Local Community Response to Mass Asymptomatic COVID-19 Testing in Liverpool, England: Social Media Analysis
Bibliographic record
Abstract
BACKGROUND: Mass asymptomatic testing for COVID-19 was piloted for the first time in the United Kingdom in Liverpool in November 2020. There is limited evidence on uptake of mass testing, and previously where surge testing has been deployed, uptake has been low. OBJECTIVE: There was an urgent need to rapidly evaluate acceptance of asymptomatic testing, specifically identifying barriers and facilitators to taking part. METHODS: As part of the wider evaluation, we conducted a rapid thematic analysis of local community narratives on social media to provide insights from people unlikely to engage in testing or other standard evaluation techniques, such as surveys or interviews. We identified 3 publicly available data sources: the comments section of a local online newspaper, the city council Facebook page, and Twitter. Data were collected between November 2, 2020, and November 8, 2020, to cover the period between announcement of mass testing in Liverpool and the first week of testing. Overall, 1096 comments were sampled: 219 newspaper comments, 472 Facebook comments, and 405 tweets. Data were analyzed using an inductive thematic approach. RESULTS: Key barriers were accessibility, including site access and concerns over queuing. Queues were also highlighted as a concern due to risk of transmission. Consequences of testing, including an increase in cases leading to further restrictions and financial impact of the requirement for self-isolation, were also identified as barriers. In addition, a lack of trust in authorities and the test (including test accuracy and purpose of testing) was identified. Comments coded as indicative of lack of trust were coded in some cases as indicative of strong collective identity with the city of Liverpool and marginalization due to feeling like test subjects. However, other comments coded as identification with Liverpool were coded as indicative of motivation to engage in testing and encourage others to do so; for this group, being part of a pilot was seen as a positive experience and an opportunity to demonstrate the city could successfully manage the virus. CONCLUSIONS: Our analysis highlights the importance of promoting honest and open communication to encourage and harness existing community identities to enhance the legitimacy of asymptomatic testing as a policy. In addition, adequate and accessible financial support needs to be in place prior to the implementation of community asymptomatic testing to mitigate any concerns surrounding financial hardship. Rapid thematic analysis of social media is a pragmatic method to gather insights from communities around acceptability of public health interventions, such as mass testing or vaccination uptake.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".