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Yang M, Ma W, Jiang J, Lu Z, Wang X, Shen Y, Zou H, Meng X. COVID-19 vaccination and concerns regarding vaccine hesitancy after the termination of the zero-COVID policy in China: A nationwide cross-sectional study. Hum Vaccin Immunother 2024; 20:2388938. [PMID: 39140437 PMCID: PMC11326449 DOI: 10.1080/21645515.2024.2388938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Revised: 07/18/2024] [Accepted: 08/02/2024] [Indexed: 08/15/2024] Open
Abstract
COVID-19 vaccine hesitancy remains prevalent globally. However, national data on this issue in the general population after the termination of the zero-COVID policy in China are limited. In March 2023, we conducted a nationwide cross-sectional survey among Chinese adults using a self-administered questionnaire. Descriptive statistics and multivariate logistic regressions were employed. Among 4,966 participants, 43.8% reported COVID-19 vaccine hesitancy following the end of the zero-COVID policy in China. Higher rates of vaccine hesitancy were associated with being married (married: OR 1.36, 95%CI 1.17-1.57; other marital status: OR 1.86, 95%CI 1.36-2.55), working in healthcare (OR 1.64, 95%CI 1.38-1.96), having both minors and older adults in the household (OR 1.45, 95%CI 1.20-1.75), having no minors and older adults in the household (OR 1.44, 95%CI 1.17-1.77), having chronic diseases (OR 1.42, 95%CI 1.23-1.64), experiencing adverse events post-vaccination (OR 1.39, 95%CI 1.19-1.61), and uncertainty about previous COVID-19 infection (OR 1.45, 95%CI 1.13-1.86). Conversely, participants who had received the influenza vaccine in the past three years (OR 0.62, 95%CI 0.54-0.72), had previously taken the COVID-19 vaccine (OR 0.44, 95%CI 0.32-0.59), and had higher confidence in vaccines (OR 0.63, 95%CI 0.60-0.67) were less likely to exhibit hesitancy. Our findings indicate a significant level of vaccine hesitancy, underscoring the urgent need for tailored public health strategies to address vaccine hesitancy and improve uptake post-zero-COVID policy in China. A comprehensive understanding of public concerns and related factors is essential for developing effective vaccine communication strategies.
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Affiliation(s)
- Min Yang
- Wuxi Center for Disease Control and Prevention, The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University, Wuxi, China
| | - Wenjuan Ma
- Wuxi Center for Disease Control and Prevention, The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University, Wuxi, China
| | - Jingfeng Jiang
- Wuxi Center for Disease Control and Prevention, The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University, Wuxi, China
| | - Zhen Lu
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, China
| | - Xuwen Wang
- Wuxi Center for Disease Control and Prevention, The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University, Wuxi, China
| | - Yuan Shen
- Wuxi Center for Disease Control and Prevention, The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University, Wuxi, China
| | - Huachun Zou
- School of Public Health, Fudan University, Shanghai, China
| | - Xiaojun Meng
- Wuxi Center for Disease Control and Prevention, The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University, Wuxi, China
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Qu L, Xie C, Qiu M, Yi L, Liu Z, Zou L, Hu P, Jiang H, Lian H, Yang M, Yang H, Zeng H, Chen H, Zhao J, Xiao J, He J, Yang Y, Chen L, Li B, Sun J, Lu J. Characterizing Infections in Two Epidemic Waves of SARS-CoV-2 Omicron Variants: A Cohort Study in Guangzhou, China. Viruses 2024; 16:649. [PMID: 38675989 PMCID: PMC11053513 DOI: 10.3390/v16040649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Revised: 04/06/2024] [Accepted: 04/17/2024] [Indexed: 04/28/2024] Open
Abstract
BACKGROUND After the adjustment of COVID-19 epidemic policy, mainland China experienced two consecutive waves of Omicron variants within a seven-month period. In Guangzhou city, as one of the most populous regions, the viral infection characteristics, molecular epidemiology, and the dynamic of population immunity are still elusive. METHODS We launched a prospective cohort study in the Guangdong Provincial CDC from December 2022 to July 2023. Fifty participants who received the same vaccination regimen and had no previous infection were recruited. RESULTS 90% of individuals were infected with Omicron BA.5* variants within three weeks in the first wave. Thirteen cases (28.26%) experienced infection with XBB.1* variants, occurring from 14 weeks to 21 weeks after the first wave. BA.5* infections exhibited higher viral loads in nasopharyngeal sites compared to oropharyngeal sites. Compared to BA.5* infections, the XBB.1* infections had significantly milder clinical symptoms, lower viral loads, and shorter durations of virus positivity. The infection with the BA.5* variant elicited varying levels of neutralizing antibodies against XBB.1* among different individuals, even with similar levels of BA.5* antibodies. The level of neutralizing antibodies specific to XBB.1* determined the risk of reinfection. CONCLUSIONS The rapid large-scale infections of the Omicron variants have quickly established herd immunity among the population in mainland China. In the future of the COVID-19 epidemic, a lower infection rate but a longer duration can be expected. Given the large population size and ongoing diversified herd immunity, it remains crucial to closely monitor the molecular epidemiology of SARS-CoV-2 for the emergence of new variants of concern in this region. Additionally, the timely evaluation of the immune status across different age groups is essential for informing future vaccination strategies and intervention policies.
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Affiliation(s)
- Lin Qu
- School of Public Health, Sun Yat-sen University, Guangzhou 510080, China; (L.Q.); (M.Q.); (H.Y.)
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; (L.Z.); (J.H.); (B.L.)
| | - Chunyan Xie
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; (L.Z.); (J.H.); (B.L.)
- School of Basic Medicine and Public Health, Jinan University, Guangzhou 510632, China
| | - Ming Qiu
- School of Public Health, Sun Yat-sen University, Guangzhou 510080, China; (L.Q.); (M.Q.); (H.Y.)
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; (L.Z.); (J.H.); (B.L.)
| | - Lina Yi
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; (L.Z.); (J.H.); (B.L.)
| | - Zhe Liu
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; (L.Z.); (J.H.); (B.L.)
| | - Lirong Zou
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; (L.Z.); (J.H.); (B.L.)
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China;
| | - Pei Hu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China;
| | - Huimin Jiang
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; (L.Z.); (J.H.); (B.L.)
- School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Huimin Lian
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; (L.Z.); (J.H.); (B.L.)
- School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Mingda Yang
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; (L.Z.); (J.H.); (B.L.)
- School of Basic Medicine and Public Health, Jinan University, Guangzhou 510632, China
| | - Haiyi Yang
- School of Public Health, Sun Yat-sen University, Guangzhou 510080, China; (L.Q.); (M.Q.); (H.Y.)
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; (L.Z.); (J.H.); (B.L.)
| | - Huiling Zeng
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; (L.Z.); (J.H.); (B.L.)
- School of Public Health, Guangdong Pharmaceutical University, Guangzhou 510310, China
| | - Huimin Chen
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; (L.Z.); (J.H.); (B.L.)
- School of Basic Medicine and Public Health, Jinan University, Guangzhou 510632, China
| | - Jianguo Zhao
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
| | - Jianpeng Xiao
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
| | - Jianfeng He
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; (L.Z.); (J.H.); (B.L.)
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China;
| | - Ying Yang
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
| | - Liang Chen
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
| | - Baisheng Li
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; (L.Z.); (J.H.); (B.L.)
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China;
| | - Jiufeng Sun
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; (L.Z.); (J.H.); (B.L.)
| | - Jing Lu
- School of Public Health, Sun Yat-sen University, Guangzhou 510080, China; (L.Q.); (M.Q.); (H.Y.)
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; (L.Z.); (J.H.); (B.L.)
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Wang JL, Xiao XL, Zhang FF, Pei X, Li MT, Zhang JP, Zhang J, Sun GQ. Forecast of peak infection and estimate of excess deaths in COVID-19 transmission and prevalence in Taiyuan City, 2022 to 2023. Infect Dis Model 2024; 9:56-69. [PMID: 38130878 PMCID: PMC10733700 DOI: 10.1016/j.idm.2023.11.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 11/03/2023] [Accepted: 11/10/2023] [Indexed: 12/23/2023] Open
Abstract
In this paper, with the method of epidemic dynamics, we assess the spread and prevalence of COVID-19 after the policy adjustment of prevention and control measure in December 2022 in Taiyuan City in China, and estimate the excess population deaths caused by COVID-19. Based on the transmission mechanism of COVID-19 among individuals, a dynamic model with heterogeneous contacts is established to describe the change of control measures and the population's social behavior in Taiyuan city. The model is verified and simulated by basing on reported case data from November 8th to December 5th, 2022 in Taiyuan city and the statistical data of the questionnaire survey from December 1st to 23rd, 2022 in Neijiang city. Combining with reported numbers of permanent residents and deaths from 2017 to 2021 in Taiyuan city, we apply the dynamic model to estimate theoretical population of 2022 under the assumption that there is no effect of COVID-19. In addition, we carry out sensitivity analysis to determine the propagation character of the Omicron strain and the effect of the control measures. As a result of the study, it is concluded that after adjusting the epidemic policy on December 6th, 2022, three peaks of infection in Taiyuan are estimated to be from December 22nd to 31st, 2022, from May 10th to June 1st, 2023, and from September 5th to October 13th, 2023, and the corresponding daily peaks of new cases can reach 400 000, 44 000 and 22 000, respectively. By the end of 2022, excess deaths can range from 887 to 4887, and excess mortality rate can range from 3.06% to 14.82%. The threshold of the infectivity of the COVID-19 variant is estimated 0.0353, that is if the strain infectivity is above it, the epidemic cannot be control with the previous normalization measures.
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Affiliation(s)
- Jia-Lin Wang
- Complex Systems Research Center, Shanxi University, Taiyuan, 030006, China
- School of Mathematical Sciences, Shanxi University, Taiyuan, 030006, China
| | - Xin-Long Xiao
- Complex Systems Research Center, Shanxi University, Taiyuan, 030006, China
- School of Mathematical Sciences, Shanxi University, Taiyuan, 030006, China
| | - Fen-Fen Zhang
- School of Mathematics, North University of China, Taiyuan, 030051, China
| | - Xin Pei
- College of Mathematics, Taiyuan University of Technology, Taiyuan, 030024, China
| | - Ming-Tao Li
- College of Mathematics, Taiyuan University of Technology, Taiyuan, 030024, China
| | - Ju-Ping Zhang
- Complex Systems Research Center, Shanxi University, Taiyuan, 030006, China
- Complex Systems and Data Science Key Laboratory of Ministry of Education, Taiyuan, 030006, China
| | - Juan Zhang
- Complex Systems Research Center, Shanxi University, Taiyuan, 030006, China
- Complex Systems and Data Science Key Laboratory of Ministry of Education, Taiyuan, 030006, China
| | - Gui-Quan Sun
- School of Mathematics, North University of China, Taiyuan, 030051, China
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Fang X, Tao G, Zhou H, Zhou Y. Vaccines reduced hospital length of stay and fraction of inspired oxygen of COVID-19 patients: A retrospective cohort study. Prev Med Rep 2024; 39:102632. [PMID: 38348219 PMCID: PMC10859302 DOI: 10.1016/j.pmedr.2024.102632] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 01/23/2024] [Accepted: 01/25/2024] [Indexed: 02/15/2024] Open
Abstract
Few studies have focused on the evaluation of vaccine effectiveness (VE) in mainland China. This study was to characterize the VE including the frequent symptoms, laboratory indices, along with endotracheal intubation, hospital length of stay (LoS), and survival status. This retrospective cohort study included patients with COVID-19 admitted to our hospital. Statistical comparisons of continuous variables were carried out with an independent Student's t-test or Mann-Whitney U test. For categorical variables, the Chi-square test and Fisher exact test were used. Multivariable regression analysis was performed to adjust the confounding factors such as age, gender, body mass index (BMI), residential area, smoking status, the Charlson comorbidity index (CCI) score, followed by investigating the effects of vaccination on critical ill prevention, reduced mortality and endotracheal intubation, LoS and inspired oxygen. This study included 549 hospitalized patients with COVID-19, including 222 (40.43 %) vaccinated participants and 327 (59.57 %) unvaccinated counterparts. There was no obvious difference between the two groups in typical clinical symptoms of COVID-19, clinical laboratory results and mortality. Multivariable analysis showed that COVID-19 vaccine obviously reduced LoS by 1.2 days (lnLoS = -0.14, 95 %CI[-0.24,-0.04]; P = 0.005) and decreased fraction of inspired oxygen by 40 % (OR: 0.60; 95 %CI[0.40,0.90]; P = 0.013) after adjusting age, gender, BMI, residential area, smoking status and CCI score. In contrast, vaccination induced reduction in the critically ill, mortality, and endotracheal intubation compared with the unvaccinated counterparts, but with no statistical differences. Vaccinated patients hospitalized with COVID-19 have a reduced LoS and fraction of inspired oxygen compared to unvaccinated cases in China.
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Affiliation(s)
- Xiaomei Fang
- Department of Nursing, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, Zhejiang Province, P. R. China
| | - Guofang Tao
- Department of Nursing, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, Zhejiang Province, P. R. China
| | - Hua Zhou
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, Zhejiang Province, P. R. China
| | - Yuxia Zhou
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, Zhejiang Province, P. R. China
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Chen MP, Jiang DX, Rang JX, Zhuo HB, Zhou ZG. Comparison of azvudine, molnupiravir, and nirmatrelvir/ritonavir in adult patients with mild-to-moderate COVID-19: a retrospective cohort study. Sci Rep 2024; 14:3318. [PMID: 38337014 PMCID: PMC10858188 DOI: 10.1038/s41598-024-53862-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 02/06/2024] [Indexed: 02/12/2024] Open
Abstract
This study aimed to explore the effectiveness and safety of azvudine, nirmatrelvir/ritonavir, and molnupiravir in adult patients with mild-to-moderate COVID-19. This retrospective cohort study included patients with mild-to-moderate COVID-19 (asymptomatic, mild, and common types) at the First Hospital of Changsha (Hunan Province, China) between March and November 2022. Eligible patients were classified into the azvudine, nirmatrelvir/ritonavir, or molnupiravir groups according to the antiviral agents they received. The outcomes were the times to nucleic acid negative conversion (NANC). This study included 157 patients treated with azvudine (n = 66), molnupiravir (n = 66), or nirmatrelvir/ritonavir (n = 25). There were no statistically significant differences in the time from diagnosis to NANC among the azvudine, molnupiravir, and nirmatrelvir/ritonavir groups [median, 9 (95% CI 9-11) vs. 11 (95% CI 10-12) vs. 9 (95% CI 8-12) days, P = 0.15], time from administration to NANC [median, 9 (95% CI 8-10) vs. 10 (95% CI 9.48-11) vs. 8.708 (95% CI 7.51-11) days, P = 0.50], or hospital stay [median, 11 (95% CI 11-13) vs. 13 (95% CI 12-14) vs. 12 (95% CI 10-14) days, P = 0.14], even after adjustment for sex, age, COVID-19 type, comorbidities, Ct level, time from diagnosis to antiviral treatment, and number of symptoms. The cumulative NANC rates in the azvudine, molnupiravir, and nirmatrelvir/ritonavir groups were 15.2%/12.3%/16.0% at day 5 (P = 0.858), 34.8%/21.5%/32.0% at day 7 (P = 0.226), 66.7%/52.3%/60.0% at 10 days (P = 0.246), and 86.4%/86.2%/80.0% at day 14 (P = 0.721). No serious adverse events were reported. Azvudine may be comparable to nirmatrelvir/ritonavir and molnupiravir in adult patients with mild-to-moderate COVID-19 regarding time to NANC, hospital stay, and AEs.
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Affiliation(s)
- Mei-Ping Chen
- Department of Infectious Disease, The Affiliated Changsha Hospital of Xiangya School of Medicine, Central South University (The First Hospital of Changsha), Changsha, 410000, People's Republic of China
| | - Di-Xuan Jiang
- Department of Respiratory and Critical Care Medicine, The Affiliated Changsha Hospital of Xiangya School of Medicine, Central South University (The First Hospital of Changsha), Changsha, 410000, People's Republic of China
| | - Jia-Xi Rang
- Department of Nurse, The Affiliated Changsha Hospital of Xiangya School of Medicine, Central South University (The First Hospital of Changsha), Changsha, 410000, People's Republic of China
| | - Hai-Bo Zhuo
- Department of Respiratory and Critical Care Medicine, The Affiliated Changsha Hospital of Xiangya School of Medicine, Central South University (The First Hospital of Changsha), Changsha, 410000, People's Republic of China
| | - Zhi-Guo Zhou
- Department of Respiratory and Critical Care Medicine, The Affiliated Changsha Hospital of Xiangya School of Medicine, Central South University (The First Hospital of Changsha), Changsha, 410000, People's Republic of China.
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