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Objective  Human astroviruses (HAstVs) are single-stranded RNA viruses of the  Astroviridae  family. Infection of classic HAstVs is one of the most common causes of acute viral gastroenteritis (infectious viral diarrhea). There is a lack of data on the prevalence and genetic characterization of classic HAstVs in acute viral gastroenteritis in the whole population. This study aimed to investigate the epidemiological trend, genotypes, viral co-infections, and viral loads of classic HAstVs in Shanghai, China, from January 2015 to December 2016.    Methods  A total of 6,051 non-redundant stool samples were collected in outpatients with acute diarrhea in Shanghai from January 2015 to December 2016. One-step real-time RT-PCR was used for screening viral diarrhea, including rotavirus A, rotavirus B, rotavirus C, norovirus genotype I and II, classic human astroviruses, and sapovirus. Real-time PCR was used for screening human enteric adenoviruses. Conventional RT-PCR was used for the amplification of viral fragments for genotyping. PCR products were sequenced and used for the construction of phylogenetic trees.    Results  The detection rate of classic HAstVs was 1.55% (94/6,051). The prevalence of HAstV infection displayed a typical winter/spring (December to March) seasonality and was highest in the 5–14 age group. Eighty-six samples were genotyped, which revealed HAstV-1 as the most prevalent genotype, followed by HAstV-5, HAstV-4, HAstV- 2, HAstV-8, and HAstV-3. There was a dramatic rise in the prevalence of HAstV-4 from December 2015 to March 2016, and the viral loads of HAstV-4 were significantly higher than those of other genotypes. Among the mixed infection samples, noroviruses were found to be the most frequently co-infected enteric viruses with HAstV.    Conclusion  Multiple genotypes of classic HAstVs circulated in Shanghai from January 2015 to December 2016. For the first time, HAstV-3\4\5\8 were detected in Shanghai.

Epidemiology and Genetic Characterization of Classical Human Astrovirus Infection in Shanghai, 2015–2016