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Trust, Risk Perception and the Infection Rate of Diseases: Evidence from COVID-19 in China

Previous studies have revealed factors altering responses to unexpected infectious diseases from medical, democratic and political dimensions. However, few studies concerning risk management have attempted to explore the factors affecting disease infection from the social dimension. Trust, which is one of the most important aspects in the social dimension, has an impact on people’s risk perception toward hazards and may also affect people’s risk perception toward infectious diseases, since they are also hazardous. Additionally, much research regarding medicine has demonstrated that risk perception toward diseases helps prevent people from being infected because it can promote responsible behaviors. In this sense, trust may alter the infection rate of diseases, so it needs to be investigated. To achieve this goal, this study uses the COVID-19 outbreak in China as an example and applies an original dataset including real-time big data, official data and survey data to demonstrate whether trust influences the infection rate of diseases. The analyses of a multilevel regression show three main results: 
 
1) trust in local government and media helps to reduce the infection rate of diseases; 
 
2) generalized trust promotes a higher infection rate rather than decreasing it; and 
 
3) the effects of different types of trust are either completely or partly mediated by risk perception toward diseases. 
 
The theoretical and practical implications of this study are expected to provide suggestions for improving the public health system in response to possible infectious diseases.