국내 소아 무균성 뇌막염의 전국적 발생 양상

• 영문명: Six year national trend of childhood aseptic meningitis incidence in Korea, 1996-2001
• 발행기관: 한국역학회
• 저자명: 정해관(Hae-Kwan Cheong) 박수경(Sue Kyung Park) 기모란(Moran Ki) 이관(Kwan Lee)
• 간행물 정보: 『한국역학회지』韓國疫學會誌 第30卷 第2號, 252~262쪽, 전체 11쪽
• 주제분류: 의약학 > 면역학
• 파일형태: PDF
• 발행일자: 2008.12.31

영문 초록

Background and objectives: Aseptic meningitis is a disease of children with seasonal outbreak in summer. In spite of high morbidity, it is not notifiable without reported nationwide morbidity. The authors estimated incidence of aseptic meningitis and its descriptive characteristics and time- and space-clustering pattern. Subjects and methods: Cases of aseptic meningitis were extracted from National Health Insurance payment request data of National Health Insurance Corporation from January 1996 to December 2001. Cases were classified by region, institution, and hospitalization. Standardized incidence was calculated and compared by the region, month of the year whether there is any clustering. Results: Nationwide incidence of aseptic meningitis among children under 15 years old over the six year period was 3.48 per 1,000 per year. Incidence was higher in female (2.80/1,000) compared to male (4.02/1,000). Age-specific incidence was highest in 5 years old. Annual incidence was highest in 1997 (8.44/1,000) and lowest in 2000 (0.79/1,000) with outbreak every 3 or 4 years. Outbreak was mostly confined in summer months, between May and September. However, seasonal pattern was variable by year. Southern provinces and metropolitan areas had higher incidences and pattern was more prominent in the years with higher outbreak. Time-dependent pattern of the disease from south to north was not prominent. Discussions and conclusions: We have calculated the nationwide incidence of the aseptic meningitis over six year period. In terms of aseptic meningitis, using National Health Insurance data for the estimation of the incidence is a plausible method for the surveillance of the disease.

키워드

Aseptic meningitis Enterovirus Descriptive epidemiology Clustering