Herd Protection by a Bivalent Killed Whole-Cell Oral Cholera Vaccine in the Slums of Kolkata, India
Bibliographic record
Abstract
BACKGROUND: We evaluated the herd protection conferred by an oral cholera vaccine using 2 approaches: cluster design and geographic information system (GIS) design. METHODS: Residents living in 3933 dwellings (clusters) in Kolkata, India, were cluster-randomized to receive either cholera vaccine or oral placebo. Nonpregnant residents aged≥1 year were invited to participate in the trial. Only the first episode of cholera detected for a subject between 14 and 1095 days after a second dose was considered. In the cluster design, indirect protection was assessed by comparing the incidence of cholera among nonparticipants in vaccine clusters vs those in placebo clusters. In the GIS analysis, herd protection was assessed by evaluating association between vaccine coverage among the population residing within 250 m of the household and the occurrence of cholera in that population. RESULTS: Among 107 347 eligible residents, 66 990 received 2 doses of either cholera vaccine or placebo. In the cluster design, the 3-year data showed significant total protection (66% protection, 95% confidence interval [CI], 50%-78%, P<.01) but no evidence of indirect protection. With the GIS approach, the risk of cholera among placebo recipients was inversely related to neighborhood-level vaccine coverage, and the trend was highly significant (P<.01). This relationship held in multivariable models that also controlled for potentially confounding demographic variables (hazard ratio, 0.94 [95% CI, .90-.98]; P<.01). CONCLUSIONS: Indirect protection was evident in analyses using the GIS approach but not the cluster design approach, likely owing to considerable transmission of cholera between clusters, which would vitiate herd protection in the cluster analyses. CLINICAL TRIALS REGISTRATION: NCT00289224.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".