Climate change and health care facilities: A risk analysis framework through a mapping review

Guihenneuc, Jérémy; Ayraud-Thevenot, Sarah; Roschnik, Sonia; Dupuis, Antoine; Migeot, Virginie

doi:10.1016/j.envres.2022.114709

Cited by 11 publications

(5 citation statements)

References 39 publications

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“…(ii) The significance of harnessing spatiotemporal big data and cutting-edge GeoAI technologies cannot be overstated, as these tools are instrumental in precisely predicting and comprehending health needs and resource distribution in smaller areas [ 86 ]. (iii) Finally, our framework stresses the imperative for flexible policies and interventions capable of adapting to ongoing challenges brought about by climate change, environmental degradation, and social inequality, all of which substantially affect the local demand for and allocation of health resources [ 87 ]. By spatiotemporally understanding healthcare requirements and disparities, policymakers can dynamically allocate resources, design preemptive healthcare strategies, and ensure equitable healthcare access across all regions, ultimately contributing to a more resilient and responsive healthcare system globally.…”

Section: Discussionmentioning

confidence: 99%

Revealing spatiotemporal inequalities, hotspots, and determinants in healthcare resource distribution: insights from hospital beds panel data in 2308 Chinese counties

Song,

Fang,

Xie

et al. 2024

BMC Public Health

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Background Ensuring universal health coverage and equitable access to health services requires a comprehensive understanding of spatiotemporal heterogeneity in healthcare resources, especially in small areas. The absence of a structured spatiotemporal evaluation framework in existing studies inspired us to propose a conceptual framework encompassing three perspectives: spatiotemporal inequalities, hotspots, and determinants. Methods To demonstrate our three-perspective conceptual framework, we employed three state-of-the-art methods and analyzed 10 years’ worth of Chinese county-level hospital bed data. First, we depicted spatial inequalities of hospital beds within provinces and their temporal inequalities through the spatial Gini coefficient. Next, we identified different types of spatiotemporal hotspots and coldspots at the county level using the emerging hot spot analysis (Getis-Ord Gi* statistics). Finally, we explored the spatiotemporally heterogeneous impacts of socioeconomic and environmental factors on hospital beds using the Bayesian spatiotemporally varying coefficients (STVC) model and quantified factors’ spatiotemporal explainable percentages with the spatiotemporal variance partitioning index (STVPI). Results Spatial inequalities map revealed significant disparities in hospital beds, with gradual improvements observed in 21 provinces over time. Seven types of hot and cold spots among 24.78% counties highlighted the persistent presence of the regional Matthew effect in both high- and low-level hospital bed counties. Socioeconomic factors contributed 36.85% (95% credible intervals [CIs]: 31.84–42.50%) of county-level hospital beds, while environmental factors accounted for 59.12% (53.80–63.83%). Factors’ space-scale variation explained 75.71% (68.94–81.55%), whereas time-scale variation contributed 20.25% (14.14–27.36%). Additionally, six factors (GDP, first industrial output, local general budget revenue, road, river, and slope) were identified as the spatiotemporal determinants, collectively explaining over 84% of the variations. Conclusions Three-perspective framework enables global policymakers and stakeholders to identify health services disparities at the micro-level, pinpoint regions needing targeted interventions, and create differentiated strategies aligned with their unique spatiotemporal determinants, significantly aiding in achieving sustainable healthcare development.

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Section: Discussionmentioning

confidence: 99%

Revealing spatiotemporal inequalities, hotspots, and determinants in healthcare resource distribution: insights from hospital beds panel data in 2308 Chinese counties

Song,

Fang,

Xie

et al. 2024

BMC Public Health

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“…Enhanced diagnostic accuracy and speed, followed by immediate treatment, is vital for hospitals and other community medical institutions in order to reduce morbidity and mortality [ 26 ]. Lastly, understanding the impact of heat waves on health care services underscores the need for climate change mitigation and adaptation, such as increasing the resilience of health care systems and being responsive to the effects of heat waves [ 93 , 94 ].…”

Section: Discussionmentioning

confidence: 99%

The Impact of Heat Waves on Health Care Services in Low- or Middle-Income Countries: Protocol for a Systematic Review

Sapari,

Selamat,

Isa

et al. 2023

JMIR Res Protoc

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Background Heat waves significantly impact ecosystems and human health, especially that of vulnerable populations, and are associated with increased morbidity and mortality. Besides being directly related to climate-sensitive health outcomes, heat waves have indirectly increased the burden on our health care systems. Although the existing literature examines the impact of heat waves and morbidity, past research has mostly been conducted in high-income countries (HICs), and studies on the impact of heat waves on morbidity in low- or middle-income countries (LMICs) are still scarce. Objective This paper presents the protocol for a systematic review that aims to provide evidence of the impact of heat waves on health care services in LMICs. Methods We will identify peer-reviewed studies from 3 online databases, including the Web of Science, PubMed, and SCOPUS, published from January 2002 to April 2023, using the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) guidelines. Quality assessment will be conducted using the Navigation Guide checklist. Key search terms include heatwaves, extreme heat, hospitalization, outpatient visit, burden, health services, and morbidity. Results This systematic review will provide insight into the impact of heat waves on health care services in LMICs, especially on emergency department visits, ambulance call-outs, hospital admissions, outpatient department visits, in-hospital mortality, and health care operational costs. Conclusions The results of this review are anticipated to help policymakers and key stakeholders obtain a better understanding of the impact of heat waves on health care services and prioritize investments to mitigate the effects of heat waves in LMICs. This entails creating a comprehensive heat wave plan and ensuring that adequate infrastructure, capacity, and human resources are allocated in the health care sector. These measures will undoubtedly contribute to the development of resilience in health care systems and hence protect the health and well-being of individuals and communities. Trial Registration PROSPERO CRD42022365471; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=365471 International Registered Report Identifier (IRRID) DERR1-10.2196/44702

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“…-Part 3: Elderly's previous information about climate change and its effect on health and source of information if present. Tool II: Climate change knowledge questionnaire: This tool was developed by the researcher after reviewing the relevant literatures (28)(29)(30)(31)(32) to assess baseline knowledge of elderly about climate change and related health impact. It included 32 ).…”

Section: Sample Size Calculationmentioning

confidence: 99%

Climate Change and Health: Effect of Awareness Program on Knowledge, Attitudes and Practices of Community Dwelling Elderly

Ibrahim,

Abd Elmawla,

Ali

2023

Tanta Scientific Nursing Journal

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Background: Climate change is the biggest global health threat of the 21 st century with both direct and indirect effects on human health especially for vulnerable groups as elderly. So, it's important to raise their awareness about climate change to reduce its adverse effect on health. Aim: To evaluate the effect of awareness program on knowledge, attitudes and practices of community dwelling elderly regarding climate change and health. Method: A quasi-experimental, pre and post intervention research design was implemented. A convenience sample of 72 community dwelling elderly attending El-Amal elderly club in Mansoura city. Tools: Five tools were used for data collection; Demographic and Health profile structured interview sheet, Climate change knowledge questionnaire, Elderly's attitude toward climate change self-rating scale, Elderly's self-reported practices about their adaption towards climate change checklist and Elderly's awareness level about climate change and its effect of health questionnaire. Results: There were significant improvement in elderly's total mean score of knowledge, practices, attitudes and awareness after 3 months from implementation of the awareness program than before (P=0.000**). Also, a statistically significant strong positive correlation was found between the total knowledge score of the studied elderly and both total practices scores, total attitudes scores and total awareness score after implementation of the awareness program Conclusion: The awareness program improved knowledge, attitudes and practices of community dwelling elderly about climate change and health. Recommendations: Dissemination of developed illustrated awareness program booklet about climate change and health to all elderly at Mansoura City should be done.

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Climate change and health care facilities: A risk analysis framework through a mapping review

Cited by 11 publications

References 39 publications

Revealing spatiotemporal inequalities, hotspots, and determinants in healthcare resource distribution: insights from hospital beds panel data in 2308 Chinese counties

Revealing spatiotemporal inequalities, hotspots, and determinants in healthcare resource distribution: insights from hospital beds panel data in 2308 Chinese counties

The Impact of Heat Waves on Health Care Services in Low- or Middle-Income Countries: Protocol for a Systematic Review

Climate Change and Health: Effect of Awareness Program on Knowledge, Attitudes and Practices of Community Dwelling Elderly

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