Geographic, gender, and age distribution of measles deaths in India: estimates from a nationally representative study of over 12000 child deaths
Bibliographic record
Abstract
Background: Measles is an important cause of childhood mortality in India, however, its true burden and sub-national distribution is unknown. India's national measles mortality reduction plan identified key information gaps to be the lack of information on age, gender, and geographic distribution of measles transmission and deaths. Our objective is to address these gaps in knowledge and use a nationally-representative study of mortality to estimate the number and distribution of measles deaths in children aged 1 to 59 months. Methods: We used verbal autopsy data from the Million Death Study (MDS), which surveyed 6.3 million people in 1.1 million nationally representative Indian households. Each verbal autopsy was reviewed by at least two trained physicians who determined the final cause of death using ICD-10 classification. The proportion of MDS deaths caused by measles was applied to the gender and age specific number of childhood deaths from each region within India. Results: There were a total of 758 measles deaths identified in the MDS in children aged 1 to 59 months, representing approximately 6% of deaths in this age group. We estimate there were approximately 92 000 (99% CI 63 000 – 137 000) measles deaths in India in 2005 representing a mortality rate of 3.3 (99% CI 2.3-5.0) per 1000 livebirths. The mortality rate from measles was nearly 70% greater in girls than in boys. Approximately 60% of measles deaths occur in 3 states, Uttar Pradesh (35 000 deaths, mortality rate 6.1 per 1000 live births), Bihar (11 000 deaths, mortality rate 3.7 per 1000 live births), and Madhya Pradesh (8 000 deaths, mortality rate 4.0 per 1000 live births)(Figure 1). Conclusion: We address key gaps in knowledge regarding the epidemiology of measles in India. Measles kills over 90 000 children annually and girls are at much higher risk than boys. The majority of measles deaths occur in a few states. The results of this study clearly delineate the states and populations that must be targeted for increased measles vaccination rates and a second dose of measles containing vaccine in order to reduce overall, and gender inequities in, measles mortality.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".