The ecology of infectious disease in wildlife has become a pivotal theme in animal and public health. Studies of infectious disease ecology rely on robust surveillance of pathogens in reservoir hosts, often based on serology, which is the detection of specific antibodies in the blood and is used to infer infection history. However, serological data can be inaccurate for inference to infection history for a variety of reasons. Two major aspects in any serological test can substantially impact results and interpretation of antibody prevalence data: cross-reactivity and cut-off thresholds used to discriminate positive and negative reactions. Given the ubiquitous use of serology as a tool for surveillance and epidemiological modeling of wildlife diseases, it is imperative to consider the strengths and limitations of serological test methodologies and interpretation of results, particularly when using data that may affect management and policy for the prevention and control of infectious diseases in wildlife. Greater consideration of population age structure and cohort representation, serological test suitability and standardized sample collection protocols can ensure that reliable data are obtained for downstream modeling applications to characterize, and evaluate interventions for, wildlife disease systems.