Do population density, socio-economic ranking and Gini Index of cities influence infection rates from coronavirus? Israel as a case study

The Annals of Regional Science - Tập 68 - Trang 181-206 - 2021
Yuval Arbel1, Chaim Fialkoff2, Amichai Kerner3, Miryam Kerner4
1Sir Harry Solomon School of Economics and Management, Western Galilee College, Acre, Israel
2Institute of Urban and Regional Studies, Hebrew University of Jerusalem, Jerusalem, Israel
3School of Real Estate, Netanya Academic College, Netanya, Israel
4The Ruth and Bruce Rappaport Faculty of Medicine, Technion—Israel Institute of Technology, Haifa, Israel

Tóm tắt

A prominent characteristic of the COVID-19 pandemic is the marked geographic variation in COVID-19 prevalence. The objective of the current study is to assess the influence of population density and socio-economic measures (socio-economic ranking and the Gini Index) across cities on coronavirus infection rates. Israel provides an interesting case study based on the highly non-uniform distribution of urban populations, the existence of one of the most densely populated cities in the world and diversified populations. Moreover, COVID19 challenges the consensus regarding compact planning design. Consequently, it is important to analyze the relationship between COVID19 spread and population density. The outcomes of our study show that ceteris paribus projected probabilities to be infected from coronavirus rise with population density from 1.6 to 2.72% up to a maximum of 5.17–5.238% for a population density of 20,282–20,542 persons per square kilometer (sq. km.). Above this benchmark, the anticipated infection rate drops up to 4.06–4.50%. Projected infection rates of 4.06–4.50% are equal in cities, towns and regional councils (Local Authorities) with the maximal population density of 26,510 and 11,979–13,343 persons per sq. km. A possible interpretation is that while denser cities facilitate human interactions, they also enable and promote improved health infrastructure. This, in turn, contributes to medical literacy, namely, elevated awareness to the benefits associated with compliance with hygienic practices (washing hands), social distancing rules and wearing masks. Findings may support compact planning design principles, namely, development of dense, mixed use, walkable and transit accessible community design in compact and polycentric regions. Indeed, city planners should weigh the costs and benefits of many risk factors, including the COVID19 pandemic.

Tài liệu tham khảo

Alperovich G (1984) The size distribution of cities: on the empirical validity of the rank-size rule. J Urban Econ 16:232–239 Amemiya T (1981) Qualitative response models: a survey. J Econ Lit 19(4):1483 Arbel Y, Fialkoff C, Kerner A (2019) The chicken and egg problem: obesity and the urban monocentric model. J Real Estate Finance Econ. https://doi.org/10.1007/s11146-019-09737-5 Avnimelech G, Schwartz D, Bar-El R (2007) Entrepreneurial high-tech cluster development: israel’s experience with venture capital and technological incubators. Eur Plan Stud 15(9):1181–1198. https://doi.org/10.1080/09654310701529078 Beenstock M, Felsenstein D, Zeev NB (2011) Capital deepening and regional inequality: an empirical analysis. Ann Reg Sci 47(3):599–617 Bell DM, Isaac IB, Hernandez-Avila M, Del Rio C, Bustamante X, Rodier G (2009) Pandemic Influenza as 21st Century urban public health crisis. Emerg Infect Dis 15(12):1963–1969. https://doi.org/10.3201/eid1512.091232 Blasius B (2020) Power-law distribution in the number of confirmed COVID-19 cases. Available at: https://arxiv.org/pdf/2004.00940.pdf. Clarke H, Whitely P (2020) Economic Inequality Can Help Predict COVID19 Deaths in the US. Available at: https://blogs.lse.ac.uk/usappblog/2020/05/06/economic-inequality-can-help-predict-covid-19-deaths-in-the-us/. Cochrane D, Orcutt GH (1949) Application of least squares regression to relationships containing auto- correlated error terms. J Am Stat Assoc 44(245):32–61. https://doi.org/10.2307/2280349 Dye C (2008) Health and Urban living. Science (new York, n.y.) 319(5864):766–769. https://doi.org/10.1126/science.1150198 Elster Y, Zussman A, Zussman N (2017) Rockets: the housing market effects of a credible terrorist threat. J Urban Econ 99(May):136–147. https://doi.org/10.1016/j.jue.2017.02.003 Eubank S, Guclu H, Anil Kumar VS, Marathe MV, Srinivasan A, Toroczkai Z, Wang N (2004) Modelling disease outbreaks in realistic urban social networks. Nat Int Wky J Sci 429(6988):180. https://doi.org/10.1038/nature02541 Ewing R, Meakins G, Hamidi S, Nelson AC (2014) Relationship between urban sprawl and physical activity, obesity, and morbidity – update and refinement. Health Place 26:118–126. https://doi.org/10.1016/j.healthplace.2013.12.008 Gat D (1996) Compact hedonic model of the greater Tel Aviv housing market. J Real Estate Lit 4(2):162–172 Gat D (1998) Urban focal points and design quality influence rents: the case of the Tel Aviv office market. J Real Estate Res 16(2):229–247 Glaeser E (2011) Cities, productivity, and quality of Life. Science (new York, n.y.) 333(6042):592–594. https://doi.org/10.1126/science.1209264 Hamidi S (2020) Urban sprawl and the emergence of food deserts in the USA. Urban Stud 57(8):1660–1675. https://doi.org/10.1177/0042098019841540 Hamidi S, Ewing R, Tatalovich Z, Grace JB, Berrigan D (2018) Associations between urban sprawl and life expectancy in the United States. Int J Environ Res Public Health 15(5):861. https://doi.org/10.3390/ijerph15050861 Hamidi S, Sabouri S, Ewing R (2020a) Does density aggravate the COVID-19 pandemic? Early findings and lessons for planners. J Am Plan Assoc 86(4):495 Hamidi S, Ewing R, Sabouri S (2020b) Longitudinal analyses of the relationship between development density and the COVID-19 morbidity and mortality rates: early evidence from 1,165 metropolitan counties in the United States. Health Place. https://doi.org/10.1016/j.healthplace.2020.102378 ICBD report (Israel in Figures, 2019 - Selected Data from The Statistical Abstract of Israel, 2019 Hebrew). Available at: https://www.cbs.gov.il/he/publications/DocLib/isr_in_n/isr_in_n19h.pdf ICBD report Population - Statistical Abstract of Israel 2019- No.70. Available at: https://www.cbs.gov.il/he/publications/doclib/2019/2.shnatonpopulation/02_01e.pdf. Israel Central Bureau of Statistics. Characterization and Classification of Geographical Units by the Socio-Economic Level of the Population, 2015. Available at: https://www.cbs.gov.il/en/publications/Pages/2019/Characterization-and-Classification-of-Geographical-Units-by-the-Socio-Economic-Level-of-the-Population-2015.aspx. Israel CBS: Statistical Abstract of Israel (2019) Population Density per Square Kilometer. https://www.cbs.gov.il/he/publications/doclib/2019/2.shnatonpopulation/st02_23.pdf. Israeli Ministry of Health Report (2019) Manpower in the Health Profession, 2018 (Hebrew). Available at: https://pic-upload.ynet.co.il/briut/4_5949318699042211309.pdf. Jack J, Dunardo J (1997) Econometric methods, 4th edn. McGraw Hill International Edition, New York Kahn D (2020) California saw dense housing near transit as its future. What Now? Politico Retrieved From https://www.politico.com/states/california/story/2020/03/27/california-saw-dense-housing-near-transit-as-its-future-what-now-1269263. Kmenta J (1997) Elements of econometrics, 2nd edn. The University of Michigan Press, Ann Arbor McDonald JF, McMillen D (2011) Urban economics and real estate theory and policy, 2nd edn. Wiley, Hoboken Mills ES, Hamilton BW (1989) Urban Economics (4th ed., pp. 425–434). Appendix A: Simplified Mathematical Model of Urban Structure Newman MEJ (2005) Power laws, Pareto distributions and Zipf’s law. Contemp Phys 46(5):323–351 Nistsch V (2005) Zipf zipped. J Urban Econ 57(2005):86–100 O’Sullivan A (2012) Urban economics, Eight. McGraw Hills International Edition, Singapore Office of the Registrar General & Census Commissioner, India: West Bangai. Papke LE, Wooldridge JM (1996) Econometric methods for fractional response variables with an application to 401(k) plan participation rates. J Appl Economet 11:619–632 Prais SJ, Winsten CB (1954) Trend estimation and serial correlation. Cowles Comission Discussion Paper, 383 Ramanathan R (2002) Introductory econometrics with application, 5th edn. South Western Thomson Learning, Boston Robinson JJ, Wharrad H (2001) The relationship between attendance at birth and maternal mortality rates: an exploration of united nations’ data sets including the ratios of physicians and nurses to population, GNP per capita and female literacy. J Adv Nursing 34(4):445–455. https://doi.org/10.1046/j.1365-2648.2001.01773.x Sallis JF, Cerin E, Conway TL, Adams MA, Frank LD, Pratt M, Salvo D et al (2016) Physical activity in relation to Urban environments in 14 cities worldwide: a cross-sectional study. The Lancet 387(10034):2207–2217. https://doi.org/10.1016/S0140-6736(15)01284-2 Schmitt-Grohé S, Teoh K, Uribe M (2020) Covid-19: Testing Inequality in New York City," NBER Working Papers 27019, National Bureau of Economic Research, Inc Wooldridge JM (2010) Econometric analysis of cross section and panel data, 2nd edn. MIT Press, Cambridge, MA World Health Organization (WHO): Coronavirus. Available at: https://www.who.int/health-topics/coronavirus#tab=tab_1 Accessed from 3 May 2020