Analysis on epidemiological characteristics of norovirus infection in Guangzhou of Guangdong based on epidemiology surveillance for sewage and syndrome, 2023

Objective To analyze the epidemiological and etiological characteristics and transmission dynamics of norovirus infection in Guangzhou, Guangdong province in 2023, and provide evidence for the prevention and control of norovirus infection.

Methods A total of 1 192 stool samples or anal swabs were collected from diarrhea cases in syndrome surveillance at sentinel hospitals in Guangzhou in 2023, and 1 157 sewage samples were collected in sewage surveillance from 19 wastewater treatment plants in Guangzhou. Real-time fluorescent PCR was used for the detection of norovirus nucleic acid. Reverse transcription PCR amplification and next-generation sequencing were performed for the positive samples, then genotyping and phylogenetic analysis were conducted.

Results The positive detection rate of norovirus in diarrhea cases was 13.34% (159/1 192), with the detection rate of genotype GⅡ being 12.25% and genotype GⅠ being 2.01%. GⅡ.4P16 was the most predominant genotype, especially during August - December. The norovirus infection epidemic occurred in early 2023 was caused by multiple genotypes including GⅡ.17P17 and GⅡ.6P7. GⅠ.3P13 was most common in genotype GⅠ. The overall positive rate of norovirus in sewage samples was as high as 85.48% (989/1 157), with the detection rates of genotypes GⅠ and GⅡ reaching 83.23% and 79.68%, respectively. The incidences of the infections caused by both genotypes peaked simultaneously in March. Phylogenetic analysis showed that the genotypes detected in Guangzhou had a close genetic correlation with those detected both at home and abroad.

Conclusion The norovirus infection epidemic in Guangzhou in 2023 showed the characteristic of "co-transmission of case and environment". Norovirus GⅡ.4P16 was the main pathogen, and the infections mainly occurred in winter, spring and autumn. Sewage surveillance can effectively reflect the incidence trend of norovirus infection in communities and provide early warnings. It is suggested to integrate the data from clinical syndrome surveillance, environmental surveillance and molecular typing to improve the prevention and control of norovirus infection.