SIR and SEIR Models Compare in Mpox Misinformation Study

Researchers Udoka Duruaku, Tawakalit Omolabake Agboola, and Oluwaseun Ajao conducted a proof-of-concept study to evaluate how classical epidemiological models capture the temporal dynamics of health misinformation on social media. Using the 2022 Mpox outbreak as a case study, the team compared the Susceptible-Infectious-Recovered (SIR) and adapted Susceptible-Exposed-Infectious-Recovered (SEIR) models. The study aimed to determine which compartmental framework better represents the spread of misinformation during a disease outbreak, treating the dissemination of false health information analogously to the spread of infectious diseases within communities.

The analysis utilized a publicly available dataset comprising 5,787 tweets collected between 7 and 13 July 2022. A significant limitation of this dataset is its narrow temporal window, with the vast majority of posts concentrated on a single day, 9 July 2022. Due to this concentrated activity and short observation period, the authors framed the work as an illustration of how compartmental models can be adapted to short-horizon social media bursts, rather than a definitive epidemiological characterisation of Mpox misinformation. This scope acknowledges that the findings are methodological insights rather than a comprehensive longitudinal analysis of the outbreak’s misinformation landscape.

The comparative analysis revealed distinct strengths for each model in capturing different phases of misinformation spread. The SIR model effectively captured the rapid initial dissemination patterns characteristic of viral misinformation spread. In contrast, the SEIR model more accurately represented the latency period between exposure and active sharing behaviour observed in social media contexts.

The authors discussed the sensitivity and identifiability limits of these parameters under the short observation window.

These findings contribute methodological insights for compartmental model selection in misinformation research. The authors motivate future work with larger, longitudinally collected datasets to overcome the limitations of the short-horizon data used in this proof-of-concept study.

The research underscores the challenges posed by the rapid dissemination of health misinformation through digital platforms to public health communication and response strategies.

Subject of Research: Comparison of SIR and SEIR epidemiological models for analyzing Mpox misinformation spread on social media

Article Title: Epidemiological models in health misinformation propagation of Mpox conversations

Article References: Duruaku, U., Agboola, T. O., & Ajao, O. (2026). Epidemiological models in health misinformation propagation of Mpox conversations. PLOS Digital Health, 5(11), e0001772. https://doi.org/10.1371/journal.pdig.0001772

Image Credits: AI Generated

DOI: 10.1371/journal.pdig.0001772

Keywords: Mpox, health misinformation, SIR model, SEIR model, social media, epidemiological models, proof-of-concept, temporal dynamics, viral spread, latency period, homogeneous mixing, parameter sensitivity, public health communication, digital platforms, compartmental models, outbreak response, information spread, short-horizon analysis, dataset analysis, methodological insights