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. 2015 Jan 15;12(1):816-28.
doi: 10.3390/ijerph120100816.

Cluster of human infections with avian influenza A (H7N9) cases: a temporal and spatial analysis

Yi Zhang  1 , Zhixiong Shen  2 , Chunna Ma  3 , Chengsheng Jiang  4 , Cindy Feng  5 , Nivedita Shankar  6 , Peng Yang  7 , Wenjie Sun  8 , Quanyi Wang  9
Affiliations

Cluster of human infections with avian influenza A (H7N9) cases: a temporal and spatial analysis

Yi Zhang et al. Int J Environ Res Public Health. .

Abstract

Objectives: This study aims to describe the spatial and temporal characteristics of human infections with H7N9 virus in China using data from February 2013 to March 2014 from the websites of every province's Population and Family Planning Commission.

Methods: A human infection with H7N9 virus dataset was summarized by county to analyze its spatial clustering, and by date of illness onset to analyze its space-time clustering using the ESRI® Geographic Information System (GIS) software ArcMap™ 10.1 and SatScan.

Results: Based on active surveillance data, the distribution map of H7N9 cases shows that compared to the rest of China, the areas from near the Yangtze River delta (YRD) to farther south around the Pearl River delta (PRD) had the highest densities of H7N9 cases. The case data shows a strong space-time clustering in the areas on and near the YRD from 26 March to 18 April 2013 and a weak space-time clustering only in the areas on and near the PRD between 3 and 4 February 2014. However, for the rest of the study period, H7N9 cases were spatial-temporally randomly distributed.

Conclusions: Our results suggested that the spatial-temporal clustering of H7N9 in China between 2013 and 2014 is fundamentally different.

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Figures

Figure 1
Figure 1
Weekly case number of human infection with avian influenza A (H7N9) virus and average weekly temperature.
Figure 2
Figure 2
Distribution of H7N9 cases at county level in China from the 19 February 2013 to 31 March 2014. County and province boundary data was accessed from Chinese National Fundamental Geographic Information System (www.nfgis.nsdi.gov.cn) in May 2014. Provinces (Guangdong, Zhejiang and Jiangsu) and cities (Shenzhen, Guangzhou, Hangzhou and Shanghai) mentioned in the paper are marked out. YRD: Yangtze River delta, PRD: Pearl River delta.
Figure 3
Figure 3
Results of Incremental Spatial Autocorrelation analysis (a) and Spatial Autocorrelation analysis (b).
Figure 4
Figure 4
Spatial-temporal clustering of H7N9 cases analyzed using the Hot Spot analysis tool of software ArcMap™ 10.1. See caption in Figure 3 for statistical interpretation of the GiZscore. GiZscore is a measure of the statistical significance of spatial clustering and dispersing. A GiZscore <−2.58 indicates dispersion at p = 0.01, −2.58 to −1.96 dispersion at p = 0.05, −1.96 to −1.66 dispersion at p = 0.1, −1.66 to 1.66 random distribution, 1.66 to 1.96 clustering at p = 0.1, 1.96 to 2.58 clustering at p = 0.05, and >2.58 clustering at p = 0.01.
Figure 5
Figure 5
Temporal-spatial clustering of human H7N9 cases detected by SatScan.
See this image and copyright information in PMC

References

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