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

Zhang Y, Shen Z, Ma C, Jiang C, Feng C, Shankar N, Yang P, Sun W, Wang Q - Int J Environ Res Public Health (2015)

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

View Article: PubMed Central - PubMed

Affiliation: Beijing Center for Disease Prevention and Control (CDC), Beijing 100013, China. zps347@163.com.

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.

No MeSH data available.


Related in: MedlinePlus

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.
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ijerph-12-00816-f004: 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.

Mentions: Spatial Autocorrelation analysis produced a z-score peak between 14 and 26 days temporal distance (Figure 3b). Therefore, the temporal distance at which the z-score peak starts, 14 days, was selected as the threshold temporal distance for the space-time Hot-Spot analysis. The result of the analysis is shown in Figure 4.


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

Zhang Y, Shen Z, Ma C, Jiang C, Feng C, Shankar N, Yang P, Sun W, Wang Q - Int J Environ Res Public Health (2015)

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.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4306894&req=5

ijerph-12-00816-f004: 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.
Mentions: Spatial Autocorrelation analysis produced a z-score peak between 14 and 26 days temporal distance (Figure 3b). Therefore, the temporal distance at which the z-score peak starts, 14 days, was selected as the threshold temporal distance for the space-time Hot-Spot analysis. The result of the analysis is shown in Figure 4.

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

View Article: PubMed Central - PubMed

Affiliation: Beijing Center for Disease Prevention and Control (CDC), Beijing 100013, China. zps347@163.com.

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.

No MeSH data available.


Related in: MedlinePlus