Evidence map›Paper›PMID 34733955›Full record

ArticleAnnals of translational medicine2021

Identifying unmet non-COVID-19 health needs during the COVID-19 outbreak based on social media data: a proof-of-concept study in Wuhan city.

Wei-Fa Yang, Danping Zheng, Reynold C K Cheng, Jingya Jane Pu, Yu-Xiong Su

Abstract read
In one paragraph

Article in Annals of translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Wei-Fa YangFaculty of Dentistry, The University of Hong Kong, Hong Kong, China.
Danping ZhengDepartment of Gastroenterology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Reynold C K ChengDepartment of Computer Science, The University of Hong Kong, Hong Kong, China.
Jingya Jane PuFaculty of Dentistry, The University of Hong Kong, Hong Kong, China.
Yu-Xiong SuFaculty of Dentistry, The University of Hong Kong, Hong Kong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe occupancy of healthcare resources by the COVID-19 outbreak had led to the unmet health needs of non-COVID-19 diseases. We aimed to explore whether the social media information could help surveil and understand the characteristics of unmet non-COVID-19 health needs during the COVID-19 outbreak in Wuhan city.

methodsThis was an observational study based on social media data. The study period was set during the 3 months of the COVID-19 outbreak. Non-COVID-19 urgent and emergent health needs in Wuhan city were derived from Sina Weibo-one of China's largest social media platforms. Lag Spearman correlation was used to investigate the epidemiological relationship between the COVID-19 outbreak and non-COVID-19 health needs. Patient's primary diseases and needed care were annotated and categorized according to the International Classification of Diseases 11th Revision. The delay time in seeking help was calculated and compared.

resultsAfter screening 114,795 Weibo posts, a total of 229 patients with non-COVID-19 health needs were included in our study. There were significant correlations between the daily number of COVID-19 cases at a 10-day lag, deaths at a 5-day lag, and non-COVID-19 Weibo. The actual number of non-COVID-19 patients with urgent and emergent health needs was estimated to be about 6,966. Patients with non-COVID-19 health needs were skewed to those aged 50 to 70 years. The non-COVID-19 diseases were diverse, with 46.3% as non-neoplastic diseases and 53.7% as neoplasms. The most needed cares were palliative cancer care (22.7%), chemotherapy (18.8%), and critical care (17.0%). The median delay in seeking help was 3 days [interquartile range (IQR), 1 to 15 days] for acute care, and 18.5 days (IQR, 6 to 30 days) for cancer care.

conclusionsOur preliminary findings in Wuhan city indicated that the social media data might provide a viable option to surveil and understand the unmet health needs during an outbreak. Those heterogeneous health needs derived from the social media data might inspire a more resilient healthcare system to address the unmet needs promptly.

Indexed as

Coronavirus disease 2019 (COVID-19)non-COVID-19social mediaWeiboWuhan

Identifiers

PMID34733955
PMCPMC8506784

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.