The epidemiology of human calicivirus/Sapporo/82/Japan
Part of the
Archives of Virology
book series (ARCHIVES SUPPL, volume 12)
Based on genome analysis of the RNA-dependent RNA polymerase region, it has been proposed that human caliciviruses (HuCV) can be classified into at least three genogroups: genogroup I is represented by Norwalk virus (NV), genogroup II by Snow Mountain agent (SMA) and genogroup III by HuCV/Sapporo/82/Japan (HuCV/Sa/82/J) virus. HuCV/Sa/82/J strain is genetically unique and more closely related to animal caliciviruses than are other known HuCVs, such as NV and SMA.
HuCV/Sa/82/J strain was detected in four outbreaks of HuCV gastroenteritis occurring between 1977 and 1982 in an infant home in Sapporo. The HuCVs detected from these four outbreaks all showed a typical “Star of David” configuration by electron microscopy (EM), and they were identical antigenically and genetically. This strain has also been detected in other prefectures in Japan, as well as in the USA, UK, Saudi Arabia and Kenya. Seroepidemiological studies have shown a worldwide distribution of this virus, including Japan, USA, UK, Southeast Asia, Canada, China and Kenya. This virus has been circulating in Sapporo for at least 19 years (1977-1995). HuCV/Sa/82/J strain is thought to be one of the common causes of viral gastroenteritis worldwide.
The HuCV/Sa/82/J strain has been detected mainly in infants. Age-related prevalence of antibody to this strain also shows that infections commonly occur in children less than 5 years old, although viruses in the NV and SMA genogroups commonly infect adults. The pattern of acquisition of antibodies to strain HuCV/Sa/82/J is similar to that of other common viral infections. HuCV/Sa/82/J strain is unique virologically and clinically among caliciviruses.
KeywordsAcute Gastroenteritis Seroepidemiological Study Norwalk Virus Ehime Prefecture Immune Electron Microscopy
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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