Global short-term mortality risk and burden associated with tropical cyclones from 1980 to 2019: a multi-country time-series study
Bibliographic record
Abstract
BACKGROUND: The global spatiotemporal pattern of mortality risk and burden attributable to tropical cyclones is unclear. We aimed to evaluate the global short-term mortality risk and burden associated with tropical cyclones from 1980 to 2019. METHODS: The wind speed associated with cyclones from 1980 to 2019 was estimated globally through a parametric wind field model at a grid resolution of 0·5° × 0·5°. A total of 341 locations with daily mortality and temperature data from 14 countries that experienced at least one tropical cyclone day (a day with maximum sustained wind speed associated with cyclones ≥17·5 m/s) during the study period were included. A conditional quasi-Poisson regression with distributed lag non-linear model was applied to assess the tropical cyclone-mortality association. A meta-regression model was fitted to evaluate potential contributing factors and estimate grid cell-specific tropical cyclone effects. FINDINGS: Tropical cyclone exposure was associated with an overall 6% (95% CI 4-8) increase in mortality in the first 2 weeks following exposure. Globally, an estimate of 97 430 excess deaths (95% empirical CI [eCI] 71 651-126 438) per decade were observed over the 2 weeks following exposure to tropical cyclones, accounting for 20·7 (95% eCI 15·2-26·9) excess deaths per 100 000 residents (excess death rate) and 3·3 (95% eCI 2·4-4·3) excess deaths per 1000 deaths (excess death ratio) over 1980-2019. The mortality burden exhibited substantial temporal and spatial variation. East Asia and south Asia had the highest number of excess deaths during 1980-2019: 28 744 (95% eCI 16 863-42 188) and 27 267 (21 157-34 058) excess deaths per decade, respectively. In contrast, the regions with the highest excess death ratios and rates were southeast Asia and Latin America and the Caribbean. From 1980-99 to 2000-19, marked increases in tropical cyclone-related excess death numbers were observed globally, especially for Latin America and the Caribbean and south Asia. Grid cell-level and country-level results revealed further heterogeneous spatiotemporal patterns such as the high and increasing tropical cyclone-related mortality burden in Caribbean countries or regions. INTERPRETATION: Globally, short-term exposure to tropical cyclones was associated with a significant mortality burden, with highly heterogeneous spatiotemporal patterns. In-depth exploration of tropical cyclone epidemiology for those countries and regions estimated to have the highest and increasing tropical cyclone-related mortality burdens is urgently needed to help inform the development of targeted actions against the increasing adverse health impacts of tropical cyclones under a changing climate. FUNDING: Australian Research Council and Australian National Health and Medical Research Council.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".