School of Public Health, Shanxi Medical University, Taiyuan, China.
School of Management, Shanxi Medical University, Taiyuan, China.
Front Public Health. 2023 Jun 21;11:1175869. doi: 10.3389/fpubh.2023.1175869. eCollection 2023.
On September 28, 2022, the first case of Omicron subvariant BF.7 was discovered among coronavirus disease 2019 (COVID-19) infections in Hohhot, China, and then the epidemic broke out on a large scale during the National Day holiday. It is imminently necessary to construct a mathematical model to investigate the transmission dynamics of COVID-19 in Hohhot.
In this study, we first investigated the epidemiological characteristics of COVID-19 cases in Hohhot, including the spatiotemporal distribution and sociodemographic distribution. Then, we proposed a time-varying Susceptible-Quarantined Susceptible-Exposed-Quarantined Exposed-Infected-Asymptomatic-Hospitalized-Removed (SQEIAHR) model to derive the epidemic curves. The next-generation matrix method was used to calculate the effective reproduction number (). Finally, we explored the effects of higher stringency measures on the development of the epidemic through scenario analysis.
Of the 4,889 positive infected cases, the vast majority were asymptomatic and mild, mainly concentrated in central areas such as Xincheng District. People in the 30-59 age group primarily were affected by the current outbreak, accounting for 53.74%, but females and males were almost equally affected (1.03:1). Community screening (35.70%) and centralized isolation screening (26.28%) were the main ways to identify positive infected cases. Our model predicted the peak of the epidemic on October 6, 2022, the dynamic zero-COVID date on October 15, 2022, a number of peak cases of 629, and a cumulative number of infections of 4,963 (95% confidential interval (95%CI): 4,692 ~ 5,267), all four of which were highly consistent with the actual situation in Hohhot. Early in the outbreak, the basic reproduction number () was approximately 7.01 (95%CI: 6.93 ~ 7.09), and then declined sharply to below 1.0 on October 6, 2022. Scenario analysis of higher stringency measures showed the importance of decreasing the transmission rate and increasing the quarantine rate to shorten the time to peak, dynamic zero-COVID and an below 1.0, as well as to reduce the number of peak cases and final affected population.
Our model was effective in predicting the epidemic trends of COVID-19, and the implementation of a more stringent combination of measures was indispensable in containing the spread of the virus.
2022 年 9 月 28 日，在中国呼和浩特，首例奥密克戎变异株 BF.7 新冠病毒感染病例被发现，随后在国庆假期期间疫情大规模爆发。因此，构建一个数学模型来研究呼和浩特新冠病毒的传播动力学是当务之急。
本研究首先调查了呼和浩特新冠病毒病例的流行病学特征，包括时空分布和社会人口分布。然后，我们提出了一个时变的易感-隔离-暴露-隔离-暴露-感染-无症状-住院-移除（SQEIAHR）模型来推导出疫情曲线。下一代矩阵方法用于计算有效繁殖数（）。最后，通过情景分析探讨了更高严格措施对疫情发展的影响。
在 4889 例阳性感染者中，绝大多数为无症状和轻症，主要集中在新城等中心区域。30-59 岁年龄组人群受本次疫情影响最大，占 53.74%，但男女受影响几乎均等（1.03:1）。社区筛查（35.70%）和集中隔离筛查（26.28%）是发现阳性感染者的主要方式。我们的模型预测疫情将于 2022 年 10 月 6 日达到峰值，动态零新冠日期为 2022 年 10 月 15 日，预计峰值病例数为 629 例，累计感染人数为 4963 例（95%置信区间（95%CI）：46925267），这四个结果与呼和浩特的实际情况高度一致。疫情早期，基本繁殖数（）约为 7.01（95%CI：6.937.09），随后在 2022 年 10 月 6 日急剧下降至 1.0 以下。更高严格措施的情景分析表明，降低传播率和提高隔离率对于缩短疫情峰值时间、实现动态零新冠和保持在 1.0 以下、减少峰值病例数和最终受影响人群数量至关重要。
我们的模型能够有效预测新冠疫情的发展趋势，实施更严格的综合措施对于控制病毒传播至关重要。
