Evidence map›Paper›PMID 39331161›Full record

ArticleTropical animal health and production2024

Space-time cluster analysis and maximum entropy modeling of Peste des petits ruminants (PPR) in Türkiye.

Tuba Bayir, İsmayil Safa Gürcan

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Article in Tropical animal health and production, 2024. 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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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Tuba BayirDepartment of Biometrics, Faculty of Veterinary Medicine, Fırat University, Elazığ, Türkiye, Turkey. tuubabayir@gmail.com.ORCID https://orcid.org/0000-0001-6381-0324
İsmayil Safa GürcanDepartment of Biostatistics, Faculty of Veterinary Medicine, Ankara University, Ankara, Türkiye, Turkey.ORCID https://orcid.org/0000-0002-0738-1518

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Peste des petits ruminants (PPR) is an economically important highly serious transboundary disease that mainly occurs in small ruminants such as sheep and goats. The aim of this study was to identify the probability of risk and and space-time clusters of Peste des Petits Ruminants (PPR) in Türkiye. The occurrence of PPR in Türkiye from 2017 to 2019 was investigated in this study using spatial analysis based on geographic information system (GIS). Between these dates, it was determined that 337 outbreaks and 18,467 cases. The highest number of outbreaks were detected in the Central Anatolia region. It was determined that PPR is seen more intensely in sheep compared to goats in Türkiye. In this study, 34 environmental variables (19 bioclimatic, 12 precipitation, altitude and small livestock density variables) were used to explore the environmental influences on PPR outbreak by maximum entropy modeling (Maxent). The clusters of PPR in Türkiye were identified using the retrospective space-time scan data that were computed using the space-time permutation model. A PPR prediction model was created using data on PPR outbreaks combination with environmental variables. Nineteen significant (p < 0.001) space-time clusters were determined. It was discovered that the variables altitude, sheep density, precipitation in june, and average temperature in the warmest season made important contributions to the model and the PPR outbreak may be strongly related with these variables. In this study, PPR in Türkiye has been characterized significantly spatio-temporal and enviromental factors. In this context, the disease pattern and obtained these findings will contribute to policymakers in the prevention and control of the disease.

Indexed as

Disease OutbreaksGoat DiseasesGoatsPeste-des-Petits-RuminantsSheep DiseasesAnimalsCluster AnalysisEntropyGeographic Information SystemsPeste-des-petits-ruminants virusRetrospective StudiesSheepSpace-Time ClusteringSpatio-Temporal AnalysisTurkeyEnviromental factorsMaximum entropy model (Maxent)Peste des petits ruminantsSpace-time analysisSpatial epidemiology

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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.