The Open Infectious Diseases Journal




ISSN: 1874-2793 ― Volume 10, 2018
RESEARCH ARTICLE

Improvement of Influenza Incidence Estimation Using Auxiliary Information in Sentinel Surveillance in Japan



Miyuki Kawado1, Shuji Hashimoto1, *, Akiko Ohta2, Mari S. Oba3, Kiyosu Taniguchi4, Tomimasa Sunagawa5, Tamano Matsui5, Masaki Nagai6, Yoshitaka Murakami3
1 Department of Hygiene, Fujita Health University School of Medicine, Aichi, Japan
2 Division of Public Health, Department of Social Medicine, Saitama Medical University Faculty of Medicine, Saitama, Japan
3 Department of Medical Statistics, Toho University, Tokyo, Japan
4 Department of Clinical Research, National Mie Hospital, Mie, Japan
5 Infectious Disease Surveillance Center, National Institute of Infectious Diseases, Tokyo, Japan
6 Department of Social Medicine, Saitama Medical University, Saitama, Japan

Abstract

Introduction:

Sentinel surveillance in Japan is used to estimate national influenza incidence under the assumption that Sentinel Medical Institutions (SMIs) are randomly selected. The current method might lead to overestimation when SMIs are recruited on a voluntary basis.

Aims & Objectives:

We aimed to improve influenza incidence estimation using auxiliary information without this assumption.

Materials and Method:

We used reports of influenza from SMIs in 2015, together with the number of all disease outpatients in September 2014 at all medical institutions from the Survey of Medical Institutions of Japan, as auxiliary information. The influenza incidence was estimated by the method using auxiliary information and the current method (without auxiliary information).

Result and Conclusion:

Influenza incidence rate per 1,000 population in 2015 estimated by using auxiliary information and by the current method was 63.7 (95% Confidence Interval (CI), 61.0-66.3) and 96.5 (95% CI, 93.0-100.0), respectively. The ratio of these estimates was 0.66. Our findings suggest that influenza incidence estimated by using the number of all disease outpatients as auxiliary information is more accurate than estimates by the current method.

Keywords: Surveillance, Infectious disease, Influenza, Epidemiology, Estimation, Methodology.


Article Information


Identifiers and Pagination:

Year: 2018
Volume: 10
First Page: 29
Last Page: 36
Publisher Id: TOIDJ-10-29
DOI: 10.2174/1874279301810010029

Article History:

Received Date: 6/12/2017
Revision Received Date: 06/4/2018
Acceptance Date: 13/4/2018
Electronic publication date: 14/05/2018
Collection year: 2018

Article Metrics:

CrossRef Citations:
0

Total Statistics:

Full-Text HTML Views: 243
Abstract HTML Views: 317
PDF Downloads: 175
ePub Downloads: 185
Total Views/Downloads: 920

Unique Statistics:

Full-Text HTML Views: 159
Abstract HTML Views: 193
PDF Downloads: 135
ePub Downloads: 123
Total Views/Downloads: 610
Geographical View

© 2018 Kawado et al.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


* Address correspondence to this author at the Department of Hygiene, Fujita Health University School of Medicine, 1-98, Dengakugakubo, Kutsukake-cho, Toyoake, Aichi 470-1192, Japan; Tel: +81-562-93-2456; Fax: +81-562-93-2456, E-mail: hasimoto@fujita-hu.ac.jp




1. INTRODUCTION

Influenza sentinel surveillance has been established in many countries [1Costagliola D, Flahault A, Galinec D, Garnerin P, Menares J, Valleron AJ. A routine tool for detection and assessment of epidemics of influenza-like syndromes in France. Am J Public Health 1991; 81(1): 97-9.[http://dx.doi.org/10.2105/AJPH.81.1.97] [PMID: 1983924] -5Taniguchi K, Hashimoto S, Kawado M, et al. Overview of infectious disease surveillance system in Japan, 1999-2005. J Epidemiol 2007; 17(Suppl): S3-S13.[http://dx.doi.org/10.2188/jea.17.S3] [PMID: 18239339] ]. To estimate national incidence, the number of influenza patients reported by Sentinel Medical Institutions (SMIs) and the coverage of SMIs for the national population are often used [3Fleming DM, Zambon M, Bartelds AI. Population estimates of persons presenting to general practitioners with influenza-like illness, 1987-96: A study of the demography of influenza-like illness in sentinel practice networks in England and Wales, and in The Netherlands. Epidemiol Infect 2000; 124(2): 245-53.[http://dx.doi.org/10.1017/S0950268899003660] [PMID: 10813150] ]. In Japan, based on well-designed criteria for selecting SMIs in the guidelines for surveillance, influenza incidence is estimated under the assumption that SMIs are randomly selected [6Hashimoto S, Murakami Y, Taniguchi K, et al. Annual incidence rate of infectious diseases estimated from sentinel surveillance data in Japan. J Epidemiol 2003; 13(3): 136-41.[http://dx.doi.org/10.2188/jea.13.136] [PMID: 12749600] , 7Kawado M, Hashimoto S, Murakami Y, et al. Annual and weekly incidence rates of influenza and pediatric diseases estimated from infectious disease surveillance data in Japan, 2002-2005. J Epidemiol 2007; 17(Suppl): S32-41.[http://dx.doi.org/10.2188/jea.17.S32] [PMID: 18239340] ]. Previous studies have indicated that if SMIs were recruited on a voluntary basis, medical institutions with more patient visits for influenza would likely be selected as SMIs [6Hashimoto S, Murakami Y, Taniguchi K, et al. Annual incidence rate of infectious diseases estimated from sentinel surveillance data in Japan. J Epidemiol 2003; 13(3): 136-41.[http://dx.doi.org/10.2188/jea.13.136] [PMID: 12749600] , 8Nakamura Y, Sugawara T, Kawanohara H, Ohkusa Y, Kamei M, Oishi K. Evaluation of estimated number of influenza patients from national sentinel surveillance using the national database of electronic medical claims. Jpn J Infect Dis 2015; 68(1): 27-9.[http://dx.doi.org/10.7883/yoken.JJID.2014.092] [PMID: 25420664] ]; therefore, this method would lead to overestimation of influenza incidence. In Japan, the population coverage of each medical institution is unavailable owing to the free access healthcare system [6Hashimoto S, Murakami Y, Taniguchi K, et al. Annual incidence rate of infectious diseases estimated from sentinel surveillance data in Japan. J Epidemiol 2003; 13(3): 136-41.[http://dx.doi.org/10.2188/jea.13.136] [PMID: 12749600] , 9Statistics and Information Department, Minister’s Secretariat, Ministry of Health, Labour and Welfare of Japan. The Survey of Medical Institutions 2014 Tokyo: Health and Welfare Statistics Association of Japan; 2016 ]. However, data on the number of outpatients with diseases and injuries treated at each medical institution (all disease outpatients), available from the Survey of Medical Institutions conducted by the Ministry of Health, Labour and Welfare, would be useful as a substitute for the population coverage of SMIs when estimating national incidence [6Hashimoto S, Murakami Y, Taniguchi K, et al. Annual incidence rate of infectious diseases estimated from sentinel surveillance data in Japan. J Epidemiol 2003; 13(3): 136-41.[http://dx.doi.org/10.2188/jea.13.136] [PMID: 12749600] , 10Health Insurance Claims Review and Reimbursement Services of Japan. Annual Report 2013 Available at 2013. Accessed August 17, 2017.http://www.ssk.or.jp/tokeijoho/tokeijoho_03.html-12Fowlkes A, Dasgupta S, Chao E, et al. Estimating influenza incidence and rates of influenza-like illness in the outpatient setting. Influenza Other Respir Viruses 2013; 7(5): 694-700.[http://dx.doi.org/10.1111/irv.12014] [PMID: 22984820] ].

We attempted to improve influenza incidence estimation from sentinel surveillance data in Japan by using the number of all disease outpatients as auxiliary information and not using the assumption that SMIs were randomly selected.

2. MATERIALS AND METHODS

2.1. Surveillance for Influenza in Japan

The National Epidemiological Surveillance for Infectious Diseases (NESID) in Japan has been described elsewhere [5Taniguchi K, Hashimoto S, Kawado M, et al. Overview of infectious disease surveillance system in Japan, 1999-2005. J Epidemiol 2007; 17(Suppl): S3-S13.[http://dx.doi.org/10.2188/jea.17.S3] [PMID: 18239339] , 13Infectious Disease Surveillance Center, National Institute of Infectious Diseases. The National Epidemiological Surveillance of Infectious Diseases in Compliance with the Enforcement of the New Infectious Diseases Control Law. IASR (Infectious Agents Surveillance Report) 1999;20(4):No230 Available at 1999. Accessed August 17, 2017http://idsc.nih.go.jp/iasr/20/230/de2309.html]. It is organized by the Ministry of Health, Labour and Welfare, and involves a sentinel surveillance system for influenza. Prefecture governments select SMIs (about 3,000 pediatric and about 2,000 internal medicine SMIs) according to the Ministry guideline [14Tuberculosis and Infectious Diseases Control Division, Health Service Bureau, Ministry of Health, Labour and Welfare of Japan. The Guideline for National Epidemiological Surveillance of Infectious Diseases (kansensho-hasseidokochosajigyo-jissiyoko). Weekly News of Public Health (Shukan-hoken-eisei) 1999; 998(5): 14-26., 15Hashimoto S, Kawado M, Murakami Y, et al. Number of sentinel medical institutions needed for estimating prefectural incidence in influenza surveillance in Japan. J Epidemiol 2014; 24(3): 183-92.[http://dx.doi.org/10.2188/jea.JE20130077] [PMID: 24584400] ]. The numbers of SMIs in the areas covered by health centers are approximately proportional to their population sizes. In reality, SMIs would rather select on a voluntary basis; although the Ministry guideline recommends random sampling of SMIs from all medical institutions with pediatric and/or internal medicine departments in the covered areas [6Hashimoto S, Murakami Y, Taniguchi K, et al. Annual incidence rate of infectious diseases estimated from sentinel surveillance data in Japan. J Epidemiol 2003; 13(3): 136-41.[http://dx.doi.org/10.2188/jea.13.136] [PMID: 12749600] , 16Murakami Y, Hashimoto S, Taniguchi K, Kosaka K, Fuchigami H, Nagai M. Distribution of monitoring stations in the surveillance of infectious disease after the legislation of new infectious disease control law in Japan. Nippon Koshu Eisei Zasshi 2003; 50(8): 732-8.[PMID: 14515750] , 17Murakami Y, Hashimoto S, Kawado M, et al. Estimated number of patients with influenza A(H1) pdm09, or other viral types, from 2010 to 2014 in Japan. PLoS One 2016; 11(1): e0146520.[http://dx.doi.org/10.1371/journal.pone.0146520] [PMID: 26784031] ]. Each SMI reports the weekly number of influenza cases to the regional health center. Notification by health centers to the prefectural government and the Ministry is made through an online reporting platform.

2.2. Data

We analyzed reports of influenza in 2015 from SMIs included in the NESID in collaboration with the National Institute of Infectious Diseases of Japan, which routinely summarizes surveillance data. With permission from the Ministry, we also collected data of all disease outpatients in September 2014 from each hospital pediatric and internal medicine department and from each clinic of the Survey of Medical Institutions of Japan [10Health Insurance Claims Review and Reimbursement Services of Japan. Annual Report 2013 Available at 2013. Accessed August 17, 2017.http://www.ssk.or.jp/tokeijoho/tokeijoho_03.html, 11Ministry of Health, Labour and Welfare of Japan. List of Statistical Surveys conducted by Ministry of Health, Labour and Welfare Available at Accessed August 17, 2017http://www.mhlw.go.jp/toukei/itiran/eiyaku.html, 13Infectious Disease Surveillance Center, National Institute of Infectious Diseases. The National Epidemiological Surveillance of Infectious Diseases in Compliance with the Enforcement of the New Infectious Diseases Control Law. IASR (Infectious Agents Surveillance Report) 1999;20(4):No230 Available at 1999. Accessed August 17, 2017http://idsc.nih.go.jp/iasr/20/230/de2309.html]. This survey is conducted every 3 years to determine the status of medical institutions (including all disease outpatients only in September) in Japan. The data of about 94% of SMIs are linked with the number of all disease outpatients by the name and address of the medical institution, and these data are available for estimating influenza incidence. Because these statistical data do not include personally identifiable information, no ethical review was needed.

2.3. Estimation of Influenza Incidence

Influenza incidence was estimated in the present study by two methods: without the use of auxiliary information (the current method), and with the number of all disease outpatients as auxiliary information [6Hashimoto S, Murakami Y, Taniguchi K, et al. Annual incidence rate of infectious diseases estimated from sentinel surveillance data in Japan. J Epidemiol 2003; 13(3): 136-41.[http://dx.doi.org/10.2188/jea.13.136] [PMID: 12749600] , 7Kawado M, Hashimoto S, Murakami Y, et al. Annual and weekly incidence rates of influenza and pediatric diseases estimated from infectious disease surveillance data in Japan, 2002-2005. J Epidemiol 2007; 17(Suppl): S32-41.[http://dx.doi.org/10.2188/jea.17.S32] [PMID: 18239340] ].

The current method of estimating influenza incidence, without the use of auxiliary information, has been previously described [6Hashimoto S, Murakami Y, Taniguchi K, et al. Annual incidence rate of infectious diseases estimated from sentinel surveillance data in Japan. J Epidemiol 2003; 13(3): 136-41.[http://dx.doi.org/10.2188/jea.13.136] [PMID: 12749600] , 7Kawado M, Hashimoto S, Murakami Y, et al. Annual and weekly incidence rates of influenza and pediatric diseases estimated from infectious disease surveillance data in Japan, 2002-2005. J Epidemiol 2007; 17(Suppl): S32-41.[http://dx.doi.org/10.2188/jea.17.S32] [PMID: 18239340] ]. Influenza incidence in each prefecture and the type of medical institution is estimated as the number of influenza patients at SMIs divided by the proportion of SMIs to all medical institutions. Total incidence is estimated as the total of influenza incidence estimates for all prefectures and type of medical institution. The four types of medical institution are as follows: 1) hospital pediatrics department, 2) clinic with pediatrics as the main department, 3) clinic with internal medicine and with pediatrics not as the main department, and 4) hospital internal medicine department and clinic with internal medicine but no pediatrics department.

To estimate influenza incidence by the new method, we used the ratio estimation method with the number of all disease outpatients as auxiliary information [18Snedecor GW, Cochran WG. Statistical methods 6th ed. 6th ed.1967., 19Souty C, Boëlle PY. Improving incidence estimation in practice-based sentinel surveillance networks using spatial variation in general practitioner density. BMC Med Res Methodol 2016; 16(1): 156.[http://dx.doi.org/10.1186/s12874-016-0260-x] [PMID: 27846798] ]. The incidence of influenza in each prefecture and the type of medical institution was estimated as the number of influenza patients at SMIs divided by the ratio of the sum of the number of all disease outpatients at SMIs to the sum of those in all medical institutions. We used five types of medical institution in the new method. Three types of medical institution (1) (2) and (3) from the list above) are used in the current method. We divided type 4) in the current method (hospital internal medicine department and clinic with internal medicine but no pediatrics department) into two types: 4) hospital internal medicine department, and 5) clinic with internal medicine but no pediatrics department. The reason for this is because the number of all disease outpatients obtained in the survey is by hospital department but is only by the institution in clinics [10Health Insurance Claims Review and Reimbursement Services of Japan. Annual Report 2013 Available at 2013. Accessed August 17, 2017.http://www.ssk.or.jp/tokeijoho/tokeijoho_03.html, 11Ministry of Health, Labour and Welfare of Japan. List of Statistical Surveys conducted by Ministry of Health, Labour and Welfare Available at Accessed August 17, 2017http://www.mhlw.go.jp/toukei/itiran/eiyaku.html]. The appendix describes both methods in detail.

3. RESULTS

Table 1 shows the mean number of all disease outpatients in September 2014 at all medical institutions and SMIs. There were a total of 4,619 SMIs (6.9% of all medical institutions). Mean numbers of all disease outpatients at each type of medical institution were higher in SMIs than in all medical institutions. The ratios of mean numbers of all disease outpatients ranged from 1.1 to 1.6 at the five types of medical institution.

Table 1
Mean number of all disease outpatients in September 2014 at all and sentinel medical institutions.


Fig. (1) shows weekly influenza incidence rate in 2015 estimated using auxiliary information and the current method. Influenza incidence rate estimated by using auxiliary information was lower in each week than that by the current method. The ratios of estimates ranged from 0.45 to 0.72 during the period between weeks 1 and 16, with estimated weekly influenza incidence rate of more than 1 per 1,000 population.

Fig. (1)
Weekly influenza incidence rate in 2015 estimated by methods with and without use of auxiliary information.


Table 2 shows influenza incidence in 2015 estimated using auxiliary information and the current method; estimated influenza incidence rate per 1,000 population by these two methods was 63.7 (95% Confidence Interval (CI), 61.0-66.3) and 96.5 (95% CI, 93.0-100.0), respectively. The ratio of those estimates was 0.66. The incidence by the new and by the current method was 8,090,000 (95% CI, 7,750,000-8,430,000) and 12,270,000 (95% CI, 11,830,000-12,710,000), respectively.

Table 2
Influenza incidence in 2015 estimated by current method (without auxiliary information) and using auxiliary information.


4. DISCUSSION

Our study showed that the average number of all disease outpatients at SMIs was higher than that of all medical institutions, for all types of medical institution. These data indicated that the mean size of the population who made influenza visits was larger at SMIs than at all medical institutions. From these data, we hypothesized that the assumption that SMIs were chosen by random sampling from all medical institutions was invalid [6Hashimoto S, Murakami Y, Taniguchi K, et al. Annual incidence rate of infectious diseases estimated from sentinel surveillance data in Japan. J Epidemiol 2003; 13(3): 136-41.[http://dx.doi.org/10.2188/jea.13.136] [PMID: 12749600] , 7Kawado M, Hashimoto S, Murakami Y, et al. Annual and weekly incidence rates of influenza and pediatric diseases estimated from infectious disease surveillance data in Japan, 2002-2005. J Epidemiol 2007; 17(Suppl): S32-41.[http://dx.doi.org/10.2188/jea.17.S32] [PMID: 18239340] ]. As mentioned in previous studies [6Hashimoto S, Murakami Y, Taniguchi K, et al. Annual incidence rate of infectious diseases estimated from sentinel surveillance data in Japan. J Epidemiol 2003; 13(3): 136-41.[http://dx.doi.org/10.2188/jea.13.136] [PMID: 12749600] -8Nakamura Y, Sugawara T, Kawanohara H, Ohkusa Y, Kamei M, Oishi K. Evaluation of estimated number of influenza patients from national sentinel surveillance using the national database of electronic medical claims. Jpn J Infect Dis 2015; 68(1): 27-9.[http://dx.doi.org/10.7883/yoken.JJID.2014.092] [PMID: 25420664] , 17Murakami Y, Hashimoto S, Kawado M, et al. Estimated number of patients with influenza A(H1) pdm09, or other viral types, from 2010 to 2014 in Japan. PLoS One 2016; 11(1): e0146520.[http://dx.doi.org/10.1371/journal.pone.0146520] [PMID: 26784031] ], use of the current method under this assumption could lead to overestimation of influenza incidence. However, the method using auxiliary information does not use this assumption.

Based on the other information, we discuss the accuracy of influenza incidence estimated by the current method and the method using auxiliary information. Table 3 shows influenza incidence estimated by the current method, the numbers of influenza patients from the National Database of Health Insurance Claims and Specific Health Checkups of Japan (NDB), and the NDB coverages for all medical claims for three influenza seasons; this information was obtained from a previous study [8Nakamura Y, Sugawara T, Kawanohara H, Ohkusa Y, Kamei M, Oishi K. Evaluation of estimated number of influenza patients from national sentinel surveillance using the national database of electronic medical claims. Jpn J Infect Dis 2015; 68(1): 27-9.[http://dx.doi.org/10.7883/yoken.JJID.2014.092] [PMID: 25420664] ] and a report of the Health Insurance Claims Review and Reimbursement Services of Japan [9Statistics and Information Department, Minister’s Secretariat, Ministry of Health, Labour and Welfare of Japan. The Survey of Medical Institutions 2014 Tokyo: Health and Welfare Statistics Association of Japan; 2016 ]. The universal insurance system in Japan covers most Japanese citizens. An NDB system to collect data for all medical claims in electronic format from the insurance system has recently been established by the Ministry of Health, Labour and Welfare of Japan [20Ministry of Health, Labour and Welfare of Japan. The First Open Data from the National Database of Health Insurance Claims and Specific Health Checkups of Japan (NDB), October 2016. Available at 2016. Accessed August 17, 2017.http://www.mhlw.go.jp/stf/seisakunitsuite/bunya/0000139390.html, 21Kubota K, Kamijima Y, Sato T, et al. Epidemiology of psoriasis and palmoplantar pustulosis: a nationwide study using the Japanese national claims database. BMJ Open 2015; 5(1): e006450.[http://dx.doi.org/10.1136/bmjopen-2014-006450] [PMID: 25588781] ]. The coverage of the NDB for all medical claims (including medical claims in non-electronic format) has increased rapidly, from 50.2% in 2008 to 93.1 in 2010 and 95.5% in 2012 [9Statistics and Information Department, Minister’s Secretariat, Ministry of Health, Labour and Welfare of Japan. The Survey of Medical Institutions 2014 Tokyo: Health and Welfare Statistics Association of Japan; 2016 , 20Ministry of Health, Labour and Welfare of Japan. The First Open Data from the National Database of Health Insurance Claims and Specific Health Checkups of Japan (NDB), October 2016. Available at 2016. Accessed August 17, 2017.http://www.mhlw.go.jp/stf/seisakunitsuite/bunya/0000139390.html]. Assuming that the actual influenza incidence is equal to the number of influenza patients from the NDB divided by the coverage, the magnitude of overestimation of influenza incidence by the current method is calculated to be 1.76, 1.71, and 1.55 in the 2010/2011, 2011/2012, and 2012/2013 seasons, respectively [8Nakamura Y, Sugawara T, Kawanohara H, Ohkusa Y, Kamei M, Oishi K. Evaluation of estimated number of influenza patients from national sentinel surveillance using the national database of electronic medical claims. Jpn J Infect Dis 2015; 68(1): 27-9.[http://dx.doi.org/10.7883/yoken.JJID.2014.092] [PMID: 25420664] ]. Considering that influenza patient visits are more likely to be at clinics, completion of the electronic medical claims system has been delayed at clinics, and that the NDB coverage for all medical claims has rapidly increased, the magnitude of overestimation of influenza incidence by the current method in 2012/2013 (1.55 times) might be more accurate than in 2010/2011 and 2011/2012 [20Ministry of Health, Labour and Welfare of Japan. The First Open Data from the National Database of Health Insurance Claims and Specific Health Checkups of Japan (NDB), October 2016. Available at 2016. Accessed August 17, 2017.http://www.mhlw.go.jp/stf/seisakunitsuite/bunya/0000139390.html].

Table 3
Influenza incidence estimates by current method, influenza patients from NDB, and NDB coverages for all medical claims in 2010/2011, 2011/2012 and 2012/2013 seasons.


The present study showed that influenza incidence in 2015 estimated by using auxiliary information was lower than that by the current method, without using auxiliary information; the ratio of those estimates was 0.66. Assuming that the actual influenza incidence was equal to the number of influenza patients from the NDB divided by the coverage, the magnitude of overestimation of influenza incidence by the new method (using auxiliary information) would be calculated as the ratio of 0.66 multiplied by the magnitudes of overestimation by the current method (1.76, 1.71, and 1.55), yielding 1.16, 1.13, and 1.02 in 2010/2011, 2011/2012, and 2012/2013, respectively. Although the ratio of 0.66 based on the influenza incidence in 2015 might not directly apply in other years, the new method using auxiliary information would greatly reduce the overestimation of influenza incidence compared with that of the current method, and could lead to estimates that are close to the actual influenza incidence. Therefore, it would be appropriate to change the current method to the method that includes auxiliary information to estimate influenza incidence in the NESID.

To improve the current method of influenza incidence estimation, we used the ratio estimation method with all disease outpatients as auxiliary information [18Snedecor GW, Cochran WG. Statistical methods 6th ed. 6th ed.1967., 19Souty C, Boëlle PY. Improving incidence estimation in practice-based sentinel surveillance networks using spatial variation in general practitioner density. BMC Med Res Methodol 2016; 16(1): 156.[http://dx.doi.org/10.1186/s12874-016-0260-x] [PMID: 27846798] ]. The reasons were as follows. The population coverage of each medical institution is unavailable in Japan owing to the free access healthcare system [6Hashimoto S, Murakami Y, Taniguchi K, et al. Annual incidence rate of infectious diseases estimated from sentinel surveillance data in Japan. J Epidemiol 2003; 13(3): 136-41.[http://dx.doi.org/10.2188/jea.13.136] [PMID: 12749600] , 19Souty C, Boëlle PY. Improving incidence estimation in practice-based sentinel surveillance networks using spatial variation in general practitioner density. BMC Med Res Methodol 2016; 16(1): 156.[http://dx.doi.org/10.1186/s12874-016-0260-x] [PMID: 27846798] ]. To improve estimation of the number of patients in sample surveys, ratio estimation is used relatively frequently. The Patient Survey with a sample of medical institutions throughout Japan conducted by the Ministry of Health, Labour and Welfare can serve as an example. In that survey, the number of patients with diseases and injuries nationally is estimated by ratio estimation, with all disease inpatients and outpatients used as auxiliary information [11Ministry of Health, Labour and Welfare of Japan. List of Statistical Surveys conducted by Ministry of Health, Labour and Welfare Available at Accessed August 17, 2017http://www.mhlw.go.jp/toukei/itiran/eiyaku.html, 22Statistics and Information Department, Minister’s Secretariat, Ministry of Health, Labour and Welfare of Japan. The Patient Survey 2014 Tokyo: Health and Welfare Statistics Association of Japan; 2016 ]. A previous study proposed ratio estimation using local general practitioner density (the number of general practitioners per the population in a local area) as auxiliary information, to improve influenza incidence estimated without use of auxiliary information in sentinel surveillance in France [19Souty C, Boëlle PY. Improving incidence estimation in practice-based sentinel surveillance networks using spatial variation in general practitioner density. BMC Med Res Methodol 2016; 16(1): 156.[http://dx.doi.org/10.1186/s12874-016-0260-x] [PMID: 27846798] ].

Ratio estimation requires auxiliary information about the entire population [18Snedecor GW, Cochran WG. Statistical methods 6th ed. 6th ed.1967.]. We used the number of all disease outpatients in September as auxiliary information. Many diseases, including pediatric diseases, have seasonal variation, and the number of all disease outpatients varies with season. The number of all disease outpatients in September might not be the best auxiliary information to use for estimating influenza incidence with great seasonal variation. However, we are unaware of a better alternative that can be regularly obtained in Japan. The number of all disease outpatients is provided by the Survey of Medical Institutions at triennial intervals and is used as auxiliary information to estimate the number of patients with diseases and injuries nationally in the Patient Survey of Japan [10Health Insurance Claims Review and Reimbursement Services of Japan. Annual Report 2013 Available at 2013. Accessed August 17, 2017.http://www.ssk.or.jp/tokeijoho/tokeijoho_03.html, 11Ministry of Health, Labour and Welfare of Japan. List of Statistical Surveys conducted by Ministry of Health, Labour and Welfare Available at Accessed August 17, 2017http://www.mhlw.go.jp/toukei/itiran/eiyaku.html, 22Statistics and Information Department, Minister’s Secretariat, Ministry of Health, Labour and Welfare of Japan. The Patient Survey 2014 Tokyo: Health and Welfare Statistics Association of Japan; 2016 ]. Information on the local general practitioner density proposed in the aforementioned study in France would not be useful to estimate influenza incidence based on sentinel surveillance in Japan because the numbers of SMIs in local areas are approximately proportional to their population sizes [15Hashimoto S, Kawado M, Murakami Y, et al. Number of sentinel medical institutions needed for estimating prefectural incidence in influenza surveillance in Japan. J Epidemiol 2014; 24(3): 183-92.[http://dx.doi.org/10.2188/jea.JE20130077] [PMID: 24584400] , 19Souty C, Boëlle PY. Improving incidence estimation in practice-based sentinel surveillance networks using spatial variation in general practitioner density. BMC Med Res Methodol 2016; 16(1): 156.[http://dx.doi.org/10.1186/s12874-016-0260-x] [PMID: 27846798] ].

As mentioned above, four types of medical institution are used as the strata in the current method of the NESID whereas five types of the institution were used in the new method of the present study. The influenza incidence in 2015 estimated by the current method was 10,920,000 using the strata with five types of medical institution, which was 0.89 times that in the strata with four types (Table 2). The difference in these estimates using strata with four or five types of the medical institution would be associated with the distribution of influenza patients in medical institutions and SMIs in the strata of hospital internal medicine department and clinic with internal medicine but no pediatrics department. The reasons for this difference are unknown.

This study has some limitations. We estimated the influenza incidence in Japan for 2015 only. The influenza incidence rate has varied widely by year and by area [7Kawado M, Hashimoto S, Murakami Y, et al. Annual and weekly incidence rates of influenza and pediatric diseases estimated from infectious disease surveillance data in Japan, 2002-2005. J Epidemiol 2007; 17(Suppl): S32-41.[http://dx.doi.org/10.2188/jea.17.S32] [PMID: 18239340] , 23Tokars JI, Olsen SJ, Reed C. The seasonal incidence of symptomatic influenza in the United States. Clin Infect Dis 2017; 66(10): 1511-8.[http://dx.doi.org/10.1093/cid/cix1060] [PMID: 29206909] ]. The dominant virological type of seasonal influenza has changed by year; in the 2014/2015 season, influenza type A(H3) was dominant in Japan [24National Institute of Infectious Diseases of Japan. Isolation/detection of influenza virus in Japan, week 36/2014-week 35/2015. Available at 2015. Accessed March 30, 2018http://www.niid.go.jp/niid/en/influenza-e/2099-idsc/iasr-flu-e/5600-iasr-inf-e20150528.html]. Although the accuracy of influenza incidences in Japan estimated by the two methods might not have been extremely affected by the year or virological type of seasonal influenza, it is important to examine the estimates for several years [17Murakami Y, Hashimoto S, Kawado M, et al. Estimated number of patients with influenza A(H1) pdm09, or other viral types, from 2010 to 2014 in Japan. PLoS One 2016; 11(1): e0146520.[http://dx.doi.org/10.1371/journal.pone.0146520] [PMID: 26784031] ]. The numbers of all disease outpatients in September 2014, not in 2015 were used. About 94% of SMIs linked their data of numbers of all disease outpatients by the medical institution name and address, to estimate influenza incidence. Our influenza incidence estimate in 2015 was 0.97 times that based on data of all SMIs (12,590,000 reported in the NESID). We did not directly evaluate the accuracy of influenza incidence estimated by the method using auxiliary information. To evaluate the accuracy, we used numbers of influenza patients in the 2010/2011, 2011/2012 and 2012/2013 seasons from the NDB that were published in a previous study [8Nakamura Y, Sugawara T, Kawanohara H, Ohkusa Y, Kamei M, Oishi K. Evaluation of estimated number of influenza patients from national sentinel surveillance using the national database of electronic medical claims. Jpn J Infect Dis 2015; 68(1): 27-9.[http://dx.doi.org/10.7883/yoken.JJID.2014.092] [PMID: 25420664] ]. The NDB had been made available on a trial basis for research until March 2013, but it was unavailable in 2015 [8Nakamura Y, Sugawara T, Kawanohara H, Ohkusa Y, Kamei M, Oishi K. Evaluation of estimated number of influenza patients from national sentinel surveillance using the national database of electronic medical claims. Jpn J Infect Dis 2015; 68(1): 27-9.[http://dx.doi.org/10.7883/yoken.JJID.2014.092] [PMID: 25420664] , 20Ministry of Health, Labour and Welfare of Japan. The First Open Data from the National Database of Health Insurance Claims and Specific Health Checkups of Japan (NDB), October 2016. Available at 2016. Accessed August 17, 2017.http://www.mhlw.go.jp/stf/seisakunitsuite/bunya/0000139390.html]. Direct evaluation of the accuracy of influenza incidence estimated by the method using auxiliary information based on actual incidences is very important and requires further investigation in the future.

CONCLUSION

Our findings suggest that influenza incidence estimated by using the number of all disease outpatients as auxiliary information would be more accurate than estimates made without using such information.

ETHICS APPROVAL AND CONSENT TO PARTICIPATE

Not applicable.

HUMAN AND ANIMAL RIGHTS

No animals/humans were used for studies that are the basis of this research.

CONSENT FOR PUBLICATION

Not applicable.

CONFLICT OF INTEREST

The authors declare no conflict of interest, financial or otherwise.

ACKNOWLEDGEMENTS

This study was supported by a Research grant on Emerging and Re-emerging Infectious Diseases of the Ministry of Health, Labour and Welfare of Japan [grant number H27-Shinkougyousei-Shitei-001].

APPENDIX

Methods of Estimating Influenza Incidence

The methods of estimating influenza incidence (current method and by including auxiliary information) are as follows [6Hashimoto S, Murakami Y, Taniguchi K, et al. Annual incidence rate of infectious diseases estimated from sentinel surveillance data in Japan. J Epidemiol 2003; 13(3): 136-41.[http://dx.doi.org/10.2188/jea.13.136] [PMID: 12749600] , 7Kawado M, Hashimoto S, Murakami Y, et al. Annual and weekly incidence rates of influenza and pediatric diseases estimated from infectious disease surveillance data in Japan, 2002-2005. J Epidemiol 2007; 17(Suppl): S32-41.[http://dx.doi.org/10.2188/jea.17.S32] [PMID: 18239340] ]. Let n, v and ξ be the number of SMIs, the number of all medical institutions, and the total number of all disease outpatients in all medical institutions, respectively. Let Yi and xi be influenza incidence and the number of all disease outpatients in the i-th SMI, respectively, for i = 1, 2,..., n. Let , sy, and be the mean and standard deviation of {Yi}, and the mean of {xi}, respectively.

Let α be the total influenza incidence in all medical institutions. By the current method, the estimate of α is given to be ; i.e., the incidence is estimated as the total incidence in SMIs divided by the proportion of SMIs among all medical institutions (n/v). The approximate confidence interval for α is given to be where sv2 is an estimate of variance of and is given to be

By the method using auxiliary information, the estimate of α is given to be where i.e., the incidence is estimated as the total incidence in SMIs divided by the ratio of the sum of the numbers of all disease outpatients in SMIs to the sum of those in all medical institutions The approximate confidence interval for α is given to be where is an estimate of variance of and is given to be [16Murakami Y, Hashimoto S, Taniguchi K, Kosaka K, Fuchigami H, Nagai M. Distribution of monitoring stations in the surveillance of infectious disease after the legislation of new infectious disease control law in Japan. Nippon Koshu Eisei Zasshi 2003; 50(8): 732-8.[PMID: 14515750] ].

Consider that the incidences in some strata, such as type of medical institution and prefecture, are estimated using the above methods. Let k be the number of strata, the estimated incidences in the strata, and s12, s22, ..., sk2 their estimated variances by the either method (with or without auxiliary information). The approximate confidence interval for the total incidence is given as

REFERENCES

[1] Costagliola D, Flahault A, Galinec D, Garnerin P, Menares J, Valleron AJ. A routine tool for detection and assessment of epidemics of influenza-like syndromes in France. Am J Public Health 1991; 81(1): 97-9.[http://dx.doi.org/10.2105/AJPH.81.1.97] [PMID: 1983924]
[2] Thacker SB, Stroup DF. Future directions for comprehensive public health surveillance and health information systems in the United States. Am J Epidemiol 1994; 140(5): 383-97.[http://dx.doi.org/10.1093/oxfordjournals.aje.a117261] [PMID: 8067331]
[3] Fleming DM, Zambon M, Bartelds AI. Population estimates of persons presenting to general practitioners with influenza-like illness, 1987-96: A study of the demography of influenza-like illness in sentinel practice networks in England and Wales, and in The Netherlands. Epidemiol Infect 2000; 124(2): 245-53.[http://dx.doi.org/10.1017/S0950268899003660] [PMID: 10813150]
[4] Lee JS, Shin KC, Na BK, et al. Influenza surveillance in Korea: Establishment and first results of an epidemiological and virological surveillance scheme. Epidemiol Infect 2007; 135(7): 1117-23.[http://dx.doi.org/10.1017/S0950268807007820] [PMID: 17291376]
[5] Taniguchi K, Hashimoto S, Kawado M, et al. Overview of infectious disease surveillance system in Japan, 1999-2005. J Epidemiol 2007; 17(Suppl): S3-S13.[http://dx.doi.org/10.2188/jea.17.S3] [PMID: 18239339]
[6] Hashimoto S, Murakami Y, Taniguchi K, et al. Annual incidence rate of infectious diseases estimated from sentinel surveillance data in Japan. J Epidemiol 2003; 13(3): 136-41.[http://dx.doi.org/10.2188/jea.13.136] [PMID: 12749600]
[7] Kawado M, Hashimoto S, Murakami Y, et al. Annual and weekly incidence rates of influenza and pediatric diseases estimated from infectious disease surveillance data in Japan, 2002-2005. J Epidemiol 2007; 17(Suppl): S32-41.[http://dx.doi.org/10.2188/jea.17.S32] [PMID: 18239340]
[8] Nakamura Y, Sugawara T, Kawanohara H, Ohkusa Y, Kamei M, Oishi K. Evaluation of estimated number of influenza patients from national sentinel surveillance using the national database of electronic medical claims. Jpn J Infect Dis 2015; 68(1): 27-9.[http://dx.doi.org/10.7883/yoken.JJID.2014.092] [PMID: 25420664]
[9] Statistics and Information Department, Minister’s Secretariat, Ministry of Health, Labour and Welfare of Japan. The Survey of Medical Institutions 2014 Tokyo: Health and Welfare Statistics Association of Japan; 2016
[10] Health Insurance Claims Review and Reimbursement Services of Japan. Annual Report 2013 Available at 2013. Accessed August 17, 2017.http://www.ssk.or.jp/tokeijoho/tokeijoho_03.html
[11] Ministry of Health, Labour and Welfare of Japan. List of Statistical Surveys conducted by Ministry of Health, Labour and Welfare Available at Accessed August 17, 2017http://www.mhlw.go.jp/toukei/itiran/eiyaku.html
[12] Fowlkes A, Dasgupta S, Chao E, et al. Estimating influenza incidence and rates of influenza-like illness in the outpatient setting. Influenza Other Respir Viruses 2013; 7(5): 694-700.[http://dx.doi.org/10.1111/irv.12014] [PMID: 22984820]
[13] Infectious Disease Surveillance Center, National Institute of Infectious Diseases. The National Epidemiological Surveillance of Infectious Diseases in Compliance with the Enforcement of the New Infectious Diseases Control Law. IASR (Infectious Agents Surveillance Report) 1999;20(4):No230 Available at 1999. Accessed August 17, 2017http://idsc.nih.go.jp/iasr/20/230/de2309.html
[14] Tuberculosis and Infectious Diseases Control Division, Health Service Bureau, Ministry of Health, Labour and Welfare of Japan. The Guideline for National Epidemiological Surveillance of Infectious Diseases (kansensho-hasseidokochosajigyo-jissiyoko). Weekly News of Public Health (Shukan-hoken-eisei) 1999; 998(5): 14-26.
[15] Hashimoto S, Kawado M, Murakami Y, et al. Number of sentinel medical institutions needed for estimating prefectural incidence in influenza surveillance in Japan. J Epidemiol 2014; 24(3): 183-92.[http://dx.doi.org/10.2188/jea.JE20130077] [PMID: 24584400]
[16] Murakami Y, Hashimoto S, Taniguchi K, Kosaka K, Fuchigami H, Nagai M. Distribution of monitoring stations in the surveillance of infectious disease after the legislation of new infectious disease control law in Japan. Nippon Koshu Eisei Zasshi 2003; 50(8): 732-8.[PMID: 14515750]
[17] Murakami Y, Hashimoto S, Kawado M, et al. Estimated number of patients with influenza A(H1) pdm09, or other viral types, from 2010 to 2014 in Japan. PLoS One 2016; 11(1): e0146520.[http://dx.doi.org/10.1371/journal.pone.0146520] [PMID: 26784031]
[18] Snedecor GW, Cochran WG. Statistical methods 6th ed. 6th ed.1967.
[19] Souty C, Boëlle PY. Improving incidence estimation in practice-based sentinel surveillance networks using spatial variation in general practitioner density. BMC Med Res Methodol 2016; 16(1): 156.[http://dx.doi.org/10.1186/s12874-016-0260-x] [PMID: 27846798]
[20] Ministry of Health, Labour and Welfare of Japan. The First Open Data from the National Database of Health Insurance Claims and Specific Health Checkups of Japan (NDB), October 2016. Available at 2016. Accessed August 17, 2017.http://www.mhlw.go.jp/stf/seisakunitsuite/bunya/0000139390.html
[21] Kubota K, Kamijima Y, Sato T, et al. Epidemiology of psoriasis and palmoplantar pustulosis: a nationwide study using the Japanese national claims database. BMJ Open 2015; 5(1): e006450.[http://dx.doi.org/10.1136/bmjopen-2014-006450] [PMID: 25588781]
[22] Statistics and Information Department, Minister’s Secretariat, Ministry of Health, Labour and Welfare of Japan. The Patient Survey 2014 Tokyo: Health and Welfare Statistics Association of Japan; 2016
[23] Tokars JI, Olsen SJ, Reed C. The seasonal incidence of symptomatic influenza in the United States. Clin Infect Dis 2017; 66(10): 1511-8.[http://dx.doi.org/10.1093/cid/cix1060] [PMID: 29206909]
[24] National Institute of Infectious Diseases of Japan. Isolation/detection of influenza virus in Japan, week 36/2014-week 35/2015. Available at 2015. Accessed March 30, 2018http://www.niid.go.jp/niid/en/influenza-e/2099-idsc/iasr-flu-e/5600-iasr-inf-e20150528.html

Endorsements



"Open access will revolutionize 21st century knowledge work and accelerate the diffusion of ideas and evidence that support just in time learning and the evolution of thinking in a number of disciplines."


Daniel Pesut
(Indiana University School of Nursing, USA)

"It is important that students and researchers from all over the world can have easy access to relevant, high-standard and timely scientific information. This is exactly what Open Access Journals provide and this is the reason why I support this endeavor."


Jacques Descotes
(Centre Antipoison-Centre de Pharmacovigilance, France)

"Publishing research articles is the key for future scientific progress. Open Access publishing is therefore of utmost importance for wider dissemination of information, and will help serving the best interest of the scientific community."


Patrice Talaga
(UCB S.A., Belgium)

"Open access journals are a novel concept in the medical literature. They offer accessible information to a wide variety of individuals, including physicians, medical students, clinical investigators, and the general public. They are an outstanding source of medical and scientific information."


Jeffrey M. Weinberg
(St. Luke's-Roosevelt Hospital Center, USA)

"Open access journals are extremely useful for graduate students, investigators and all other interested persons to read important scientific articles and subscribe scientific journals. Indeed, the research articles span a wide range of area and of high quality. This is specially a must for researchers belonging to institutions with limited library facility and funding to subscribe scientific journals."


Debomoy K. Lahiri
(Indiana University School of Medicine, USA)

"Open access journals represent a major break-through in publishing. They provide easy access to the latest research on a wide variety of issues. Relevant and timely articles are made available in a fraction of the time taken by more conventional publishers. Articles are of uniformly high quality and written by the world's leading authorities."


Robert Looney
(Naval Postgraduate School, USA)

"Open access journals have transformed the way scientific data is published and disseminated: particularly, whilst ensuring a high quality standard and transparency in the editorial process, they have increased the access to the scientific literature by those researchers that have limited library support or that are working on small budgets."


Richard Reithinger
(Westat, USA)

"Not only do open access journals greatly improve the access to high quality information for scientists in the developing world, it also provides extra exposure for our papers."


J. Ferwerda
(University of Oxford, UK)

"Open Access 'Chemistry' Journals allow the dissemination of knowledge at your finger tips without paying for the scientific content."


Sean L. Kitson
(Almac Sciences, Northern Ireland)

"In principle, all scientific journals should have open access, as should be science itself. Open access journals are very helpful for students, researchers and the general public including people from institutions which do not have library or cannot afford to subscribe scientific journals. The articles are high standard and cover a wide area."


Hubert Wolterbeek
(Delft University of Technology, The Netherlands)

"The widest possible diffusion of information is critical for the advancement of science. In this perspective, open access journals are instrumental in fostering researches and achievements."


Alessandro Laviano
(Sapienza - University of Rome, Italy)

"Open access journals are very useful for all scientists as they can have quick information in the different fields of science."


Philippe Hernigou
(Paris University, France)

"There are many scientists who can not afford the rather expensive subscriptions to scientific journals. Open access journals offer a good alternative for free access to good quality scientific information."


Fidel Toldrá
(Instituto de Agroquimica y Tecnologia de Alimentos, Spain)

"Open access journals have become a fundamental tool for students, researchers, patients and the general public. Many people from institutions which do not have library or cannot afford to subscribe scientific journals benefit of them on a daily basis. The articles are among the best and cover most scientific areas."


M. Bendandi
(University Clinic of Navarre, Spain)

"These journals provide researchers with a platform for rapid, open access scientific communication. The articles are of high quality and broad scope."


Peter Chiba
(University of Vienna, Austria)

"Open access journals are probably one of the most important contributions to promote and diffuse science worldwide."


Jaime Sampaio
(University of Trás-os-Montes e Alto Douro, Portugal)

"Open access journals make up a new and rather revolutionary way to scientific publication. This option opens several quite interesting possibilities to disseminate openly and freely new knowledge and even to facilitate interpersonal communication among scientists."


Eduardo A. Castro
(INIFTA, Argentina)

"Open access journals are freely available online throughout the world, for you to read, download, copy, distribute, and use. The articles published in the open access journals are high quality and cover a wide range of fields."


Kenji Hashimoto
(Chiba University, Japan)

"Open Access journals offer an innovative and efficient way of publication for academics and professionals in a wide range of disciplines. The papers published are of high quality after rigorous peer review and they are Indexed in: major international databases. I read Open Access journals to keep abreast of the recent development in my field of study."


Daniel Shek
(Chinese University of Hong Kong, Hong Kong)

"It is a modern trend for publishers to establish open access journals. Researchers, faculty members, and students will be greatly benefited by the new journals of Bentham Science Publishers Ltd. in this category."


Jih Ru Hwu
(National Central University, Taiwan)


Browse Contents



Advertisements


Webmaster Contact: info@benthamopen.com
Copyright © 2018 Bentham Open