Spatiotemporal distribution of varicella in the Republic of Korea

Varicella is a highly contagious disease caused by the varicella‐zoster virus (VZV). Given its tendency to cluster geographically, spatial analyses may provide a better understanding of the pattern of varicella transmission. We investigated the spatial characteristics of varicella in Korea and the r...

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Veröffentlicht in:Journal of medical virology 2022-02, Vol.94 (2), p.703-712
Hauptverfasser: Lee, Young Hwa, Choe, Young June, Hwang, Seung‐sik, Cho, Sung‐il
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Sprache:eng
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Zusammenfassung:Varicella is a highly contagious disease caused by the varicella‐zoster virus (VZV). Given its tendency to cluster geographically, spatial analyses may provide a better understanding of the pattern of varicella transmission. We investigated the spatial characteristics of varicella in Korea and the risk factors for varicella at a national level. Using national surveillance and demographic data, we examined the spatial distribution of incidence rates and their spatial autocorrelation and calculated Moran's index. Spatial regression analysis was used to identify sociodemographic predictors of varicella incidence at the district level. An increasing tendency in the annual incidence of varicella was observed over a 12‐year period (2006–2018), with a surge in 2017. There was a clear positive spatial autocorrelation of the varicella incidence rate during the surveillance period. During 2006–2014, High‐High (HH) clusters were mostly confined to the northeast region and neighboring districts. The spatial error model showed that population density had a negative coefficient and childhood percentage, percentage of children under 12 years of age among the total population, had positive coefficient, whereas vaccine coverage was insignificant. The varicella incidence according to geographic region varied with population density, childhood percentage, suggesting the importance of community‐level surveillance and monitoring strategies. Highlights The incidence of varicella in Korea showed a temporal uptrend from 2006 to 2018 with a clear seasonal pattern. The local spatial clusters of “hot‐spots” occurred in remote rural areas during the early surveillance period and gradually scattered and faded. In the spatial regression analysis, sociodemographic predictors such as childhood percentage had a positive effect on the incidence, whereas population density and number of hospitals per 1000 persons had negative effects.
ISSN:0146-6615
1096-9071
DOI:10.1002/jmv.27434