Injuries, Death, and Disability Associated with 11 Years of Conflict in Baghdad, Iraq: A Randomized Household Cluster Survey
Bibliographic record
Abstract
BACKGROUND: The objective of this study was to characterize injuries, deaths, and disabilities arising during 11 years of conflict in Baghdad. METHODS: Using satellite imagery and administrative population estimated size for Baghdad, 30 clusters were selected, proportionate to population size estimates. Interviews were conducted during April and May 2014 in 900 households containing 5148 persons. Details about injuries and disabilities occurring from 2003 through May 2014 and resultant disabilities were recorded. FINDINGS: There were 553 injuries reported by Baghdad residents, 225 of which were intentional, and 328 unintentional. For intentional injuries, the fatality rate was 39.1% and the disability rate 56.0%. Gunshots where the major cause of injury through 2006 when blasts/explosions became the most common cause and remained so through 2014. Among unintentional injuries, the fatality rate was 7.3% and the disability rate 77.1%. The major cause of unintentional injuries was falls (131) which have increased dramatically since 2008, followed by traffic related injuries (81), which have steadily increased. The proportion of injuries ending in disabilities remained fairly constant through the survey period. INTERPRETATION: Intentional injuries added substantially to the burden of unintentional injuries for the population. For Baghdad, the phases of the Iraqi conflict are reflected in the patterns of injuries and consequent deaths reported. The scale of injuries during conflict is most certainly under-reported. Difficulties recalling injuries in a survey covering 11 years is a limitation, but it is likely that minor injuries were under-reported more than severe injuries. The in- and out-migration of Baghdad populations likely had effects on the events reported which we could not measure or estimate. Damage to the health infrastructure and the flight of health workers may have contributed to mortality and morbidity. Civilian injuries as well as mortality should be measured during conflicts, though not currently done.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".