Detecting Spatial-Temporal Clusters of HFMD from 2007 to 2011 in Shandong Province, China

Abstract

BackgroundHand, foot, and mouth disease (HFMD) has caused major public health concerns worldwide, and has become one of the leading causes of children death. China is the most serious epidemic area with a total of 3,419,149 reported cases just from 2008 to 2010, and its different geographic areas might have different spatial epidemiology characteristics at different spatial-temporal scale levels. We conducted spatial and spatial-temporal epidemiology analysis to HFMD at county level in Shandong Province, China.MethodsBased on the China National Disease Surveillance Reporting and Management System, the spatial-temporal database of HFMD from 2007 to 2011 was built. The global autocorrelation statistic (Moran’s I) was first used to detect the spatial autocorrelation of HFMD cases in each year. Purely Spatial scan statistics combined with Space-time scan statistic were used to detect epidemic clusters.ResultsThe annual average incidence rate was 93.70 per 100,000 in Shandong Province. Most HFMD cases (93.94%) were aged within 0–5 years old with an average male-to-female sex ratio 1.71, and the incidence seasonal peak was between April and July. The dominant pathogen was EV71 (47.35%), and CoxA16 (26.59%). HFMD had positive spatial autocorrelation at medium spatial scale level (county level) with higher Moran’s I from 0.31 to 0.62 (P<0.001). Seven spatial-temporal clusters were detected from 2007 to 2011 in the landscape of the whole Shandong, with EV71 or CoxA16 as the dominant pathogen for most hotspots areas.ConclusionsThe spatial-temporal clusters of HFMD wandered around the whole Shandong Province during 2007 to 2011, with EV71 or CoxA16 as the dominant pathogen. These findings suggested that a real-time spatial-temporal surveillance system should be established for identifying high incidence region and conducting prevention to HFMD timely.

The effect of meteorological factors on adolescent hand, foot, and mouth disease and associated effect modifiers

“…We classified the children into two groups by age using 2 years old as cut-off point, as children younger than 2 years old could not walk independently (28). By occupation, the children were grouped into scattered children and schooling children, where the scattered children were the pre-school children who have not been to kindergarten or school (29). We tested the statistical significance of differences between the effect estimates of the strata divided by potential effect modifiers by calculating the 95% confidence interval as:$(Q_1-Q_2)\pm 1.96\sqrt{{(S{E}_1)}^2+{(S{E}_2)}^2}$ where Q 1 and Q 2 were the effect estimates for each stratum (such as male and female), and SE 1 and SE 2 were their corresponding standard errors (30).…”

Spatial Clustering of Severe Hand-Foot-Mouth Disease Cases on Hainan Island, China

“…However, no spatial clustering studies of the incidence of severe HFMD or the proportion of severe HFMD cases among total HFMD cases have been conducted. Several studies have reported spatial clustering of the incidence of general HFMD (7)(8)(9)(10)(11), although all previous studies of HFMD clusters used district-level incidence data, which might have masked the potential effect of local environment. Thus, we analyzed the incidence of severe HFMD and the proportion of severe HFMD among total HFMD cases at the township level, which facilitated evaluation of the link between severe HFMD and environment factors at a higher geographical resolution.…”

Spatio-Temporal Distribution and Hotspots of Hand, Foot and Mouth Disease (HFMD) in Northern Thailand

“…Spatio-temporal analysis is increasingly used in epidemiological research based on specific or routinely collected data from different sources [19,20,21]. Therefore, a better understanding of the spatio-temporal distribution patterns of HFMD would help in identifying areas and populations at high risk and then formulating and implementing appropriate regional public health intervention strategies to prevent and control the outbreak [22]. …”