Open Access Research article

Geodemographics profiling of influenza A and B virus infections in community neighborhoods in Japan

Yoshinari Kimura12*, Reiko Saito1, Yoshiki Tsujimoto3, Yasuhiko Ono3, Tomoki Nakaya4, Yugo Shobugawa1, Asami Sasaki1, Taeko Oguma1 and Hiroshi Suzuki5

Author Affiliations

1 Division of Public Health, Department of Infectious Disease Control and International Medicine, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan

2 Department of Geography, Graduate School of Literature and Human Sciences, Osaka City University, Osaka, Japan

3 Isahaya City Medical Association, Nagasaki, Japan

4 Department of Geography, Ritsumeikan University, Kyoto, Japan

5 Department of Nursing, Niigata Seiryo University, Niigata, Japan

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BMC Infectious Diseases 2011, 11:36  doi:10.1186/1471-2334-11-36

Published: 2 February 2011



The spread of influenza viruses in a community are influenced by several factors, but no reports have focused on the relationship between the incidence of influenza and characteristics of small neighborhoods in a community. We aimed to clarify the relationship between the incidence of influenza and neighborhood characteristics using GIS and identified the type of small areas where influenza occurs frequently or infrequently.


Of the 19,077 registered influenza cases, we analyzed 11,437 influenza A and 5,193 influenza B cases that were diagnosed by the rapid antigen test in 66-86 medical facilities in Isahaya City, Japan, from 2004 to 2008. We used the commercial geodemographics dataset, Mosaic Japan to categorize and classify each neighborhood. Furthermore, we calculated the index value of influenza in crude and age adjusted rates to evaluate the incidence of influenza by Mosaic segmentation. Additional age structure analysis was performed to geodemographics segmentation to explore the relationship between influenza and family structure.


The observed number of influenza A and B patients in the neighborhoods where young couples with small children lived was approximately 10-40% higher than the expected number (p < 0.01) during all seasons. On the contrary, the number of patients in the neighborhoods of the aging society in a rural area was 20-50% lower than the expected number (p < 0.01) during all seasons. This tendency was consistent after age adjustment except in the case of influenza B, which lost significance in higher incidence areas, but the overall results indicated high transmission of influenza in areas where young families with children lived.


Our analysis indicated that the incidence of influenza A and B in neighborhood groups is related to the family structure, especially the presence of children in households. Simple statistical analysis of geodemographics data is an effective method to understand the differences in the incidence of influenza among neighborhood groups, and it provides a valuable basis for community strategies to control influenza.