Discipline of Public Administration, School of Public Management, Zhejiang Gongshang University, Hangzhou, China.
School of Politics and Public Administration, China South Normal University, University City, Guangzhou, China.
BMC Public Health. 2022 Jan 11;22(1):70. doi: 10.1186/s12889-021-12419-8.
After the lockdown of Wuhan on January 23, 2020, the government used community-based pandemic prevention and control as the core strategy to fight the pandemic, and explored a set of standardized community pandemic prevention measures that were uniformly implemented throughout the city. One month later, the city announced its first lists of "high-risk" communities and COVID-19-free communities. Under the standardized measures of pandemic prevention and mitigation, why some communities showed a high degree of resilience and effectively avoided escalation, while the situation spun out of control in other communities? This study investigated: 1) key factors that affect the effective response of urban communities to the pandemic, and 2) types of COVID-19 susceptible communities.
This study employs the crisp-set qualitative comparative analysis method to explore the influencing variables and possible causal condition combination paths that affect community resilience during the pandemic outbreak. Relying on extreme-case approach, 26 high-risk communities and 14 COVID-19 free communities were selected as empirical research subjects from the lists announced by Wuhan government. The community resilience assessment framework that evaluates the communities' capacity on pandemic prevention and mitigation covers four dimensions, namely spatial resilience, capital resilience, social resilience, and governance resilience, each dimension is measured by one to three variables.
The results of measuring the necessity of 7 single-condition variables found that the consistency index of "whether the physical structure of the community is favorable to virus transmission" reached 0.9, which constitutes a necessary condition for COVID-19 susceptible communities. By analyzing the seven condition configurations with high row coverage and unique coverage in the obtained complex solutions and intermediate solutions, we found that outbreaks are most likely to occur in communities populated by disadvantaged populations. However, if lacking spatial-, capital-, and governance resilience, middle-class and even wealthy communities could also become areas where COVID-19 spreads easily.
Three types of communities namely vulnerable communities, alienated communities, and inefficient communities have lower risk resilience. Spatial resilience, rather than social resilience, constitutes the key influencing factor of COVID-19-susceptible communities, and the dual deficiencies of social resilience and governance resilience are the common features of these communities.
2020 年 1 月 23 日武汉封城后,政府以社区为基础的疫情防控作为核心策略来对抗疫情,探索出一整套标准化的社区疫情防控措施,并在全市范围内统一实施。一个月后,武汉公布了第一批“高风险”社区和无新冠肺炎社区名单。在标准化的疫情防控措施下,为什么有些社区表现出高度的弹性,有效地避免了升级,而其他社区的情况却失控了?本研究调查了:1)影响城市社区对疫情有效应对的关键因素,2)COVID-19 易感社区的类型。
本研究采用清晰集定性比较分析方法,探讨影响疫情期间社区弹性的变量和可能的因果条件组合路径。依托极值案例法,从武汉政府公布的名单中选取 26 个高风险社区和 14 个无新冠肺炎社区作为实证研究对象。评估社区在疫情防控方面能力的社区弹性评估框架涵盖四个维度,即空间弹性、资本弹性、社会弹性和治理弹性,每个维度用一到三个变量来衡量。
对 7 个单条件变量的必要性进行测量的结果发现,“社区的物理结构是否有利于病毒传播”的一致性指数达到 0.9,构成了 COVID-19 易感社区的必要条件。通过分析在获得的复杂解和中间解中具有高行覆盖率和独特覆盖率的七个条件配置,可以发现,弱势群体聚居的社区最容易爆发疫情。但是,如果缺乏空间、资本和治理弹性,中产阶级甚至富裕社区也可能成为 COVID-19 容易传播的区域。
三种类型的社区即脆弱社区、异化社区和低效社区风险弹性较低。空间弹性而不是社会弹性是 COVID-19 易感社区的关键影响因素,社会弹性和治理弹性的双重不足是这些社区的共同特征。