Parameter estimation for an eco-epidemiological model of Brown Ear tick (Rhipicephalus appendiculatus, Acari: Ixodidae) transmitted East Coast Fever in African livestock (Bollettino di zoologia agraria e bachicoltura, 2024)
An eco-epidemiological model of the dynamics of East Coast Fever (ECF) in East Africa caused by the protozoan parasite Theileria parva and vectored by the Brown Ear Tick Rhipicephalus appendiculatus Neumann (Acarina: Ixodidae) has been developed. In the compartment model, ticks are present either on-host or off-host and, in both cases, differ in their capacity to receive and transmit the disease agent. As a result, the ticks are assigned to four compartments, while cattle are assigned to compartments of a) susceptible, b) infected and infectious as well as c) recovered animals with immunity to the disease but the capacity to infect to ticks.This paper deals with parameter estimation of the eco-epidemiological model. For ticks, we estimated fecundity and mortality rates for populations with time invariant age structure, attachment and detachment rates. For cattle of primarily European breeds, we estimated fecundity and mortality rates in absence of disease agent. The attack rate of ticks on cattle density was represented by Monod's functional response that requires the estimation of the semi-saturation term. The transmission rate of parva from cattle to ticks, the rate of transmisston of the disease from ticks to cattle, the recovery rate of infected cattle, and the additional cattle mortality were also estimated on the basis of published literature information.A numerica! simulation is carried out to illustrate the dynamics resulting from the estimated parameters. The model satisfactorily represents the ECF epidemiology, adequately takes into account important components of more realistic and complex models, despite of model development on very restrictive assumptions, and serves as an entry point for model extensions. This can efficiently be done in an adaptive management framework.
Keywords: Theileria parva; Rhipicephalus appendiculatus; eco-epidemiology; disease transmission model; parameter estimation; numerical simulation