Estimating the health impact of vaccination against 10 pathogens in 98 low and middle income countries from 2000 to 2030
Bibliographic record
Abstract
Abstract Background The last two decades have seen substantial expansion of childhood vaccination programmes in low and middle income countries (LMICs). Here we quantify the health impact of these programmes by estimating the deaths and disability-adjusted life years (DALYs) averted by vaccination with ten antigens in 98 LMICs between 2000 and 2030. Methods Independent research groups provided model-based disease burden estimates under a range of vaccination coverage scenarios for ten pathogens: hepatitis B (HepB), Haemophilus influenzae type b (Hib), human papillomavirus (HPV), Japanese encephalitis (JE), measles, Neisseria meningitidis serogroup A (MenA), Streptococcus pneumoniae , rotavirus, rubella, yellow fever. Using standardized demographic data and vaccine coverage estimates for routine and supplementary immunization activities, the impact of vaccination programmes on deaths and DALYs was determined by comparing model estimates from the no vaccination counterfactual scenario with those from a default coverage scenario. We present results in two forms: deaths/DALYs averted in a particular calendar year, and in a particular annual birth cohort. Findings We estimate that vaccination will have averted 69 (2.5-97.5% quantile range 52-88) million deaths between 2000 and 2030 across the 98 countries and ten pathogens considered, 35 (29-45) million of these between 2000-2018. From 2000-2018, this represents a 44% (36-57%) reduction in deaths due to the ten pathogens relative to the no vaccination counterfactual. Most (96% (93-97%)) of this impact is in under-five age mortality, notably from measles. Over the lifetime of birth cohorts born between 2000 and 2030, we predict that 122 (96-147) million deaths will be averted by vaccination, of which 58 (39-75) and 38 (26-52) million are due to measles and Hepatitis B vaccination, respectively. We estimate that recent increases in vaccine coverage and introductions of additional vaccines will result in a 72% (61-79%) reduction in lifetime mortality caused by these 10 pathogens in the 2018 birth cohort. Interpretation Increases in vaccine coverage and the introduction of new vaccines into LMICs over the last two decades have had a major impact in reducing mortality. These public health gains are predicted to increase in coming decades if progress in increasing coverage is sustained.
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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 | 0.001 | 0.000 |
| 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".