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Record W4411188669 · doi:10.1080/16549716.2025.2513856

The escalating health crisis in Gaza amidst armed conflict and heatwaves

2025· article· en· W4411188669 on OpenAlexaff
Luc Souilla, Amira Shaheen, Amira N. Mostafa, Samer Abuzerr

Bibliographic record

VenueGlobal Health Action · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsArmed conflictPolitical scienceDevelopment economicsGeographyEconomic growthEnvironmental healthMedicineEconomics

Abstract

fetched live from OpenAlex

The ongoing conflict in Gaza has resulted in a catastrophic humanitarian crisis, displacing over 1.7 million people and causing widespread damage to infrastructure, which has severely limited access to adequate shelter, clean water, and healthcare. With summer temperatures exceeding 38°C (100 °F), conflict has heightened the population's vulnerability to heat-related health risks, compounded by a combination of environmental, individual, and conflict-induced factors. Gaza's dense population, high numbers of vulnerable groups (e.g. infants, pregnant women, the elderly), and widespread pre-existing health conditions further amplify susceptibility to heat stress. Overcrowded shelters foster rapid dehydration and the spread of infectious diseases, while the destruction of Gaza's power grid has led to widespread electricity shortages, depriving families of fans, air conditioning, and refrigeration, which are critical for cooling. Immediate global intervention is required to implement emergency public health measures and establish long-term resilience to extreme heat. Proposed actions include the provision of solar-powered cooling shelters, ensuring access to clean drinking water, distributing essential supplies such as solar-powered fans and hydration kits, and investing in climate-resilient infrastructure. Without urgent action, the convergence of extreme heat and the ongoing conflict in Gaza threatens to trigger a devastating heat-related health crisis that disproportionately affects the most vulnerable segments of the population.

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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.777
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.054
GPT teacher head0.418
Teacher spread0.364 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2025
Admission routes1
Has abstractyes

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