Serodynamics: a review of methods for epidemiological inference using serological data

Abstract

The availability and diversity of serological data measuring antibody responses to infectious pathogens, accelerated in response to the SARS-CoV-2 pandemic, has enabled key insights into infectious disease dynamics and population health. Here, we present a review of analytical approaches and considerations for inference using serological data, highlighting the range of epidemiological and biological insights that are possible using appropriate mathematical and statistical models. This in-depth review focuses on methods to understand transmission dynamics and infer past exposures from serological data, referred to as serodynamics, though we note that such analyses often address complementary immunological questions. We first discuss key considerations for data processing and interpretation of raw serological data which are prerequisite for fitting serodynamical models. We then review a range of approaches for estimating epidemiological trends, ranging from classical serocatalytic models applied to binary serostatus data, to contemporary methods using full quantitative antibody measurements and immunological understanding to estimate if and when individuals have been previously infected. Here, we collate and synthesize these approaches within the context of a unifying framework for the overall data-generation process, consisting of key concepts including antibody kinetics, quantitative models to represent within-host and epidemic processes, and considerations for linking observed serological data to models. We close with a discussion of the types of methodological developments needed to meet the increasingly complex serological data becoming available that provide new avenues for scientific discovery and public health insights.

The re-emergence of sexually transmissible multidrug resistant Shigella flexneri 3a, England, United Kingdom

“…36 NFDS is a type of natural selection, where the advantageous nature of a bene cial mutation or acquired gene diminishes over time, as the trait becomes more common in a population; particularly in the case of bacterial interactions with the human immune system, as a speci c antigen becoming more common in a population of bacteria means that a greater proportion of human hosts will produce antibodies, which is especially noteworthy in interconnected sexual networks of MSM at a higher risk of shigellosis. Further research involving mathematical modelling and immunological studies (the usefulness of these reviewed elsewhere 37 ) are needed to elucidate the role of immunity and NFDS in the re-emergence of S. exneri 3a and other serotypes and species of S. exneri and Shigella, respectively.…”

Evaluating Scope and Bias of Population-Level Measles Serosurveys: A Systematized Review and Bias Assessment

“…As such, seroprevalence data can be used as tools to guide decisions to and strengthen immunization programs, as inputs to dynamic models of disease transmission, and, additionally, to provide insights into vaccine field effectiveness and for the assessment of case ascertainment rates [ 7 , 8 ]. The interpretation of seroprevalence data is complicated, however, because of the potential for bias.…”