The effect of official intervention on reducing the use of potentially discriminatory language during the COVID-19 pandemic in China

The COVID-19 pandemic underscored the importance of effective public health crisis management, including addressing the social stigma directed toward the source of the outbreak. Social stigma, prejudice, and discriminatory remarks can undermine transparency and hinder disease control efforts. Historical examples, such as the Spanish Flu and Ebola, demonstrate the harmful consequences of stigmatizing disease outbreaks. The World Health Organization (WHO) emphasizes the role of governments, citizens, and media in preventing such stigma. This study focuses on official intervention in China, utilizing the Baidu Index—a large-scale dataset reflecting internet search behavior—to examine changes in the use of potentially discriminatory language (e.g., "Wuhan pneumonia") following the official naming of the virus. The analysis investigates the impact of government intervention, the evolution of discriminatory language use over time, and the influence of socioeconomic factors on this phenomenon. The study aims to offer strategies for mitigating social stigma during future infectious disease outbreaks.

Existing literature highlights the significant impact of social stigma on infectious disease prevention and control. The WHO defines social stigma in this context as the labeling, stereotyping, or isolation of individuals or regions affected by an outbreak. This can lead to discrimination and isolation, hindering efforts to contain the disease. Studies have shown that social stigma can deter individuals from seeking medical care, leading to delayed treatment and increased mortality. The naming of diseases has also been implicated in the perpetuation of stigma, with names that associate a disease with a specific geographic location or group often resulting in discrimination. Conversely, research suggests that official interventions and public health campaigns can play a vital role in reducing stigma by promoting awareness, combating misinformation, and emphasizing empathy and compassion.

This study leveraged the Baidu Index, China's dominant search engine, to analyze internet search behavior related to the COVID-19 outbreak. The researchers focused on the keywords "Wuhan pneumonia" (considered potentially discriminatory) and "novel coronavirus pneumonia" (considered neutral). The study period spanned three weeks, from January 19 to February 8, 2020, encompassing key events such as the Wuhan lockdown and the official naming of the virus. The researchers calculated a daily "discrimination index" by dividing the search volume for "Wuhan pneumonia" by the combined search volume for both keywords. This index served as the dependent variable in subsequent analyses. To investigate the influence of socioeconomic factors, the researchers collected data on various variables at the provincial level, including population density, GDP, CPI, unemployment rate, fiscal expenditure, education levels, and internet penetration rate. The study employed both temporal and regional analysis to track the evolution of the discrimination index over time and across different provinces. Regression analysis was used to examine the relationship between the discrimination index and the socioeconomic factors. A panel data approach was used to account for potential confounding effects and to assess the impact of official interventions.

The study found a strong correlation between official intervention and a decrease in the use of potentially discriminatory language in internet searches. After the official naming of the virus as COVID-19 on February 12, 2020, and subsequent government communications emphasizing the avoidance of discriminatory language, there was a significant drop in the discrimination index. The analysis revealed regional variations in the use of discriminatory language. Provinces with higher levels of socioeconomic development and population density initially exhibited higher levels of discriminatory language. However, this relationship weakened considerably after official intervention. Furthermore, the study found that regions with lower CPI and unemployment rates showed less discriminatory language initially but this difference diminished after intervention. The regression analysis showed that official intervention, measured by the number of official social media posts, had a significant positive impact on reducing the discrimination index. Socioeconomic factors, such as GDP and education levels, were positively associated with discriminatory language use in the initial stages of the outbreak, but this relationship disappeared after official intervention. The analysis of media coverage revealed that official media outlets were more cautious in their use of potentially discriminatory language compared to other media platforms.

The findings demonstrate the effectiveness of official intervention in mitigating social stigma associated with the COVID-19 outbreak in China. The rapid decline in discriminatory language use after the official naming of the virus and government communication highlights the importance of clear, timely, and consistent messaging from authorities. The weakening of the relationship between socioeconomic factors and discriminatory language after intervention suggests that official campaigns can overcome existing inequalities and biases. The study also underlines the role of media in shaping public perception and the need for responsible reporting during public health crises. The limitations of this study should be considered, including the focus on internet search behavior as a proxy for actual discriminatory attitudes and behaviors. Future research could explore other indicators of social stigma and investigate the long-term impact of official interventions.

This study highlights the crucial role of official intervention in mitigating the spread of discriminatory language during public health crises. The findings underscore the importance of early and consistent official communication, emphasizing the need to avoid stigmatizing language and promote accurate information. Further research could explore the effectiveness of different communication strategies, investigate cross-cultural comparisons, and consider other methods for measuring social stigma.

The study relies on internet search data as a proxy for actual discriminatory attitudes and behaviors. The Baidu Index may not fully capture the diversity of online and offline expressions of stigma. The study is limited to the context of China and its findings may not be generalizable to other countries or cultures. Further research is needed to explore the long-term impact of official interventions on social stigma.