probability was shown to differ depending on the production types of holdings.

To demonstrate how the methodology may be used for risk assessment, disease transmissions via animal movements were simulated with the model used for analysis of contacts, and parameterized by the analyzed posterior distribution. A Generalized Linear Model showed that herds with production types Sow pool center, Multiplying herd and Nucleus herd have higher risk of generating a large number of new infections. Multiplying herds are also expected to generate many long distance transmissions, while transmissions generated by Sow pool centers are confined to more local areas. We argue that the methodology presented may be a useful tool for improvement of risk assessment based on data found in central databases.

Place, publisher, year, edition, pages
Elsevier, 2011
Keywords
Markov Chain Monte Carlo; Hierarchical Bayesian; Mixture models; Indicator variable; Animal databases; Animal movements; Contact structure
National Category
Natural Sciences
Identifiers
urn:nbn:se:liu:diva-54835 (URN)10.1016/j.prevetmed.2010.11.005 (DOI)000287904900002 ()
Available from: 2010-04-15 Created: 2010-04-15 Last updated: 2017-12-12
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Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-7856-2925

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