Department of Medicine, Weill Cornell Medical College, Cornell University, New York, New York, United States of America.
Department of Statistics and Data Science, Cornell University, Ithaca, New York, United States of America.
PLoS One. 2022 Mar 30;17(3):e0266127. doi: 10.1371/journal.pone.0266127. eCollection 2022.
City-wide lockdowns and school closures have demonstrably impacted COVID-19 transmission. However, simulation studies have suggested an increased risk of COVID-19 related morbidity for older individuals inoculated by house-bound children. This study examines whether the March 2020 lockdown in New York City (NYC) was associated with higher COVID-19 hospitalization rates in neighborhoods with larger proportions of multigenerational households.
We obtained daily age-segmented COVID-19 hospitalization counts in each of 166 ZIP code tabulation areas (ZCTAs) in NYC. Using Bayesian Poisson regression models that account for spatiotemporal dependencies between ZCTAs, as well as socioeconomic risk factors, we conducted a difference-in-differences study amongst ZCTA-level hospitalization rates from February 23 to May 2, 2020. We compared ZCTAs in the lowest quartile of multigenerational housing to other quartiles before and after the lockdown.
Among individuals over 55 years, the lockdown was associated with higher COVID-19 hospitalization rates in ZCTAs with more multigenerational households. The greatest difference occurred three weeks after lockdown: Q2 vs. Q1: 54% increase (95% Bayesian credible intervals: 22-96%); Q3 vs. Q1: 48% (17-89%); Q4 vs. Q1: 66% (30-211%). After accounting for pandemic-related population shifts, a significant difference was observed only in Q4 ZCTAs: 37% (7-76%).
By increasing house-bound mixing across older and younger age groups, city-wide lockdown mandates imposed during the growth of COVID-19 cases may have inadvertently, but transiently, contributed to increased transmission in multigenerational households.
全市范围的封锁和学校关闭已明显影响了 COVID-19 的传播。然而,模拟研究表明,由于被居家隔离的儿童接种疫苗,年龄较大的人感染 COVID-19 的相关发病率会增加。本研究调查了 2020 年 3 月纽约市(NYC)的封锁是否与拥有更多代际家庭比例的社区中 COVID-19 住院率升高有关。
我们获取了 NYC 166 个邮政编码区(ZCTA)中每天的按年龄分段的 COVID-19 住院人数。使用贝叶斯泊松回归模型,该模型考虑了 ZCTA 之间的时空依赖性以及社会经济风险因素,我们在 2020 年 2 月 23 日至 5 月 2 日之间进行了 ZCTA 级住院率的差分研究。我们在封锁前后将 ZCTA 按多代家庭的最低四分位数与其他四分位数进行了比较。
在 55 岁以上的人群中,封锁与多代家庭比例较高的 ZCTA 中 COVID-19 住院率升高有关。封锁后第三周的差异最大:Q2 与 Q1 相比:增加了 54%(95%贝叶斯可信区间:22-96%);Q3 与 Q1 相比:增加了 48%(17-89%);Q4 与 Q1 相比:增加了 66%(30-211%)。在考虑了与大流行相关的人口转移之后,仅在 Q4 ZCTA 中观察到了显著差异:增加了 37%(7-76%)。
通过增加年龄较大和年龄较小的人群之间的居家混合,在 COVID-19 病例增长期间实施的全市范围封锁可能会无意间但短暂地增加代际家庭中的传播。