The application of System Dynamics Modelling approach to understand the
brucellosis transmission system
Background: Brucella transmission is a complex multisector system. A
better understanding of transmission dynamics helps pinpoint the most
effective interventions to reduce human cases. Modelling methodologies
have not been applied extensively to brucellosis. This paper applies
System Dynamics Modelling to identify the interplay between the
different sectors that drive disease transmission and suggest and assess
scenarios to control brucellosis. Methods: The study applied a
qualitative in-depth analysis of Brucella transmission system in Jordan.
Current published literature, government and policy documents were
reviewed supplemented by interviews with stakeholders. Data were
analysed manually to establish causal pathways to develop a Stock and
Flow (SF) model. The structure was examined and reviewed by key
informants. Several scenarios to control Brucella transmission were
assessed. Results: The model demonstrated the complex interaction of
different sectors that drove transmission. Brucella transmission among
sheep and between farms and markets are the main drivers of human
incidence. Farmers’ visits to veterinary clinics are a critical
intervention point for control regarding access to vaccination.
Vaccination by itself might not be efficient due to the low compliance
of farmers. Test and cull sheep is the most efficient control strategy.
Conclusions: The synthesis of the current knowledge through the model
enabled better understanding, visualisation and interpretation of the
sectors involved in Brucella transmission. The model highlighted
specific leverage points at which the transmission could be controlled
like encouraging visits to the veterinary clinics. There is a strong
synergy between sectors, therefore, a greater control might be produced
by utilising multi-sectoral relationships embedded in the system. This
application of System Dynamics Approach to understand disease
transmission systems can be used to complement other methods and detect
leverage points for disease control.