Social inequality and cultural factors impact the awareness and reaction during the cryptic transmission period of pandemic

The World Health Organization (WHO) declared the COVID-19 outbreak a Public Health Emergency of International Concern on 2020 January 31. However, rumors of a "mysterious virus" had already been circulating in China in 2019 December, possibly preceding the first confirmed COVID-19 case. Understanding how awareness about an emerging pandemic spreads through society is vital not only for enhancing disease surveillance, but also for mitigating demand shocks and social inequities, such as shortages of personal protective equipment and essential supplies. Here we leverage a massive e-commerce dataset comprising 150 billion online queries and purchase records from 94 million people to detect the traces of early awareness and public response during the cryptic transmission period of COVID-19. Our analysis focuses on identifying information gaps across different demographic cohorts, revealing significant social inequities and the role of cultural factors in shaping awareness diffusion and response behaviors. By modeling awareness diffusion in heterogeneous social networks and analyzing online shopping behavior, we uncover the evolving characteristics of vulnerable populations. Our findings expand the theoretical understanding of awareness spread and social inequality in the early stages of a pandemic, highlighting the critical importance of e-commerce data and social network data in effectively and timely addressing future pandemic challenges. We also provide actionable recommendations to better manage and mitigate dynamic social inequalities in public health crises.

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Publication Details

Journal
PNAS Nexus
Published
2025-02-01
DOI
https://doi.org/10.1093/pnasnexus/pgaf043
Citations
1
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
1.37

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article

Social inequality and cultural factors impact the awareness and reaction during the cryptic transmission period of pandemic

Zhuoren Jiang, Yangyang Kang, Yong‐Yeol Ahn, Johan Bollen et al.
1 citations
PNAS Nexus
COVID-19 epidemiological studies
1.37
article

Social inequality and cultural factors impact the awareness and reaction during the cryptic transmission period of pandemic

Zhuoren Jiang, Yangyang Kang, Yong‐Yeol Ahn, Johan Bollen, Xiaozhong Liu, Changlong Sun
article en
1 citations

Abstract

The World Health Organization (WHO) declared the COVID-19 outbreak a Public Health Emergency of International Concern on 2020 January 31. However, rumors of a "mysterious virus" had already been circulating in China in 2019 December, possibly preceding the first confirmed COVID-19 case. Understanding how awareness about an emerging pandemic spreads through society is vital not only for enhancing disease surveillance, but also for mitigating demand shocks and social inequities, such as shortages of personal protective equipment and essential supplies. Here we leverage a massive e-commerce dataset comprising 150 billion online queries and purchase records from 94 million people to detect the traces of early awareness and public response during the cryptic transmission period of COVID-19. Our analysis focuses on identifying information gaps across different demographic cohorts, revealing significant social inequities and the role of cultural factors in shaping awareness diffusion and response behaviors. By modeling awareness diffusion in heterogeneous social networks and analyzing online shopping behavior, we uncover the evolving characteristics of vulnerable populations. Our findings expand the theoretical understanding of awareness spread and social inequality in the early stages of a pandemic, highlighting the critical importance of e-commerce data and social network data in effectively and timely addressing future pandemic challenges. We also provide actionable recommendations to better manage and mitigate dynamic social inequalities in public health crises.

PNAS NexusVol. 4(2)
Worcester Polytechnic Institute (US), Indiana University Bloomington (US), Alibaba Group (China) (CN), Zhejiang University (CN)
National Science Foundation, National Natural Science Foundation of China, Defense Advanced Research Projects Agency
Openalex Percentile: Top 26%
COVID-19 epidemiological studies
1.37
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