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Epidemiological Risk Factors and Modelling Approaches for Risk Assessment of Lumpy Skin Disease Virus Introduction
Kei Owada1, Timothy J Mahony2, Rebecca K Ambrose3
1Queensland Alliance for One Health Sciences, School of Veterinary Science, The University of Queensland, Gatton 4343, Australia.
Lumpy skin disease (LSD) is a growing threat to Australia. This review evaluated LSDV models, identifying risk factors for spread and control strategies, highlighting a need for Australia-specific geospatial models.
Area of Science:
- Veterinary Epidemiology
- Disease Modelling
- Risk Assessment
Background:
- Lumpy skin disease (LSD) is a significant vector-borne threat caused by the lumpy skin disease virus (LSDV).
- LSDV is spreading through Asia, posing a substantial risk to Australia's cattle industry, despite not yet occurring in the country.
- Geospatial decision support tools are crucial for assessing and managing LSDV risks.
Purpose of the Study:
- To evaluate existing LSDV epidemiological models.
- To identify key risk factors for LSDV introduction and spread.
- To consider control strategies for LSDV, informing risk-based surveillance design for Australia.
Main Methods:
- A comprehensive literature review was conducted following PRISMA guidelines.
- PICO methodology was used to formulate search terms across four databases.
- 68 articles were included, extracting data on model structure, parameterization, risk factors, and control strategies.
Main Results:
- Key LSDV transmission risk factors include airborne vector movement (e.g., stable flies) and cattle movement.
- LSDV spread is influenced by environmental factors, weather, and livestock/vector populations.
- Most existing models focus on LSDV transmission mechanisms or spread in endemic regions; few address introduction risks in LSD-free countries, and none explore spread post-introduction or geospatial suitability for incursions.
Conclusions:
- There is a significant gap in the literature regarding LSDV spread and geospatial modeling in LSD-free countries like Australia.
- Existing models primarily focus on endemic settings and lack Australia-specific risk factor analysis.
- Developing Australia-specific geospatial models incorporating identified risk factors is essential for effective, risk-based surveillance.
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