Using data and modelling to better understand how ASF spreads and how it can be controlled more effectively.
Outbreak patterns of African swine fever virus are varying depending on local conditions, and the disease does not follow a single pattern of spread. Instead, transmission is shaped by a combination of factors, including farming systems, wild boar populations, environmental conditions, and human activities.
To better understand these dynamics, VAX4ASF is developing modelling tools that analyse how the virus may move across different farming settings and wild boar populations. These approaches integrate available data—such as outbreak records, and the geographical and temporal distribution of wild boars and different types of pig production systems (e.g. small holders and commercial farms) —to provide a clearer picture of how ASF spreads under different conditions.
This work helps identify key factors that influence transmission, supporting a more informed interpretation of spread patterns across regions.
Supporting informed decision-making
One of the strengths of modelling is its ability to explore different scenarios in a structured and risk-free way. Modelling tools are used to examine how different control approaches might influence the evolution of ASF outbreaks. Rather than testing measures directly in the field, these simulations allow researchers to explore potential outcomes under a range of scenarios.
The project supports a broader understanding of how vaccination could complement existing control measures in different environments.
These scenarios may include variations in surveillance intensity, biosecurity measures, or possible vaccination approaches. The goal is not to prescribe a single solution, but to provide a scientific basis that can support decision-makers when designing control strategies adapted to specific contexts.
Preparing the ground for future vaccination strategies
As research progresses towards new ASF vaccine candidates within VAX4ASF, it becomes essential to consider how such tools could be implemented in practice.
Modelling activities within VAX4ASF contribute to this by exploring how different future vaccination scenarios may interact with disease dynamics. This includes considering broader aspects such as timing, geographical targeting, and population coverage, without focusing on specific products or technical details.
For wild boar populations, these considerations are particularly important, as disease management must consider ecological factors and animal behaviour. The project therefore supports a broader understanding of how vaccination could complement existing control measures in different environments.
Enhancing surveillance approaches
Effective surveillance is key to controlling ASF. Detecting the virus early allows authorities to respond quickly and limit its spread.
Building on this, risk-based surveillance approaches help optimise how and where monitoring activities are carried out. These approaches consider factors such as local risk levels, population characteristics, and available diagnostic tools.
These activities are closely connected with stakeholder engagement efforts within the project, ensuring that proposed approaches are both scientifically sound and practically relevant.
As new tools such as DIVA (Differentiating Infected from Vaccinated Animals) tests currently under developing within the project, surveillance strategies will also need to evolve. Modelling helps anticipate these changes, ensuring that monitoring systems remain robust and fit for purpose.
From science to policy support
The insights generated go beyond scientific analysis. They are designed to inform practical discussions with policymakers, veterinary authorities, and other stakeholders involved in ASF management.
By translating complex data into accessible insights, VAX4ASF contributes to evidence-based decision-making. This supports the development of coordinated and effective strategies aligned with European and international animal health frameworks.
Importantly, these activities are closely connected with stakeholder engagement efforts within the project, ensuring that proposed approaches are both scientifically sound and practically relevant.
Towards smarter ASF management
ASF control remains a challenge, and therefore there is a need for extending the tools used to control it. Through the integration of epidemiology, modelling, and collaboration, VAX4ASF is contributing to a more adaptive and informed response to the disease. Smart surveillance based on data, analysis, and cooperation offers a pathway towards more effective prevention and control. By strengthening our ability to understand and anticipate ASF dynamics, these approaches potentially support a more resilient and sustainable future for pig farming.