Evidence map›Paper›PMID 42871476›Full record

ArticleOne health (Amsterdam, Netherlands)2026

Climate-driven shifts in lumpy skin disease risk across Iran: Insights from ensemble species distribution models.

Seyed Erfan Momenpour, Masoumeh Moghbel, Seyed Soheil Ghaemmaghami, Kambiz Amjadigolpayegani

Abstract read
In one paragraph

Article in One health (Amsterdam, Netherlands), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Seyed Erfan MomenpourFaculty of Geography, University of Tehran, Tehran, Iran.
Masoumeh MoghbelFaculty of Geography, University of Tehran, Tehran, Iran.
Seyed Soheil GhaemmaghamiInstitute of Agricultural Education and Extension, Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran.
Kambiz AmjadigolpayeganiIran Veterinary Organization, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to identify the environmental determinants influencing the distribution of lumpy skin disease and to predict changes in its spatial distribution risk and potential geographic range across Iran under future climate change scenarios using ensemble Species Distribution Models (SDMs). To this end, following data cleaning and quality control of 3654 disease occurrence records, a total of 2849 presence points recorded between 2013 and 2024 were retained for model development. The CTA, GAM, GBM, and RF algorithms were implemented within an ensemble modelling framework. The final ensemble model (EMca) achieved a True Skill Statistic (TSS) score of 0.85, an area under the receiver operating characteristic curve (AUC) of 0.96, and a Boyce index of 0.96 during calibration. For the validation data, the corresponding scores were 0.66, 0.89, and 0.93, respectively. The model therefore demonstrated broadly consistent predictive performance across calibration and validation based on these three evaluation metrics. Future projections were generated using three General Circulation Models (GCMs) HadGEM3-GC31-LL, MIROC6, and MPI-ESM1-2-HR under the SSP2-4.5 and SSP5-8.5 climate scenarios for the 2021-2040 and 2041-2060 time periods. The results indicated that hydrological, anthropogenic, and climatic variables were the three primary determinants of the spatial distribution of lumpy skin disease. Among the predictor variables, distance to rivers, distance to roads, and annual precipitation were identified as the most influential factors governing disease distribution, respectively. Furthermore, the risk maps revealed that western and northwestern Iran, together with the Zagros Mountain Range, which currently represent the principal disease hotspots, are projected to remain the major potential hotspots under future climate change scenarios. Range size analysis further indicated that although a proportion of the currently suitable areas for lumpy skin disease is projected to be lost under future climate conditions, the emergence of newly suitable areas is expected to largely offset these losses. Consequently, the net change in the disease's potential range is predicted to be minimal during the 2021-2040 period (-0.98%). However, this decline is projected to increase to -4.34% under the SSP2-4.5 scenario and -8.01% under the SSP5-8.5 scenario during the 2041-2060 period. Overall, the findings suggest that, in the near future, climate change is more likely to drive a spatial reorganization of disease risk hotspots than to cause a substantial expansion of the disease's potential distribution. These findings provide a robust scientific basis for targeted surveillance, strategic vaccination, and the development of early warning systems for the effective management of lumpy skin disease in Iran.

Indexed as

Climate changeEnsemble modelsLumpy skin disease (LSD)Range size analysisSpecies distribution models

Identifiers

PMID42871476
PMCPMC13659675

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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.