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1.
Journal of Public Health and Preventive Medicine ; (6): 33-36, 2020.
Article Dans Chinois | WPRIM | ID: wpr-862511

Résumé

Objective To analyze the epidemiological characteristics and spatiotemporal clustering of scarlet fever in Jinan, from 2014-2019, and to provide a basis for scarlet fever prevention and control. Methods The case data of scarlet fever in Jinan during 2013-2019 were extracted from the Chinese National Notifiable Infectious Disease Reporting System. Descriptive epidemiology and spatiotemporal rearrangement scanning methods were used to analyze the epidemiological characteristics and spatiotemporal distribution of scarlet fever. The RR values of scarlet fever in different towns (streets) were calculated, and the contour map of RR value was drawn. Results A total of 9 715 cases of scarlet fever were reported in Jinan from 2014 to 2019. During this period, the number of cases and the incidence rate showed a gradual increase, with two seasonal peaks in the winter and spring each year. Spatiotemporal clustering analysis detected a total of eight spatiotemporal aggregation areas, and the strongest one was in Licheng and Lixia Districts, from March 2017 to December 2019 (RR=3.45, LLR=577.88, P<0.001). The relative risk maps in each year from 2014 to 2019 were similar, and the areas with the highest risk were located in the central area of Jinan. Conclusion From 2014 to 2019, scarlet fever is highly prevalent in the central area of Jinan, with obvious spatial and temporal clustering. There are clustering areas in the central, southwest and eastern areas of Jinan, and there was a tendency for the disease to spread to Zhangqiu in the east and Pingyin in the southwest.

2.
Asian Pacific Journal of Tropical Biomedicine ; (12): 862-869, 2017.
Article Dans Chinois | WPRIM | ID: wpr-950519

Résumé

Objective To assess the spatiotemporal trait of cutaneous leishmaniasis (CL) in Fars province, Iran. Methods Spatiotemporal cluster analysis was conducted retrospectively to find spatiotemporal clusters of CL cases. Time-series data were recorded from 29 201 cases in Fars province, Iran from 2010 to 2015, which were used to verify if the cases were distributed randomly over time and place. Then, subgroup analysis was applied to find significant sub-clusters within large clusters. Spatiotemporal permutation scans statistics in addition to subgroup analysis were implemented using SaTScan software. Results This study resulted in statistically significant spatiotemporal clusters of CL (P < 0.05). The most likely cluster contained 350 cases from 1 July 2010 to 30 November 2010. Besides, 5 secondary clusters were detected in different periods of time. Finally, statistically significant sub-clusters were found within the three large clusters (P < 0.05). Conclusions Transmission of CL followed spatiotemporal pattern in Fars province, Iran. This can have an important effect on future studies on prediction and prevention of CL.

3.
Asian Pacific Journal of Tropical Biomedicine ; (12): 862-869, 2017.
Article Dans Chinois | WPRIM | ID: wpr-667511

Résumé

Objective: To assess the spatiotemporal trait of cutaneous leishmaniasis (CL) in Fars province, Iran. Methods: Spatiotemporal cluster analysis was conducted retrospectively to find spatio-temporal clusters of CL cases.Time-series data were recorded from 29 201 cases in Fars province,Iran from 2010 to 2015,which were used to verify if the cases were distributed randomly over time and place. Then, subgroup analysis was applied to find significant sub-clusters within large clusters.Spatiotemporal permutation scans statistics in addition to subgroup analysis were implemented using SaTScan software. Results: This study resulted in statistically significant spatiotemporal clusters of CL (P<0.05).The most likely cluster contained 350 cases from 1 July 2010 to 30 November 2010. Besides, 5 secondary clusters were detected in different periods of time. Finally, statistically significant sub-clusters were found within the three large clusters(P<0.05). Conclusions: Transmission of CL followed spatiotemporal pattern in Fars province, Iran.This can have an important effect on future studies on prediction and prevention of CL.

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