Pandemic preparedness: perceptions of vulnerable migrants in Thailand towards WHO-recommended non-pharmaceutical interventions: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Non-pharmaceutical interventions (NPIs) constituted the principal public health response to the previous influenza A (H1N1) 2009 pandemic and are one key area of ongoing preparation for future pandemics. Thailand is an important point of focus in terms of global pandemic preparedness and response due to its role as the major transportation hub for Southeast Asia, the endemic presence of multiple types of influenza, and its role as a major receiving country for migrants. Our aim was to collect information about vulnerable migrants' perceptions of and ability to implement NPIs proposed by the WHO. We hope that this information will help us to gauge the capacity of this population to engage in pandemic preparedness and response efforts, and to identify potential barriers to NPI effectiveness. METHODS: A cross-sectional survey was performed. The study was conducted during the influenza H1N1 2009 pandemic and included 801 migrant participants living in border areas thought to be high risk by the Thailand Ministry of Public Health. Data were collected by Migrant Community Health Workers using a 201-item interviewer-assisted questionnaire. Univariate descriptive analyses were conducted. RESULTS: With the exception of border measures, to which nearly all participants reported they would be adherent, attitudes towards recommended NPIs were generally negative or uncertain. Other potential barriers to NPI implementation include limited experience applying these interventions (e.g., using a thermometer, wearing a face mask) and inadequate hand washing and household disinfection practices. CONCLUSIONS: Negative or ambivalent attitudes towards NPIs combined with other barriers identified suggest that vulnerable migrants in Thailand have a limited capacity to participate in pandemic preparedness efforts. This limited capacity likely puts migrants at risk of propagating the spread of a pandemic virus. Coordinated risk communication and public education are potential strategies that may reduce barriers to individual NPI implementation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".