JOURNAL ARTICLE

Primates and pandemics: A biocultural approach to understanding disease transmission in human and nonhuman primates.

  • Published In: American Journal of Biological Anthropology, 2023, v. 182, n. 4. P. 595 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Radhakrishna, Sindhu 3 of 3

Abstract

Investigations into zoonotic disease outbreaks have been largely epidemiological and microbiological, with the primary focus being one of disease control and management. Increasingly though, the human–animal interface has proven to be an important driver for the acquisition and transmission of pathogens in humans, and this requires syncretic bio‐socio‐cultural enquiries into the origins of disease emergence, for more efficacious interventions. A biocultural lens is imperative for the examination of primate‐related zoonoses, for the human‐primate interface is broad and multitudinous, involving both physical and indirect interactions that occur due to shared spaces and ecologies. I use the case example of a viral zoonotic epidemic that is currently endemic to India, the Kysanaur Forest Disease, to show how biocultural anthropology provides a broad and integrative perspective into infectious disease ecology and presents new insights into the determinants of disease outbreaks. Drawing on insights from epidemiology, political ecology, primate behavioral ecology and ethnoprimatology, this paper demonstrates how human‐primate interactions and shared ecologies impact infectious disease spread between human and nonhuman primate groups. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:American Journal of Biological Anthropology. 2023/12, Vol. 182, Issue 4, p595
  • Document Type:Article
  • Subject Area:Life Sciences
  • Publication Date:2023
  • ISSN:2692-7691
  • DOI:10.1002/ajpa.24613
  • Accession Number:173824170
  • Copyright Statement:Copyright of American Journal of Biological Anthropology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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