Improved susceptible–infectious–susceptible epidemic equations based on uncertainties and autocorrelation functions

2020/02/01 by Gilberto M. Nakamura, George C. Cardoso, Alexandre Souto Martinêz · 1 citation
Medicine · Mathematics · Biochemistry, Genetics and Molecular Biology · #Mathematical and Theoretical Epidemiology and Ecology Models #COVID-19 epidemiological studies #Evolution and Genetic Dynamics

paper · doi:10.1098/rsos.191504

openalex publication_date 2020/02/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01

Abstract

Compartmental equations are primary tools in the study of disease spreading processes. They provide accurate predictions for large populations but poor results whenever the integer nature of the number of agents is evident. In the latter instance, uncertainties are relevant factors for pathogen transmission. Starting from the agent-based approach, we investigate the role of uncertainties and autocorrelation functions in the susceptible-infectious-susceptible (SIS) epidemic model, including their relationship with epidemiological variables. We find new differential equations that take uncertainties into account. The findings provide improved equations, offering new insights on disease spreading processes.

Citations

• Epidemic Spreading in Scale-Free Networks
• A general method for numerically simulating the stochastic time evolution of coupled chemical reactions
• Shot Noise in Mesoscopic Conductors
• Statistical mechanics of complex networks
• A contribution to the mathematical theory of epidemics
• The Structure and Function of Complex Networks
• The N-intertwined SIS epidemic network model

Cited by

• Compartmental models (epidemiology) [wikipedia]

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