对气候敏感疾病的可扩展,开放和多学科数据整合管道
Abhishek Dasgupta1,2, Iago Perez-Fernandez3, Tuyen Huynh4
1Oxford Research Software Engineering Group, Doctoral Training Centre, University of Oxford, Oxford, UK.
Wellcome open research
|November 28, 2025
概括
气候变化加剧了传染病. 我们开发了一个开放访问管道,以整合各种数据来分析气候敏感疾病传播,提高研究可重复性.
科学领域:
- 环境科学环境科学
- 流行病学 流行病学
- 计算生物学是一种计算生物学.
背景情况:
- 气候变化对人类,动物和环境健康产生重大影响,超过一半的已知传染病可能会因气候变化而恶化.
- 媒介性疾病的传播受气候条件的影响,但社会经济,行为和土地利用因素也起着至关重要的作用.
- 分析气候敏感疾病需要将跨学科数据与流行病学,基因组学和临床信息相结合,这是当前数据整合工具所阻碍的任务.
研究的目的:
- 开发一个可扩展的,开放的数据集成管道,用于分析气候敏感传染病.
- 解决现有工具的局限性,这些工具通常是特定于数据类型或依赖专有软件的.
- 提高研究气候与疾病之间的复杂相互作用的可复制性和可访问性.
主要方法:
- 开发了一个可扩展和开放的管道,用于集成多个时空数据集.
- 管道需要最小的用户输入,只需要研究的国家,时间范围和分辨率.
- 包括气候数据的偏差校正模块,以提高下游建模的准确性.
主要成果:
- 证明了管道对越南登革热模型的实用性,满足当地数据要求.
- 成功简化了复杂的数据下载,校正和聚合流程.
- 该工具促进了基于数据的发现传染病及其驱动因素之间的时空关系.
结论:
- 登革热高级准备工具管道 (DART-P) 通过简化气候疾病建模的数据集成来赋予研究人员权力.
- 该管道提高了研究可重现性,并促进了疾病驱动因子关系的发现.
- 管道的开放和可扩展性质允许适应各种用例,而不仅仅是展示的例子.
更多相关视频
09:33Visualizing Field Data Collection Procedures of Exposure and Biomarker Assessments for the Household Air Pollution Intervention Network Trial in India
Published on: December 23, 2022
2.6K
08:51Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts
Published on: September 20, 2024
2.0K
相关概念视频
01:26Principles of Disease Surveillance
440
Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...
440
01:12Statistical Software for Data Analysis and Clinical Trials
1.4K
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
1.4K
01:25Statistical Methods for Analyzing Epidemiological Data
875
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
875