Does mammal (or primate) biodiversity impact on the outbreak of viral zoonoses in Africa?
Allbwn ymchwil: Cyfraniad at gynhadledd › Crynodeb › adolygiad gan gymheiriaid
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2020. Ffurflen grynodeb PSGB Spring Meeting 2020, Liverpool, Y Deyrnas Unedig.
Allbwn ymchwil: Cyfraniad at gynhadledd › Crynodeb › adolygiad gan gymheiriaid
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T1 - Does mammal (or primate) biodiversity impact on the outbreak of viral zoonoses in Africa?
AU - Watkins, Holly
AU - Winder, Isabelle C.
N1 - Poster presentation cancelled due to coronavirus; abstracts published in Primate Eye instead.
PY - 2020/4
Y1 - 2020/4
N2 - Zoonotic diseases are threatening public health worldwide. The Ebola outbreak in western Africa from 2013 to 2016, for instance, is estimated to have killed 40% of those infected and caused the deaths of>11,000 people. Biodiversity seems to be linked to disease prevalence and distribution, though the mechanisms via which biodiversity impacts on disease outbreaks are not well understood. Increasing human activity has, however, already facilitated the spread of pathogens between humans and both wild and domestic animals, so understanding the relationships between biodiversity and zoonotic disease outbreaks is imperative. This study aimed to determine the relationship between biodiversity and outbreaks of seven distinct viral zoonoses in Africa, with a focus on the link between disease outbreaks and primate diversity. Non-human primates, being closely related to humans, may be particularly likely to pass pathogens to their human neighbours. The locations of zoonotic disease outbreaks were compiled from primary literature and from the World Health Organisation (WHO). Niche models were created in MaxEnt for each of our selected diseases using different combinations of abiotic and biotic variables. The construction of these models allowed us to determine the way biodiversity effected disease distribution, and the different groups of species that are important to the distribution of each disease. High human pressure was found to increase the likelihood of disease occurrence in all instances. Primate diversity was deemed important for many diseases, though medium to low primate diversity had the higher risk of disease occurrence. Further work is necessary to determine specific groups of species that are important predictors of each disease.
AB - Zoonotic diseases are threatening public health worldwide. The Ebola outbreak in western Africa from 2013 to 2016, for instance, is estimated to have killed 40% of those infected and caused the deaths of>11,000 people. Biodiversity seems to be linked to disease prevalence and distribution, though the mechanisms via which biodiversity impacts on disease outbreaks are not well understood. Increasing human activity has, however, already facilitated the spread of pathogens between humans and both wild and domestic animals, so understanding the relationships between biodiversity and zoonotic disease outbreaks is imperative. This study aimed to determine the relationship between biodiversity and outbreaks of seven distinct viral zoonoses in Africa, with a focus on the link between disease outbreaks and primate diversity. Non-human primates, being closely related to humans, may be particularly likely to pass pathogens to their human neighbours. The locations of zoonotic disease outbreaks were compiled from primary literature and from the World Health Organisation (WHO). Niche models were created in MaxEnt for each of our selected diseases using different combinations of abiotic and biotic variables. The construction of these models allowed us to determine the way biodiversity effected disease distribution, and the different groups of species that are important to the distribution of each disease. High human pressure was found to increase the likelihood of disease occurrence in all instances. Primate diversity was deemed important for many diseases, though medium to low primate diversity had the higher risk of disease occurrence. Further work is necessary to determine specific groups of species that are important predictors of each disease.
M3 - Abstract
T2 - PSGB Spring Meeting 2020
Y2 - 23 April 2020 through 24 April 2020
ER -