Epidemiological Characteristics and Spatial-Temporal Distribution of Hand, Foot, and Mouth Disease in Chongqing, China, 2009–2016

Abstract

(1) Objective: Even with licensed vaccine for enterovirus 71 (EV71) put into market in 2016 in China, hand, foot, and mouth disease (HFMD) is still a threat for children’s health in Chongqing. We described the epidemiological characteristics and spatial–temporal patterns of HFMD in Chongqing from 2009 to 2016, in order to provide information and evidence for guiding public health response and intervention. (2) Methods: We retrieved the HFMD surveillance data from January 2009 to December 2016 from “National Disease Reporting Information System”, and then analyzed demographic and geographical information integrally. Descriptive analysis was conducted to evaluate the epidemic features of HFMD in Chongqing. The spatial–temporal methods were performed to explore the clusters at district/county level. (3) Results: A total of 276,207 HFMD cases were reported during the study period (total population incidence: 114.8 per 100,000 per year), including 641 severe cases (129 deaths). The annual incidence of HFMD sharply increased in even-numbered years, but remained stable or decreased in odd-numbered years. A semiannual seasonality was observed during April to July, and October to December in each year. The male-to-female ratios of the mild and severe cases were 1.4:1 and 1.5:1, with the median age of 2.3 years and 1.9 years, respectively. More than 90% of the cases were children equal to and less than 5 years old. High-incidence clustered regions included the main urban districts and northeast regions according to incidence rates comparison or space–time cluster analysis. A total of 19,482 specimen were collected from the reported cases and 13,277 (68.2%) were positive for enterovirus. EV71 was the major causative agent for severe cases, while other enteroviruses were the predominant serotype for mild cases. (4) Conclusions: The characteristics of HFMD in Chongqing exhibited a phenomenon of increasing incidence in two-year cycles and semiannual seasonality in time distribution. Children ≤5 years old, especially boys, were more affected by HFMD. EV71 was the major causative agent for severe cases. We suggest initiating mass EV71 vaccination campaigns among children aged 6 months to 5 years in Chongqing, especially in the main urban districts and northern regions, in order to reduce case fatality, and take integrated measurements for controlling and preventing HFMD attributed to other enteroviruses.

Spatio-Temporal Epidemiology of Viral Hepatitis in China (2003–2015): Implications for Prevention and Control Policies

“…The space-time scan statistic is defined by a cylindrical window with a circular geographical base which is centered on the centroids of areas, and with height corresponding to time. For this analysis, a discrete Poisson based model was used, where the number of cases in an area is Poisson distributed according to a known underlying population at risk [ 24 ]. The null hypothesis assumed that the relative risk (RR) of the incidence was the same within the window as compared with outside.…”

Epidemiological and clinical characteristics of severe hand-foot-and-mouth disease (HFMD) among children: a 6-year population-based study

“…Previous studies about HFMD were mainly focused on the features of mild HFMD, therefore, the incidence of HFMD worldwide has been controlled to a certain degree [23][24][25]. However, to our knowledge, relevant researches about the clinical or epidemiological characteristics of severe HFMD patients or fatal cases was few, which may impede the further reduction in case fatality.…”

Space-Time Clustering Characteristics of Tuberculosis in Khyber Pakhtunkhwa Province, Pakistan, 2015–2019

“…This group of methods (which infer the geographical location and time-period of the clusters) can further be divided into two categories [26]: clustering-based methods [27][28][29] and scan statistics methods [23][24][25]. Scan statistics methods are the most widely used methods in public health and epidemiology [30][31][32][33][34][35][36][37].…”