22 research outputs found

    Transmission of Infectious Diseases En Route to Habitat Hotspots

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    <div><p>Background</p><p>The spread of infectious diseases in wildlife populations is influenced by patterns of between-host contacts. Habitat “hotspots” - places attracting a large numbers of individuals or social groups - can significantly alter contact patterns and, hence, disease propagation. Research on the importance of habitat hotspots in wildlife epidemiology has primarily focused on how inter-individual contacts occurring at the hotspot itself increase disease transmission. However, in territorial animals, epidemiologically important contacts may primarily occur as animals cross through territories of conspecifics en route to habitat hotspots. So far, the phenomenon has received little attention. Here, we investigate the importance of these contacts in the case where infectious individuals keep visiting the hotspots and in the case where these individuals are not able to travel to the hotspot any more.</p><p>Methodology and Principal Findings</p><p>We developed a simulation epidemiological model to investigate both cases in a scenario when transmission at the hotspot does not occur. We find that (i) hotspots still exacerbate epidemics, (ii) when infectious individuals do not travel to the hotspot, the most vulnerable individuals are those residing at intermediate distances from the hotspot rather than nearby, and (iii) the epidemiological vulnerability of a population is the highest when the number of hotspots is intermediate.</p><p>Conclusions and Significance</p><p>By altering animal movements in their vicinity, habitat hotspots can thus strongly increase the spread of infectious diseases, even when disease transmission does not occur at the hotspot itself. Interestingly, when animals only visit the nearest hotspot, creating additional artificial hotspots, rather than reducing their number, may be an efficient disease control measure.</p></div

    Influence of multiple model parameters on attack rate, when infected groups do not travel (Sick-stay model).

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    <p>The fraction of groups infected increases with the hotspot radius of attraction, but varies with the traveler-resident transmission probability <i>P<sub>T</sub></i> (four lines in each graph), within-group transmission probability <i>P<sub>w</sub></i> (three different columns of graphs), and between-neighbour transmission probability <i>P<sub>B</sub></i> (four different rows of graphs). Each value is based on 1000 simulations in which disease was introduced randomly in one of the eigth groups adjacent to the hotspot.</p

    Number of hotspots.

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    <p>Each line graphs the change in attack rate as a function of the number of hotspots, for a different value of <i>P<sub>B</sub></i> (from 4e-04 to 16e-04). Results are presented for hotspots ranging from 1–100 (left) and 1–500 (right) in the Sick-stay model (top) and the Sick-travel model (bottom). Each value is averaged over 1000 stochastic simulations assuming <i>R</i> = 30, <i>P<sub>w</sub></i> = 0.06, <i>P<sub>T</sub></i> = 4e-04. Each hotspot was located randomly in the population, and disease was introduced into the group ranging in the middle of the habitat.</p

    Model schematic.

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    <p>The hotspot is located at the center of a 51×51 lattice. All other cells correspond to a group's territory. Groups with at least one infected individual are considered infected, indicated in dark grey. A 9×9 section of the lattice depicts the SIR transmission dynamics among individuals that are either in the same group or neighbouring groups (bottom). Groups follow Biased Random Walks (BRW) during their daylong trips to the hotspot (top right). Transmission is possible between a travelling group and the groups residing in cells traversed en route to the hotspot.</p

    Attack rate decreases with the distance between the hotspot and point of disease introduction.

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    <p>Sick-stay model (solid lines) and Sick-travel model (dashed lines) are compared for different values of the hotspot radius of attraction (<i>R</i>). Each graph presents a different value of the traveler-resident transmission rate (<i>P<sub>T</sub></i>). Each value is averaged over 1000 stochastic simulations, assuming <i>P<sub>B</sub></i> = 8e-04 and <i>P<sub>w</sub></i> = 0.06.</p

    Probability of infection depends on distance to hotspot.

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    <p>The relationship is presented for different values of the hotspot radius of attraction (<i>R</i>) in Sick-stay model (left) and Sick-travel model (right). Vertical lines compare the probability of infection when there is no hotspot (<i>R</i> = 0) to the probability of infection when there is a hotspot (<i>R</i>>0), for groups residing beyond the radius of attraction (distance to hotspot greater than <i>R</i>). This quantifies the indirect epidemiological impact of the hotpot on groups that never travel themselves or encounter travelers en route to the hotspot. Black arrows show the analytical prediction of the most vulnerable group to disease for R = 10, 20 and 30 respectively. Parameter values are <i>P<sub>B</sub></i> = 8e-04, <i>P<sub>T</sub></i> = 0.001 and <i>P<sub>w</sub></i> = 0.06. Each value is based on 1000 stochastic simulations in which disease was introduced randomly in one of the eight groups adjacent to the hotspot. Results for other parameter values are shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0031290#pone.0031290.s002" target="_blank">Fig. S2</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0031290#pone.0031290.s003" target="_blank">S3</a>.</p

    <i>ITGB4</i> mutation analysis.

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    <p>(A) Genomic structure of <i>ITGB4</i> sequence based in the information obtained by BAC clone sequencing and RNA-seq data. Grey boxes represent exons. Grey lines crossing the exons represent the two mutations with protein effects found in this study (<i>c</i>.<i>1337G>A</i> and <i>c</i>.<i>4412_4415del</i>). The red box highlights the exon 33 in which <i>c</i>.<i>4412_4415del</i> is located. (B) The first sequence corresponds to exon 33 and its translation in a wild type protein, the second sequence corresponds to mutant exon 33 and the resulting translation. The affected codons at exon 33 are highlighted in red. This 4-bp deletion leads to a truncated protein of 1,472 amino acids (1,470 amino acids of normal integrin ÎČ4 followed by two missense amino acids and a premature termination codon). (C) Putative resulting protein of <i>ITGB4</i> gene (GenBank KP025765). The mutation is predicted to delete the region spanning the last 281 amino acids in the intracellular domain, including the third and fourth FNIII repeats.</p

    GWA and homozygosity mapping analyses for ovine LCH.

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    <p>(A) Manhattan plot resulting from the case-control association analysis performed with 7 affected animals and 33 controls. The X-axis shows the positions of the genome analyzed across the 26 ovine autosomes, whereas the Y-axis represents the -log<sub>10</sub> P-values obtained after 100,000 permutations using PLINK. Alternating colors mark the limits between autosomes. The arrow indicates the most significant association identified, which was located on OAR4 (at 42,810,217 bp position). (B) Homozygosity mapping of the LCH mutation. The analysis of SNP genotypes from affected lambs indicated that they all shared an extended overlapping homozygous region on OAR 4 (indicated by orange blocks). The common haplotype block, where the causative mutation is located, expands between 42.369 and 47.251 Mb on OAR4 (indicated by the red box). (C) Gene content of the 4.8-Mb homozygosity block interval shared by the affected individuals based on the comparative genomic map with the orthologous regions in human and cow and including the <i>RELN</i> gene. </p

    Immunohistochemical labeling of collagen VII and integrins α6 and ÎČ4.

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    <p>The three proteins are labeled (brown signal) in the skin samples of the control lamb, at the basal cell layer while in the samples from the affected lamb integrin ÎČ4. The signal of the other two proteins is normal. Note the localization of collagen VII at the base of the blister in the sample from the affected lamb while the integrin α6 remains attached to the basal keratinocytes, at the roof of the blister.</p
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