ArticleInfectious diseases of poverty2023
High-risk spatiotemporal patterns of cutaneous leishmaniasis: a nationwide study in Iran from 2011 to 2020.
Article in Infectious diseases of poverty, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed.
- GIS-based neural network framework for zoonotic cutaneous leishmaniasis risk mapping in Western Iran.Environmental monitoring and assessment · 2026Article
- A study protocol for developing a spatial vulnerability index for infectious diseases of poverty in the Caribbean region.Global health action · 2025Article
- Pneumonia incidence and determinants in South Punjab, Pakistan (2016-2020): a spatial epidemiological study at Tehsil-level.International journal of health geographics · 2025Article
- Trends and spatio temporal distribution of HIV related programmatic indicators in North West Ethiopia from July 2018 up to June 2024.Scientific reports · 2025Article
- Contribution of epidermal growth factor (EGF) in the treatment of cutaneous leishmaniasis caused by Leishmania major in BALB/c mice.PLoS neglected tropical diseases · 2025Article
- From pre-oral secretions to gut digestion: How do Lucilia sericata (Diptera: Calliphoridae) larvae handle Leishmania major?PloS one · 2025Article
- Retrospective analysis of spatiotemporal variation of scrub typhus in Yunnan Province, 2006-2022.PLoS neglected tropical diseases · 2024Article
- Analysis of cutaneous leishmaniasis among military personnel in the Islamic Republic of Iran: a spatiotemporal study between 2018 and 2022, trend forecasting based on ARIMA model.BMC infectious diseases · 2024Article
- High-risk spatiotemporal patterns of leprosy in the southeastern region of Yunnan province from 2010 to 2022: an analysis at the township level.BMC public health · 2024Article
- The Impact of Climatological Factors on the Incidence of Cutaneous Leishmaniasis (CL) in Colombian Municipalities from 2017 to 2019.Pathogens (Basel, Switzerland) · 2024Article
- Geography and health: role of human translocation and access to care.Infectious diseases of poverty · 2024Article
- A gender-specific geodatabase of five cancer types with the highest frequency of occurrence in Iran.BMC research notes · 2024Article
- Clinical and laboratory characterization of cutaneous leishmaniasis in Chinese migrant workers returned from Iraq.PLoS neglected tropical diseases · 2024Article
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Abstract
backgroundCutaneous leishmaniasis (CL) is a wide-reaching infection of major public health concern. Iran is one of the six most endemic countries in the world. This study aims to provide a spatiotemporal visualization of CL cases in Iran at the county level from 2011 to 2020, detecting high-risk zones, while also noting the movement of high-risk clusters.
methodsOn the basis of clinical observations and parasitological tests, data of 154,378 diagnosed patients were obtained from the Iran Ministry of Health and Medical Education. Utilizing spatial scan statistics, we investigated the disease's purely temporal, purely spatial, spatial variation in temporal trends and spatiotemporal patterns. At P = 0.05 level, the null hypothesis was rejected in every instance.
resultsIn general, the number of new CL cases decreased over the course of the 9-year research period. From 2011 to 2020, a regular seasonal pattern, with peaks in the fall and troughs in the spring, was found. The period of September-February of 2014-2015 was found to hold the highest risk in terms of CL incidence rate in the whole country [relative risk (RR) = 2.24, P < 0.001)]. In terms of location, six significant high-risk CL clusters covering 40.6% of the total area of the country were observed, with the RR ranging from 1.87 to 9.69. In addition, spatial variation in the temporal trend analysis found 11 clusters as potential high-risk areas that highlighted certain regions with an increasing tendency. Finally, five space-time clusters were found. The geographical displacement and spread of the disease followed a moving pattern over the 9-year study period affecting many regions of the country.
conclusionsOur study has revealed significant regional, temporal, and spatiotemporal patterns of CL distribution in Iran. Over the years, there have been multiple shifts in spatiotemporal clusters, encompassing many different parts of the country from 2011 to 2020. The results reveal the formation of clusters across counties that cover certain parts of provinces, indicating the importance of conducting spatiotemporal analyses at the county level for studies that encompass entire countries. Such analyses, at a finer geographical scale, such as county level, might provide more precise results than analyses at the scale of the province.
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