{ "abstract": "Background: Global distribution of human resources for health (HRH) is highly unequal and less resourced regions may particularly be vulnerable to disastrous emergencies. We examined HRH losses attributable to epidemics of infectious diseases, both globally and geographically. Methods and findings: First, using 30-year ecological data from the 1990 to 2019 records at international Emergency Events Database and HRH density statistics from the Global Burden of Disease study, we extracted estimates of annual country-specific epidemic events and cadre-specific HRH density data across 194 countries and territories. The association between the number of epidemics and HRH density (number of HRH per 10,000 population) was established using the Generalized Estimating Equation model, adjusted for geographic and socioeconomic status. Second, based on the country- and year-specific number of epidemics, HRH density, and epidemic-HRH density associations, we further estimated the annual average absolute number of HRH losses and the average relative number of HRH losses per 10,000 HRHs that can be attributed to epidemic events, globally, by region, and by country. Conclusions: Epidemics of infectious diseases are associated with HRH losses globally, particularly in low- and middle-income countries, further aggravating the global inequity in the health workforce. Why was this study done?: What did the researchers do and find?: What do these findings mean?: Manman Chen, Wanzhou Wang and colleagues examined how infectious disease epidemics were associated with changes in the health workforce across 194 countries and territories from 1990 to 2019. Their findings suggest that epidemic events were linked to health workforce losses worldwide, with the largest relative impacts observed in low- and middle-income countries.", "abstract_shown": true, "affiliations": [ "School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China", "National Institute of Health Data Science, Peking University, Beijing, China", "Center for Digital Health and Artificial Intelligence, Peking University First Hospital, Beijing, China", "Department of Computational Biology and Medical Big Data, Faculty of Computer Science and Artificial Intelligence, Shenzhen University of Advanced Technology, Shenzhen, Guangdong, China", "Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China", "School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China", "Renal Division, Department of Medicine, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China", "School of Economics and Management, Harbin Institute of Technology, Harbin, China", "School of Disaster and Emergency Medicine, Tianjin University, Tianjin, China" ], "article_type": "Research Article", "arxiv": null, "author_total": 10, "authors": [ { "affs": [ 0 ], "name": "Manman Chen" }, { "affs": [ 1 ], "name": "Wanzhou Wang" }, { "affs": [ 2 ], "name": "Feng Sha" }, { "affs": [ 3 ], "name": "Zichen Ye" }, { "affs": [ 4 ], "name": "Yuankai Zhao" }, { "affs": [ 5 ], "name": "Chao Yang" }, { "affs": [ 6 ], "name": "Ze Liang" }, { "affs": [ 7 ], "name": "Yu Jiang" }, { "affs": [ 8 ], "name": "Xijie Wang" }, { "name": "Jinling Tang" } ], "bibtex": "https://research.draconitic.com/paper/4ppxdwpfpph9s.bib", "cited_by": 0, "doi": "10.1371/journal.pmed.1005134", "fulltext_url": "https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1005134", "id": "4ppxdwpfpph9s", "issns": [ "1549-1676" ], "landing_url": "https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1005134", "language": null, "licence": "CC-BY-4.0", "licence_label": "CC BY 4.0", "licence_source": "journal", "licence_url": "https://creativecommons.org/licenses/by/4.0/", "metadata_licence": null, "native_subjects": [ [ "openalex", "3604|Global Health Workforce Issues" ], [ "plos", "/Earth sciences/Geography/Human geography/Social geography" ], [ "plos", "/Medicine and health sciences/Critical care and emergency medicine" ], [ "plos", "/Medicine and health sciences/Epidemiology/Infectious disease epidemiology" ], [ "plos", "/Medicine and health sciences/Epidemiology/Spatial epidemiology" ], [ "plos", "/Medicine and health sciences/Health care/Socioeconomic aspects of health" ], [ "plos", "/Medicine and health sciences/Medical conditions/Infectious diseases/Infectious disease epidemiology" ], [ "plos", "/Medicine and health sciences/Public and occupational health/Global health" ], [ "plos", "/Medicine and health sciences/Public and occupational health/Socioeconomic aspects of health" ], [ "plos", "/People and places/Geographical locations/Africa" ], [ "plos", "/People and places/Geographical locations/Asia" ], [ "plos", "/Social sciences/Human geography/Social geography" ] ], "openalex": "W7214015008", "pdf_url": "https://journals.plos.org/plosmedicine/article/file?id=10.1371/journal.pmed.1005134&type=printable", "pmcid": null, "pmid": null, "published": "2026-09-22", "publisher": "Public Library of Science", "ris": "https://research.draconitic.com/paper/4ppxdwpfpph9s.ris", "sources": [ { "first_seen": "2026-10-30T12:17:43Z", "native_id": "10.1371/journal.pmed.1005134", "source": "plos", "url": "https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1005134" } ], "subjects": [ { "field": "medicine", "origin": "plos:epidemiology", "subfield": "epidemiology-public-health" } ], "title": "Global, regional, and national impact of epidemic disasters on health workforce equality between 1990 and 2019: An ecological and modeling study", "title_text": "Global, regional, and national impact of epidemic disasters on health workforce equality between 1990 and 2019: An ecological and modeling study", "type": "peer-reviewed", "updated_at": "2026-10-30T12:17:43Z", "url": "https://research.draconitic.com/paper/4ppxdwpfpph9s", "venue": "PLOS Medicine", "versions": [] }