大数据-行星健康方法用于评估巴西登革热控制计划
Fernando Xavier1, Gerson Laurindo Barbosa2, Cristiano Corrêa de Azevedo Marques2
1Universidade de São Paulo. Programa de Pós-Graduação em Engenharia Elétrica. São Paulo, SP, Brasil.
Revista de saude publica
|May 8, 2024
概括
大数据分析揭示了圣保罗的缺陷.
科学领域:
- 公共卫生 公共卫生
- 数据科学数据科学数据科学
- 环境健康 环境健康
背景情况:
- 唐纳贝迪安模型是评估医疗保健质量的框架.
- 星球健康考虑人类文明的健康状况以及它们所依赖的自然系统的状态.
- 大数据为大规模的卫生计划评估提供了新的机会.
研究的目的:
- 将行星健康和大数据概念整合到Donabedian模型中.
- 评估巴西圣保罗州的登革热控制计划.
主要方法:
- 利用数据科学方法分析2010-2019年登革热相关数据.
- 将来自DATASUS,IBGE,WorldClim和MapBiomas的数据整合到一个数据仓库中.
- 应用K-means集群,统计分析和空间可视化.
主要成果:
- 根据气候变量,确定了四个不同的市镇群.
- 在登革热控制方面表现最差的城市经济状况更好,但人均医疗保健资源较少.
- 较高的城市化率和人类活动与较差的登革热控制结果相关.
结论:
- 该方法确定了圣保罗的登革热控制计划实施中的重大缺陷.
- 使用集成数据库和数据科学进行大规模评估是可行的.
- 调查结果可以为公共管理部门提供有针对性的行动和投资的信息.
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