TY - JOUR
T1 - Spontaneous social distancing in response to a simulated epidemic
T2 - a virtual experiment
AU - Kleczkowski, Adam
AU - Maharaj, Savi
AU - Rasmussen, Susan
AU - Williams, Lynn
AU - Cairns, Nicole
PY - 2015/9/28
Y1 - 2015/9/28
N2 - Studies of social distancing during epidemics have found that the strength of the response can have a decisive impact on the outcome. In previous work we developed a model of social distancing driven by individuals’ risk attitude, a parameter which determines the extent to which social contacts are reduced in response to a given infection level. We showed by simulation that a strong response, driven by a highly cautious risk attitude, can quickly suppress an epidemic. However, a moderately cautious risk attitude gives weak control and, by prolonging the epidemic with out reducing its impact, may yield a worse outcome than doing nothing. In real societies, social distancing may arise spontaneously from individual choices rather than being imposed centrally. There is little data available about this as opportunistic data collection during epidemics is difficult. Our study uses a simulated epidemic in a computer game setting to measure the social distancing response.
AB - Studies of social distancing during epidemics have found that the strength of the response can have a decisive impact on the outcome. In previous work we developed a model of social distancing driven by individuals’ risk attitude, a parameter which determines the extent to which social contacts are reduced in response to a given infection level. We showed by simulation that a strong response, driven by a highly cautious risk attitude, can quickly suppress an epidemic. However, a moderately cautious risk attitude gives weak control and, by prolonging the epidemic with out reducing its impact, may yield a worse outcome than doing nothing. In real societies, social distancing may arise spontaneously from individual choices rather than being imposed centrally. There is little data available about this as opportunistic data collection during epidemics is difficult. Our study uses a simulated epidemic in a computer game setting to measure the social distancing response.
KW - epidemics
KW - social distancing
KW - agent based models
KW - participatory simulation
KW - virtual experiments
UR - http://www.biomedcentral.com/bmcpublichealth
UR - http://www.biomedcentral.com/1471-2458/15/973
U2 - 10.1186/s12889-015-2336-7
DO - 10.1186/s12889-015-2336-7
M3 - Article
SN - 1471-2458
VL - 15
JO - BMC Public Health
JF - BMC Public Health
M1 - 973
ER -