Department of Biology, Carleton University, 1125 Colonel By Drive, Ottawa, ON, K1S 5B6, Canada.
Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, 960 Carling Avenue, Ottawa, ON, K1A 0C6, Canada.
BMC Infect Dis. 2024 Oct 24;24(1):1198. doi: 10.1186/s12879-024-10017-8.
Mathematical modelling of (re)emerging infectious respiratory diseases among humans poses multiple challenges for modellers, which can arise as a result of limited data and surveillance, uncertainty in the natural history of the disease, as well as public health and individual responses to outbreaks. Here, we propose a COVID-19-inspired health state diagram (HSD) to serve as a foundational framework for conceptualising the modelling process for (re)emerging respiratory diseases, and public health responses, in the early stages of their emergence. The HSD aims to serve as a starting point for reflection on the structure and parameterisation of a transmission model to assess the impact of the (re)emerging disease and the capacity of public health interventions to control transmission. We also explore the adaptability of the HSD to different (re)emerging diseases using the characteristics of three respiratory diseases of historical public health importance. We outline key questions to contemplate when applying and adapting this HSD to (re)emerging infectious diseases and provide reflections on adapting the framework for public health-related interventions.
人类新发呼吸道传染病的数学建模给建模者带来了诸多挑战,这些挑战可能源于数据和监测的局限性、疾病自然史的不确定性,以及公共卫生和个人对疫情的反应。在这里,我们提出了一个基于 COVID-19 的健康状态图(HSD),作为一个概念化框架,用于在新发呼吸道传染病及其公共卫生应对措施出现的早期阶段,对建模过程进行概念化。HSD 的目的是作为对传输模型的结构和参数化进行反思的起点,以评估新发疾病的影响和公共卫生干预措施控制传播的能力。我们还使用历史上具有重要公共卫生意义的三种呼吸道疾病的特征,探讨了 HSD 对不同新发疾病的适应性。我们概述了在应用和调整该 HSD 以应对新发传染病时需要考虑的关键问题,并对调整该框架以适应与公共卫生相关的干预措施进行了思考。