Evidence map›Paper›PMID 34099986›Full record

ArticleHeliyon2021

Using SNSs for early detection of disease outbreak in developing countries: evidence from COVID-19 pandemic in Nigeria.

Tunde Adebisi, Ayooluwa Aregbesola, Festus Asamu, Ogadimma Arisukwu, Eyitayo Oyeyipo

Open access · goldAbstract read
In one paragraph

Article in Heliyon, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.1field-weighted citation impact, top 23% of its field
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

3 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
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 at 1 institution in 1 country.

Tunde AdebisiSDG 16, Peace, Justice and Strong Institutions, SDG 10, Reduced Inequality, Department of Sociology, Landmark University, Omu-Aran Kwara, Nigeria.
Ayooluwa AregbesolaSDG 4, Quality Education, Centre for Learning Resources, Landmark University, Omu-Aran Kwara, Nigeria.
Festus AsamuSDG 10, Reduced Inequality, Department of Sociology, Landmark University, Omu-Aran Kwara, Nigeria.
Ogadimma ArisukwuSDG 16, Peace, Justice and Strong Institutions, SDG 10, Reduced Inequality, Department of Sociology, Landmark University, Omu-Aran Kwara, Nigeria.
Eyitayo OyeyipoSDG 10, Reduced Inequality, Department of Sociology, Landmark University, Omu-Aran Kwara, Nigeria.
Landmark University · NG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Developing countries, particularly Nigeria, continually find it challenging to proactively and actively carry out early-stage surveillance for disease outbreaks due to the lack of quality workforce, a dearth of public health data, and the absence of automated surveillance systems in the country. This study presents the potential and ability of Twitter in tracking early detection of COVID-19, monitoring the dissemination of information, and exploration of public awareness and attitudes among Nigerians. Tweets mentioning COVID-19 and related keywords were collected in 11 batches via the NCapture™ plugin available on Google Chrome from February 20 - May 6, 2020. The analysis includes a time series analysis to track the distribution of data and content analysis to analyze the knowledge and attitudes of Nigerians. A total of 67,989 tweets (1,484 unique and 66,505 retweets) citing COVID-19 and related keywords were returned. The Tweets started to emerge earlier to the first confirmed case in Nigeria while maintaining a dangling-upward movement up to the 11th week under study. Matters arising from the tweets include a dearth of information on COVID-19 and optimism among others. The results provide insight into the intersection of SNSs and public health surveillance. Results show how helpful Twitter is to educate education in public health. Health organizations and the government may benefit from paying attention to both amusing and emotional contents from the Twitter community to formulate a viable policy for treatment and control.

Indexed as

COVID-19NigeriaPublic health surveillanceQualitative researchTwitter

Identifiers

PMID34099986
PMCPMC8165079
OpenAlexW3172339469

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.