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为何性别和性征在传染病建模中至关重要:一个概念框架

Why gender and sex matter in infectious disease modelling: A conceptual framework.

作者信息

Auderset Diane, Riou Julien, Clair Carole, Perreau Matthieu, Mueller Yolanda, Schwarz Joëlle

机构信息

Faculty of Health Sciences, Simon Fraser University, Burnaby, Canada.

Gender and Health Unit, Department of Ambulatory Care, Unisanté, Centre for Primary Care and Public Health & University of Lausanne, Lausanne, Switzerland.

出版信息

SSM Popul Health. 2025 Mar 12;30:101775. doi: 10.1016/j.ssmph.2025.101775. eCollection 2025 Jun.

Abstract

The COVID-19 pandemic underscored the differential impact of infectious diseases across population groups, with gender and sex identified as important dimensions influencing transmission and health outcomes. Sex-related biological factors, such as differences in immune response and comorbidities, contribute to men's heightened severity risks, while gender norms and roles influence exposure patterns, adherence to prevention measures, and healthcare access, influencing women's higher reported infection rates in certain contexts. Despite widely observed gender/sex disparities, infectious disease models frequently overlook gender and sex as key dimensions, leading to gaps in understanding and potential blind spots in public health interventions. This paper develops a conceptual framework based on the Susceptible-Exposed-Infectious-Recovered/Deceased (SEIR/D) compartmental model to map pathways through which gender and sex may influence susceptibility, exposure, transmission, recovery, and mortality. Using a narrative review of modelling, epidemiological, and clinical studies, this framework identifies and characterises the main social and biological mechanisms on this matter-including gendered occupational exposure, differential adherence to preventive measures, and disparities in healthcare-seeking behaviour-alongside sex-based differences in immune response and disease severity. The framework also examines potential gender-related variations in epidemiological surveillance data, highlighting disparities in testing uptake and hospitalisation referrals that could influence model outputs. By synthesising these insights, this paper provides a theoretical foundation for integrating gender and sex into infectious disease models. It advocates for interdisciplinary collaboration between modellers, social scientists, and clinicians to advance gender- and sex-sensitive modelling approaches. Accounting for gender and sex can enhance predictive accuracy, inform intervention strategies, and promote health equity in pandemic response.

摘要

新冠疫情凸显了传染病在不同人群中的差异影响,性别被确定为影响传播和健康结果的重要因素。与性别相关的生物学因素,如免疫反应和合并症的差异,导致男性面临更高的重症风险,而性别规范和角色则影响接触模式、对预防措施的遵守情况以及医疗保健的可及性,在某些情况下导致女性报告的感染率较高。尽管性别差异普遍存在,但传染病模型常常忽视性别这一关键因素,导致在理解上存在差距以及公共卫生干预中可能出现盲点。本文基于易感-暴露-感染-康复/死亡(SEIR/D)分区模型开发了一个概念框架,以描绘性别可能影响易感性、暴露、传播、康复和死亡率的途径。通过对建模、流行病学和临床研究的叙述性综述,该框架识别并描述了这一问题上的主要社会和生物学机制,包括按性别划分的职业暴露、对预防措施的不同遵守情况以及就医行为的差异,以及免疫反应和疾病严重程度方面基于性别的差异。该框架还研究了流行病学监测数据中潜在的与性别相关的差异,强调了检测接受率和住院转诊方面的差异,这些差异可能影响模型输出。通过综合这些见解,本文为将性别因素纳入传染病模型提供了理论基础。它倡导建模人员、社会科学家和临床医生之间开展跨学科合作,以推进对性别敏感的建模方法。考虑性别因素可以提高预测准确性,为干预策略提供信息,并在应对疫情中促进健康公平。

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