Pandemic Impacts, Social Networks, and Mental Health in Chinatown, Manhattan

• In Event: Immigrant Health - Changing Contexts, Heterogeneity, Resilience, and Selectivity

Abstract

The COVID-19 pandemic brought severe economic and social disruptions on Manhattan's Chinatown, yet the lingering mental health consequences for small business owners in this historic immigrant enclave remain underexplored. This study investigates the determinants of psychological distress among small business owners surveyed in 2025, examining how pandemic impacts, social networks, business characteristics, and spatial factors shape mental health outcomes five years after the pandemic's onset. The results reveal three main findings. First, the severity of pandemic impacts on business in 2020 continues to predict poorer mental health in 2025, demonstrating lasting psychological effects that persist beyond economic recovery. Second, having female friends in one's social network is associated with significantly better mental health, but this protective effect is concentrated among male business owners, suggesting gendered patterns in the availability and effectiveness of emotional support. Third, spatial analysis reveals that the effects of key variables increase substantially with distance from the main commercial streets, with businesses located more than 100 meters from Canal or Mott Streets showing the strongest associations. Furthermore, spatial models provide evidence of mental health interdependencies among neighboring businesses at the 20-meter threshold, with indirect effects accounting for approximately 20-25 percent of direct effects. These findings highlight the importance of attending to long-term mental health needs in post-pandemic recovery efforts, the value of social network interventions tailored by gender, and the necessity of considering spatial context in understanding mental health dynamics of this immigrant community.

Authors

• Jiahao Zhang, University at Albany

• Zai Liang, State University of New York at Albany