ArticleVeterinary world2023
Risk factors, logistic model, and vulnerability mapping of lumpy skin disease in livestock at the farm level in Indragiri Hulu District, Riau Province, Indonesia, in 2022.
Article in Veterinary world, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.
- A systematic review of epidemiological modelling in response to lumpy skin disease outbreaks.Frontiers in veterinary science · 2024Pooled it
- Knowledge mapping of risk mitigation measures against vector-borne diseases.EFSA journal. European Food Safety Authority · 2026Article
- Spatial epidemiology of lumpy skin disease outbreaks in Thailand: proximity patterns, case concentrations, spatio-temporal clusters, and interpolated case distribution.Frontiers in veterinary science · 2026Article
- Clinical and molecular description of natural infections with an Asian strain of lumpy skin disease virus in Bos indicus.Scientific reports · 2025Article
- Prevalence of lumpy skin disease and associated risk factors in beef cattle in Rembang Regency, Central Java, Indonesia.Veterinary world · 2025Article
- Investigating Transboundary Spread Patterns and Cluster Characteristics of Lumpy Skin Disease (LSD) Outbreaks in Asia: Levering the Outbreak Data (2019-2023) to Support the LSD Prevention and Control Strategies.Transboundary and emerging diseases · 2025Article
- Analysis of factors associated with the first lumpy skin disease outbreaks in naïve cattle herds in different regions of Thailand.Frontiers in veterinary science · 2024Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and Aim: Lumpy skin disease (LSD) is an emerging epidemic in livestock in Indonesia. It was first reported in the Indragiri Hulu Regency of Riau Province, which has more cases than the surrounding regencies. This study aimed to identify the risk factors and generate a logistic regression model and vulnerability map of LSD in the Indragiri Hulu Regency. Materials and Methods: We used a structured questionnaire to interview the case and control farm owners to evaluate the risk factors. We evaluated 244 samples, consisting of 122 case and control farm samples each. At the cattle farm level, the risk factor data related to LSD were analyzed using descriptive statistics, bivariate analysis with Chi-square, and odds ratio, while the logistic model was derived using multivariate logistic regression analysis. Using variables, such as the number of cases and risk factor variables included in the model logistic, and the temperature, humidity, and rainfall data from the Meteorology, Climatology, and Geophysical Agency, we analyzed the vulnerability map of LSD in the regency using scoring, weighting, and overlay methods. Results: Ten significant risk factors were associated with LSD occurrence. The LSD model obtained from the logistic regression analysis was LSD (Y) = -3.92095 + 1.13107 (number of cattle >3) + 1.50070 (grazing cattle together with other farmers' cattle) + 1.03500 (poor management of farm waste/dirt) + 2.49242 (presence of livestock collectors/traders near the farm location) + 1.40543 (introduction of new livestock) + 2.15196 (lack of vector control measures on the farm). The LSD vulnerability map indicated that the villages with high vulnerability levels were Rantau Bakung, Kuantan Babu, and Sungai Lala in the Rengat Barat, Rengat, and Sungai Lala subdistricts, respectively. Conclusion: We found 10 significant risk factors associated with LSD occurrence. The LSD model included the number of cattle (>3), cograzing with other farmers' cattle, poor management of farm waste/dirt, the presence of livestock collectors/traders near the farm, introduction of new livestock, and lack of vector control measures on the farm. The LSD vulnerability map indicated that villages with high vulnerability levels included Rantau Bakung in the Rengat Barat subdistrict, Kuantan Babu in the Rengat subdistrict, and Sungai Lala in the Sungai Lala subdistrict.
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