The estimated impact of decreased childhood vaccination due to COVID-19 using a dynamic transmission model of mumps in Japan
Bibliographic record
Abstract
The exact impact of the decline in childhood vaccination coverage during COVID-19 outbreak has not been estimated for any vaccine-preventable diseases. Our objective was to evaluate the impact of decreased mumps vaccination due to COVID-19 on the disease burden of mumps in Japan. Using a previously validated dynamic transmission model of mumps infection in Japan, the incidence rate of mumps over the next 30 y since July 2020 was estimated. The estimated average incidences were 269.1, 302.0, and 455.4/100,000 person-years in rapid recovery, slow recovery, and permanent decline scenarios. Compared with the rapid recovery scenario, the incremental number of mumps cases, total costs, and QALYs loss over the next 30 y were 6.53 million cases, 2.63 billion USD, and 49,246 for the permanent decline scenario, respectively. In conclusion, the persistent decline of mumps vaccination rate as an impact of COVID-19 causes a significant incremental disease burden of mumps, which is consistent irrespective of the possible decline of transmission rate of mumps infection, unless the rapid recovery of coverage rate is achieved. The immediate measures to advocate the vaccination program is essential to mitigate the incremental disease burden in the COVID-19 period.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".