JOURNAL ARTICLE
From ancient pathogens to modern pandemics: Integrating evolutionary, ecological, and sociopolitical dynamics of infectious disease and pandemics through biological anthropology.
Published In: American Journal of Biological Anthropology, 2023, v. 182, n. 4. P. 505 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Kim, Andrew Wooyoung; Agarwal, Sabrina C. 3 of 3
Abstract
This article explores the role of biological anthropology in understanding infectious diseases and pandemics, using the COVID-19 pandemic as an example. It emphasizes the interdisciplinary nature of the field and its ability to shed light on the evolutionary, ecological, and sociopolitical dynamics of pandemics. The article highlights the contributions of various subfields within biological anthropology, such as evolutionary anthropology, bioarcheology, primatology, and human biology, in studying infectious diseases and pandemics. It stresses the importance of taking a holistic approach and integrating different perspectives to analyze the complex dynamics of pandemics throughout history. However, it also acknowledges that the literature on pandemics in biological anthropology is relatively limited compared to the broader study of infectious diseases. The article concludes by discussing the impact of pandemics on marginalized communities and the need to address health inequities. Overall, biological anthropology offers valuable insights into the causes, spread, and effects of pandemics, which are crucial for preparing for future outbreaks. [Extracted from the article]
Additional Information
- Source:American Journal of Biological Anthropology. 2023/12, Vol. 182, Issue 4, p505
- Document Type:Article
- Subject Area:Anthropology
- Publication Date:2023
- ISSN:2692-7691
- DOI:10.1002/ajpa.24869
- Accession Number:173824177
- 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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