Long-term effects of non-pharmaceutical interventions on total disease burden in parsimonious epidemiological models

IF 1.9 4区 数学 Q2 BIOLOGY Journal of Theoretical Biology Pub Date : 2024-04-09 DOI:10.1016/j.jtbi.2024.111817
Tak Fung , Jonah Goh , Ryan A. Chisholm
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Abstract

The recent global COVID-19 pandemic resulted in governments enacting non-pharmaceutical interventions (NPIs) targeted at reducing transmission of SARS-CoV-2. But the NPIs also affected the transmission of viruses causing non-target seasonal respiratory diseases, including influenza and respiratory syncytial virus (RSV). In many countries, the NPIs were found to reduce cases of such seasonal respiratory diseases, but there is also evidence that subsequent relaxation of NPIs led to outbreaks of these diseases that were larger than pre-pandemic ones, due to the accumulation of susceptible individuals prior to relaxation. Therefore, the net long-term effects of NPIs on the total disease burden of non-target diseases remain unclear. Knowledge of this is important for infectious disease management and maintenance of public health. In this study, we shed light on this issue for the simplified scenario of a set of NPIs that prevent or reduce transmission of a seasonal respiratory disease for about a year and are then removed, using mathematical analyses and numerical simulations of a suite of four epidemiological models with varying complexity and generality. The model parameters were estimated using empirical data pertaining to seasonal respiratory diseases and covered a wide range. Our results showed that NPIs reduced the total disease burden of a non-target seasonal respiratory disease in the long-term. Expressed as a percentage of population size, the reduction was greater for larger values of the basic reproduction number and the immunity loss rate, reflecting larger outbreaks and hence more infections averted by imposition of NPIs. Our study provides a foundation for exploring the effects of NPIs on total disease burden in more-complex scenarios.

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非药物干预对准流行病学模型中疾病总负担的长期影响
最近在全球范围内流行的 COVID-19 导致各国政府颁布了旨在减少 SARS-CoV-2 传播的非药物干预措施(NPIs)。但是,非药物干预措施也影响了导致非目标季节性呼吸道疾病的病毒传播,包括流感和呼吸道合胞病毒(RSV)。在许多国家,非传染性疾病预防措施减少了此类季节性呼吸道疾病的病例,但也有证据表明,由于在非传染性疾病预防措施放宽前易感人群的积累,非传染性疾病预防措施随后的放宽导致这些疾病的爆发比流行前更大。因此,非传染性疾病对非目标疾病总疾病负担的长期净影响仍不清楚。了解这一点对于传染病管理和维护公共卫生非常重要。在本研究中,我们通过对复杂程度和通用性各不相同的四种流行病学模型进行数学分析和数值模拟,针对一组非传染性疾病(NPIs)在一年左右的时间内阻止或减少一种季节性呼吸道疾病的传播,然后将其去除的简化情景,阐明了这一问题。模型参数是利用与季节性呼吸道疾病有关的经验数据估算的,涵盖范围很广。我们的研究结果表明,长期来看,非传染性疾病减少了非目标季节性呼吸道疾病的总疾病负担。以占人口数量的百分比表示,基本繁殖数和免疫力丧失率的数值越大,减少的疾病负担就越大,这反映了更大规模的疾病爆发,因此通过实施非传染性疾病预防措施可以避免更多的感染。我们的研究为探索非传染性疾病在更复杂情况下对疾病总负担的影响奠定了基础。
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来源期刊
CiteScore
4.20
自引率
5.00%
发文量
218
审稿时长
51 days
期刊介绍: The Journal of Theoretical Biology is the leading forum for theoretical perspectives that give insight into biological processes. It covers a very wide range of topics and is of interest to biologists in many areas of research, including: • Brain and Neuroscience • Cancer Growth and Treatment • Cell Biology • Developmental Biology • Ecology • Evolution • Immunology, • Infectious and non-infectious Diseases, • Mathematical, Computational, Biophysical and Statistical Modeling • Microbiology, Molecular Biology, and Biochemistry • Networks and Complex Systems • Physiology • Pharmacodynamics • Animal Behavior and Game Theory Acceptable papers are those that bear significant importance on the biology per se being presented, and not on the mathematical analysis. Papers that include some data or experimental material bearing on theory will be considered, including those that contain comparative study, statistical data analysis, mathematical proof, computer simulations, experiments, field observations, or even philosophical arguments, which are all methods to support or reject theoretical ideas. However, there should be a concerted effort to make papers intelligible to biologists in the chosen field.
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