I investigate the prevalence of co-infection in a sample of ticks. My dataset contains an excess amount of zeros (269/286), and the result of my binomial logistic regression model is non-significant. I would be grateful if anyone can tell me why this excessive number of zeros is a problem? what happens when you have too many zeros? Why is the model no longer a good choice? In the end, I assume it means that the risk of infection can be underestimated and that I instead should use Zero-inflated negative binomial regression. I just would like to really understand what happens with the binomial logistic model when you have too many zeros before I move on.

I would really appreciate your help!

Kind regards/ Hanna