Open AccessEpidemiological characteristics and spatial-temporal clusters of hand, foot, and mouth disease in Qingdao City, China, 2013-2018
Author(s) -
Zengqiang Kou,
Jun Jia,
Xiaohui Liu,
Tingting Luo,
Xueling Xin,
Jicheng Gong,
Jingfei Zhang,
Dianjianyi Sun,
Fachun Jiang,
Ruqin Gao
Publication year - 2020
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0233914
Subject(s) - hand foot and mouth disease , geography , epidemiology , spatial epidemiology , disease surveillance , cluster (spacecraft) , enterovirus 71 , demography , incidence (geometry) , spatial analysis , china , cartography , medicine , environmental health , veterinary medicine , enterovirus , virology , pathology , remote sensing , virus , physics , archaeology , sociology , computer science , optics , programming language
Background Hand, foot, and mouth disease (HFMD) has become one of the most important infectious diseases recent years. Qingdao City has suffered from serious HFMD epidemic. This study aimed to describe epidemiological characteristics and investigate spatial-temporal distribution at town level in Qingdao City. Method The surveillance data of HFMD during 2013–2018 were collected from the National Notifiable Disease Surveillance System. The global Moran’s I statistic was used to detect the spatial autocorrelation of HFMD cases by ArcGis 10.0 software. Purely spatial and spatial-temporal analysis was used to detect epidemic clusters by SatScan TM v9.6 software. Results The annual average incidence of HFMD cases in Qingdao City from 2013 to 2018 was 123.16 per 1, while the incidence rate of children≤5years old was 2879.80 per 1. The majority (88.97%) of HFMD cases were aged within 0–5 years old and the males were 60.20%. Other enterovirus (EV), enteriovirus 71(EV71), and Coxsackievirus A16 (CA16) accounted for 48.75%, 30.91% and 20.34%. The seasonal peak was between May and October. HFMD had positive spatial autocorrelation at town level with global Moran’s I from 0.19 to 0.31(P<0.001). Spatial-temporal cluster analysis detected six most likely clusters and three secondary clusters from 2013 to 2018. The most likely cluster was located in urban and urban-rural fringe areas. Conclusions Urban and urban-rural fringe areas were the major locations of the clusters with other EV as the dominant pathogen between May and October. The findings suggested that the prevention and control of HFMD in Qingdao City should be focus on these high-risk periods and locations which had important public health significance for the allocation of public health resources.