Monitoring Interest in Herpes Zoster Vaccination: Analysis of Google Search Data
Bibliographic record
Abstract
BACKGROUND: A new recombinant subunit vaccine for herpes zoster (HZ or shingles) was approved by the United States Food and Drug Administration on October 20, 2017 and is expected to replace the previous live attenuated vaccine. There have been low coverage rates with the live attenuated vaccine (Zostavax), ranging from 12-32% of eligible patients receiving the HZ vaccine. OBJECTIVE: This study aimed to provide insight into trends and potential reasons for interest in HZ vaccination. METHODS: Internet search data were queried from the Google Health application programming interface from 2004-2017. Seasonality of normalized search volume was analyzed using wavelets and Fisher's g test. RESULTS: The search terms "shingles vaccine," "zoster vaccine," and "zostavax" all exhibited significant periodicity in the fall months (P<.001), with sharp increases after recommendations for vaccination by public health-related organizations. Although the terms "shingles blisters," "shingles itch," "shingles rash," "skin rash," and "shingles medicine" exhibited statistically significant periodicities with a seasonal peak in the summer (P<.001), the terms "shingles contagious," "shingles pain," "shingles treatment," and "shingles symptoms" did not reveal an annual trend. CONCLUSIONS: There may be increased interest in HZ vaccination during the fall and after public health organization recommendations are broadcast. This finding points to the possibility that increased awareness of the vaccine through public health announcements could be evaluated as a potential intervention for increasing vaccine coverage.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.020 | 0.024 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".