Literature DB >> 32686766

Serosurvey of SARS-CoV-2 among hospital visitors in China.

Wenhua Liang1, Yongping Lin2, Jianping Bi3, Jianfu Li1, Ying Liang2, Sook-San Wong1, Mark Zanin1,4, Zifeng Yang1, Caichen Li1, Ran Zhong1, Guowu Jiang5, Guang Han6, Desheng Hu7, Jianxing He8,9, Nanshan Zhong1.   

Abstract

Entities:  

Mesh:

Substances:

Year:  2020        PMID: 32686766      PMCID: PMC7369564          DOI: 10.1038/s41422-020-0371-0

Source DB:  PubMed          Journal:  Cell Res        ISSN: 1001-0602            Impact factor:   46.297


× No keyword cloud information.
Dear Editor, In China, the epidemic of COVID-19 has been temporarily brought under control due to strong measures, while there are few new cases except some imported ones (https://static.wecity.qq.com/wuhan-haiwai-pre/dist/index.html#/). The PCR-based test result combined with clinical symptoms has widely been used for the detection and confirmation of COVID-19.[1] However, the prevalence of asymptomatic or subclinical SARS-CoV-2 infection in China remained unknown. Serological investigation can comprehensively identify the infected people in community, especially those asymptomatic. Presence of positive IgM antibody in serum indicates an early infection, while positivity in IgG antibody, which persists for a long time after disease, indicates a prior infection. A recent study demonstrated that 100% of COVID-19 patients were tested positive for antiviral immunoglobulin.[2] Although the antibody test has a false rate of 10%–15% (false negative and false positive), it can detect the former asymptomatic infections and be used to estimate the true infection rate of the population. A serosurvey in Santa Clara county at California indicated that the infection rate of SARS-CoV-2 may be 30–50 times of that in official reports based on nucleic-acid diagnoses.[3] Here, we studied the seroprevalence of IgM/IgG antibodies to SARS-CoV-2 of hospital visitors from the First Affiliated Hospital of Guangzhou Medical University in Guangzhou, the largest city in Southern China, and the Hubei Cancer Hospital in Wuhan, the epicenter of the outbreak, respectively. These visitors, including inpatients and their healthy companions, represented a population with a common social exposure and without COVID-19-related symptoms. Up to April 30th, a total of 8272 individuals in the Wuhan cohort (epicenter) and 8782 individuals in the Guangzhou cohort (non-epicenter) were included (Supplementary information, Table S1); the median age was 54 (IQR (interquartile range), 44–62) and 55 (IQR, 38–67), respectively. All these individuals were tested negative for SARS-CoV-2 RNA, and most of them had no COVID-19-related symptoms within the past three months. The seroprevalence of IgM/IgG was 2.1% in Wuhan and 0.6% in Guangzhou, respectively (Fig. 1a). In Wuhan, the seroprevalence against SARS-CoV-2 of IgG is higher than that of IgM (Fig. 1b). There was no significant difference of seroprevalence in sex and age subgroups (Fig. 1c; Supplementary information, Table S2). The time trend of IgM and IgG prevalence among hospital visitors in Guangzhou cohort was illustrated in Fig. 1d, which matched with ‘two peaks’ of the total RNA-positive (RNA+) case number in Guangzhou with a slight delay in time.
Fig. 1

Summary of SARS-CoV-2 seroprevalance among hospital visitors.

a Positive rate of SARS-CoV-2 IgM/IgG in Wuhan and Guangzhou. b Proportion of IgM positive, IgG positive and IgM+IgG double positive in Wuhan and Guangzhou. c Positive rate of IgM/IgG in different age groups. x-axis, age ranges; y-axis, positive rate. d IgM (blue bars and fitted line) and IgG (red bars and fitted line) prevalence in cases tested in Guangzhou hospital cohort, and total RNA-confirmed cases (gray areas) in Guangzhou city, in each week since outbreak. x-axis, date ranges; y-axis, positivity burden. n, number of positivity (b, d).

Summary of SARS-CoV-2 seroprevalance among hospital visitors.

a Positive rate of SARS-CoV-2 IgM/IgG in Wuhan and Guangzhou. b Proportion of IgM positive, IgG positive and IgM+IgG double positive in Wuhan and Guangzhou. c Positive rate of IgM/IgG in different age groups. x-axis, age ranges; y-axis, positive rate. d IgM (blue bars and fitted line) and IgG (red bars and fitted line) prevalence in cases tested in Guangzhou hospital cohort, and total RNA-confirmed cases (gray areas) in Guangzhou city, in each week since outbreak. x-axis, date ranges; y-axis, positivity burden. n, number of positivity (b, d). This serosurvey of hospital visitors detected individuals positive for antibodies against SARS-CoV-2. These individuals had no history of COVID-19 symptoms, and therefore regarded as asymptomatic or mild. There was no consensus on whether individuals with asymptomatic patients are infectious or not. On this basis, public health interventions are still required to avoid the second wave of outbreak. In addition, serosurveys might partially reflect the disease prevalence.[3] In this survey, the seroprevalence of epicenter Wuhan was higher than that in Guangzhou, which is outside the epicenter, and the trends of RNA+ cases in Guangzhou and antibody positive rates of hospital visitors in Guangzhou were well matched with each other. Admittedly, the current seroprevalence might be underestimated due to the sensitivity of assays and biased by the comorbidity burden among patients requiring hospitalization. There might be also a bias for the investigated population (patients with other disease and without significant COVID-19 symptoms), as most RNA+ cases has been detected and isolated due to the comprehensive screening strategy in China. On this basis, this study did not provide an exact number of infection prevalence and of the comparison between the two cities. Still, the relatively low seropositivity suggests that prevention and control measures in China are effective.[4] On the other hand, this study showed that in Wuhan and Guangzhou, whether inside or outside the epicenter of outbreak, the population immunity is still at a low level. Therefore, there is an urgent need for an effective vaccine against SARS-CoV-2, and strict isolation and community measures should be continued until such a vaccine is available.
  3 in total

1.  Antibody responses to SARS-CoV-2 in patients with COVID-19.

Authors:  Quan-Xin Long; Bai-Zhong Liu; Hai-Jun Deng; Gui-Cheng Wu; Kun Deng; Yao-Kai Chen; Pu Liao; Jing-Fu Qiu; Yong Lin; Xue-Fei Cai; De-Qiang Wang; Yuan Hu; Ji-Hua Ren; Ni Tang; Yin-Yin Xu; Li-Hua Yu; Zhan Mo; Fang Gong; Xiao-Li Zhang; Wen-Guang Tian; Li Hu; Xian-Xiang Zhang; Jiang-Lin Xiang; Hong-Xin Du; Hua-Wen Liu; Chun-Hui Lang; Xiao-He Luo; Shao-Bo Wu; Xiao-Ping Cui; Zheng Zhou; Man-Man Zhu; Jing Wang; Cheng-Jun Xue; Xiao-Feng Li; Li Wang; Zhi-Jie Li; Kun Wang; Chang-Chun Niu; Qing-Jun Yang; Xiao-Jun Tang; Yong Zhang; Xia-Mao Liu; Jin-Jing Li; De-Chun Zhang; Fan Zhang; Ping Liu; Jun Yuan; Qin Li; Jie-Li Hu; Juan Chen; Ai-Long Huang
Journal:  Nat Med       Date:  2020-04-29       Impact factor: 53.440

2.  Clinical Characteristics of Coronavirus Disease 2019 in China.

Authors:  Wei-Jie Guan; Zheng-Yi Ni; Yu Hu; Wen-Hua Liang; Chun-Quan Ou; Jian-Xing He; Lei Liu; Hong Shan; Chun-Liang Lei; David S C Hui; Bin Du; Lan-Juan Li; Guang Zeng; Kwok-Yung Yuen; Ru-Chong Chen; Chun-Li Tang; Tao Wang; Ping-Yan Chen; Jie Xiang; Shi-Yue Li; Jin-Lin Wang; Zi-Jing Liang; Yi-Xiang Peng; Li Wei; Yong Liu; Ya-Hua Hu; Peng Peng; Jian-Ming Wang; Ji-Yang Liu; Zhong Chen; Gang Li; Zhi-Jian Zheng; Shao-Qin Qiu; Jie Luo; Chang-Jiang Ye; Shao-Yong Zhu; Nan-Shan Zhong
Journal:  N Engl J Med       Date:  2020-02-28       Impact factor: 91.245

3.  Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions.

Authors:  Zifeng Yang; Zhiqi Zeng; Ke Wang; Sook-San Wong; Wenhua Liang; Mark Zanin; Peng Liu; Xudong Cao; Zhongqiang Gao; Zhitong Mai; Jingyi Liang; Xiaoqing Liu; Shiyue Li; Yimin Li; Feng Ye; Weijie Guan; Yifan Yang; Fei Li; Shengmei Luo; Yuqi Xie; Bin Liu; Zhoulang Wang; Shaobo Zhang; Yaonan Wang; Nanshan Zhong; Jianxing He
Journal:  J Thorac Dis       Date:  2020-03       Impact factor: 3.005

  3 in total
  5 in total

Review 1.  SARS-CoV-2 seroprevalence around the world: an updated systematic review and meta-analysis.

Authors:  Mobin Azami; Yousef Moradi; Asra Moradkhani; Abbas Aghaei
Journal:  Eur J Med Res       Date:  2022-06-02       Impact factor: 4.981

2.  Willingness to receive future COVID-19 vaccines following the COVID-19 epidemic in Shanghai, China.

Authors:  Yehong Zhou; Junjie Zhang; Wenwen Wu; Man Liang; Qiang-Song Wu
Journal:  BMC Public Health       Date:  2021-06-09       Impact factor: 3.295

3.  Serological investigation of asymptomatic cases of SARS-CoV-2 infection reveals weak and declining antibody responses.

Authors:  Yong Yang; Xi Wang; Rong-Hui Du; Wei Zhang; Hao-Rui Si; Yan Zhu; Xu-Rui Shen; Qian Li; Bei Li; Dong Men; Ya-Na Zhou; Hui Wang; Xiao-Lin Tong; Xian-En Zhang; Zheng-Li Shi; Peng Zhou
Journal:  Emerg Microbes Infect       Date:  2021-12       Impact factor: 7.163

4.  [Seroprevalence of SARS-CoV-2 antibodies among travellers and workers screened at the Saint Luc Clinic in Bukavu, a city in eastern Democratic Republic of the Congo, from May to August 2020].

Authors:  Philippe Bianga Katchunga; Aimé Murhula; Prince Akilimali; Jean Claude Zaluka; Racine Karhikalembu; Mack Makombo; Justin Bisimwa; Eugene Mubalama
Journal:  Pan Afr Med J       Date:  2021-01-27

Review 5.  SARS-CoV-2: Origin, Evolution, and Targeting Inhibition.

Authors:  Shuo Ning; Beiming Yu; Yanfeng Wang; Feng Wang
Journal:  Front Cell Infect Microbiol       Date:  2021-06-17       Impact factor: 5.293

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.