Fig 1.
Overview of the multi-layer network model with hybrid simulation.
SEIR (susceptible, exposed, infectious and recovered) and IWAN (indifferent, worried, afraid and numb) denote the states of the people inside a node. The nodes in the emotional contagion layer have more large-distance links than those in the disease transmission layer.
Fig 2.
Illustration of the concepts and structures in our model.
(a) Illustration of random network structure; (b) illustration of scale-free network structure; (c) illustration of SEIR (susceptible, exposed, infectious and recovered) model; (d) illustration of IWAN (indifferent, worried, afraid and numb) model. ‘+’ denotes increase and ‘-’ denotes decrease. Network visualization in (a) and (b) was done using the Pajek program for large network analysis [30].
Table 1.
Description of the notations used in our model.
Fig 3.
The cumulative number of infected persons in the cities of China.
(a) Guangzhou, (b) Nanjing, (c) Zhengzhou, (d) Changsha. Actual data are fitted onto the curve (red circles).
Table 2.
The peak of cumulative number of infected persons in the four cities of China: Guangzhou, Nanjing, Zhengzhou and Changsha.
Fig 4.
The suppression effect of emotional contagion.
(a) Guangzhou, China, (b) London, the UK and (c) New York, the US. The solid lines denote simulation results with the emotional contagion layer and the dotted lines denote results without the emotional contagion layer. Red circles denote the actual data.
Table 3.
The emotional contagion parameters in Guangzhou, London and New York.
The up arrow denotes that the higher the parameter is, the more effective the emotional contagion will be and vice versa. Here, wn and wm denote the weights of the number of new confirmed cases in the city and the panic messages received. And wc and t denote the weight and the threshold of the concern level.
Fig 5.
The sensitivity analysis of (a) wn, (b) wm and (c) wc in Guangzhou.