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Record W3203972593 · doi:10.1371/journal.pmed.1003678

Drought and child vaccination coverage in 22 countries in sub-Saharan Africa: A retrospective analysis of national survey data from 2011 to 2019

2021· article· en· W3203972593 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePLoS Medicine · 2021
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune responses and vaccinations
Canadian institutionsUniversity of Toronto
FundersNational Institute of Allergy and Infectious DiseasesAmerican Heart Association
KeywordsVaccinationMedicineMeaslesPoliomyelitisDemographyEnvironmental healthHealth facilityPediatricsPopulationImmunology

Abstract

fetched live from OpenAlex

BACKGROUND: Extreme weather events, including droughts, are expected to increase in parts of sub-Saharan Africa and are associated with a number of poor health outcomes; however, to the best of our knowledge, the link between drought and childhood vaccination remains unknown. The objective of this study was to evaluate the relationship between drought and vaccination coverage. METHODS AND FINDINGS: We investigated the association between drought and vaccination coverage using a retrospective analysis of Demographic and Health Surveys data in 22 sub-Saharan African countries among 137,379 children (50.4% male) born from 2011 to 2019. Drought was defined as an established binary variable of annual rainfall less than or equal to the 15th percentile relative to the 29 previous years, using data from Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data. We evaluated the association between drought at the date of birth and receipt of bacillus Calmette-Guérin (BCG), diphtheria-pertussis-tetanus (DPT), and polio vaccinations, and the association between drought at 12 months of age and receipt of measles vaccination. We specified logistic regression models with survey fixed effects and standard errors clustered at the enumeration area level, adjusting for child-, mother-, and household-level covariates and estimated marginal risk differences (RDs). The prevalence of drought at date of birth in the sample was 11.8%. Vaccination rates for each vaccination ranged from 70.6% (for 3 doses of the polio vaccine) to 86.0% (for BCG vaccination); however, only 57.6% of children 12 months and older received all recommended doses of BCG, DPT, polio, and measles vaccinations. In adjusted models, drought at date of birth was negatively associated with BCG vaccination (marginal RD = -1.5; 95% CI -2.2, -0.9), DPT vaccination (marginal RD = -1.4; 95% CI -2.2, -0.5), and polio vaccination (marginal RD = -1.3; 95% CI -2.3, -0.3). Drought at 12 months was negatively associated with measles vaccination (marginal RD = -1.9; 95% CI -2.8, -0.9). We found a dose-response relationship between drought and DPT and polio vaccinations, with the strongest associations closest to the timing of drought. Limitations include some heterogeneity in findings across countries. CONCLUSIONS: In this study, we observed that drought was associated with lower odds of completion of childhood BCG, DPT, and polio vaccinations. These findings indicate that drought may hinder vaccination coverage, one of the most important interventions to prevent infections among children. This work adds to a growing body of literature suggesting that health programs should consider impacts of severe weather in their programming.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.095
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.033
GPT teacher head0.285
Teacher spread0.252 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it