Abstract

BackgroundNoroviruses are a leading cause of acute gastroenteritis (AGE) worldwide. The geographical characteristics of norovirus outbreaks in Beijing and their influencing factors remain unknown. This study aimed to explore the spatial distributions, geographical characteristics, and influencing factors of norovirus outbreaks in Beijing, China.MethodsEpidemiological data and specimens were collected through the AGE outbreak surveillance system in all 16 districts of Beijing. Data on spatial distribution, geographical characteristics, and influencing factors of norovirus outbreaks were analyzed using descriptive statistics methods. We measured spatial, geographical clustering of high- or low-value deviance from random distribution using Z-scores and P-values as statistical significance measures with Global Moran’s I statistics and Getis-Ord Gi in ArcGIS. Linear regression and correlation methods were used to explore influencing factors.ResultsBetween September 2016 and August 2020, 1,193 norovirus outbreaks were laboratory-confirmed. The number of outbreaks varied seasonally, typically peaking in spring (March to May) or winter (October to December). Outbreaks primarily occurred around central districts at the town level, and spatial autocorrelation was evident in both the entire study period and in individual years. Hotspots of norovirus outbreaks in Beijing were primarily found in contiguous areas between three central districts (Chaoyang, Haidian, Fengtai) and four suburban districts (Changping, Daxing, Fangshan, Tongzhou). The average population numbers, mean number of all schools, and mean number of kindergartens and primary schools for towns in central districts and hotspot areas were higher than those in suburban districts and non-hotspot areas respectively. Additionally, population numbers and densities of kindergartens and primary schools were influencing factors at the town level.ConclusionsHotspots of norovirus outbreaks in Beijing were in contiguous areas between central and suburban districts with high populations, and high kindergarten and primary school densities were the likely driving forces. Outbreak surveillance needs to focus on contiguous areas between central and suburban districts with increased monitoring, medical resources, and health education.

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