Volume 76, Issue 12 (March 2019)
Tehran Univ Med J 2019, 76(12): 822-826 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Jafarinia B, Rashti R, Halvaei Zadeh R, Moazen J, Kalantari H. Spatial, temporal, and spatiotemporal analysis of cutaneous leishmaniasis in North Khuzestan Province, Iran, from 2011 to 2015: brief report. Tehran Univ Med J 2019; 76 (12) :822-826
URL: http://tumj.tums.ac.ir/article-1-9419-en.html
URL: http://tumj.tums.ac.ir/article-1-9419-en.html
1- Department of Epidemiology, Department of Health, Dezful University of Medical Sciences, Dezful, Iran.
2- Department of Epidemiology, Department of Health, Dezful University of Medical Sciences, Dezful, Iran. , roya.rashti73@gmail.com
3- Department of Public Health, Department of Health, Dezful University of Medical Sciences, Dezful, Iran.
4- Department of Infectious Disease and Tropical Medicine, Department of Education, Dezful University of Medical Sciences, Dezful, Iran.
5- Department of Medical Entomology, Department of Health, Dezful University of Medical Sciences, Dezful, Iran.
2- Department of Epidemiology, Department of Health, Dezful University of Medical Sciences, Dezful, Iran. , roya.rashti73@gmail.com
3- Department of Public Health, Department of Health, Dezful University of Medical Sciences, Dezful, Iran.
4- Department of Infectious Disease and Tropical Medicine, Department of Education, Dezful University of Medical Sciences, Dezful, Iran.
5- Department of Medical Entomology, Department of Health, Dezful University of Medical Sciences, Dezful, Iran.
Abstract: (2739 Views)
Background: Leishmaniasis is a zoonosis disease. About 350 million people are at risk of developing a disease, with 1.5 to 2 million new cases every year in the world. The aim of this study was to determine the space-time clusters of cutaneous leishmaniasis in north of Khuzestan Province, Iran.
Methods: In this cross-sectional study, the annual cutaneous leishmaniasis incidence per 100,000 individuals in each county was determined for the past five years. Reported from 2011 to 2015 in North of Khuzestan Province, Iran. Geographical information system (GIS) and spatial scan statistic method were used to identify spatial clusters of cutaneous leishmaniasis cases at the county level. Pure retrospective temporal analysis scanning was performed to detect the temporal clusters of cutaneous leishmaniasis cases with high rates using the discrete Poisson model. The space-time cluster was detected with high rates through the retrospective space-time analysis scanning using the discrete Poisson model.
Results: The overall cutaneous leishmaniasis incidence increased from 2011 to 2015. A total of 3 high-risk counties were determined through Local Moran’s I analysis from 2011 to 2015. Local Moran’s I enabled the detection of the spatial autocorrelation for a county with its adjacent county. The method of spatial scan statistics identified different 11 significant spatial clusters. The space-time clustering analysis determined that the most likely cluster included 11 counties, and the time frame was October 2014. The secondary cluster included one counties in October 2014. The tertiary cluster included six counties, and the time frame was from June 2014 to November 2015.
Conclusion: Spatial and temporal clusters of cutaneous leishmaniasis have increased in the northern region of Khuzestan Province, and most clusters have occurred in November.
Methods: In this cross-sectional study, the annual cutaneous leishmaniasis incidence per 100,000 individuals in each county was determined for the past five years. Reported from 2011 to 2015 in North of Khuzestan Province, Iran. Geographical information system (GIS) and spatial scan statistic method were used to identify spatial clusters of cutaneous leishmaniasis cases at the county level. Pure retrospective temporal analysis scanning was performed to detect the temporal clusters of cutaneous leishmaniasis cases with high rates using the discrete Poisson model. The space-time cluster was detected with high rates through the retrospective space-time analysis scanning using the discrete Poisson model.
Results: The overall cutaneous leishmaniasis incidence increased from 2011 to 2015. A total of 3 high-risk counties were determined through Local Moran’s I analysis from 2011 to 2015. Local Moran’s I enabled the detection of the spatial autocorrelation for a county with its adjacent county. The method of spatial scan statistics identified different 11 significant spatial clusters. The space-time clustering analysis determined that the most likely cluster included 11 counties, and the time frame was October 2014. The secondary cluster included one counties in October 2014. The tertiary cluster included six counties, and the time frame was from June 2014 to November 2015.
Conclusion: Spatial and temporal clusters of cutaneous leishmaniasis have increased in the northern region of Khuzestan Province, and most clusters have occurred in November.
Type of Study: Brief Report |
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
