Nakamura Takahiro, Maruyama Aya, Misaki Takako, Okabe Nobuhiko, Shinmei Keita, Hashizume Masahiro, Murakami Yoshitaka, Nishiwaki Yuji
Department of Environmental and Occupational Health, School of Medicine, Toho University, Tokyo, Japan.
Kawasaki City Institute for Public Health.
Nihon Koshu Eisei Zasshi. 2018;65(11):666-676. doi: 10.11236/jph.65.11_666.
Objectives In Japan, nationwide data of the incidence of infectious diseases have been collected via the National Epidemiological Surveillance of Infectious Diseases (NESID) since 1981. In addition, since March 2014, Kawasaki City has operated its own real-time surveillance (RTS) system to collect data of the incidence of influenza from medical institutions across the city. This study aimed to describe the characteristics of the RTS system and compare the two surveillance systems to improve measures against infectious diseases in the future.Methods NESID and RTS data from March 2014 to October 2017 were obtained from the Kawasaki City Institute for Public Health. First, the operating methodologies of the two surveillance systems were compared. Second, RTS data were used to analyze the daily epidemic curve, and then the daily number of influenza cases was converted into weekly data for comparison with NESID data. Pearson's correlation coefficients and 95% confidence intervals (CIs) were calculated. Correlations were also analyzed after data for the last and first weeks of each year were excluded because few hospitals remain open around the New Year holiday, resulting in a disproportionately large number of patients visiting the few institutions that remain open.Results The NESID relies on data provided by a fixed number of medical institutions determined each fiscal year (mean: 56.0±4.2 institutions), while the number of institutions providing data for the RTS varies daily or monthly. In September 2017, 691 of the 1,032 eligible institutions (67.0%) were registered for the RTS. Pearson's correlation coefficient for the two surveillance systems was 0.975 (95%CI, 0.967-0.981); when data for the last and first week of each year were excluded, it was 0.989 (95%CI 0.986-0.992). In each of the three seasons that were investigated, an increase in the incidence of type A influenza preceded an increase in the incidence of type B influenza.Conclusion The operating methodologies of the two surveillance systems differed; however, the results identified a strong correlation, confirming the reliability of the RTS. The RTS collects daily data by influenza type; therefore, it detects epidemic onsets at an earlier stage, facilitating more detailed epidemiological analysis, compared with that of the NESID. It is necessary to understand differences in the characteristics between two surveillance systems when we analyze influenza surveillance data.
目标 在日本，自1981年起通过全国传染病流行病学监测（NESID）收集全国传染病发病率数据。此外，自2014年3月起，川崎市运行了自己的实时监测（RTS）系统，以收集全市医疗机构的流感发病率数据。本研究旨在描述RTS系统的特点，并比较这两种监测系统，以改进未来针对传染病的措施。
方法 获取川崎市公共卫生研究所2014年3月至2017年10月的NESID和RTS数据。首先，比较两种监测系统的运行方法。其次，使用RTS数据分析每日疫情曲线，然后将每日流感病例数转换为每周数据，以便与NESID数据进行比较。计算Pearson相关系数和95%置信区间（CI）。在排除每年最后一周和第一周的数据后也进行了相关性分析，因为新年假期前后很少有医院营业，导致少数仍营业的机构就诊患者数量过多。
结果 NESID依赖于每个财政年度确定的固定数量医疗机构提供的数据（平均：56.0±4.2个机构），而提供RTS数据的机构数量每天或每月都有所不同。2017年9月，1032家符合条件的机构中有691家（67.0%）注册了RTS。两种监测系统的Pearson相关系数为0.975（95%CI，0.967 - 0.981）；排除每年最后一周和第一周的数据后，为0.989（95%CI 0.986 - 0.992）。在调查的三个季节中，甲型流感发病率的上升均先于乙型流感发病率的上升。
结论 两种监测系统的运行方法不同；然而，结果显示出很强的相关性，证实了RTS的可靠性。RTS按流感类型收集每日数据；因此，与NESID相比，它能在更早阶段检测到疫情爆发，便于进行更详细的流行病学分析。在分析流感监测数据时，有必要了解两种监测系统特点的差异。
