Title :
Epidemiological modeling of bovine brucellosis in India
Author :
Kang, Gloria J. ; Gunaseelan, L. ; Abbas, Kaja M.
Author_Institution :
Dept. of Population Health Sci., Virginia Tech, Blacksburg, VA, USA
Abstract :
The study objective is to develop an epidemiological model of brucellosis transmission dynamics among cattle in India and to estimate the impact of different prevention and control strategies. The prevention and control strategies are test-and-slaughter, transmission rate reduction, and mass vaccination. We developed a mathematical model based on the susceptible-infectious-recovered epidemic model to simulate brucellosis transmission dynamics, calibrated to the endemically stable levels of bovine brucellosis prevalence of cattle in India. We analyzed the epidemiological benefit of different rates of reduced transmission and vaccination. Test-and-slaughter is an effective strategy for elimination and eradication of brucellosis, but socio-cultural constraints forbid culling of cattle in India. Reducing transmission rates lowered the endemically stable levels of brucellosis prevalence correspondingly. One-time vaccination lowered prevalence initially but increased with influx of new susceptible births. While this epidemiological model is a basic representation of brucellosis transmission dynamics in India and constrained by limitations in surveillance data, this study illustrates the comparative epidemiological impact of different bovine brucellosis prevention and control strategies.
Keywords :
diseases; epidemics; zoology; India; bovine brucellosis control strategies; bovine brucellosis prevalence; bovine brucellosis prevention; brucellosis transmission dynamics; cattle; epidemiological modeling; mass vaccination; socio-cultural constraints; susceptible-infectious-recovered epidemic model; test-and-slaughter; transmission rate reduction; Cows; Diseases; Mathematical model; Public healthcare; Sociology; Statistics; India; brucellosis; epidemiology; mathematical model; prevention and control strategies; vaccination;
Conference_Titel :
Big Data (Big Data), 2014 IEEE International Conference on
Conference_Location :
Washington, DC
DOI :
10.1109/BigData.2014.7004420