The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Epidemiology and transmission of COVID-19 in 391 cases and 1286 of their close contacts in Shenzhen, China: a retrospective cohort study
Open accessPublished version of a preprint
Abstract
Summary Background Rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Wuhan, China, prompted heightened surveillance in Shenzhen, China. The resulting data provide a rare opportunity to measure key metrics of disease course, transmission, and the impact of control measures. Methods From Jan 14 to Feb 12, 2020, the Shenzhen Center for Disease Control and Prevention identified 391 SARS-CoV-2 cases and 1286 close contacts. We compared cases identified through symptomatic surveillance and contact tracing, and estimated the time from symptom onset to confirmation, isolation, and admission to hospital. We estimated metrics of disease transmission and analysed factors influencing transmission risk. Findings Cases were older than the general population (mean age 45 years) and balanced between males (n=187) and females (n=204). 356 (91%) of 391 cases had mild or moderate clinical severity at initial assessment. As of Feb 22, 2020, three cases had died and 225 had recovered (median time to recovery 21 days; 95% CI 20–22). Cases were isolated on average 4·6 days (95% CI 4·1–5·0) after developing symptoms; contact tracing reduced this by 1·9 days (95% CI 1·1–2·7). Household contacts and those travelling with a case were at higher risk of infection (odds ratio 6·27 [95% CI 1·49–26·33] for household contacts and 7·06 [1·43–34·91] for those travelling with a case) than other close contacts. The household secondary attack rate was 11·2% (95% CI 9·1–13·8), and children were as likely to be infected as adults (infection rate 7·4% in children <10 years vs population average of 6·6%). The observed reproductive number (R) was 0·4 (95% CI 0·3–0·5), with a mean serial interval of 6·3 days (95% CI 5·2–7·6). Interpretation Our data on cases as well as their infected and uninfected close contacts provide key insights into the epidemiology of SARS-CoV-2. This analysis shows that isolation and contact tracing reduce the time during which cases are infectious in the community, thereby reducing the R. The overall impact of isolation and contact tracing, however, is uncertain and highly dependent on the number of asymptomatic cases. Moreover, children are at a similar risk of infection to the general population, although less likely to have severe symptoms; hence they should be considered in analyses of transmission and control. Funding Emergency Response Program of Harbin Institute of Technology, Emergency Response Program of Peng Cheng Laboratory, US Centers for Disease Control and Prevention.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Chen, N., Zhou, M., Dong, X., Qu, J., Gong, F., Han, Y., Qiu, Y., Wang, J., Liu, Y., Wei, Y., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30211-7 · Cited by 21,415
Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia
Li, Q., Guan, X., Wu, P., Wang, X., Zhou, L., Tong, Y., Ren, R., Leung, K. S. M., Lau, E. H. Y., Wong, J. Y., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2001316 · Cited by 16,575
Self-citationLauer, S. A., Grantz, K. H., Bi, Q., Jones, F. K., Zheng, Q., Meredith, H. R., Azman, A. S., Reich, N. G., & Lessler, J. (2020) · Annals of Internal Medicine · doi:10.7326/m20-0504 · Cited by 5,970
Self-citationA leisurely look at the bootstrap, the jackknife, and cross-validation
Efron, B., & Gong, G. (1983) · The American Statistician · doi:10.1080/00031305.1983.10483087 · Cited by 3,229
Report 3: Transmissibility of 2019-nCoV
Imai, N., Cori, A., Dorigatti, I., Baguelin, M., Donnelly, C., Riley, S., & Ferguson, N. (2020) · Imperial College London · doi:10.25561/77148 · Cited by 210
Research works printed but not linked: 13
- Wang, 2020, Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China, JAMA, 323, 1061, 10.1001/jama.2020.1585 · DOI · Paper page
- Yang, 2020, Epidemiological and clinical features of the 2019 novel coronavirus outbreak in China, MedRxiv
- Backer, 2020, Incubation period of 2019 novel coronavirus (2019-nCoV) infections among travellers from Wuhan, China, 20–28 January 2020, Euro Surveill, 25, 10.2807/1560-7917.ES.2020.25.5.2000062 · DOI · Paper page
- Chan, 2020, A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster, Lancet, 395, 514, 10.1016/S0140-6736(20)30154-9 · DOI · Paper page
- Lessler, 2009, Outbreak of 2009 pandemic influenza A (H1N1) at a New York City school, N Engl J Med, 361, 2628, 10.1056/NEJMoa0906089 · DOI · Paper page
- Lipsitch, 2003, Transmission dynamics and control of severe acute respiratory syndrome, Science, 300, 1966, 10.1126/science.1086616 · DOI · Paper page
- Lessler, 2016, Estimating the severity and subclinical burden of Middle East respiratory syndrome coronavirus infection in the Kingdom of Saudi Arabia, Am J Epidemiol, 183, 657, 10.1093/aje/kwv452 · DOI
- Reich, 2009, Estimating incubation period distributions with coarse data, Stat Med, 28, 2769, 10.1002/sim.3659 · DOI
- Reich, 2012, Estimating absolute and relative case fatality ratios from infectious disease surveillance data, Biometrics, 68, 598, 10.1111/j.1541-0420.2011.01709.x · DOI
- Peiris, 2003, Clinical progression and viral load in a community outbreak of coronavirus-associated SARS pneumonia: a prospective study, Lancet, 361, 1767, 10.1016/S0140-6736(03)13412-5 · DOI · Paper page
- Zou, 2020, SARS-CoV-2 viral load in upper respiratory specimens of infected patients, N Engl J Med, 382, 1177, 10.1056/NEJMc2001737 · DOI · Paper page
- Pan, 2020, Time course of lung changes on chest CT during recovery from 2019 novel coronavirus (COVID-19) pneumonia, Radiology, 10.1148/radiol.2020200370 · DOI · Paper page
- Fang, 2020, Sensitivity of chest CT for COVID-19: comparison to RT-PCR, Radiology, 10.1148/radiol.2020200432 · DOI · Paper page
Cited by
Estimates of the severity of coronavirus disease 2019: a model-based analysis
Verity, R., Okell, L. C., Dorigatti, I., Winskill, P., Whittaker, C., Imai, N., Cuomo-Dannenburg, G., Thompson, H., Walker, P. G. T., Fu, H., et al. (2020) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(20)30243-7 · Cited by 3,660
Projecting the transmission dynamics of SARS-CoV-2 through the postpandemic period
Kissler, S. M., Tedijanto, C., Goldstein, E., Grad, Y. H., & Lipsitch, M. (2020) · Science · doi:10.1126/science.abb5793 · Cited by 2,611
Estimated transmissibility and impact of SARS-CoV-2 lineage B.1.1.7 in England
Davies, N. G., Abbott, S., Barnard, R. C., Jarvis, C. I., Kucharski, A. J., Munday, J. D., Pearson, C. A. B., Russell, T. W., Tully, D. C., Washburne, A. D., et al. (2021) · Science · doi:10.1126/science.abg3055 · Cited by 2,581
Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing
Ferretti, L., Wymant, C., Kendall, M., Zhao, L., Nurtay, A., Abeler-Dörner, L., Parker, M., Bonsall, D., & Fraser, C. (2020) · Science · doi:10.1126/science.abb6936 · Cited by 2,512
Mobility network models of COVID-19 explain inequities and inform reopening
Chang, S., Pierson, E., Koh, P. W., Gerardin, J., Redbird, B., Grusky, D., & Leskovec, J. (2021) · Nature · doi:10.1038/s41586-020-2923-3 · Cited by 1,533
Assessing transmissibility of SARS-CoV-2 lineage B.1.1.7 in England
The COVID-19 Genomics UK (COG-UK) consortium, Volz, E., Mishra, S., Chand, M., Barrett, J. C., Johnson, R., Geidelberg, L., Hinsley, W. R., Laydon, D. J., Dabrera, G., et al. (2021) · Nature · doi:10.1038/s41586-021-03470-x · Cited by 1,611
Changes in contact patterns shape the dynamics of the COVID-19 outbreak in China
Zhang, J., Litvinova, M., Liang, Y., Wang, Y., Wang, W., Zhao, S., Wu, Q., Merler, S., Viboud, C., Vespignani, A., et al. (2020) · Science · doi:10.1126/science.abb8001 · Cited by 1,107
Self-citationCastagnoli, R., Votto, M., Licari, A., Brambilla, I., Bruno, R., Perlini, S., Rovida, F., Baldanti, F., & Marseglia, G. L. (2020) · JAMA Pediatrics · doi:10.1001/jamapediatrics.2020.1467 · Cited by 1,085
Estimating the burden of SARS-CoV-2 in France
Salje, H., Tran Kiem, C., Lefrancq, N., Courtejoie, N., Bosetti, P., Paireau, J., Andronico, A., Hozé, N., Richet, J., Dubost, C.-L., et al. (2020) · Science · doi:10.1126/science.abc3517 · Cited by 1,038
Self-citationWalker, P. G. T., Whittaker, C., Watson, O. J., Baguelin, M., Winskill, P., Hamlet, A., Djafaara, B. A., Cucunubá, Z., Olivera Mesa, D., Green, W., et al. (2020) · Science · doi:10.1126/science.abc0035 · Cited by 993
Stringhini, S., Wisniak, A., Piumatti, G., Azman, A. S., Lauer, S. A., Baysson, H., De Ridder, D., Petrovic, D., Schrempft, S., Marcus, K., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)31304-0 · Cited by 990
Kucharski, A. J., Klepac, P., Conlan, A. J. K., Kissler, S. M., Tang, M. L., Fry, H., Gog, J. R., Edmunds, W. J., Emery, J. C., Medley, G., et al. (2020) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(20)30457-6 · Cited by 900
Badr, H. S., Du, H., Marshall, M., Dong, E., Squire, M. M., & Gardner, L. M. (2020) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(20)30553-3 · Cited by 851
Davies, N. G., Kucharski, A. J., Eggo, R. M., Gimma, A., Edmunds, W. J., Jombart, T., O'Reilly, K., Endo, A., Hellewell, J., Nightingale, E. S., et al. (2020) · The Lancet Public Health · doi:10.1016/s2468-2667(20)30133-x · Cited by 848
Self-citationImpact of delays on effectiveness of contact tracing strategies for COVID-19: a modelling study
Kretzschmar, M. E., Rozhnova, G., Bootsma, M. C. J., van Boven, M., van de Wijgert, J. H. H. M., & Bonten, M. J. M. (2020) · The Lancet Public Health · doi:10.1016/s2468-2667(20)30157-2 · Cited by 697
Hodgson, S. H., Mansatta, K., Mallett, G., Harris, V., Emary, K. R. W., & Pollard, A. J. (2021) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(20)30773-8 · Cited by 633
Estimated transmissibility and impact of SARS-CoV-2 lineage B.1.1.7 in England
Davies, N. G., Abbott, S., Barnard, R. C., Jarvis, C. I., Kucharski, A. J., Munday, J. D., Pearson, C. A. B., Russell, T. W., Tully, D. C., Washburne, A. D., et al. (2020) · doi:10.1101/2020.12.24.20248822 · Cited by 2,557
Epidemiology and transmission dynamics of COVID-19 in two Indian states
Laxminarayan, R., Wahl, B., Dudala, S. R., Gopal, K., Mohan B, C., Neelima, S., Jawahar Reddy, K. S., Radhakrishnan, J., & Lewnard, J. A. (2020) · Science · doi:10.1126/science.abd7672 · Cited by 485
Serial interval and incubation period of COVID-19: a systematic review and meta-analysis
Alene, M., Yismaw, L., Assemie, M. A., Ketema, D. B., Gietaneh, W., & Birhan, T. Y. (2021) · BMC Infectious Diseases · doi:10.1186/s12879-021-05950-x · Cited by 354
Proinflammatory IgG Fc structures in patients with severe COVID-19
Chakraborty, S., Gonzalez, J., Edwards, K., Mallajosyula, V., Buzzanco, A. S., Sherwood, R., Buffone, C., Kathale, N., Providenza, S., Xie, M. M., et al. (2021) · Nature Immunology · doi:10.1038/s41590-020-00828-7 · Cited by 326
Estimating the false-negative test probability of SARS-CoV-2 by RT-PCR
Wikramaratna, P. S., Paton, R. S., Ghafari, M., & Lourenço, J. (2020) · Eurosurveillance · doi:10.2807/1560-7917.es.2020.25.50.2000568 · Cited by 313
Global seroprevalence of SARS-CoV-2 antibodies: A systematic review and meta-analysis
Bobrovitz, N., Arora, R. K., Cao, C., Boucher, E., Liu, M., Donnici, C., Yanes-Lane, M., Whelan, M., Perlman-Arrow, S., Chen, J., et al. (2021) · PLOS ONE · doi:10.1371/journal.pone.0252617 · Cited by 246
Bellmann-Weiler, R., Lanser, L., Barket, R., Rangger, L., Schapfl, A., Schaber, M., Fritsche, G., Wöll, E., & Weiss, G. (2020) · Journal of Clinical Medicine · doi:10.3390/jcm9082429 · Cited by 244
Subjective neurological symptoms frequently occur in patients with SARS-CoV2 infection
Liguori, C., Pierantozzi, M., Spanetta, M., Sarmati, L., Cesta, N., Iannetta, M., Ora, J., Mina, G. G., Puxeddu, E., Balbi, O., et al. (2020) · Brain, Behavior, and Immunity · doi:10.1016/j.bbi.2020.05.037 · Cited by 212
Immunological imprinting of the antibody response in COVID-19 patients
Aydillo, T., Rombauts, A., Stadlbauer, D., Aslam, S., Abelenda-Alonso, G., Escalera, A., Amanat, F., Jiang, K., Krammer, F., Carratala, J., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-23977-1 · Cited by 223
Effects of COVID‐19 on Parkinson's Disease Clinical Features: A Community‐Based Case‐Control Study
Cilia, R., Bonvegna, S., Straccia, G., Andreasi, N. G., Elia, A. E., Romito, L. M., Devigili, G., Cereda, E., & Eleopra, R. (2020) · Movement Disorders · doi:10.1002/mds.28170 · Cited by 185
Timing the SARS-CoV-2 index case in Hubei Province
Pekar, J., Worobey, M., Moshiri, N., Scheffler, K., & Wertheim, J. O. (2021) · Science · doi:10.1126/science.abf8003 · Cited by 156
Qiu, X., Nergiz, A. I., Maraolo, A. E., Bogoch, I. I., Low, N., & Cevik, M. (2021) · Clinical Microbiology and Infection · doi:10.1016/j.cmi.2021.01.011 · Cited by 135
Association of Age and Pediatric Household Transmission of SARS-CoV-2 Infection
Paul, L. A., Daneman, N., Schwartz, K. L., Science, M., Brown, K. A., Whelan, M., Chan, E., & Buchan, S. A. (2021) · JAMA Pediatrics · doi:10.1001/jamapediatrics.2021.2770 · Cited by 140
The timing of COVID-19 transmission
Ferretti, L., Ledda, A., Wymant, C., Zhao, L., Ledda, V., Abeler-Dörner, L., Kendall, M., Nurtay, A., Cheng, H.-Y., Ng, T.-C., et al. (2020) · doi:10.1101/2020.09.04.20188516 · Cited by 112
Ainslie, K. E. C., Walters, C. E., Fu, H., Bhatia, S., Wang, H., Xi, X., Baguelin, M., Bhatt, S., Boonyasiri, A., Boyd, O., et al. (2020) · Wellcome Open Research · doi:10.12688/wellcomeopenres.15843.1 · Cited by 121
Data resource profile: COVerAGE-DB: a global demographic database of COVID-19 cases and deaths
Riffe, T., Acosta, E., the COVerAGE-DB team, Acosta, E. J., Manuel Aburto, D., Alburez-Gutierrez, A., Altová, A., Alustiza, U., Basellini, S., Bignami, D., et al. (2021) · International Journal of Epidemiology · doi:10.1093/ije/dyab027 · Cited by 110
Warp Speed for Coronavirus Disease 2019 (COVID-19) Vaccines: Why Are Children Stuck in Neutral?
Anderson, E. J., Campbell, J. D., Creech, C. B., Frenck, R., Kamidani, S., Munoz, F. M., Nachman, S., & Spearman, P. (2021) · Clinical Infectious Diseases · doi:10.1093/cid/ciaa1425 · Cited by 89
Effective contact tracing for COVID-19: A systematic review
Juneau, C.-E., Briand, A.-S., Collazzo, P., Siebert, U., & Pueyo, T. (2023) · Global Epidemiology · doi:10.1016/j.gloepi.2023.100103 · Cited by 85
Rumain, B., Schneiderman, M., & Geliebter, A. (2021) · PLOS ONE · doi:10.1371/journal.pone.0242587 · Cited by 73
Scully, E. P., Schumock, G., Fu, M., Massaccesi, G., Muschelli, J., Betz, J., Klein, E. Y., West, N. E., Robinson, M., Garibaldi, B. T., et al. (2021) · Open Forum Infectious Diseases · doi:10.1093/ofid/ofab448 · Cited by 73
Modelling the medium-term dynamics of SARS-CoV-2 transmission in England in the Omicron era
Barnard, R. C., Davies, N. G., Centre for Mathematical Modelling of Infectious Diseases COVID-19 working group, Munday, J. D., Lowe, R., Knight, G. M., Leclerc, Q. J., Tully, D. C., Hodgson, D., Pung, R., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-32404-y · Cited by 68
The Importance of Advancing Severe Acute Respiratory Syndrome Coronavirus 2 Vaccines in Children
Kao, C. M., Orenstein, W. A., & Anderson, E. J. (2021) · Clinical Infectious Diseases · doi:10.1093/cid/ciaa712 · Cited by 56
Long-term consequences in critically ill COVID-19 patients: a prospective cohort study
Schandl, A., Hedman, A., Lyngå, P., Fathi Tachinabad, S., Svefors, J., Roël, M., Geborek, A., Andersson Franko, M., Söderberg, M., Joelsson‐Alm, E., et al. (2021) · Acta Anaesthesiologica Scandinavica · doi:10.1111/aas.13939 · Cited by 50
Wegehaupt, O., Endo, A., & Vassall, A. (2023) · BMC Public Health · doi:10.1186/s12889-023-15915-1 · Cited by 45
Blair, A., Pan, S. Y., Subedi, R., Yang, F.-J., Aitken, N., & Steensma, C. (2022) · Canada Communicable Disease Report · doi:10.14745/ccdr.v48i01a05 · Cited by 27
Metadata
- Authors
- Bi, Q., Wu, Y., Mei, S., Ye, C., Zou, X., Zhang, Z., Liu, X., Wei, L., Truelove, S. A., Zhang, T., Gao, W., Cheng, C., Tang, X., Wu, X., Wu, Y., Sun, B., Huang, S., Sun, Y., Zhang, J., Ma, T., Lessler, J., & Feng, T.
- Venue
- The Lancet Infectious Diseases
- Publisher
- Elsevier BV
- Published
- 2020-08
- Volume
- 20
- Issue
- 8
- Pages
- 911-919
- ISSN
- 1473-3099 (ISSN-L)
- OpenAlex
- W3020184843
- Cited by
- 1,958
- References
- 5
- FWCI
- 70.57
- Type
- journal article
- Language
- en
- Update notices
- erratum (2020-07-01)
- Open access
- bronze
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- Funders
- Centers for Disease Control and Prevention (NU2GGH002000)
- Harbin Institute of Technology (PCLERP001, HITERP010)
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.