Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, MD, USA.
Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT, USA.
Nat Microbiol. 2019 Oct;4(10):1612-1619. doi: 10.1038/s41564-019-0565-8. Epub 2019 Sep 20.
The continued growth of the world's population and increased interconnectivity heighten the risk that infectious diseases pose for human health worldwide. Epidemiological modelling is a tool that can be used to mitigate this risk by predicting disease spread or quantifying the impact of different intervention strategies on disease transmission dynamics. We illustrate how four decades of methodological advances and improved data quality have facilitated the contribution of modelling to address global health challenges, exemplified by models for the HIV crisis, emerging pathogens and pandemic preparedness. Throughout, we discuss the importance of designing a model that is appropriate to the research question and the available data. We highlight pitfalls that can arise in model development, validation and interpretation. Close collaboration between empiricists and modellers continues to improve the accuracy of predictions and the optimization of models for public health decision-making.
随着世界人口的持续增长和相互联系的日益紧密,传染病对全球人类健康构成的威胁越来越大。流行病学建模是一种可以通过预测疾病传播或量化不同干预策略对疾病传播动态的影响来降低这种风险的工具。我们举例说明了方法学的进步和数据质量的提高如何促进了建模在解决全球卫生挑战方面的作用,其中包括 HIV 危机、新出现的病原体和大流行防范模型。在整个过程中,我们讨论了设计适合研究问题和可用数据的模型的重要性。我们强调了模型开发、验证和解释中可能出现的陷阱。经验主义者和建模者之间的密切合作继续提高预测的准确性和优化公共卫生决策的模型。