The DOI matches its Crossref record; 47 of the 47 references it cites were found in a registry or an index.
Serial interval of SARS-CoV-2 was shortened over time by nonpharmaceutical interventions
Open accessAbstract
From cough to splutter: In epidemiology, serial intervals are measured from when one infected person starts to show symptoms to when the next person infected becomes symptomatic. For any specific infection, the serial interval is assumed to be a fixed characteristic. Using valuable transmission pair data for coronavirus disease (COVID-19) in mainland China, Ali et al. noticed that the average serial interval changed as nonpharmaceutical interventions were introduced. In mid-January 2020, serial intervals were on average 7.8 days, whereas in early February 2020, they decreased to an average of 2.2 days. The more quickly infected persons were identified and isolated, the shorter the serial interval became and the fewer the opportunities for virus transmission. The change in serial interval may not only measure the effectiveness of infection control interventions but may also indicate rising population immunity. Science , this issue p. 1106
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
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-citationVirological assessment of hospitalized patients with COVID-2019
Wölfel, R., Corman, V. M., Guggemos, W., Seilmaier, M., Zange, S., Müller, M. A., Niemeyer, D., Jones, T. C., Vollmar, P., Rothe, C., et al. (2020) · Nature · doi:10.1038/s41586-020-2196-x · Cited by 6,661
SARS-CoV-2 Viral Load in Upper Respiratory Specimens of Infected Patients
Zou, L., Ruan, F., Huang, M., Liang, L., Huang, H., Hong, Z., Yu, J., Kang, M., Song, Y., Xia, J., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmc2001737 · Cited by 4,810
Presumed Asymptomatic Carrier Transmission of COVID-19
Bai, Y., Yao, L., Wei, T., Tian, F., Jin, D.-Y., Chen, L., & Wang, M. (2020) · JAMA · doi:10.1001/jama.2020.2565 · Cited by 4,498
Wu, J. T., Leung, K., & Leung, G. M. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30260-9 · Cited by 4,389
Self-citationTemporal dynamics in viral shedding and transmissibility of COVID-19
He, X., Lau, E. H. Y., Wu, P., Deng, X., Wang, J., Hao, X., Lau, Y. C., Wong, J. Y., Guan, Y., Tan, X., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-0869-5 · Cited by 4,247
Self-citationThe effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak
Chinazzi, M., Davis, J. T., Ajelli, M., Gioannini, C., Litvinova, M., Merler, S., Pastore y Piontti, A., Mu, K., Rossi, L., Sun, K., et al. (2020) · Science · doi:10.1126/science.aba9757 · Cited by 3,694
How will country-based mitigation measures influence the course of the COVID-19 epidemic?
Anderson, R. M., Heesterbeek, H., Klinkenberg, D., & Hollingsworth, T. D. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30567-5 · Cited by 3,648
The effect of human mobility and control measures on the COVID-19 epidemic in China
Kraemer, M. U. G., Yang, C.-H., Gutierrez, B., Wu, C.-H., Klein, B., Pigott, D. M., Open COVID-19 Data Working Group, du Plessis, L., Faria, N. R., Li, R., et al. (2020) · Science · doi:10.1126/science.abb4218 · Cited by 2,950
Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts
Hellewell, J., Abbott, S., Gimma, A., Bosse, N. I., Jarvis, C. I., Russell, T. W., Munday, J. D., Kucharski, A. J., Edmunds, W. J., Sun, F., et al. (2020) · The Lancet Global Health · doi:10.1016/s2214-109x(20)30074-7 · Cited by 2,550
Cited by
Inferring the effectiveness of government interventions against COVID-19
Brauner, J. M., Mindermann, S., Sharma, M., Johnston, D., Salvatier, J., Gavenčiak, T., Stephenson, A. B., Leech, G., Altman, G., Mikulik, V., et al. (2021) · Science · doi:10.1126/science.abd9338 · Cited by 1,065
Household Transmission of SARS-CoV-2: A Systematic Review and Meta-analysis
Madewell, Z. J., Yang, Y., Longini, I. M., Halloran, M. E., & Dean, N. E. (2020) · JAMA Network Open · doi:10.1001/jamanetworkopen.2020.31756 · Cited by 716
Non-pharmaceutical interventions during the COVID-19 pandemic: A review
Perra, N. (2021) · Physics Reports · doi:10.1016/j.physrep.2021.02.001 · Cited by 531
Emergence and Expansion of the SARS-CoV-2 Variant B.1.526 Identified in New York
Annavajhala, M. K., Mohri, H., Wang, P., Nair, M., Zucker, J. E., Sheng, Z., Gomez-Simmonds, A., Kelley, A. L., Tagliavia, M., Huang, Y., et al. (2021) · doi:10.1101/2021.02.23.21252259
The origin and early spread of SARS-CoV-2 in Europe
Nadeau, S. A., Vaughan, T. G., Scire, J., Huisman, J. S., & Stadler, T. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2012008118 · Cited by 93
Metadata
- Authors
- Ali, S. T., Wang, L., Lau, E. H. Y., Xu, X.-K., Du, Z., Wu, Y., Leung, G. M., & Cowling, B. J.
- Venue
- Science
- Published
- 2020-08-28
- Volume
- 369
- Issue
- 6507
- Pages
- 1106-1109
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W3045248985
- Cited by
- 331
- References
- 47
- FWCI
- 10.92
- Type
- journal article
- Language
- en
- Open access
- hybrid
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Serial interval of SARS-CoV-2 was shortened over time by nonpharmaceutical interventions. https://app.cochat.ai/papers/10.1126/science.abc9004
- The paper
- Ali, S. T., Wang, L., Lau, E. H. Y., Xu, X.-K., Du, Z., Wu, Y., Leung, G. M., & Cowling, B. J. (2020). Serial interval of SARS-CoV-2 was shortened over time by nonpharmaceutical interventions. Science. https://doi.org/10.1126/science.abc9004
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.