Over the next century, human population growth and consequent interactions with wildlife are expected to escalate the frequency of viral zoonotic transmission. Consequently, proactive measures preparing for the emergence of novel viral pathogens have become prudent. Effective combat against a novel virus is often hindered by a lack of knowledge regarding the duration of protective immunity— information that is essential to modeling and dictates both short- and long-term policy responses. Estimation of the durability of immunity would classically be presumed to require multi-year, long-term studies. However, the COVID-19 pandemic highlighted the pyrrhic consequences of waiting out the extensive timeline required for traditional data collection to obtain vital policy-relevant information. Here we demonstrate the robust viability of leveraging evolutionary approaches with long-term infection and antibody data in response to current human-infecting or animal-infecting viruses. Using this approach we estimate infection probabilities in relation to antibody declines and translate these probabilities into inferred times to reinfection and durabilities of immunity against SARS-CoV-2. We further demonstrate that this approach can be extended to estimate distribution of likely times to breakthrough infection following vaccination against SARS-CoV-2 as well as the probability of breakthrough infection under alternate mRNA booster vaccination schedules for individuals with atypical immune statuses. These results demonstrate the utility of comparative phylogenetic methods in providing a quantitative basis for otherwise unknown parameters that are fundamental to personal, clinical, and public health policy decision-making.