Liliana Salvador

Interests

Teaching

Ecology of Infectious Diseases

Research

My research focuses on combining different data sources (ecological, genomic, epidemiological, and movement data) and developing computational and mathematical models to understand the ecology and evolution of bacterial zoonotic diseases at the wildlife, livestock, and human interface. I aim to identify the epidemiological, ecological, and evolutionary circumstances involved in pathogen spillover events, amplification, and spread, essential for prioritizing One Health surveillance strategies and predicting future disease emergence risk in vulnerable populations.

Courses

Scholarly Contributions

Journals/Publications

• Akhmetova, A., Guerrero, J., McAdam, P., Salvador, L. C., Crispell, J., Lavery, J., Presho, E., Kao, R. R., Biek, R., Menzies, F., Trimble, N., Harwood, R., Pepler, P. T., Oravcova, K., Graham, J., Skuce, R., du Plessis, L., Thompson, S., Wright, L., , Byrne, A. W., et al. (2023). Genomic epidemiology of infection in sympatric badger and cattle populations in Northern Ireland. Microbial genomics, 9(5).
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  Bovine tuberculosis (bTB) is a costly, epidemiologically complex, multi-host, endemic disease. Lack of understanding of transmission dynamics may undermine eradication efforts. Pathogen whole-genome sequencing improves epidemiological inferences, providing a means to determine the relative importance of inter- and intra-species host transmission for disease persistence. We sequenced an exceptional data set of 619 isolates from badgers and cattle in a 100 km bTB 'hotspot' in Northern Ireland. Historical molecular subtyping data permitted the targeting of an endemic pathogen lineage, whose long-term persistence provided a unique opportunity to study disease transmission dynamics in unparalleled detail. Additionally, to assess whether badger population genetic structure was associated with the spatial distribution of pathogen genetic diversity, we microsatellite genotyped hair samples from 769 badgers trapped in this area. Birth death models and TransPhylo analyses indicated that cattle were likely driving the local epidemic, with transmission from cattle to badgers being more common than badger to cattle. Furthermore, the presence of significant badger population genetic structure in the landscape was not associated with the spatial distribution of genetic diversity, suggesting that badger-to-badger transmission is not playing a major role in transmission dynamics. Our data were consistent with badgers playing a smaller role in transmission of infection in this study site, compared to cattle. We hypothesize, however, that this minor role may still be important for persistence. Comparison to other areas suggests that transmission dynamics are likely to be context dependent, with the role of wildlife being difficult to generalize.
• Klever, A. M., Alexander, K. A., Almeida, D., Anderson, M. Z., Ball, R. L., Beamer, G., Boggiatto, P., Buikstra, J. E., Chandler, B., Claeys, T. A., Concha, A. E., Converse, P. J., Derbyshire, K. M., Dobos, K. M., Dupnik, K. M., Endsley, J. J., Endsley, M. A., Fennelly, K., Franco-Paredes, C., , Hagge, D. A., et al. (2023). The Many Hosts of Mycobacteria 9 (MHM9): A conference report. Tuberculosis (Edinburgh, Scotland), 142, 102377.
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  The Many Hosts of Mycobacteria (MHM) meeting series brings together basic scientists, clinicians and veterinarians to promote robust discussion and dissemination of recent advances in our knowledge of numerous mycobacterial diseases, including human and bovine tuberculosis (TB), nontuberculous mycobacteria (NTM) infection, Hansen's disease (leprosy), Buruli ulcer and Johne's disease. The 9th MHM conference (MHM9) was held in July 2022 at The Ohio State University (OSU) and centered around the theme of "Confounders of Mycobacterial Disease." Confounders can and often do drive the transmission of mycobacterial diseases, as well as impact surveillance and treatment outcomes. Various confounders were presented and discussed at MHM9 including those that originate from the host (comorbidities and coinfections) as well as those arising from the environment (e.g., zoonotic exposures), economic inequality (e.g. healthcare disparities), stigma (a confounder of leprosy and TB for millennia), and historical neglect (a confounder in Native American Nations). This conference report summarizes select talks given at MHM9 highlighting recent research advances, as well as talks regarding the historic and ongoing impact of TB and other infectious diseases on Native American Nations, including those in Southwestern Alaska where the regional TB incidence rate is among the highest in the Western hemisphere.
• O'Brien, D. J., Thacker, T. C., Salvador, L. C., Duffiney, A. G., Robbe-Austerman, S., Camacho, M. S., Lombard, J. E., & Palmer, M. V. (2023). The devil you know and the devil you don't: current status and challenges of bovine tuberculosis eradication in the United States. Irish veterinary journal, 76(Suppl 1), 16.
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  Having entered into its second century, the eradication program for bovine tuberculosis (bTB, caused by Mycobacterium bovis) in the United States of America occupies a position both enviable and daunting. Excepting four counties in Michigan comprising only 6109 km (0.06% of US land area) classified as Modified Accredited, as of April 2022 the entire country was considered Accredited Free of bTB by the US Department of Agriculture for cattle and bison. On the surface, the now well-described circumstances of endemic bTB in Michigan, where white-tailed deer (Odocoileus virginianus) serve as a free-ranging wildlife maintenance host, may appear to be the principal remaining barrier to national eradication. However, the situation there is unique in the U.S., and far-removed from the broader issues of bTB control in the remainder of the country. In Michigan, extensive surveillance for bTB in deer over the last quarter century, and regulatory measures to maximize the harvest of publicly-owned wildlife, have been implemented and sustained. Prevalence of bTB in deer has remained at a low level, although not sufficiently low to eliminate cattle herd infections. Public attitudes towards bTB, cattle and deer, and their relative importance, have been more influential in the management of the disease than any limitations of biological science. However, profound changes in the demographics and social attitudes of Michigan's human population are underway, changes which are likely to force a critical reevaluation of the bTB control strategies thus far considered integral. In the rest of the U.S. where bTB is not self-sustaining in wildlife, changes in the scale of cattle production, coupled with both technical and non-technical issues have created their own substantial challenges. It is against this diverse backdrop that the evolution of whole genome sequencing of M. bovis has revolutionized understanding of the history and ecology of bTB in Michigan, resolved previously undiscernible epidemiological puzzles, provided insights into zoonotic transmission, and unified eradication efforts across species and agencies. We describe the current status of bTB eradication in the U.S., how circumstances and management have changed, what has been learned, and what remains more elusive than ever.
• Shibabaw, A., Gelaw, B., Ghanem, M., Legall, N., Schooley, A. M., Soehnlen, M. K., Salvador, L. C., Gebreyes, W., Wang, S. H., & Tessema, B. (2023). Molecular epidemiology and transmission dynamics of multi-drug resistant tuberculosis strains using whole genome sequencing in the Amhara region, Ethiopia. BMC genomics, 24(1), 400.
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  Drug resistant Mycobacterium tuberculosis prevention and care is a major challenge in Ethiopia. The World health organization has designated Ethiopia as one of the 30 high burden multi-drug resistant tuberculosis (MDR-TB) countries. There is limited information regarding genetic diversity and transmission dynamics of MDR-TB in Ethiopia.
• Xu, R., Prakoso, D., Salvador, L. C., & Rajeev, S. (2023). transcriptome sequencing using long-read technology reveals unannotated transcripts and potential polyadenylation of RNA molecules. Microbiology spectrum, 11(6), e0223423.
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  Leptospirosis, caused by the spirochete bacteria , is a zoonotic disease of humans and animals, accounting for over 1 million annual human cases and over 60,000 deaths. We have characterized operon transcriptional units, identified novel RNA coding regions, and reported evidence of potential posttranscriptional polyadenylation in the transcriptomes for the first time using Oxford Nanopore Technology RNA sequencing protocols. The newly identified RNA coding regions and operon transcriptional units were detected only in the pathogenic transcriptomes, suggesting their significance in virulence-related functions. This article integrates bioinformatics, infectious diseases, microbiology, molecular biology, veterinary sciences, and public health. Given the current knowledge gap in the regulation of leptospiral pathogenicity, our findings offer valuable insights to researchers studying leptospiral pathogenicity and provide both a basis and a tool for researchers focusing on prokaryotic molecular studies for the understanding of RNA compositions and prokaryotic polyadenylation for their organisms of interest.
• Xu, R., Rajeev, S., & Salvador, L. C. (2023). The selection of software and database for metagenomics sequence analysis impacts the outcome of microbial profiling and pathogen detection. PloS one, 18(4), e0284031.
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  Shotgun metagenomic sequencing analysis is widely used for microbial profiling of biological specimens and pathogen detection. However, very little is known about the technical biases caused by the choice of analysis software and databases on the biological specimen. In this study, we evaluated different direct read shotgun metagenomics taxonomic profiling software to characterize the microbial compositions of simulated mice gut microbiome samples and of biological samples collected from wild rodents across multiple taxonomic levels. Using ten of the most widely used metagenomics software and four different databases, we demonstrated that obtaining an accurate species-level microbial profile using the current direct read metagenomics profiling software is still a challenging task. We also showed that the discrepancies in results when different databases and software were used could lead to significant variations in the distinct microbial taxa classified, in the characterizations of the microbial communities, and in the differentially abundant taxa identified. Differences in database contents and read profiling algorithms are the main contributors for these discrepancies. The inclusion of host genomes and of genomes of the interested taxa in the databases is important for increasing the accuracy of profiling. Our analysis also showed that software included in this study differed in their ability to detect the presence of Leptospira, a major zoonotic pathogen of one health importance, especially at the species level resolution. We concluded that using different databases and software combinations can result in confounding biological conclusions in microbial profiling. Our study warrants that software and database selection must be based on the purpose of the study.
• Beliakova-Bethell, N., Maruthai, K., Xu, R., Salvador, L. C., & Garg, A. (2022). Monocytic-Myeloid Derived Suppressor Cells Suppress T-Cell Responses in Recovered SARS CoV2-Infected Individuals. Frontiers in immunology, 13, 894543.
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  Coronavirus disease 2019 (COVID-19) caused by SARS Coronavirus 2 (CoV2) is associated with massive immune activation and hyperinflammatory response. Acute and severe CoV2 infection is characterized by the expansion of myeloid derived suppressor cells (MDSC) because of cytokine storm, these MDSC suppress T cell functions. However, the presence of MDSC and its effect on CoV2 antigen specific T cell responses in individuals long after first detection of CoV2 and recovery from infection has not been studied. We and others have previously shown that CD11bCD33CD14HLA-DR monocytic MDSC (M-MDSC) are present in individuals with clinical recovery from viral infection. In this study, we compared the frequency, functional and transcriptional signatures of M-MDSC isolated from CoV2 infected individuals after 5-months of the first detection of the virus (CoV2+) and who were not infected with CoV2 (CoV2-). Compared to CoV2- individuals, M-MDSC were present in CoV2+ individuals at a higher frequency, the level of M-MDSC correlated with the quantity of IL-6 in the plasma. Compared to CoV2-, increased frequency of PD1, CD57 and CX3CR1 T effector memory (T) cell subsets was also present in CoV2+ individuals, but these did not correlate with M-MDSC levels. Furthermore, depleting M-MDSC from peripheral blood mononuclear cells (PBMC) increased T cell cytokine production when cultured with the peptide pools of immune dominant spike glycoprotein (S), membrane (M), and nucleocapsid (N) antigens of CoV2. M-MDSC suppressed CoV2 S- antigen-specific T cell in ROS, Arginase, and TGFβ dependent manner. Our gene expression, RNA-seq and pathway analysis studies further confirm that M-MDSC isolated from CoV2+ individuals are enriched in pathways that regulate both innate and adaptive immune responses, but the genes regulating these functions (, , , , , , ) remained downregulated in M-MDSC isolated from CoV2+ individuals. These results demonstrate that M-MDSC suppresses recall responses to CoV2 antigens long after recovery from infection. Our findings suggest M-MDSC as novel regulators of CoV2 specific T cell responses, and should be considered as target to augment responses to vaccine.
• Gorman, M., Xu, R., Prakoso, D., Salvador, L. C., & Rajeev, S. (2022). Leptospira enrichment culture followed by ONT metagenomic sequencing allows better detection of Leptospira presence and diversity in water and soil samples. PLoS neglected tropical diseases, 16(10), e0010589.
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  Leptospirosis, a life-threatening disease in humans and animals, is one of the most widespread global zoonosis. Contaminated soil and water are the major transmission sources in humans and animals. Clusters of disease outbreaks are common during rainy seasons.
• Legall, N., & Salvador, L. C. (2022). Selective sweep sites and SNP dense regions differentiate isolates across scales. Frontiers in microbiology, 13, 787856.
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  , a bacterial zoonotic pathogen responsible for the economically and agriculturally important livestock disease bovine tuberculosis (bTB), infects a broad mammalian host range worldwide. This characteristic has led to bidirectional transmission events between livestock and wildlife species as well as the formation of wildlife reservoirs, impacting the success of bTB control measures. Next Generation Sequencing (NGS) has transformed our ability to understand disease transmission events by tracking variant sites, however the genomic signatures related to host adaptation following spillover, alongside the role of other genomic factors in the transmission process are understudied problems. We analyzed publicly available datasets collected from 700 hosts across three countries with bTB endemic regions (United Kingdom, United States, and New Zealand) to investigate if genomic regions with high SNP density and/or selective sweep sites play a role in adaptation to new environments (e.g., at the host-species, geographical, and/or sub-population levels). A simulated alignment was created to generate null distributions for defining genomic regions with high SNP counts and regions with selective sweeps evidence. Random Forest (RF) models were used to investigate evolutionary metrics within the genomic regions of interest to determine which genomic processes were the best for classifying across ecological scales. We identified in the bovis genomes 14 and 132 high SNP density and selective sweep regions, respectively. Selective sweep regions were ranked as the most important in classifying across the different scales in all RF models. SNP dense regions were found to have high importance in the badger and cattle specific RF models in classifying badger derived isolates from livestock derived ones. Additionally, the genes detected within these genomic regions harbor various pathogenic functions such as virulence and immunogenicity, membrane structure, host survival, and mycobactin production. The results of this study demonstrate how comparative genomics alongside machine learning approaches are useful to investigate further the nature of host-pathogen interactions.
• Reis, A. C., Salvador, L. C., Robbe-Austerman, S., Tenreiro, R., Botelho, A., Albuquerque, T., & Cunha, M. V. (2021). Whole Genome Sequencing Refines Knowledge on the Population Structure of from a Multi-Host Tuberculosis System. Microorganisms, 9(8).
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  Classical molecular analyses of based on spoligotyping and Variable Number Tandem Repeat (MIRU-VNTR) brought the first insights into the epidemiology of animal tuberculosis (TB) in Portugal, showing high genotypic diversity of circulating strains that mostly cluster within the European 2 clonal complex. Previous surveillance provided valuable information on the prevalence and spatial occurrence of TB and highlighted prevalent genotypes in areas where livestock and wild ungulates are sympatric. However, links at the wildlife-livestock interfaces were established mainly via classical genotype associations. Here, we apply whole genome sequencing (WGS) to cattle, red deer and wild boar isolates to reconstruct the population structure in a multi-host, multi-region disease system and to explore links at a fine genomic scale between from wildlife hosts and cattle. Whole genome sequences of 44 representative isolates, obtained between 2003 and 2015 from three TB hotspots, were compared through single nucleotide polymorphism (SNP) variant calling analyses. Consistent with previous results combining classical genotyping with Bayesian population admixture modelling, SNP-based phylogenies support the branching of this population into five genetic clades, three with apparent geographic specificities, as well as the establishment of an SNP catalogue specific to each clade, which may be explored in the future as phylogenetic markers. The core genome alignment of SNPs was integrated within a spatiotemporal metadata framework to further structure this population by host species and TB hotspots, providing a baseline for network analyses in different epidemiological and disease control contexts. WGS of isolates from Portugal is reported for the first time in this pilot study, refining the spatiotemporal context of TB at the wildlife-livestock interface and providing further support to the key role of red deer and wild boar on disease maintenance. The SNP diversity observed within this dataset supports the natural circulation of for a long time period, as well as multiple introduction events of the pathogen in this Iberian multi-host system.
• Larsen, M. H., Lacourciere, K., Parker, T. M., Kraigsley, A., Achkar, J. M., Adams, L. B., Dupnik, K. M., Hall-Stoodley, L., Hartman, T., Kanipe, C., Kurtz, S. L., Miller, M. A., Salvador, L. C., Spencer, J. S., & Robinson, R. T. (2020). The Many Hosts of Mycobacteria 8 (MHM8): A conference report. Tuberculosis (Edinburgh, Scotland), 121, 101914.
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  Mycobacteria are important causes of disease in human and animal hosts. Diseases caused by mycobacteria include leprosy, tuberculosis (TB), nontuberculous mycobacteria (NTM) infections and Buruli Ulcer. To better understand and treat mycobacterial disease, clinicians, veterinarians and scientists use a range of discipline-specific approaches to conduct basic and applied research, including conducting epidemiological surveys, patient studies, wildlife sampling, animal models, genetic studies and computational simulations. To foster the exchange of knowledge and collaboration across disciplines, the Many Hosts of Mycobacteria (MHM) conference series brings together clinical, veterinary and basic scientists who are dedicated to advancing mycobacterial disease research. Started in 2007, the MHM series recently held its 8th conference at the Albert Einstein College of Medicine (Bronx, NY). Here, we review the diseases discussed at MHM8 and summarize the presentations on research advances in leprosy, NTM and Buruli Ulcer, human and animal TB, mycobacterial disease comorbidities, mycobacterial genetics and 'omics, and animal models. A mouse models workshop, which was held immediately after MHM8, is also summarized. In addition to being a resource for those who were unable to attend MHM8, we anticipate this review will provide a benchmark to gauge the progress of future research concerning mycobacteria and their many hosts.
• Chaters, G. L., Johnson, P. C., Cleaveland, S., Crispell, J., de Glanville, W. A., Doherty, T., Matthews, L., Mohr, S., Nyasebwa, O. M., Rossi, G., Salvador, L. C., Swai, E., & Kao, R. R. (2019). Analysing livestock network data for infectious disease control: an argument for routine data collection in emerging economies. Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 374(1776), 20180264.
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  Livestock movements are an important mechanism of infectious disease transmission. Where these are well recorded, network analysis tools have been used to successfully identify system properties, highlight vulnerabilities to transmission, and inform targeted surveillance and control. Here we highlight the main uses of network properties in understanding livestock disease epidemiology and discuss statistical approaches to infer network characteristics from biased or fragmented datasets. We use a 'hurdle model' approach that predicts (i) the probability of movement and (ii) the number of livestock moved to generate synthetic 'complete' networks of movements between administrative wards, exploiting routinely collected government movement permit data from northern Tanzania. We demonstrate that this model captures a significant amount of the observed variation. Combining the cattle movement network with a spatial between-ward contact layer, we create a multiplex, over which we simulated the spread of 'fast' ( R = 3) and 'slow' ( R = 1.5) pathogens, and assess the effects of random versus targeted disease control interventions (vaccination and movement ban). The targeted interventions substantially outperform those randomly implemented for both fast and slow pathogens. Our findings provide motivation to encourage routine collection and centralization of movement data to construct representative networks. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'. This theme issue is linked with the earlier issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'.
• Salvador, L. C., O'Brien, D. J., Cosgrove, M. K., Stuber, T. P., Schooley, A. M., Crispell, J., Church, S. V., Gröhn, Y. T., Robbe-Austerman, S., & Kao, R. R. (2019). Disease management at the wildlife-livestock interface: Using whole-genome sequencing to study the role of elk in Mycobacterium bovis transmission in Michigan, USA. Molecular ecology, 28(9), 2192-2205.
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  The role of wildlife in the persistence and spread of livestock diseases is difficult to quantify and control. These difficulties are exacerbated when several wildlife species are potentially involved. Bovine tuberculosis (bTB), caused by Mycobacterium bovis, has experienced an ecological shift in Michigan, with spillover from cattle leading to an endemically infected white-tailed deer (deer) population. It has potentially substantial implications for the health and well-being of both wildlife and livestock and incurs a significant economic cost to industry and government. Deer are known to act as a reservoir of infection, with evidence of M. bovis transmission to sympatric elk and cattle populations. However, the role of elk in the circulation of M. bovis is uncertain; they are few in number, but range further than deer, so may enable long distance spread. Combining Whole Genome Sequences (WGS) for M. bovis isolates from exceptionally well-observed populations of elk, deer and cattle with spatiotemporal locations, we use spatial and Bayesian phylogenetic analyses to show strong spatiotemporal admixture of M. bovis isolates. Clustering of bTB in elk and cattle suggests either intraspecies transmission within the two populations, or exposure to a common source. However, there is no support for significant pathogen transfer amongst elk and cattle, and our data are in accordance with existing evidence that interspecies transmission in Michigan is likely only maintained by deer. This study demonstrates the value of whole genome population studies of M. bovis transmission at the wildlife-livestock interface, providing insights into bTB management in an endemic system.
• Orton, R. J., Deason, M., Bessell, P. R., Green, D. M., Kao, R. R., & Salvador, L. C. (2018). Identifying genotype specific elevated-risk areas and associated herd risk factors for bovine tuberculosis spread in British cattle. Epidemics, 24, 34-42.
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  Bovine tuberculosis (bTB) is a chronic zoonosis with major health and economic impact on the cattle industry. Despite extensive control measures in cattle and culling trials in wildlife, the reasons behind the expansion of areas with high incidence of bTB breakdowns in Great Britain remain unexplained. By balancing the importance of cattle movements and local transmission on the observed pattern of cattle outbreaks, we identify areas at elevated risk of infection from specific Mycobacterium bovis genotypes. We show that elevated-risk areas (ERAs) were historically more extensive than previously understood, and that cattle movements alone are insufficient for ERA spread, suggesting the involvement of other factors. For all genotypes, we find that, while the absolute risk of infection is higher in ERAs compared to areas with intermittent risk, the statistically significant risk factors are remarkably similar in both, suggesting that these risk factors can be used to identify incipient ERAs before this is indicated by elevated incidence alone. Our findings identify research priorities for understanding bTB dynamics, improving surveillance and guiding management to prevent further ERA expansion.
• Salvador, L. C., Deason, M., Enright, J., Bessell, P. R., & Kao, R. R. (2018). Risk-based strategies for surveillance of tuberculosis infection in cattle for low-risk areas in England and Scotland. Epidemiology and infection, 146(1), 107-118.
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  Disease surveillance can be made more effective by either improving disease detection, providing cost savings, or doing both. Currently, cattle herds in low-risk areas (LRAs) for bovine tuberculosis (bTB) in England are tested once every 4 years. In Scotland, the default herd testing frequency is also 4 years, but a risk-based system exempts some herds from testing altogether. To extend this approach to other areas, a bespoke understanding of at-risk herds and how risk-based surveillance can affect bTB detection is required. Here, we use a generalized linear mixed model to inform a Bayesian probabilistic model of freedom from infection and explore risk-based surveillance strategies in LRAs and Scotland. Our analyses show that in both areas the primary herd-level risk factors for bTB infection are the size of the herd and purchasing cattle from high-risk areas of Great Britain and/or Ireland. A risk-based approach can improve the current surveillance system by both increasing detection (9% and 7% fewer latent infections), and reducing testing burden (6% and 26% fewer animal tests) in LRAs and Scotland, respectively. Testing at-risk herds more frequently can also improve the level of detection by identifying more infected cases and reducing the hidden burden of the disease, and reduce surveillance effort by exempting low-risk herds from testing.
• O'Hare, A., Lycett, S. J., Doherty, T., Salvador, L. C., & Kao, R. R. (2016). Broadwick: a framework for computational epidemiology. BMC bioinformatics, 17, 65.
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  Modelling disease outbreaks often involves integrating the wealth of data that are gathered during modern outbreaks into complex mathematical or computational models of transmission. Incorporating these data into simple compartmental epidemiological models is often challenging, requiring the use of more complex but also more efficient computational models. In this paper we introduce a new framework that allows for a more systematic and user-friendly way of building and running epidemiological models that efficiently handles disease data and reduces much of the boilerplate code that usually associated to these models. We introduce the framework by developing an SIR model on a simple network as an example.
• Doherty, T., Doidge, M., Ferrari, T., Salvador, L., Walsh, J., & Washbrook, A. (2014). Many-core on the Grid: From exploration to production. Journal of Physics: Conference Series, 513(052037). doi:10.1088/1742-6596/513/5/052037
• Salvador, L. C., Bartumeus, F., Levin, S. A., & Ryu, W. S. (2014). Mechanistic analysis of the search behaviour of Caenorhabditis elegans. Journal of the Royal Society, Interface, 11(92), 20131092.
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  A central question in movement research is how animals use information and movement to promote encounter success. Current random search theory identifies reorientation patterns as key to the compromise between optimizing encounters for both nearby and faraway targets, but how the balance between intrinsic motor programmes and previous environmental experience determines the occurrence of these reorientation behaviours remains unknown. We used high-resolution tracking and imaging data to describe the complete motor behaviour of Caenorhabditis elegans when placed in a novel environment (one in which food is absent). Movement in C. elegans is structured around different reorientation behaviours, and we measured how these contributed to changing search strategies as worms became familiar with their new environment. This behavioural transition shows that different reorientation behaviours are governed by two processes: (i) an environmentally informed 'extrinsic' strategy that is influenced by recent experience and that controls for area-restricted search behaviour, and (ii) a time-independent, 'intrinsic' strategy that reduces spatial oversampling and improves random encounter success. Our results show how movement strategies arise from a balance between intrinsic and extrinsic mechanisms, that search behaviour in C. elegans is initially determined by expectations developed from previous environmental experiences, and which reorientation behaviours are modified as information is acquired from new environments.

Proceedings Publications

• Antunes, L., Laplante, S., Pinto, A., & Salvador, L. (2009). Cryptographic Security of Individual Instance. In Information Theoretic Security. ICITS 2007., 4883, 195-210.