Abstract Migration can allow individuals to escape parasite infection, which can lead to a lower infection probability (prevalence) in a population and/or fewer parasites per individual (intensity). Because individuals with more parasites often have lower survival and/or fecundity, infection intensity shapes the life‐history trade‐offs determining when migration is favored as a strategy to escape infection. Yet, most theory relies on susceptible‐infected (SI) modeling frameworks, defining individuals as either healthy or infected, ignoring details of infection intensity. Here, we develop a novel modeling approach that captures infection intensity as a spectrum, and ask under what conditions migration evolves as function of how infection intensity changes over time. We show that relative timescales of migration and infection accumulation determine when migration is favored. We also find that population‐level heterogeneity in infection intensity can lead to partial migration, where less‐infected individuals migrate while more infected individuals remain resident. Our model is one of the first to consider how infection intensity can lead to migration. Our results frame migratory escape in light of infection intensity rather than prevalence, thus demonstrating that decreased infection intensity should be considered a benefit of migration, alongside other typical drivers of migration.
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Active Control and Sustained Oscillations in actSIS Epidemic Dynamics
An actively controlled Susceptible-Infected-Susceptible (actSIS) contagion model is presented for studying epidemic dynamics with continuous-time feedback control of infection rates. Our work is inspired by the observation that epidemics can be controlled through decentralized disease-control strategies such as quarantining, sheltering in place, social distancing, etc., where individuals can actively modify their contact rates in response to observations of the infection levels in the population. Accounting for a time lag in observations and categorizing individuals into distinct sub-populations based on their risk profiles, we show that the actSIS model manifests qualitatively different features as compared with the SIS model. In a homogeneous population of risk-averters, the endemic equilibrium is always reduced, although the transient infection level can overshoot or undershoot. In a homogeneous population of risk-tolerating individuals, the system exhibits bistability, which can also lead to reduced infection. For a heterogeneous population comprised of risk-tolerators and risk-averters, we prove conditions on model parameters for the existence of a Hopf bifurcation and sustained oscillations in the infected population.
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- Award ID(s):
- 1635056
- PAR ID:
- 10208274
- Date Published:
- Journal Name:
- 3rd IFAC Workshop on Cyber-Physical & Human Systems
- Page Range / eLocation ID:
- 1 - 6
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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