Department of Geography, Florida State University, 113 Collegiate Loop, Tallahassee, FL, 32306, USA.
Florida Department of Health, 4052 Bald Cypress Way, Tallahassee, FL, 32399, USA.
Environ Health. 2019 Jul 9;18(1):59. doi: 10.1186/s12940-019-0499-x.
Elevated and prolonged exposure to extreme heat is an important cause of excess summertime mortality and morbidity. To protect people from health threats, some governments are currently operating syndromic surveillance systems. However, A lack of resources to support time- and labor- intensive diagnostic and reporting processes make it difficult establishing region-specific surveillance systems. Big data created by social media and web search may improve upon the current syndromic surveillance systems by directly capturing people's individual and subjective thoughts and feelings during heat waves. This study aims to investigate the relationship between heat-related web searches, social media messages, and heat-related health outcomes.
We collected Twitter messages that mentioned "air conditioning (AC)" and "heat" and Google search data that included weather, medical, recreational, and adaptation information from May 7 to November 3, 2014, focusing on the state of Florida, U.S. We separately associated web data against two different sources of health outcomes (emergency department (ED) and hospital admissions) and five disease categories (cardiovascular disease, dehydration, heat-related illness, renal disease, and respiratory disease). Seasonal and subseasonal temporal cycles were controlled using autoregressive moving average-generalized autoregressive conditional heteroscedasticity (ARMA-GARCH) and generalized linear model (GLM).
The results show that the number of heat-related illness and dehydration cases exhibited a significant positive relationship with web data. Specifically, heat-related illness cases showed positive associations with messages (heat, AC) and web searches (drink, heat stroke, park, swim, and tired). In addition, terms such as park, pool, swim, and water tended to show a consistent positive relationship with dehydration cases. However, we found inconsistent relationships between renal illness and web data. Web data also did not improve the models for cardiovascular and respiratory illness cases.
Our findings suggest web data created by social medias and search engines could improve the current syndromic surveillance systems. In particular, heat-related illness and dehydration cases were positively related with web data. This paper also shows that activity patterns for reducing heat stress are associated with several health outcomes. Based on the results, we believe web data could benefit both regions without the systems and persistently hot and humid climates where excess heat early warning systems may be less effective.
高温暴露时间延长是导致夏季超额死亡和发病的重要原因。为保护民众免受健康威胁，一些政府目前正在运营症候群监测系统。然而，由于缺乏资源来支持耗时耗力的诊断和报告流程，建立具有区域针对性的监测系统变得困难重重。社交媒体和网络搜索所产生的大数据或许可以通过直接捕捉人们在热浪期间的个体和主观想法与感受，来改善当前的症候群监测系统。本研究旨在调查与热相关的网络搜索、社交媒体信息和与热相关的健康结果之间的关系。
我们收集了 2014 年 5 月 7 日至 11 月 3 日期间与佛罗里达州有关的提到“空调（AC）”和“热”的 Twitter 消息，以及包含天气、医疗、娱乐和适应信息的谷歌搜索数据。我们分别将网络数据与两个不同的健康结果来源（急诊部（ED）和住院）和五个疾病类别（心血管疾病、脱水、与热相关的疾病、肾脏疾病和呼吸道疾病）联系起来。使用自回归移动平均-广义自回归条件异方差（ARMA-GARCH）和广义线性模型（GLM）来控制季节性和亚季节性时间周期。
结果表明，与热相关的疾病和脱水病例数量与网络数据呈显著正相关。具体来说，与热相关的疾病病例与信息（热、AC）和网络搜索（喝、中暑、公园、游泳和疲倦）呈正相关。此外，公园、游泳池、游泳和水等术语与脱水病例呈一致的正相关关系。然而，我们发现肾脏疾病与网络数据之间存在不一致的关系。网络数据也没有改善心血管和呼吸道疾病病例的模型。
我们的研究结果表明，社交媒体和搜索引擎创建的网络数据可以改进当前的症候群监测系统。特别是，与热相关的疾病和脱水病例与网络数据呈正相关。本文还表明，减少热应激的活动模式与几种健康结果相关。基于这些结果，我们相信网络数据可能有益于没有系统的地区和持续炎热潮湿的气候地区，因为在这些地区，提前预警高温的系统可能效果不佳。
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