Ajuntament de Barcelona, Barcelona, Spain.
CIBER de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
Int J Equity Health. 2022 Feb 19;21(1):28. doi: 10.1186/s12939-022-01628-1.
Spain has been hit hard by COVID-19 since March 2020, especially in its metropolitan areas. We share experiences from Barcelona in measuring socioeconomic inequalities in the incidence of COVID-19 in the different waves, and in implementing coordinated and equity-oriented public health policy responses.
We collected daily data on confirmed COVID-19 cases, geocoded the address of residence to assign each case to one of the 73 neighborhoods and 1068 census tracts, and calculated the cumulative incidence of COVID-19 by neighborhood and five income groups (quintiles of census tracts) by sex across four waves of the pandemic. We adjusted hierarchical Bayesian spatial models to obtain the relative risk (RR) of cumulative incidences in each quintile compared with the richest areas. A variety of public health policies implemented to tackle the pandemic and especially these inequalities in COVID-19 incidence and vaccination are selected and described.
Area-level income inequalities in the incidence of COVID-19 were present at different degree in all four waves. In the second wave (10/1/2020 to 12/6/2020), RR for the poorest income quintile census tracts compared with the richest was 1.43 (95% credible interval-CI-: 1.22-1.67) for men and 1.58 (95% CI: 1.35-1.83) for women. Later, inequalities in vaccination coverage also arose. Equity-oriented policy responses included: "health hotels" or home delivery of basic products for individuals with COVID-19 and without adequate conditions for isolation; new emergency facilities for homeless people, including those with active drug use; mass screening in high incidence areas; contingency plans for nursing homes and schools; adapting community health programs for their early reactivation; digital self-appointment support points and community vaccination days.
COVID-19 hit Barcelona neighborhoods unequally, with variations between waves. The rapid availability of geolocalized data and by socioeconomic level helped public authorities to implement targeted policies and collaborative interventions for the most vulnerable populations. Further studies would be needed to evaluate their impact.
自 2020 年 3 月以来，西班牙受到 COVID-19 的严重打击，尤其是在其大都市区。我们分享了巴塞罗那在衡量 COVID-19 在不同波次中的发病率的社会经济不平等方面的经验，以及实施协调和公平导向的公共卫生政策应对措施方面的经验。
我们收集了每日确诊的 COVID-19 病例数据，将居住地的地址进行地理编码，将每个病例分配到 73 个街区和 1068 个普查区之一，并按性别和四个流行波次计算了 COVID-19 的累计发病率。我们调整了分层贝叶斯空间模型，以获得每个五分位数（普查区五分位数）与最富裕地区相比的累计发病率的相对风险（RR）。选择并描述了为应对大流行以及 COVID-19 发病率和疫苗接种方面的这些不平等而实施的各种公共卫生政策。
在所有四个波次中，COVID-19 发病率的地区收入不平等程度不同。在第二波（2020 年 10 月 1 日至 12 月 6 日）中，与最富裕地区相比，最贫困收入五分位数的普查区的 RR 为男性 1.43（95%可信区间[CI]：1.22-1.67），女性 1.58（95% CI：1.35-1.83）。之后，疫苗接种覆盖率也出现了不平等。公平导向的政策应对措施包括：为 COVID-19 患者和无适当隔离条件的基本产品提供“健康酒店”或送货上门服务；为无家可归者提供新的紧急设施，包括那些有药物滥用的人；在高发病率地区进行大规模筛查；为疗养院和学校制定应急计划；调整社区卫生计划以提前重新启动；数字自我预约支持点和社区接种日。
COVID-19 对巴塞罗那的社区造成了不平等的影响，各波次之间存在差异。快速获得地理位置和社会经济水平数据有助于公共当局为最弱势群体实施有针对性的政策和协作干预措施。需要进一步研究来评估其影响。
