The theta parameter is not part of the main model parameters in glm.nb (as extracted by coef()) but it is treated as a nuisance parameter. However, the fitted model object contains the parameter estimate ($theta) and its standard error ($SE.theta). So you can easily employ a Wald confidence interval based on the asymptotic normal distribution (essentially +/- two standard errors).
library("MASS")
a <- glm.nb(Days ~ Eth + Sex, data = quine)
a$theta + qnorm(c(0.025, 0.975)) * a$SE.theta
## [1] 0.8872956 1.4555238