Spatial, temporal and spatio-temporal clusters of measles incidence at the county level in Guangxi, China during 2004–2014: flexibly shaped scan statistics

Abstract

BackgroundOutbreaks of measles re-emerged in Guangxi province during 2013–2014, where measles again became a major public health concern. A better understanding of the patterns of measles cases would help in identifying high-risk areas and periods for optimizing preventive strategies, yet these patterns remain largely unknown. Thus, this study aimed to determine the patterns of measles clusters in space, time and space-time at the county level over the period 2004–2014 in Guangxi.MethodsAnnual data on measles cases and population sizes for each county were obtained from Guangxi CDC and Guangxi Bureau of Statistics, respectively. Epidemic curves and Kulldorff’s temporal scan statistics were used to identify seasonal peaks and high-risk periods. Tango’s flexible scan statistics were implemented to determine irregular spatial clusters. Spatio-temporal clusters in elliptical cylinder shapes were detected by Kulldorff’s scan statistics. Population attributable risk percent (PAR%) of children aged ≤24 months was used to identify regions with a heavy burden of measles.ResultsSeasonal peaks occurred between April and June, and a temporal measles cluster was detected in 2014. Spatial clusters were identified in West, Southwest and North Central Guangxi. Three phases of spatio-temporal clusters with high relative risk were detected: Central Guangxi during 2004–2005, Midwest Guangxi in 2007, and West and Southwest Guangxi during 2013–2014. Regions with high PAR% were mainly clustered in West, Southwest, North and Central Guangxi.ConclusionsA temporal uptrend of measles incidence existed in Guangxi between 2010 and 2014, while downtrend during 2004–2009. The hotspots shifted from Central to West and Southwest Guangxi, regions overburdened with measles. Thus, intensifying surveillance of timeliness and completeness of routine vaccination and implementing supplementary immunization activities for measles should prioritized in these regions.

Notifiable Respiratory Infectious Diseases in China: A Spatial–Temporal Epidemiology Analysis

“…Measles displayed a high-incidence season in spring, and mumps peak incidence occurred during the summer months with a peak of about half the size occurring in spring. Previous studies have revealed an association between the RIDs and seasons [18,22,30,36,37]. The occurrence of RIDs is related to climatic factors, such as the amount of sunshine, changes in the temperature, and indoor activity.…”

Spatial, temporal, and spatiotemporal analysis of mumps in Guangxi Province, China, 2005–2016

“…This condition explains why some clusters are found in poor counties located in the western and northern parts of Guangxi, such as Jiangzhou, Xilin, and Luocheng. In addition, only a few children who migrate to the urban or suburban areas with their parents can timely receive free mumps vaccination [ 21 , 38 ]. Meanwhile, the current immunization strategies do not allow local children to develop high antibody concentration.…”

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

“…Spatial scan statistics and Anselin's Moran I are widely used to detect spatial cluster for infectious disease (18,19). The strength of the scan statistic is that it can detect clusters over space and time.…”

“…However, some geographic units are sometimes included in both high-risk and low-risk clusters, this made it difficult to compare population density between high-and low-risk townships in our study. Anselin's Local Moran I is calculated for each geographic unit, therefore it is not sensitive to the shape of geographic features, and the detected clusters do not geographically overlap (19)(20)(21). Hence, we chose Anselin's Local Moran I to identify clusters of severe HFMD cases in our study.…”