ArticleParasites & vectors2020
A spatio-temporal agent-based approach for modeling the spread of zoonotic cutaneous leishmaniasis in northeast Iran.
Article in Parasites & vectors, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 29 citations in OpenAlex.
- Data-intensive immune network modelling for One Health.Briefings in bioinformatics · 2026Review
- Toward Eliminating Leishmaniasis as a Public Health Problem in Yemen: Advocating for a One Health Approach.Research and reports in tropical medicine · 2026Review
- Trend analysis and spatiotemporal distribution of leishmaniasis disease incidence in Sri Lanka: A detailed review from 2009 to 2023.PLoS neglected tropical diseases · 2025Review
- A Comprehensive Review of Epidemiology, Environmental Factors, and Control Strategies for Zoonotic CutaneousAdvanced biomedical research · 2025Review
- A Geomedical Survey: Is There an Association Between Climatic Conditions and Leishmania Species Distribution in Iran During the Years 1999-2021?Acta parasitologica · 2024Article
- Global Dilemma and Needs Assessment Toward Achieving Sustainable Development Goals in Controlling Leishmaniasis.Journal of epidemiology and global health · 2024Review
- Article
- In silico and in vitro potentials of crocin and amphotericin B on Leishmania major: Multiple synergistic mechanisms of actions.PloS one · 2023Article
- Cutaneous leishmaniasis situation analysis in the Islamic Republic of Iran in preparation for an elimination plan.Frontiers in public health · 2023Review
- Spatiotemporal distribution of cutaneous leishmaniasis in Sri Lanka and future case burden estimates.PLoS neglected tropical diseases · 2021Article
- Field Efficacy of Topical Nano-Liposomal Amphotericin B (Sina Ampholeish®) Alone or in Combination with Glucantime® and Cryotherapy on Human Cutaneous Leishmaniasis.Iranian journal of parasitologyArticle
Corrections and comments
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Authors and funding
6 authors at 5 institutions in 5 countries.
Funding
Abstract
backgroundZoonotic cutaneous leishmaniasis (ZCL) is a neglected tropical disease worldwide, especially the Middle East. Although previous works attempt to model the ZCL spread using various environmental factors, the interactions between vectors (Phlebotomus papatasi), reservoir hosts, humans, and the environment can affect its spread. Considering all of these aspects is not a trivial task.
methodsAn agent-based model (ABM) is a relatively new approach that provides a framework for analyzing the heterogeneity of the interactions, along with biological and environmental factors in such complex systems. The objective of this research is to design and develop an ABM that uses Geospatial Information System (GIS) capabilities, biological behaviors of vectors and reservoir hosts, and an improved Susceptible-Exposed-Infected-Recovered (SEIR) epidemic model to explore the spread of ZCL. Various scenarios were implemented to analyze the future ZCL spreads in different parts of Maraveh Tappeh County, in the northeast region of Golestan Province in northeastern Iran, with alternative socio-ecological conditions.
resultsThe results confirmed that the spread of the disease arises principally in the desert, low altitude areas, and riverside population centers. The outcomes also showed that the restricting movement of humans reduces the severity of the transmission. Moreover, the spread of ZCL has a particular temporal pattern, since the most prevalent cases occurred in the fall. The evaluation test also showed the similarity between the results and the reported spatiotemporal trends.
conclusionsThis study demonstrates the capability and efficiency of ABM to model and predict the spread of ZCL. The results of the presented approach can be considered as a guide for public health management and controlling the vector population .
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.