Mortality, crime and access to basic needs before and after the Haiti earthquake: a random survey of Port-au-Prince households
Bibliographic record
Abstract
On 12 January 2010 an earthquake measuring 7.0 on the Richter Scale struck Haiti, causing unprecedented death, injury and destruction for an event of this magnitude. Our aim was to generate a rapid assessment of the primary consequences for the population of the metropolitan area of Port-au-Prince, the national capital. During the summer of 2009 we conducted a survey of 1,800 households in metropolitan Port-au-Prince. Six weeks after the earthquake, we attempted to trace these households in order to re-interview them. The questionnaire examined mortality and injuries generated by the natural disaster, as well as the character of victimization, food security and living arrangements following the quake. Data analysis incorporated sampling weights and adjusted for clustering within households. The original 2009 survey featured a 90 per cent response rate; in 2010 we re-interviewed 93 per cent of these households. We estimate that 158,679 people in Port-au-Prince (95 per cent CI 136,813-180,545) died during the quake or in the six-week period afterwards owing to injuries or illness. Children were at particular risk for death. In the six weeks after the earthquake, 10,813 people (95 per cent CI 6,726-14,900) were sexually assaulted, the vast majority of whom were female. In the same period 4,645 individuals (95 per cent CI 1,943-7,347) were physically assaulted. Of all households, 18.6 per cent (95 per cent CI 16.6-20.8) were experiencing severe food insecurity six weeks after the earthquake. 24.4 per cent (95 per cent CI 22.1-26.9) of respondents' homes were completely destroyed. Many residents of Port-au-Prince died during or as a result of the earthquake, albeit fewer than were widely reported. More than half of the capital's population experienced moderate to severe food insecurity, though remittances are a major protective factor in promoting food security. Survivors continue to experience high levels of sexual assault and limited access to durable shelter.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".