tetano
Editor, Senior Moderator
Nihon Koshu Eisei Zasshi. 2018;65(11):666-676. doi: 10.11236/jph.65.11_666.
[h=1][Evaluation of real-time surveillance of influenza incidence in Kawasaki City by comparison using the National Epidemiological Surveillance of Infectious Diseases].[/h] [Article in Japanese]
Nakamura T[SUP]1[/SUP], Maruyama A[SUP]2[/SUP], Misaki T[SUP]2[/SUP], Okabe N[SUP]2[/SUP], Shinmei K[SUP]1,[/SUP][SUP]3[/SUP], Hashizume M[SUP]4[/SUP], Murakami Y[SUP]5[/SUP], Nishiwaki Y[SUP]1[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] 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.
[h=4]KEYWORDS:[/h] Epidemic curve; Influenza; Kawasaki City; National Epidemiological Surveillance of Infectious Diseases; Real-time surveillance
PMID: 30518705 DOI: 10.11236/jph.65.11_666
[h=1][Evaluation of real-time surveillance of influenza incidence in Kawasaki City by comparison using the National Epidemiological Surveillance of Infectious Diseases].[/h] [Article in Japanese]
Nakamura T[SUP]1[/SUP], Maruyama A[SUP]2[/SUP], Misaki T[SUP]2[/SUP], Okabe N[SUP]2[/SUP], Shinmei K[SUP]1,[/SUP][SUP]3[/SUP], Hashizume M[SUP]4[/SUP], Murakami Y[SUP]5[/SUP], Nishiwaki Y[SUP]1[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] 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.
[h=4]KEYWORDS:[/h] Epidemic curve; Influenza; Kawasaki City; National Epidemiological Surveillance of Infectious Diseases; Real-time surveillance
PMID: 30518705 DOI: 10.11236/jph.65.11_666