Abstract
Abstract
Background
The first wave of the Covid-19 pandemic hit Israel in late February 2020. The present study examines patterns of the first wave of Covid-19 morbidity in Israel at the macro level, during the period of late February to early June 2020, when the first wave has faded out. The analysis focuses on the significance of four sociodemographic variables: socioeconomic status, population density, rate of elderly population and minority status (Jewish / Arab identity) of the population in cities with 5000 residents or more. Additionally, we take a closer look into the association between morbidity rates and one SES component – home Internet access.
Methods
The article is a cross sectional study of morbidity rates, investigated on a residential community basis. Following the descriptive statistics, we move on to present multivariate analysis to explore associations between these variables and Covid-19 morbidity in Israel.
Results
Both the descriptive statistics and regressions show morbidity rates to be positively associated with population density. Socioeconomic status as well as the size of elderly population were both significantly related to morbidity, but only in Jewish communities. Interestingly, the association was inverse in both cases. i.e., the higher the SES the lower the morbidity and the larger the elderly population, the lower the community’s morbidity. Another interesting result is that overall, morbidity rates in Jewish cities were consistently higher than in Arab communities.
Conclusions
We attribute the low morbidity rates in communities with relatively small elderly populations to the exceptionally high fertility rates in ultra-orthodox communities that sustained increased rates of morbidity; the lower morbidity in Arab communities is attributed to several factors, including the spatial Jewish-Arab segregation.
Publisher
Springer Science and Business Media LLC
Subject
Public Health, Environmental and Occupational Health,Health Policy
Reference31 articles.
1. Stojkoski V, Utkovski Z, Jolakoski P, Tevdovski D, Kocarev L. The Socio-Economic Determinants of the Coronavirus Disease (COVID-19) Pandemic; 2020. https://doi.org/10.2139/ssrn.3576037.
2. Abdellaoui A. Regional differences in reported Covid-19 cases show genetic correlations with higher socio-economic status and better health, potentially confounding studies on the genetics of disease susceptibility (Preprint); 2020. https://doi.org/10.1101/2020.04.24.20075333. https://www.medrxiv.org/content/10.1101/2020.04.24.20075333v1.full.pdf+html.
3. Kulu H, Dorey P. Infection Rates from Covid-19 in Great Britain by Geographical Units: A Model-based Estimation from Mortality Data; 2020. https://doi.org/10.31235/osf.io/84f3e.
4. Mansoor, Sanya. 2020. Data Suggests Many New York City Neighborhoods Hardest Hit by COVID-19 Are Also Low-Income Areas, https://time.com/5815820/data-new-york-low-income-neighborhoods-coronavirus/, retrieved May 28, 2020.
5. Gascard N, Kauffmann B, Labosse A. 26% more deaths between early March and mid-April 2020: dense municipalities are the most affected; 2020.
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