Occurrence of Capillaria sp. in the liver of sheep (Ovis aries ) in a slaughterhouse in the state of Acre, Brazil

Teixeira, Paulo Eduardo Ferlini; Corrêa, Christiane Leal; Oliveira, Fernanda Bittencourt de; Alencar, Alba Cristina Miranda de Barros; Neves, Leandro Batista das; Daipert-Garcia, Daniel; Almeida, Fernanda Barbosa de; Muniz-Pereira, Luís C.; Machado-Silva, José Roberto; Rodrigues-Silva, Rosângela

doi:10.1590/s1984-296120180030

Cited by 2 publications

(1 citation statement)

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“…Calodium hepaticum ), is a globally distributed zoonotic parasite which uses rodents as main hosts, and while it is known to cause infection in over 180 mammalian species, a recent review of hosts did not include domesticated sheep ( 26 ). However, a recent study of Capillaria in Brazil identified two cases which were possibly caused by C. hepatica ( 115 ).…”

Section: Supplementary Resultsmentioning

confidence: 99%

Predicting missing links in global host-parasite networks

Farrell

Elmasri

Stephens

et al. 2020

Preprint

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Parasites that infect multiple species cause major health burdens globally, but 1 for many, the full suite of susceptible hosts is unknown. Proactive disease 2 surveillance involves gathering host-parasite association data, predicting miss-3 ing links, and targeting efforts towards the most likely undocumented interac-4 tions. Using the largest global network of mammal host-parasite interactions 5 amalgamated to date (>29,000 interactions), we predict undocumented links 6 and conduct targeted literature searches. We find evidence for many of the 7 top "missing" links, including parasites of humans, domesticated animals, and 8 endangered wildlife, and identify regions such as tropical and central Amer-9 ica as likely hotspots of undocumented associations. This approach of iterated 10 prediction and targeted surveillance may help reduce disease burdens by iden-11 tifying undocumented reservoir species, cryptic transmission pathways, and 12 predicting future host-parasite interactions. 14Most disease-causing organisms of humans and domesticated animals can infect multiple species 15 (1, 2), which has ramifications for biodiversity conservation (3) and human health via direct 16 infection, food insecurity, and diminished livelihoods (4). The human burden of multi-host dis-17 eases falls largely on the world's poor livestock keepers (5), many of which live in biodiversity 18 hotspots (6) where resources for disease surveillance and reporting are lacking (7). Despite the 19 severe burdens they impose, we do not know the full range of susceptible host species for the 20 majority of infectious organisms (8). For a given parasite, knowledge of susceptible hosts is 21 critical for understanding disease spread and persistence in multi-host systems (9). Predicting 22 the suite of potential host species for known infectious diseases may also allow for more effec-23 tive disease control and eradication, rapid response following disease emergence (i.e. increases 24 in prevalence, geographic spread, or infection of novel host species), and reducing the risk of 25 disease spillover through limiting cross-species contact of potential hosts (10,11,12,13). 26While investigation into the specific ecologies, potential reservoirs, and susceptible hosts 27 often takes place after infectious organisms have emerged as public health threats, iterative pre-28 diction and verification of likely host species provides one approach to surveillance that can 29 strengthen capacities for disease monitoring and control of multi-host pathogens before emer-30 gence (14). By predicting undocumented host species for known infectious diseases, we can ef-31 ficiently gather baseline knowledge of the diversity of host-parasite interactions, ultimately sup-32 porting the development of fundamental theory in disease ecology and evolution, and strength-33 ening disease control and surveillance for multi-host pathogens. This form of proactive disease 34 surveillance involves synthesizing current knowledge of host-parasite associations, identifying 35 gaps, pr...

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Section: Supplementary Resultsmentioning

confidence: 99%