Development of a computer simulation model for anaplasmosis with emphasis on the Caribbean

Abstract

Anaplasmosis continues to be an enigma in the Caribbean region causing high economic losses in animal production. Since the epidemiology of this vector-borne disease is quite complex, and since an effective and rationally designed approach to its control is still unclear, it was felt that developing an epidemiologic model using computer simulation models will be useful to shed more light in this area. To represent the epidemiology of anaplasmosis, an epidemiologic simulation model which portrays realistic trends of disease dynamics has been developed. Due to the high economic losses in animal production and the complexity of controlling the disease, the model serves as tool to better understand the complex epidemiology of anaplasmosis. Additionally, the model provides decision makers with a tool to be used to evaluate various anaplasmosis control alternative for rational planning and allocation of funds. The development of the model was based on developing : an epidemiologic knowledge-base for anaplasmosis ; a conceptual model for the cattle and tick subpopulations, a systems analysis model for the cattle and tick subpopulations, a mathematical model; a computer simulation model; testing the computer simulation model and using the model to evaluate Anaplasma control alternatives. The knowledge-base was developed using the Epidemiologic Problem Oriented Approach (EPOA) to collect and compile the information into a condensed, but systematic epidemiologic knowledge-base of anaplasmosis. The information on anaplasmosis was retrieved from : selected textbooks of veterinary medicine ; current journals ; papers and questionnaires filled by Caribbean veterinarians. The epidemiologic information was presented using flowchart diagrams to conceptualize the detailed epidemiology of the disease. At the same time, it displays the fundamental parts of the anaplasmosis system to better describe and analyze the disease. Systems analysis diagrams were also used to relate the health states to specific rates which were described and defined by differential equations based on classical mass action theory. All states equations are approximated using Euler’s integration method. In this way, the dynamics of the disease was revealed. These diagrams provided the framework on which the model was built. Testing of the model shows that it is stable. Trends which were biologically sound and reasonable were displayed. The model was then used to evaluate disease patterns and various control alternatives of anaplasmosis. Disease patterns observed included: cattle and tick populations patterns with and without disease; disease dynamics when disease was introduced via infective cattle and infectious ticks. The control alternative tested were: effects of various levels of acaricides on tick population and disease dynamics; the influence of genetics on the incidence of the disease; the effects of various levels of antibiotics on disease dynamics when disease was introduced via infective cattle and infectious ticks. The computer simulation model needs systematic testing and validation to observe its sensitivity to filed conditions.