For that purpose, random seroprevalence datasets were generated, assuming independent viruses. Random data were always generated assuming that all individuals had an independent 0.5 probability of being seropositive for each pathogen. N F randomly generated risk factors were considered in the logistic regression for the two pathogens. By construction these factors have no effect (they are chosen independently of the serological status of the individuals) but from a theoretical point of view it is interesting to measure how their inclusion in the model can introduce biases depending on the approach.