The behavioural spillover effect: modelling behavioural interdependencies in multi-pathogen dynamics.

Publication date: Dec 31, 2026

During the recent pandemic, a rise in COVID-19 cases was followed by a decline in influenza. In the absence of cross-immunity, a potential explanation for the observed pattern is behavioural: non-pharmaceutical interventions (NPIs) designed and promoted for one disease also reduce the spread of others. We study short-term and long-term dynamics of two pathogens where NPIs targeting one pathogen indirectly influence the spread of another – a phenomenon we term behavioural spillover. We examine how perceived risk of and response to one disease substantially alter the spread of other pathogens, revealing how waves of different pathogens emerge over time as a result of behavioural interdependencies and human response. Our analysis identifies the parameter space where two diseases simultaneously co-exist, and where shifts in prevalence occur. Our findings are consistent with observations from the COVID-19 pandemic, where NPIs contributed to significant declines in infections such as influenza, pneumonia, and Lyme disease.

Concepts Keywords
Covid 92-10
Decline 92D30
Pathogens Behavior
Pneumonia COVID-19
Promoted Epidemic models
equilibria analysis
Humans
identifiability
Influenza, Human
Models, Biological
Pandemics
Pneumonia, Viral
risk response
SARS-CoV-2

Semantics

Type Source Name
disease MESH COVID-19
disease MESH influenza
disease MESH infections
disease MESH pneumonia
disease MESH Lyme disease
disease MESH Pneumonia Viral

Original Article

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