The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Corona Virus (COVID-19) “Infodemic” and Emerging Issues through a Data Lens: The Case of China
Open accessAbstract
Coronavirus (COVID-19) is a humanitarian emergency, which started in Wuhan in China in early December 2019, brought into the notice of the authorities in late December, early January 2020, and, after investigation, was declared as an emergency in the third week of January 2020. The WHO declared this as Public Health Emergency of International Concern (PHEIC) on 31th of January 2020, and finally a pandemic on 11th March 2020. As of March 24th, 2020, the virus has caused a casualty of over 16,600 people worldwide with more than 380,000 people confirmed as infected by it, of which more than 10,000 cases are serious. Mainly based on Chinese newspapers, social media and other digital platform data, this paper analyzes the timeline of the key actions taken by the government and people over three months in five different phases. It found that although there was an initial delay in responding, a unique combination of strong governance, strict regulation, strong community vigilance and citizen participation, and wise use of big data and digital technologies, were some of the key factors in China’s efforts to combat this virus. Being inviable and non-measurable (unlike radioactive exposure), appropriate and timely information is very important to form the basic foundation of mitigation and curative measures. Infodemic, as it is termed by WHO, is a key word, where different stakeholder’s participation, along with stricter regulation, is required to reduce the impact of fake news in this information age and social media. Although different countries will need different approaches, focusing on its humanitarian nature and addressing infodemic issues are the two critical factors for future global mitigation efforts.
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
Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China
Huang, C., Wang, Y., Li, X., Ren, L., Zhao, J., Hu, Y., Zhang, L., Fan, G., Xu, J., Gu, X., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30183-5 · Cited by 48,884
Zarocostas, J. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30461-x · Cited by 2,344
Cited by
Golinelli, D., Boetto, E., Carullo, G., Nuzzolese, A. G., Landini, M. P., & Fantini, M. P. (2020) · Journal of Medical Internet Research · doi:10.2196/22280 · Cited by 574
Okan, O., Bollweg, T. M., Berens, E.-M., Hurrelmann, K., Bauer, U., & Schaeffer, D. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17155503 · Cited by 418
Dadaczynski, K., Okan, O., Messer, M., Leung, A. Y. M., Rosário, R., Darlington, E., & Rathmann, K. (2021) · Journal of Medical Internet Research · doi:10.2196/24097 · Cited by 390
Djalante, R., Shaw, R., & DeWit, A. (2020) · Progress in Disaster Science · doi:10.1016/j.pdisas.2020.100080 · Cited by 344
Self-citationAssessing COVID-19 vaccine literacy: a preliminary online survey
Biasio, L. R., Bonaccorsi, G., Lorini, C., & Pecorelli, S. (2021) · Human Vaccines & Immunotherapeutics · doi:10.1080/21645515.2020.1829315 · Cited by 281
Metadata
- Authors
- Hua, J., & Shaw, R.
- Venue
- International Journal of Environmental Research and Public Health
- Publisher
- MDPI AG
- Published
- 2020-03-30
- Volume
- 17
- Issue
- 7
- Pages
- 2309
- ISSN
- 1660-4601 (ISSN-L)
- OpenAlex
- W3013830439
- Cited by
- 575
- References
- 2
- FWCI
- 166.25
- Type
- journal article
- Language
- en
- Open access
- gold
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: Corona Virus (COVID-19) “Infodemic” and Emerging Issues through a Data Lens: The Case of China. https://app.cochat.ai/papers/10.3390/ijerph17072309
- The paper
- Hua, J., & Shaw, R. (2020). Corona Virus (COVID-19) “Infodemic” and Emerging Issues through a Data Lens: The Case of China. International Journal of Environmental Research and Public Health. https://doi.org/10.3390/ijerph17072309
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.