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地理流行病学的多维视角：从跨学科学习与研究到以成本效益为导向的决策制定

Multidimensional perspectives of geo-epidemiology: from interdisciplinary learning and research to cost-benefit oriented decision-making.

作者信息

Smith S D, Geraghty E M, Rivas A L, Fasina F O, Kosoy M, Malania L, Hoogesteijn A L, Fair J M

机构信息

Geospatial Research Services, Ithaca, NY, United States.

Esri, Redlands, CA, United States.

出版信息

Front Public Health. 2024 Dec 30;12:1492426. doi: 10.3389/fpubh.2024.1492426. eCollection 2024.

DOI:10.3389/fpubh.2024.1492426
PMID:39807382
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11725565/
Abstract

Research typically promotes two types of outcomes (inventions and discoveries), which induce a virtuous cycle: something suspected or desired (not previously demonstrated) may become known or feasible once a new tool or procedure is invented and, later, the use of this invention may discover new knowledge. Research also promotes the opposite sequence-from new knowledge to new inventions. This bidirectional process is observed in geo-referenced epidemiology-a field that relates to but may also differ from spatial epidemiology. Geo-epidemiology encompasses several theories and technologies that promote inter/transdisciplinary knowledge integration, education, and research in population health. Based on visual examples derived from geo-referenced studies on epidemics and epizootics, this report demonstrates that this field may extract more (geographically related) information than simple spatial analyses, which then supports more effective and/or less costly interventions. Actual (not simulated) bio-geo-temporal interactions (never captured before the emergence of technologies that analyze geo-referenced data, such as geographical information systems) can now address research questions that relate to several fields, such as Network Theory. Thus, a new opportunity arises before us, which exceeds research: it also demands knowledge integration across disciplines as well as novel educational programs which, to be biomedically and socially justified, should demonstrate cost-effectiveness. Grounded on many bio-temporal-georeferenced examples, this report reviews the literature that supports this hypothesis: novel educational programs that focus on geo-referenced epidemic data may help generate cost-effective policies that prevent or control disease dissemination.

摘要

研究通常会产生两种成果（发明和发现），这会形成一个良性循环：一旦发明了新工具或新程序，某些被怀疑或期望的东西（以前未得到证实）可能会变得为人所知或可行，随后，这项发明的应用可能会发现新知识。研究也会推动相反的顺序——从新知识到新发明。这种双向过程在地参考流行病学中可以观察到，这一领域与空间流行病学相关，但也可能有所不同。地流行病学包含多种理论和技术，这些理论和技术促进了人口健康领域的跨学科知识整合、教育和研究。基于从关于流行病和动物流行病的地参考研究中获得的直观示例，本报告表明，与简单的空间分析相比，该领域可以提取更多（与地理相关的）信息，进而支持更有效和/或成本更低的干预措施。实际的（而非模拟的）生物-地理-时间相互作用（在诸如地理信息系统等分析地参考数据的技术出现之前从未被捕捉到）现在可以解决与多个领域相关的研究问题，如网络理论。因此，一个新的机遇摆在我们面前，这一机遇不仅超越了研究范畴：它还要求跨学科的知识整合以及新颖的教育项目，这些项目要在生物医学和社会层面具有合理性，就应证明其成本效益。基于众多生物-时间-地参考示例，本报告回顾了支持这一假设的文献：专注于地参考疫情数据的新颖教育项目可能有助于制定具有成本效益的政策，以预防或控制疾病传播。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93da/11725565/7a03f61a74c8/fpubh-12-1492426-g014.jpg
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