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Analysis of the geographic distribution of HFRS in Liaoning Province between 2000 and 2005.

Lin H, Liu Q, Guo J, Zhang J, Wang J, Chen H - BMC Public Health (2007)

Bottom Line: Spatial cluster analysis suggested 16 and 41 counties were at increased risk for HFRS (p < 0.01) with the maximum spatial cluster sizes at < or = 50% and < or = 30% of the total population, respectively, and the analysis showed relative humidity and forestation in the cluster areas were significantly higher than in other areas.There was strong evidence some HFRS cases in Liaoning Province formed clusters, but the mechanism underlying it remains unknown.In this study we found the clustering was consistent with the relative humidity and amount of forestation, and showed data indicating there may be some significant relationships.

View Article: PubMed Central - HTML - PubMed

Affiliation: National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China. linhualiang2002@163.com

ABSTRACT

Background: Hemorrhagic fever with renal syndrome (HFRS) is endemic in Liaoning Province, China, and this province was the most serious area affected by HFRS during 2004 to 2005. In this study, we conducted a spatial analysis of HFRS cases with the objective to determine the distribution of HFRS cases and to identify key areas for future public health planning and resource allocation in Liaoning Province.

Methods: The annual average incidence at the county level was calculated using HFRS cases reported between 2000 and 2005 in Liaoning Province. GIS-based spatial analyses were conducted to detect spatial distribution and clustering of HFRS incidence at the county level, and the difference of relative humidity and forestation between the cluster areas and non-cluster areas was analyzed.

Results: Spatial distribution of HFRS cases in Liaoning Province from 2000 to 2005 was mapped at the county level to show crude incidence, excess hazard, and spatial smoothed incidence. Spatial cluster analysis suggested 16 and 41 counties were at increased risk for HFRS (p < 0.01) with the maximum spatial cluster sizes at < or = 50% and < or = 30% of the total population, respectively, and the analysis showed relative humidity and forestation in the cluster areas were significantly higher than in other areas.

Conclusion: Some clustering of HFRS cases in Liaoning Province may be etiologically linked. There was strong evidence some HFRS cases in Liaoning Province formed clusters, but the mechanism underlying it remains unknown. In this study we found the clustering was consistent with the relative humidity and amount of forestation, and showed data indicating there may be some significant relationships.

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Spatial distribution of clusters of HFRS with significant higher incidence using the maximum cluster size < 30% of the total population in Liaoning Province, China, 2000–2005.
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Figure 5: Spatial distribution of clusters of HFRS with significant higher incidence using the maximum cluster size < 30% of the total population in Liaoning Province, China, 2000–2005.

Mentions: To investigate the possibility of smaller clusters, the same analysis was performed with a modification of the maximum spatial cluster size which was defined as ≤ 30% total population. A most likely cluster and four secondary clusters were identified (Figure 5). The most likely cluster was the same as in the 50% analysis. Four secondary sub-clusters included 29 counties which contain 61.50% of the total population. This excess risk within a nonrandom distribution pattern was also significant (p < 0.01) (Table 1).


Analysis of the geographic distribution of HFRS in Liaoning Province between 2000 and 2005.

Lin H, Liu Q, Guo J, Zhang J, Wang J, Chen H - BMC Public Health (2007)

Spatial distribution of clusters of HFRS with significant higher incidence using the maximum cluster size < 30% of the total population in Liaoning Province, China, 2000–2005.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2194774&req=5

Figure 5: Spatial distribution of clusters of HFRS with significant higher incidence using the maximum cluster size < 30% of the total population in Liaoning Province, China, 2000–2005.
Mentions: To investigate the possibility of smaller clusters, the same analysis was performed with a modification of the maximum spatial cluster size which was defined as ≤ 30% total population. A most likely cluster and four secondary clusters were identified (Figure 5). The most likely cluster was the same as in the 50% analysis. Four secondary sub-clusters included 29 counties which contain 61.50% of the total population. This excess risk within a nonrandom distribution pattern was also significant (p < 0.01) (Table 1).

Bottom Line: Spatial cluster analysis suggested 16 and 41 counties were at increased risk for HFRS (p < 0.01) with the maximum spatial cluster sizes at < or = 50% and < or = 30% of the total population, respectively, and the analysis showed relative humidity and forestation in the cluster areas were significantly higher than in other areas.There was strong evidence some HFRS cases in Liaoning Province formed clusters, but the mechanism underlying it remains unknown.In this study we found the clustering was consistent with the relative humidity and amount of forestation, and showed data indicating there may be some significant relationships.

View Article: PubMed Central - HTML - PubMed

Affiliation: National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China. linhualiang2002@163.com

ABSTRACT

Background: Hemorrhagic fever with renal syndrome (HFRS) is endemic in Liaoning Province, China, and this province was the most serious area affected by HFRS during 2004 to 2005. In this study, we conducted a spatial analysis of HFRS cases with the objective to determine the distribution of HFRS cases and to identify key areas for future public health planning and resource allocation in Liaoning Province.

Methods: The annual average incidence at the county level was calculated using HFRS cases reported between 2000 and 2005 in Liaoning Province. GIS-based spatial analyses were conducted to detect spatial distribution and clustering of HFRS incidence at the county level, and the difference of relative humidity and forestation between the cluster areas and non-cluster areas was analyzed.

Results: Spatial distribution of HFRS cases in Liaoning Province from 2000 to 2005 was mapped at the county level to show crude incidence, excess hazard, and spatial smoothed incidence. Spatial cluster analysis suggested 16 and 41 counties were at increased risk for HFRS (p < 0.01) with the maximum spatial cluster sizes at < or = 50% and < or = 30% of the total population, respectively, and the analysis showed relative humidity and forestation in the cluster areas were significantly higher than in other areas.

Conclusion: Some clustering of HFRS cases in Liaoning Province may be etiologically linked. There was strong evidence some HFRS cases in Liaoning Province formed clusters, but the mechanism underlying it remains unknown. In this study we found the clustering was consistent with the relative humidity and amount of forestation, and showed data indicating there may be some significant relationships.

Show MeSH
Related in: MedlinePlus