Department of Ecology & Evolutionary Biology and Biodiversity Institute, University of Kansas, Lawrence, Kansas, USA.
Information Systems and Modeling (A-1), Los Alamos National Laboratory, Los Alamos, NM, USA.
BMC Infect Dis. 2020 Mar 26;20(1):252. doi: 10.1186/s12879-020-04957-0.
Dengue fever is a mosquito-borne infection transmitted by Aedes aegypti and mainly found in tropical and subtropical regions worldwide. Since its re-introduction in 1986, Brazil has become a hotspot for dengue and has experienced yearly epidemics. As a notifiable infectious disease, Brazil uses a passive epidemiological surveillance system to collect and report cases; however, dengue burden is underestimated. Thus, Internet data streams may complement surveillance activities by providing real-time information in the face of reporting lags.
We analyzed 19 terms related to dengue using Google Health Trends (GHT), a free-Internet data-source, and compared it with weekly dengue incidence between 2011 to 2016. We correlated GHT data with dengue incidence at the national and state-level for Brazil while using the adjusted R squared statistic as primary outcome measure (0/1). We used survey data on Internet access and variables from the official census of 2010 to identify where GHT could be useful in tracking dengue dynamics. Finally, we used a standardized volatility index on dengue incidence and developed models with different variables with the same objective.
From the 19 terms explored with GHT, only seven were able to consistently track dengue. From the 27 states, only 12 reported an adjusted R squared higher than 0.8; these states were distributed mainly in the Northeast, Southeast, and South of Brazil. The usefulness of GHT was explained by the logarithm of the number of Internet users in the last 3 months, the total population per state, and the standardized volatility index.
The potential contribution of GHT in complementing traditional established surveillance strategies should be analyzed in the context of geographical resolutions smaller than countries. For Brazil, GHT implementation should be analyzed in a case-by-case basis. State variables including total population, Internet usage in the last 3 months, and the standardized volatility index could serve as indicators determining when GHT could complement dengue state level surveillance in other countries.
登革热是一种由埃及伊蚊传播的蚊媒感染病，主要发生在全球热带和亚热带地区。自 1986 年重新引入以来，巴西已成为登革热的热点地区，每年都发生疫情。作为一种法定传染病，巴西使用被动流行病学监测系统收集和报告病例；然而，登革热负担被低估了。因此，互联网数据流可以通过在报告滞后的情况下提供实时信息来补充监测活动。
我们使用免费的互联网数据源 Google Health Trends（GHT）分析了与登革热相关的 19 个术语，并将其与 2011 年至 2016 年期间每周的登革热发病率进行了比较。我们将 GHT 数据与巴西的国家和州级登革热发病率进行了相关分析，同时使用调整后的 R 平方统计量作为主要结果衡量指标（0/1）。我们使用关于互联网接入的调查数据和 2010 年官方人口普查中的变量，确定了 GHT 在跟踪登革热动态方面的用途。最后，我们使用了登革热发病率的标准化波动率指数，并使用相同的目标开发了具有不同变量的模型。
从 GHT 中探索的 19 个术语中，只有 7 个能够持续跟踪登革热。在 27 个州中，只有 12 个州的调整后的 R 平方高于 0.8；这些州主要分布在巴西的东北部、东南部和南部。GHT 的有用性可以用过去 3 个月的互联网用户对数、各州的总人口和标准化波动率指数来解释。
GHT 在补充传统的既定监测策略方面的潜在贡献应该在国家以下更小的地理分辨率背景下进行分析。对于巴西，应该根据具体情况分析 GHT 的实施情况。包括总人口、过去 3 个月的互联网使用情况和标准化波动率指数在内的州变量可以作为确定 GHT 在其他国家补充州级登革热监测时的指标。
