Limits...
Coupled contagion dynamics of fear and disease: mathematical and computational explorations.

Epstein JM, Parker J, Cummings D, Hammond RA - PLoS ONE (2008)

Bottom Line: In classical mathematical epidemiology, individuals do not adapt their contact behavior during epidemics.They do not endogenously engage, for example, in social distancing based on fear.Our main point is that behavioral adaptation of some sort must be considered.

View Article: PubMed Central - PubMed

Affiliation: Center on Social and Economic Dynamics, The Brookings Institution, Washington DC, United States of America. jepstein@brookings.edu

ABSTRACT

Background: In classical mathematical epidemiology, individuals do not adapt their contact behavior during epidemics. They do not endogenously engage, for example, in social distancing based on fear. Yet, adaptive behavior is well-documented in true epidemics. We explore the effect of including such behavior in models of epidemic dynamics.

Methodology/principal findings: Using both nonlinear dynamical systems and agent-based computation, we model two interacting contagion processes: one of disease and one of fear of the disease. Individuals can "contract" fear through contact with individuals who are infected with the disease (the sick), infected with fear only (the scared), and infected with both fear and disease (the sick and scared). Scared individuals--whether sick or not--may remove themselves from circulation with some probability, which affects the contact dynamic, and thus the disease epidemic proper. If we allow individuals to recover from fear and return to circulation, the coupled dynamics become quite rich, and can include multiple waves of infection. We also study flight as a behavioral response.

Conclusions/significance: In a spatially extended setting, even relatively small levels of fear-inspired flight can have a dramatic impact on spatio-temporal epidemic dynamics. Self-isolation and spatial flight are only two of many possible actions that fear-infected individuals may take. Our main point is that behavioral adaptation of some sort must be considered.

Show MeSH

Related in: MedlinePlus

The percentage of runs (out of 30) for each parameter setting in which the epidemic spreads fully across the landscape, from an index case in one corner of the lattice all the way to the opposite corner.
© Copyright Policy
Related In: Results  -  Collection


getmorefigures.php?uid=PMC2596968&req=5

pone-0003955-g007: The percentage of runs (out of 30) for each parameter setting in which the epidemic spreads fully across the landscape, from an index case in one corner of the lattice all the way to the opposite corner.

Mentions: Not only does flight increase incidence dramatically, but it also increases the rapidity and geographic scope of the epidemic. One way to measure the geographic spread of the bug is to begin the epidemic with an index case in one corner of the 2D lattice, and observe if and when the bug reaches the far diagonal corner. Figure 7 shows that epidemics rarely spread fully across the lattice with no flight—but almost always spread fully across the lattice with even a small amount of flight. Specifically, when merely 10% flee, the epidemic reaches the far corner an average of 92% of the time. However, when no agents flee, the epidemic only reaches the far corner 17% (all hiders) or 27% (90% hide / 10% ignore) of the time.


Coupled contagion dynamics of fear and disease: mathematical and computational explorations.

Epstein JM, Parker J, Cummings D, Hammond RA - PLoS ONE (2008)

The percentage of runs (out of 30) for each parameter setting in which the epidemic spreads fully across the landscape, from an index case in one corner of the lattice all the way to the opposite corner.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2596968&req=5

pone-0003955-g007: The percentage of runs (out of 30) for each parameter setting in which the epidemic spreads fully across the landscape, from an index case in one corner of the lattice all the way to the opposite corner.
Mentions: Not only does flight increase incidence dramatically, but it also increases the rapidity and geographic scope of the epidemic. One way to measure the geographic spread of the bug is to begin the epidemic with an index case in one corner of the 2D lattice, and observe if and when the bug reaches the far diagonal corner. Figure 7 shows that epidemics rarely spread fully across the lattice with no flight—but almost always spread fully across the lattice with even a small amount of flight. Specifically, when merely 10% flee, the epidemic reaches the far corner an average of 92% of the time. However, when no agents flee, the epidemic only reaches the far corner 17% (all hiders) or 27% (90% hide / 10% ignore) of the time.

Bottom Line: In classical mathematical epidemiology, individuals do not adapt their contact behavior during epidemics.They do not endogenously engage, for example, in social distancing based on fear.Our main point is that behavioral adaptation of some sort must be considered.

View Article: PubMed Central - PubMed

Affiliation: Center on Social and Economic Dynamics, The Brookings Institution, Washington DC, United States of America. jepstein@brookings.edu

ABSTRACT

Background: In classical mathematical epidemiology, individuals do not adapt their contact behavior during epidemics. They do not endogenously engage, for example, in social distancing based on fear. Yet, adaptive behavior is well-documented in true epidemics. We explore the effect of including such behavior in models of epidemic dynamics.

Methodology/principal findings: Using both nonlinear dynamical systems and agent-based computation, we model two interacting contagion processes: one of disease and one of fear of the disease. Individuals can "contract" fear through contact with individuals who are infected with the disease (the sick), infected with fear only (the scared), and infected with both fear and disease (the sick and scared). Scared individuals--whether sick or not--may remove themselves from circulation with some probability, which affects the contact dynamic, and thus the disease epidemic proper. If we allow individuals to recover from fear and return to circulation, the coupled dynamics become quite rich, and can include multiple waves of infection. We also study flight as a behavioral response.

Conclusions/significance: In a spatially extended setting, even relatively small levels of fear-inspired flight can have a dramatic impact on spatio-temporal epidemic dynamics. Self-isolation and spatial flight are only two of many possible actions that fear-infected individuals may take. Our main point is that behavioral adaptation of some sort must be considered.

Show MeSH
Related in: MedlinePlus