Won Miguel, Marques-Pita Manuel, Louro Carlota, Gonçalves-Sá Joana
Instituto Gulbenkian de Ciência, Oeiras, Portugal.
Nova Medical School, Universidade Nova de Lisboa and Saude 24, Lisbon, Portugal.
PLoS Comput Biol. 2017 Feb 3;13(2):e1005330. doi: 10.1371/journal.pcbi.1005330. eCollection 2017 Feb.
Every year, influenza epidemics affect millions of people and place a strong burden on health care services. A timely knowledge of the onset of the epidemic could allow these services to prepare for the peak. We present a method that can reliably identify and signal the influenza outbreak. By combining official Influenza-Like Illness (ILI) incidence rates, searches for ILI-related terms on Google, and an on-call triage phone service, Saúde 24, we were able to identify the beginning of the flu season in 8 European countries, anticipating current official alerts by several weeks. This work shows that it is possible to detect and consistently anticipate the onset of the flu season, in real-time, regardless of the amplitude of the epidemic, with obvious advantages for health care authorities. We also show that the method is not limited to one country, specific region or language, and that it provides a simple and reliable signal that can be used in early detection of other seasonal diseases.
每年，流感疫情都会影响数百万人，并给医疗服务带来沉重负担。及时了解疫情的爆发情况可以让这些服务机构为高峰期做好准备。我们提出了一种能够可靠地识别并发出流感爆发信号的方法。通过结合官方的流感样疾病（ILI）发病率、在谷歌上搜索与ILI相关的词汇以及一个随叫随到的分诊电话服务——“健康24”，我们能够确定8个欧洲国家流感季节的开始，比当前官方警报提前了几周。这项工作表明，无论疫情规模大小，都有可能实时检测并持续预测流感季节的开始，这对医疗保健当局具有明显优势。我们还表明，该方法不限于一个国家、特定地区或语言，并且它提供了一个简单可靠的信号，可用于早期检测其他季节性疾病。
