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Fig. 5 in A retrospective study of Babesia macropus associated with morbidity and mortality in eastern grey kangaroos (Macropus giganteus) and agile wallabies (Macropus agilis)

Fig. 5. Phylogenetic tree of heat shock protein 70 (hsp70) gene sequences of eastern grey kangaroo and agile wallaby Babesia and other piroplasm hsp70 sequences in the GenBank nucleotide database. For each sequence, the GenBank GI number is followed by the species name. The representative Babesia isolates from eastern grey kangaroos and an agile wallaby in this study are shown with a - and a ♦ respectively. The evolutionary history was inferred using the Maximum Likelihood method based on the TamuraNei model (Tamura and Nei, 1993). The tree with the highest log likelihood (−6290.3774) is shown. Initial tree for the heuristic search was obtained automatically as follows. When the number of common sites was <100 or less than one fourth of the total number of sites, the maximum parsimony method was used; otherwise, BIONJ method with MCL distance matrix was used. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. The scale bar represents the number of substitutions per nucleotide. All positions containing gaps and missing data were eliminated. There are limited data available on this locus within the public data repositories and as such there is some lack of consistency with the 18S ribosomal RNA tree.

Fig. 4 in A retrospective study of Babesia macropus associated with morbidity and mortality in eastern grey kangaroos (Macropus giganteus) and agile wallabies (Macropus agilis)

Fig. 4. Phylogenetic tree of 18S ribosomal RNA (18S rRNA) gene sequences of eastern grey kangaroo and agile wallaby Babesia and other piroplasms that are in the GenBank nucleotide database. For each sequence, the GenBank GI number is followed by the species name. The representative Babesia isolates from eastern grey kangaroos and an agile wallaby in this study are shown with a - and a ♦ respectively. Evolutionary history was inferred using the Maximum Likelihood method based on the Tamura 3-parameter model. The tree with the highest log likelihood (−1820.5242) is shown. Initial tree for the heuristic search was obtained automatically as follows. When the number of common sites was <100 or less than one fourth of the total number of sites, the maximum parsimony method was used; otherwise, BIONJ method with MCL distance matrix was used. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. The scale bar represents the number of substitutions per nucleotide. All positions containing gaps and missing data were eliminated. Evolutionary analyses were conducted in MEGA6 (Tamura et al., 2011).

Fig. 1 in A retrospective study of Babesia macropus associated with morbidity and mortality in eastern grey kangaroos (Macropus giganteus) and agile wallabies (Macropus agilis)

Fig. 1. Map showing the distribution of the 38 cases of Babesia infection in eastern grey kangaroos in coastal New South Wales and southeastern Queensland over the period 1995–2013. Insert also shows the two locations of the three cases identified in agile wallabies in northern Queensland in 2009 and 2013. The locations of cases were converted to GPS coordinates and mapped using GPS Visualizer on 21/05/2014 (www.gpsvisualizer.com).

Fig. 3 in A retrospective study of Babesia macropus associated with morbidity and mortality in eastern grey kangaroos (Macropus giganteus) and agile wallabies (Macropus agilis)

Fig. 3. Transmission electron micrographs showing the intravascular location and structure of Babesia organisms in the kidney and brain of eastern grey kangaroos. (A) Kidney, the cytoplasm of two adjacent erythrocytes contains Babesia merozoites (arrows) with a membrane-bound nucleus (N) and cytoplasm containing polymorphic vacuoles and some electron dense particles (C) (scale bar = 1.0 μm). (B) Brain, adjacent to an intact erythrocyte and the nucleus of an endothelial cell is a cluster of extraerythrocytic Babesia organisms containing electron dense micronemes and developing pellicles (arrows) (scale bar = 2.0 μm). (C) Brain, within the capillary lumen is a cluster of eight or nine extraerythrocytic organisms (thick arrow) and a distorted erythrocyte (thin arrow) containing four intracytoplasmic parasites (scale bar = 5.0 μm).

Fig. 2 in A retrospective study of Babesia macropus associated with morbidity and mortality in eastern grey kangaroos (Macropus giganteus) and agile wallabies (Macropus agilis)

Fig. 2. Photomicrographs showing the forms of Babesia seen in cytological preparations and tissue sections in macropods. (A) Agile wallaby. Giemsa stained peripheral blood smear showing extraerythrocytic zoites (thin arrow) and merozoites (thick arrow) within an intact erythrocyte. (B) Eastern grey kangaroo. Diff-Quik-stained renal impression smear demonstrating 2 or 4 merozoites within intact erythrocytes (thick arrows) and clusters of extraerythrocytic zoites (thin arrows). (C) Eastern grey kangaroo. DiffQuik-stained brain squash preparation showing large clusters of intravascular zoites (arrows). (D) Eastern grey kangaroo. H&E stained section of kidney glomerulus showing merozoites within intact erythrocytes (thick arrows) and as large extraerythrocytic clusters of zoites (thin arrows). All scale bars = 20 μm.

Fig. 1 in Equal contributions of feline immunodeficiency virus and coinfections to morbidity in African lions

Fig. 1. FIV infection is common in lions of Kruger National Park. Within the sample population, 72.8% (142/195) of lions were infected with FIV. Prevalence of FIV infection was similar between males and females (75.6% versus 70.2%; n = 74 and 121, respectively), but increased with host age (a). For ease of visualization, age has been broken up by life stage into cubs (0–2yrs), subadults (2.1–4yrs), young adults (4.1–6yrs), prime adults (6.1–8yrs), and seniors (>8yrs) based on previous age classifications (Schaller, 1976). Regional prevalence of FIV was highest in the central region and lowest in the north (b). The map to the right shows locations where lion prides were sampled.

Fig. 4 in Equal contributions of feline immunodeficiency virus and coinfections to morbidity in African lions

Fig. 4. FIV has strong direct and indirect effects on overall health. The final path model (a) shows only statistically significant relationships between manifest variables (rectangles) and latent variables (circles) for FIV infection, immune response (IMM), coinfections with hemoparasites (Hemoparasites), co-infections with gastrointestinal parasites (Helminths), and morbidity (Morbidity). Note that the parameter βx,z between each variable of interest represents the path coefficient obtained from least squares regression examining the relationship between one latent variable and the next (for example, FIV to IMM). Blue arrows represent positive relationships, whereas red arrows denote negative relationships. Final sample size was 106 lions.

Fig. 3 in Equal contributions of feline immunodeficiency virus and coinfections to morbidity in African lions

Fig. 3. FIV significantly increases the prevalence of select gastrointestinal and hemoparasitic coinfections, as well as overall parasite richness for both groups. Graph (a) shows the prevalence of coinfecting parasites isolated in lions from this study. Sample size for the parasite groups included is as follows: n = 114 for gastrointestinal parasites; n = 190 for hemoparasites; and n = 195 for viral parasites. Coinfections are broken down by FIV status (positive versus negative). The two additional graphs illustrate the relationship between FIV status and gastrointestinal parasite richness (b) and hemoparasite richness (c).

Fig. 2 in Equal contributions of feline immunodeficiency virus and coinfections to morbidity in African lions

Fig. 2. FIV has broad effects on lion health and is associated with progressive immune impairment. Box (2a) above provides a complete list of the health metrics measured for the purposes of this study. Arrows to the right of each variable summarize the directionality of statistically significant changes with FIV infection. Descriptive statistics and reference values can be found in Table 2. Complete model output can be found in supplementary tables S1–S4. For ease of visualization, each parameter has been broken into categories of clinical relevance. To the right, age-related changes in lymphocyte profiles are shown for total lymphocyte counts in FIV-positive versus FIV-negative lions (b); as well as specific lymphocyte subsets in FIV-positive lions (c). Due to small sample size for lymphocyte subsets, subadults, and cubs have been included together under the 'juvenile' category.

Fig. 5 in Morbidity in California giant salamander (Dicamptodon ensatus Eschscholtz, 1833) caused by Euryhelmis sp. Poche, 1926 (Trematoda: Heterophyiidae)

Fig. 5. Euryhelmis sp. excysted, metacercaria collected from tail skin of a euthanized, chilled larval California giant salamander (Dicamptodon ensatus). A = acetabulum; Mg = Mehlis' gland; O = ovary; Oa = oral acetabulum; P = pharynx; T = testis. Photo credit: R. A. Cole (USGS).

Fig. 4 in Morbidity in California giant salamander (Dicamptodon ensatus Eschscholtz, 1833) caused by Euryhelmis sp. Poche, 1926 (Trematoda: Heterophyiidae)

Fig. 4. Photomicrographs from euthanized, chilled larval California giant salamanders (Dicamptodon ensatus) from a morbidity event in Santa Clara and Santa Cruz Counties, California, USA. (A) Encysted metacercariae (arrows) in the subcutis of the head are surrounded by inflammation and cause undulation of the skin. Cartilage and bone of the skull are to the left. (B) Skin with two encysted metacercariae (arrows) in the subcutis surrounded by macrophages, heterophils, edema (stars). Note the elevation of the epidermis. (C) Skeletal muscle with a metacercaria (M) within a cyst wall (arrow) surrounded by a few macrophages. (D) Kidney with an encysted metacercaria (arrow) in the interstitium that is surrounded by a few macrophages. A glomerulus (G) and tubules (T) are unaffected. Photo credit: J. L. Miller (USGS).

Fig. 6 in Morbidity in California giant salamander (Dicamptodon ensatus Eschscholtz, 1833) caused by Euryhelmis sp. Poche, 1926 (Trematoda: Heterophyiidae)

Fig. 6. Molecular phylogenetic analysis by Hasegawa-Kishino-Yano method with 1000 bootstrap replications based on partial 28S rRNA gene sequence from a metacercaria identified as Euryhelmis sp. removed from the subcutaneous skin of a dead, chilled California giant salamander (Dicamptodon ensatus) from a morbidity event in Santa Clara and Santa Cruz Counties, California, USA, and sequences available in GenBank. Alaria mustelae is the outgroup. The analysis involved 12 nucleotide sequences with a total of 1125 positions in the final dataset.

Fig. 3 in Morbidity in California giant salamander (Dicamptodon ensatus Eschscholtz, 1833) caused by Euryhelmis sp. Poche, 1926 (Trematoda: Heterophyiidae)

Fig. 3. Photographs of the dorsum (A) and ventrum (B) of a euthanized, chilled larval California giant salamander (Dicamptodon ensatus) from a morbidity event in Santa Clara County, California, USA. There are numerous pinpoint to 1.5-mm diameter nodules in the skin over the body including the head, gills, dorsum, ventrum, all four limbs, and tail causing a granular texture to the body. Photo credit: J. L. Miller (USGS).

Fig. 2 in Morbidity in California giant salamander (Dicamptodon ensatus Eschscholtz, 1833) caused by Euryhelmis sp. Poche, 1926 (Trematoda: Heterophyiidae)

Fig. 2. (A) Adult California giant salamander (Dicamptodon ensatus) found mid-day in a calm pool. Note the emaciated body condition and granular textured skin. Weir Creek, Santa Cruz County, California, USA. Photo credit: L. Erickson. (B) First year larval stage D. ensatus. Note the thin wavy tail with its length longer than the snout to vent length (SVL). Weir Creek, Santa Cruz County, California, USA. Photo credit: L. Erickson (Independent contractor). (C) Second-year larval stage D. ensatus with gross disfiguration and nodules (arrows) present on the gills. Note the cloudy appearance of the eyes (arrowheads). Aldercroft Creek, Santa Clara County, California, USA. Photo credit: S. Fork, (Elkhorn Slough National Estuarine Research Reserve).

Fig. 1 in Morbidity in California giant salamander (Dicamptodon ensatus Eschscholtz, 1833) caused by Euryhelmis sp. Poche, 1926 (Trematoda: Heterophyiidae)

Fig. 1. Collection locations of diseased California giant salamanders (Dicamptodon ensatus) used for post-mortem investigation (U.S. Geological Survey National Wildlife Health Center), subsequent visual encounter surveys (VES) of D. ensatus with (VES Lesions) and without (VES No Lesions) similar clinical skin lesions, and previous visual encounter (CA Herps (https://californiaherps.com/);). D. tenebrosus range estimates according to IUCN (2022) and D. ensatus range estimates according to the California Department of Fish and Wildlife (Gogol-Prokurat, 2016).

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All cause mortality and morbidity from Influenza in the City and the Canton of Zurich, 1910-1970

Contact: PD Dr. Kaspar Staub <a href="mailto:kaspar.staub@iem.uzh.ch">kaspar.staub@iem.uzh.ch</a> For the <a href="http://leaddata.ch">LEAD Hub</a> we digitized and analyzed the following historical demographic and epidemiological data for the city and the canton of Zurich the first time: Since the end of the 19th century, the Federal Health Office (Eidgenössisches Gesundheitsamt) published a <a href="https://swisscovery.slsp.ch/permalink/41SLSP_NETWORK/gp9v4j/alma991049771079705501">weekly bulletin</a> on vital statistics, newly reported cases of notifiable infectious diseases, and hospitalisations. For the period January 1910 to December 1970, we have digitized and transcribed the following weekly series:  <ol> <li>Weekly deaths for residents and non-residents of the city of Zurich. The quality of these historical vital statistics is assessed to be very good in the literature, incompleteness and migration are no longer a problem as compared to earlier years. However, age-, sex- and cause-specific death numbers were not available on the weekly level. </li> <li>Weekly newly reported cases of influenza-like-illness for the canton and the city of Zurich. This series begins with the introduction of the reporting obligation for influenza in the canton of Zürich in mid-July 1918. As these figures do not include mild cases not treated by a doctor and misdiagnoses, they are probably underestimates, but can still track pandemic and seasonal waves. The reporting system and obligation did not change in the observed time period.</li> <li>Weekly new hospitalisation due to influenza in the canton of Zurich. This series ends in 1938. </li> </ol> The original data format in the weekly bulletins are printed, aggregated tables that have been converted into PDFs using a professional book scanner. Transcription of the data was performed by student assistants using a software and running extended quality-controls. The original tables were in German and French, the digitised data set was annotated in English. The digitized data are organized as a spreadsheet and stored in csv format. The data are organized as rows (representing reporting weeks) and columns (see variable list below). For a few weeks, information in the original sources was missing (indicated by 1 in the “interpolated” variable). In these cases, the missing values were interpolated by averaging the numbers of the week before and the week afterwards.  Codebook: Worksheet "Data" <ul> <li>StartReportingPeriod = Start date of the reporting week (dd.mm.yyyy)</li> <li>EndReportingPeriod = End date of reporting week (dd.mm.yyyy)</li> <li>Interpolated: 1=value for this week has been interpolated; 0=not interpolated</li> <li>CityDeathsTotal = Total absolute number of deaths (all-causes) in the City of Zurich (residents and non-residents)</li> <li>CityDeathsResidents = Absolute number of deaths (all-causes) in the City of Zurich for residents</li> <li>CityDeathsNonresidents = Absolute number of deaths (all-causes) in the City of Zurich for non-residents</li> <li>CantonCases = Absolute number of reported new influenza-like-illness cases by physicians in the Canton of Zurich (including the City)</li> <li>CityCases = Absolute number of reported new influenza-like-illness cases by physicians in the City of Zurich</li> <li>CantonHospitalisationsFluInfections = Absolute number of new hospitalisations due to influenza-like-illness in the Canton of Zurich (including the City)</li> </ul> Worksheet "Population" <ul> <li>Yearly population numbers for the City and the Canton of Zurich (<a href="https://hsso.ch">source</a>)</li> </ul>