Rotavirus mortality in India: estimates based on a nationally representative survey of diarrhoeal deaths
Bibliographic record
Abstract
We ascertained the number of deaths from diarrhoea among children during 2001-2003 on the basis of findings from the Million Death Study. The Million Death Study is an ongoing project conducted with the Registrar General of India and collaborators to determine causes of death in India. The study derives its data from a nationally representative sample of 6.3 million people in 1.1 million households within the Sample Registration System, a large, routine demographic survey performed by the Registrar General of India in all 28 Indian states and seven union territories that has been the primary system for the collection of Indian fertility and mortality data since 1971. Sample units are randomly selected to ensure that they are representative of the population at the state level. Enrolment in the system is voluntary and its confidentiality and consent procedures are defined as part of the Registration of Births and Deaths Act of 1969. Additional details about the Sample Registration System are available elsewhere. 12 Objective To estimate the number of rotavirus-associated deaths among Indian children younger than five years. Methods We surveyed more than 23 000 child deaths from a nationally representative survey of 1.1 million Indian households during 2001-2003. Diarrhoeal deaths were characterized by region, age and sex and were combined with the proportion of deaths attributable to rotavirus, as determined by hospital microbiologic data collected by the Indian Rotavirus Strain Surveillance Network from December 2005 to November 2007. Rotavirus vaccine efficacy data from clinical trials in developing countries were used to estimate the number of deaths preventable by a national vaccination programme. Data were analysed using Stata SE version 10. Findings Rotavirus caused an estimated 113 000 deaths (99% confidence interval, CI: 86 000-155 000); 50% (54 700) and 75% (85 400) occurred before one and two years of age, respectively. One child in 242 died from rotavirus infection before five years of age. Rotavirusassociated mortality rates overall, among girls and among boys were 4.14 (99% CI: 3.14-5.68), 4.89 (99% CI: 3.75-6.79) and 3.45 (99% CI: 2.58-4.66) deaths per 1000 live births, respectively. Rates were highest in Bihar, Uttar Pradesh and Madhya Pradesh, which together accounted for > 50% of deaths (64 400) nationally. Rotavirus vaccine could prevent 41 000-48 000 deaths among children aged 3-59 months. Conclusion The burden of rotavirus-associated mortality is high among Indian children, highlighting the potential benefits of rotavirus vaccination.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".