Effects of terrorist attacks on access to maternal healthcare services: a national longitudinal study in Burkina Faso
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Bibliographic record
Abstract
INTRODUCTION: Most of the literature on terrorist attacks' health impacts has focused on direct victims rather than on distal consequences in the overall population. There is limited knowledge on how terrorist attacks can be detrimental to access to healthcare services. The objective of this study is to assess the impact of terrorist attacks on the utilisation of maternal healthcare services by examining the case of Burkina Faso. METHODS: This longitudinal quasi-experimental study uses multiple interrupted time series analysis. Utilisation of healthcare services data was extracted from the National Health Information System in Burkina Faso. Data span the period of January 2013-December 2018 and include all public primary healthcare centres and district hospitals. Terrorist attack data were extracted from the Armed Conflict Location and Event Data project. Negative binomial regression models were fitted with fixed effects to isolate the immediate and long-term effects of terrorist attacks on three outcomes (antenatal care visits, of facility deliveries and of cesarean sections). RESULTS: During the next month of an attack, the incidence of assisted deliveries in healthcare facilities is significantly reduced by 3.8% (95% CI 1.3 to 6.3). Multiple attacks have immediate effects more pronounced than single attacks. Longitudinal analysis show that the incremental number of terrorist attacks is associated with a decrease of the three outcomes. For every additional attack in a commune, the incidence of cesarean sections is reduced by 7.7% (95% CI 4.7 to 10.7) while, for assisted deliveries, it is reduced by 2.5% (95% CI 1.9 to 3.1) and, for antenatal care visits, by 1.8% (95% CI 1.2 to 2.5). CONCLUSION: Terrorist attacks constitute a new barrier to access of maternal healthcare in Burkina Faso. The exponential increase in terrorist activities in West Africa is expected to have negative effects on maternal health in the entire region.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 it