Mathematical modeling of contact tracing and stability analysis to inform its impact on disease outbreaks; an application to COVID-19

IF 8.8 3区 医学 Q1 Medicine Infectious Disease Modelling Pub Date : 2024-02-02 DOI:10.1016/j.idm.2024.01.010
Mohamed Ladib , Aziz Ouhinou , Abdul-Aziz Yakubu
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Abstract

We develop a mathematical model to investigate the effect of contact tracing on containing epidemic outbreaks and slowing down the spread of transmissible diseases. We propose a discrete-time epidemic model structured by disease-age which includes general features of contact tracing. The model is fitted to data reported for the early spread of COVID-19 in South Korea, Brazil, and Venezuela. The calibrated values for the contact tracing parameters reflect the order pattern observed in its performance intensity within the three countries. Using the fitted values, we estimate the effective reproduction number Re and investigate its responses to varied control scenarios of contact tracing. Alongside the positivity of solutions, and a stability analysis of the disease-free equilibrium are provided.

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接触者追踪的数学建模和稳定性分析,以了解其对疾病爆发的影响;对 COVID-19 的应用
我们建立了一个数学模型来研究接触追踪对遏制流行病爆发和减缓传染性疾病传播的影响。我们提出了一个以疾病年龄为结构的离散时间流行病模型,其中包含接触追踪的一般特征。该模型适用于 COVID-19 在韩国、巴西和委内瑞拉早期传播的数据。接触追踪参数的校准值反映了在这三个国家中观察到的其表现强度的顺序模式。利用拟合值,我们估算了有效繁殖数 Re,并研究了它对不同接触追踪控制方案的反应。同时还提供了解决方案的正向性以及无疾病平衡的稳定性分析。
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来源期刊
Infectious Disease Modelling
Infectious Disease Modelling Mathematics-Applied Mathematics
CiteScore
17.00
自引率
3.40%
发文量
73
审稿时长
17 weeks
期刊介绍: Infectious Disease Modelling is an open access journal that undergoes peer-review. Its main objective is to facilitate research that combines mathematical modelling, retrieval and analysis of infection disease data, and public health decision support. The journal actively encourages original research that improves this interface, as well as review articles that highlight innovative methodologies relevant to data collection, informatics, and policy making in the field of public health.
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