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Tiantian Li

Publications and source records attributed to Tiantian Li.

2 recordsLinked to original sources

From population to individual: advocating personalised digital tools for heat-health early warning in a changing climate.

Escalating heat extremes under climate change are imposing substantial health burdens, with 2023 and 2024 consecutively breaking global temperature records. Mounting evidence suggests that heatwaves elevate the risks of hospitalisation and mortality across multiple disease categories, including ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and acute kidney injury. Nonetheless, most existing heat-health warning systems remain primarily reliant on population-level predictions, and considering individual differences and disease-specific considerations when defining warning levels would benefit the effectiveness of early prevention for high-risk groups. In this Viewpoint, which is based on the framework of precision public health-delivering the right intervention to the right population at the right time-we propose a framework for personalised digital heat-health early warning tools comprising three dimensions: individualised, risk-stratified prediction models that generate tiered early warnings; personalised health prompts coupled with theory-informed behavioural interventions; and adaptive, equity-oriented alert delivery mechanisms tailored to diverse populations. Such tools have the potential to bridge precision disease prevention and climate adaptation, thereby helping to mitigate heat exposure risks and disease burdens, particularly among high-risk populations. Future implementation research will be essential to address substantial challenges related to feasibility, validation, and equity.

Journal Article

Direct and spillover hospitalisation patterns during climate hazards across regions of different health-system resilience levels in China: a nationwide retrospective analysis.

BACKGROUND: Health-system resilience serves as a key contributor in mitigating adverse health impacts during climate hazards. However, quantitative insights into resilience-associated health-care utilisation patterns and targeted adaptation policies remain scarce. We aimed to capture the spatiotemporal health impacts in disaster-exposed counties and their neighbouring counties in China during storms, floods, tropical cyclones, and blizzards or winter storms; understand the association between health-system resilience metrics and hazard-attributable hospitalisations; and develop evidence-based adaptation policies towards climate extremes. METHODS: In this retrospective, observational analysis of county-level aggregated hospitalisation data, we used a propensity score matching-difference-in-differences framework to assess the spatiotemporal changes of nine types of disease-specific hospitalisations in both disaster-exposed and neighbouring regions during storms, floods, tropical cyclones, and blizzards in China. We quantified the relative importance and health gains of health-system metrics during such hazards through random forest approach with interpretable partial dependence plots to derive evidence-based adaptation recommendations. FINDINGS: We included hospitalisation data from Jan 1, 2016 to Dec 31, 2023. In this period, 3241 county-hazard event combinations and 41 747 482 hospitalisations were recorded across 955 Chinese counties. The disaster-exposed regions experienced an initial decline in hospitalisation rates, followed by admission surges after disasters. For example, infectious disease admissions decreased by 11·92% (95% CI -10·53 to -13·31) during the flood-active period but increased by 7·68% (6·46-8·91) after 1-2 weeks of floods. Neighbouring zones were also affected through spillover effects, with infectious disease admissions increasing by 3·18% (1·76-4·61) after 1-2 weeks of the floods. Cardiovascular disease, injuries, infectious, respiratory, and mental disorders were more sensitive across all regions. Particularly for disaster-exposed counties, cardiovascular hospitalisations increased by 14·31% (7·34-21·29) during the tropical cyclone-active period. Notably, compared with low-resilience counties, high-resilience counties were associated with 19·48-30·03% smaller hazard-related relative changes in hospitalisation rates during the hazard-active period and 27·07-31·08% smaller hazard-related relative changes in hospitalisation rates in post-hazard periods. For instance, during the storm-active period, the increase in respiratory hospitalisations was 7·21% (0·67-13·75) in high-resilience counties versus 12·13% (5·20-19·05) in low-resilience counties. Health workforce (relative importance 14·58% during the hazard-active period and 13·80% during the post-hazard period) and service delivery (14·10% during the hazard-active period and 14·17% during the post-hazard period) were identified as key contributors of health-system resilience. Empirical synergistic effects were observed when combining interventions during the post-hazard period, with the combined effect of service delivery (individual contribution 8%) and workforce (individual contribution 4%) exceeding the sum of their individual contributions (16% reduction in cumulative excess admissions) by 33%. INTERPRETATION: Climate hazards are associated with substantial changes in hospitalisation rates in both disaster-exposed and neighbouring regions. Health-system resilience is essential in addressing disaster-health challenges. Targeted adaptation interventions should be context-appropriate and threshold-aware, thereby maximising the public health benefits relative to resilience-oriented investments in health systems. FUNDING: Gates Foundation and the National Natural Science Foundation of China.

Journal Article