摘要
目的 对新型冠状病毒(简称新冠病毒)感染疫情流行态势进行预测分析,为完善新冠病毒感染疫情防控措施提供参考依据。方法 收集深圳市龙岗区2022年12月报告的每日新冠病毒感染病例数据,采用综合考虑疫苗接种、年龄构成的多组传播动力学模型进行模拟,估算感染率及感染高峰时间,预测龙岗区未来新冠病毒感染疫情流行趋势。结果 多组传播动力学模型计算结果及曲线拟合结果显示,模型与实际数据拟合效果较好(R~2=0.916,P<0.001)。预测结果显示本起疫情有效再生数(effective reproduction number, Reff)为7.13,人群累计感染率为95.46%,日感染高峰值为24.57万例,74.95%的人群感染后出现症状,日发病高峰值为15.82万例;龙岗区11个街道的人群感染率均已超过90%,其中南湾街道的Reff最高(10.20),其次是平湖街道(9.60)。结论 多组传播动力学模型可以较好地拟合与预测龙岗区新冠病毒的感染情况及感染高峰时间,为疫情防控决策的制定提供参考依据。
Objective To predict and analyze the epidemic situation of COVID-19 for reference to improve the preven-tion and control measures for this pandemic.Methods Daily data of COVID-19 reported in Longgang District of Shenzhen City in December 2022 were collected.A multi-group transmission dynamics model with comprehensive con-sideration of the vaccination and age composition was used to establish a simulation model to estimate the infection rate,peak time of infection and following trend of the pandemic in Longgang District.Results The calculation results and curve fitting results of multiple transmission dynamic models showed that the model fitted the actual data well(R2=0.916,P<0.001).The prediction results revealed that the effective regeneration number(Reff)was 7.13 for this pandemic,and the cumulative infection rate was 95.46%for the population.The daily peak infection was 245700 cases,and 74.95%of the population exhibited symptoms after infection.The daily peak incidence was 158200 cases.The infection rate of the population in all 11 communities in Longgang District exceeded 90%,and the highest Reff(10.20)was seen in Nan-wan community,followed by Pinghu community(9.60).Conclusion The multiple group transmission dynamics mod-el can better fit and predict the infection status and peak time of COVID-19 in Longgang District,which can provide a reference for the decision-making in prevention and control of COVID-19 pandemic.
作者
俞国龙
陈思婷
刘峰
林海端
叶碧莉
谢显清
金玉娟
YU Guolong;CHEN Siting;LIU Feng;LIN Haiduan;YE Bili;XIE Xianqing;JIN Yujuan(Longgang District Center for Disease Control and Prevention,Shenzhen 518172,Guangdong Province,China;Longgang District Longcheng Public Health Service Center)
出处
《热带病与寄生虫学》
CAS
2023年第6期338-343,共6页
Journal of Tropical Diseases and Parasitology
基金
深圳市龙岗区2020年度医疗卫生科技计划项目(LGKCYLWS20200164)
深圳市龙岗区“新型冠状病毒感染应急防治”技术攻关专项扶持项目(LGKCXGZX2020003)。
