Local historical experience in public health emergencies has been perceived to largely affect COVID-19’s social influence. Specifically, individuals’ personal experience in public health emergencies would likely have an impact on their reactions to the next similar event. Herein, we combined life course and risk analysis frameworks to explore how individuals’ experiences influence current risk perception and protective behaviors. We collected 1000 questionnaires of random network samples in six Chinese provinces of different risk levels from 29 April to 8 May 2020, and used the propensity score matching (PSM) model and multivariable linear regression to process the data. We categorized individual public emergency experience into three patterns: (1) having ever witnessed a public health emergency, (2) having ever experienced a public health emergency, and (3) currently experiencing a public health emergency. The study indicates that individuals’ experiences had significant positive effects on protective behaviors against COVID-19. The average effects of the three patterns on behaviors were 0.371 (p < 0.001), 0.898 (p < 0.001) and 0.319 (p < 0.05), respectively. The study also shows that for those experiencing any one pattern, the effect of risk perception on protective behaviors appeared null in the early stage of the pandemic. We propose the potential interactive mechanism of risk factors in the life course at the individual level. Academically, this study develops the risk theory of perception and behavior and expands the application of the life course approach in the public health arena. Practically, our research indicates that public health emergency experiences are valuable for responding to a future pandemic and normalizing prevention policies.

Social resilience for public health is a new theoretical framework for understanding public health risk governance capacity. This study identifies 18 indicators from the publicly available database and adopts the method of multivariable analysis to evaluate the level of social resilience for public health in 73 countries along the Belt and Road Initiative (BRI). The study finds that the main influencing factors of social resilience for public health are institutional resilience, physical resilience, and participation resilience. The capacity of public health risk governance in countries along the BRI is classified into three levels: high, medium, and low. A high level of public health risk governance capacity is mainly shown in developed European countries such as Italy, rich Southwestern Asian countries such as the United Arab Emirates, and East Asian countries represented by Japan, South Korea, and Singapore. The middle-level countries are mainly distributed at the junction of Eurasia, which Russia represents. The low-level countries are primarily distributed in South Asia, Africa, and the war zones. In general, countries along the BRI have polarized the capacity of public health risk governance and structural inequalities, mainly manifested in large differences in the organizational capacity and mobilization capacity between countries in response to public health risk events, and the gap between the rich and the poor within a country. Under such circumstances, the building of a Community of Common Health is required to be accelerated.

The application of caring robots is currently a widely accepted solution to the problem of aging. However, for the elderly groups who live in gregarious residences and share intelligence devices, caring robots will cause intimacy and assistance dilemmas in the relationship between humans and non-human agencies. This is an information-assisted machine setting, with resulting design ethics issues brought about by the binary values of human and machine, body and mind. The “vulnerability” in risk ethics demonstrates that the ethical problems of human institutions stem from the increase of dependence and the obstruction of intimacy, which are essentially caused by the increased degree of ethical risk exposure and the restriction of agency. Based on value-sensitive design, caring ethics and machine ethics, this paper proposes a flexible design with the interaction-distance-oriented concept, and reprograms the ethical design of caring robots with intentional distance, representational distance and interpretive distance as indicators. The main purpose is to advocate a new type of human-machine interaction relationship emphasizing diversity and physical interaction.

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