Association between urban green space and transmission of COVID-19 in Oslo, Norway: A Bayesian SIR modeling approach

IF 2.1 Q3 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Halvor Kjellesvig , Suleman Atique , Lars Böcker , Geir Aamodt
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引用次数: 0

Abstract

Background:

Access to green spaces can provide opportunities for physical activities and social interactions in urban areas during times with strict social distancing. In particular COVID-19 transmission is reduced in ventilated areas. During several waves of the pandemic, this study explores the association between access to urban green spaces and COVID-19 transmission at the district level in Norway’s capital, Oslo.

Methods:

We used daily numbers of confirmed laboratory PCR tests on district levels reported from the second to the fifth wave of the COVID-19 pandemic, from October 15, 2020 to April 15, 2022 in Oslo. We included the population’s access to urban green spaces using two objective measurements: percentage of green area (%Ga) and vegetation cover (NDVI) using 300 and 1000 m buffers. The socio-demographic variables percentage of low-income population, average life expectancy and population density were also included. A Bayesian Susceptible–Infected–Removed (SIR) model was used to take advantage of the daily updated data on COVID-19 incidence and account for spatial and temporal dependencies in the statistical analysis.

Results:

We found that low income as well as population density were significantly associated with incidence of COVID-19, but for the second and third waves only. For the second wave, a one percent increase in the proportion with low income at district level increased the risk of COVID-19 by 7 % (95 % CI: 3 % - 11 %) We did not find associations between access to green space and incidence rate for any of the buffer sizes. The second and third waves were more governed by socio-demographic factors than the fourth and fifth wave.

Conclusions:

Incidence rate of COVID-19 was not associated with access to green space, but to the socio-demographic variables; income, population density, and life expectancy. Access to green space is equally distributed among districts in Oslo which may explain our findings.
挪威奥斯陆城市绿地与COVID-19传播的关系:贝叶斯SIR建模方法
背景:在严格保持社交距离的时期,城市地区的绿地可以为体育活动和社会互动提供机会。特别是在通风区域,COVID-19的传播减少了。在几波大流行期间,本研究探讨了挪威首都奥斯陆地区城市绿地使用与COVID-19传播之间的关系。方法:利用2020年10月15日至2022年4月15日在奥斯陆报告的第二波至第五波COVID-19大流行期间每天的实验室PCR确认检测数。我们使用两种客观的测量方法:使用300米和1000米缓冲区的绿地面积百分比(%Ga)和植被覆盖(NDVI)来纳入人口对城市绿地的访问。社会人口变量包括低收入人口百分比、平均预期寿命和人口密度。采用贝叶斯易感-感染-去除(SIR)模型,利用每日更新的COVID-19发病率数据,并在统计分析中考虑时空依赖性。结果:我们发现低收入和人口密度与COVID-19发病率显著相关,但仅适用于第二和第三波。在第二波浪潮中,地区一级低收入人口比例每增加1%,COVID-19的风险就会增加7% (95% CI: 3% - 11%)。我们没有发现任何缓冲面积的绿地使用与发病率之间存在关联。第二次和第三次浪潮比第四次和第五次浪潮更受社会人口因素的支配。结论:2019冠状病毒病发病率与绿地可及性无关,而与社会人口学变量相关;收入,人口密度和预期寿命。在奥斯陆,绿地在各区之间分布均匀,这可以解释我们的研究结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Spatial and Spatio-Temporal Epidemiology
Spatial and Spatio-Temporal Epidemiology PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-
CiteScore
5.10
自引率
8.80%
发文量
63
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