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A spatially explicit agent-based simulation model of a reservoir host of cutaneous leishmaniasis, Rhombomys opimus

Rajabi, Mohammadreza LU ; Mansourian, A LU ; Pilesjö, Petter LU ; Shirzadi, Mohammad Reza ; Fadaei, Reza and Ramazanpour, Javad (2018) In Ecological Modelling 370. p.33-49
Abstract

Rhombomys opimus (R. opimus), a social rodent, is the main reservoir host for zoonotic cutaneous leishmaniasis (ZCL) in most parts of the Middle East and central Asia. The difficulties in monitoring rodent population patterns have hindered the effective application of preventive measures of ZCL. This study presents a spatially explicit agent-based simulation model of R. opimus behaviors that is integrated with Geographic Automata System (GAS) and a heuristic optimization method, cuckoo search (CS). The model is used to explore the relationships among rodent population dynamics, ZCL incidence and authority interventions using statistical data generated from simulated rodent societies rather than observational data, which are difficult to... (More)

Rhombomys opimus (R. opimus), a social rodent, is the main reservoir host for zoonotic cutaneous leishmaniasis (ZCL) in most parts of the Middle East and central Asia. The difficulties in monitoring rodent population patterns have hindered the effective application of preventive measures of ZCL. This study presents a spatially explicit agent-based simulation model of R. opimus behaviors that is integrated with Geographic Automata System (GAS) and a heuristic optimization method, cuckoo search (CS). The model is used to explore the relationships among rodent population dynamics, ZCL incidence and authority interventions using statistical data generated from simulated rodent societies rather than observational data, which are difficult to obtain through field surveys. The model simulation considers three agent types: rodents, colonies and cell agents. The model components and overall approach are calibrated, investigated with sensitivity analysis and validated with empirical field data in a ZCL-endemic area in Isfahan, central Iran. The results suggest that unsupervised and sporadic preventive measures could cause rodent emigration towards human population centers and start new waves of infections.

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author
; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Zoonotic cutaneous leishmaniasis, Agent-based model, Rhombomys opimus, Socio-ecological interactions, Optimization, Geospatial Artificial Intelligence (GeoAI), Artificial Intelligence (AI)
in
Ecological Modelling
volume
370
pages
17 pages
publisher
Elsevier
external identifiers
  • scopus:85041476563
ISSN
0304-3800
DOI
10.1016/j.ecolmodel.2017.12.004
language
English
LU publication?
yes
id
15e04c01-b3b1-40b9-9960-9e34308d149c
date added to LUP
2018-01-25 13:37:29
date last changed
2023-09-21 20:42:48
@article{15e04c01-b3b1-40b9-9960-9e34308d149c,
  abstract     = {{<p>Rhombomys opimus (R. opimus), a social rodent, is the main reservoir host for zoonotic cutaneous leishmaniasis (ZCL) in most parts of the Middle East and central Asia. The difficulties in monitoring rodent population patterns have hindered the effective application of preventive measures of ZCL. This study presents a spatially explicit agent-based simulation model of R. opimus behaviors that is integrated with Geographic Automata System (GAS) and a heuristic optimization method, cuckoo search (CS). The model is used to explore the relationships among rodent population dynamics, ZCL incidence and authority interventions using statistical data generated from simulated rodent societies rather than observational data, which are difficult to obtain through field surveys. The model simulation considers three agent types: rodents, colonies and cell agents. The model components and overall approach are calibrated, investigated with sensitivity analysis and validated with empirical field data in a ZCL-endemic area in Isfahan, central Iran. The results suggest that unsupervised and sporadic preventive measures could cause rodent emigration towards human population centers and start new waves of infections.</p>}},
  author       = {{Rajabi, Mohammadreza and Mansourian, A and Pilesjö, Petter and Shirzadi, Mohammad Reza and Fadaei, Reza and Ramazanpour, Javad}},
  issn         = {{0304-3800}},
  keywords     = {{Zoonotic cutaneous leishmaniasis; Agent-based model; Rhombomys opimus; Socio-ecological interactions; Optimization; Geospatial Artificial Intelligence (GeoAI); Artificial Intelligence (AI)}},
  language     = {{eng}},
  month        = {{02}},
  pages        = {{33--49}},
  publisher    = {{Elsevier}},
  series       = {{Ecological Modelling}},
  title        = {{A spatially explicit agent-based simulation model of a reservoir host of cutaneous leishmaniasis, Rhombomys opimus}},
  url          = {{http://dx.doi.org/10.1016/j.ecolmodel.2017.12.004}},
  doi          = {{10.1016/j.ecolmodel.2017.12.004}},
  volume       = {{370}},
  year         = {{2018}},
}