Egor Kotov (p), Yuri Kuchitsky, Varvara Molodtsova, Ruslan Goncharov

Philip S. Morrison

This study aims to identify the key factors of COVID-19 excess mortality at a municipal level across Russia and compare them to the factors in the European countries.

We have previously identified excess mortality factors at a regional level in Russia. However, the results were not directly comparable to similar research in Europe, as the average size of the regional units in Russia is significantly larger than in Europe. The modifiable areal unit problem and excessive averaging of the factors across urban and rural municipalities within larger regional units lead to weak explanatory models.

Full 2020 mortality data at a municipal level in Russia was published at the end of 2021. There is no official spatial data source with municipal level borders for Russia, and the GADM (Database of Global Administrative Areas) is outdated. We combine the OpenStreetMap data on municipal borders with official municipal level statistics from Russia's Federal State Statistics Service. This unique data set enables us to consider the spatial component of the spread of COVID-19, which is much more appropriate at the microgeographic level of municipalities than the regional level analysis.

We consider the previously identified factors at a regional level: share of the elderly population, the share of workers in manufacturing, humidity, number of retail locations per capita). We also revisit the factors identified by other researchers, such as transport connectivity, migration, income inequality and healthcare provision. We use the ordinary least squares model as a baseline. Using queen contiguity neighbourhood for the municipalities, we also employ spatial econometric extensions to the OLS to estimate spillover effects of individual factors.

Our findings suggest that in contrast to the regional level, at a municipal level, the factors of COVID-19 excess mortality in Russia are mainly similar to those in European countries.

Yuval Arbel (p), Chaim Fialkoff, Amichai Kerner, Miryam Kerner

Egor Kotov

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.

Tahsin Şahin (p), Mustaf Ertürk, Selim Çağatay, Çiğdem varol özden, Tanyel özelci eceral

Yuval Arbel

Although the Covid-19 crisis is widely considered in the economic sense, Small and Medium-Sized Enterprises (SMEs) were the most affected by this situation, most of them experienced a rapid decrease in income or closed. Although the Covid-19 crisis is evaluated on a global scale in terms of its impact, it requires regional thinking in terms of problem detection and solution proposals. The higher the sectoral diversity of the Region, the stronger the economic resilience coefficient or flexibility capacity (Gong, et al. 2020). In this context, the aim of the project is to analyze the effects of the Covid-19 crisis on SME scale in the city of Antalya. Research questions; 1. Based on the four periods (November 2017-November 2020) according to the economic activities in the city of Antalya, Nace Rev.2 code, which sectors are more resistant to the Covid-19 crisis, which sectors are more fragile? Accordingly, what is the economic flexibility capacity of the city of Antalya? What are the Opportunity sectors opened in Antalya during the Covid-19 crisis period? 2. Based on the data of the SGK Antalya Provincial Directorate data (Nace Rev.2 code 2-digit sectors) of the districts of the city of Antalya at the scale of SMEs, based on four periods (November 2017- November 2020). Accordingly, what is the economic flexibility capacity of the districts of Antalya? Within the scope of this purpose and research questions, the flexibility capacity of the Antalya economy will be revealed by analyzing which sectors are resistant to the Covid-19 crisis and which sectors are fragile according to the two-digit Nace Rev. Thanks to this analysis, the sectors that show specialization in the city of Antalya will be determined and the opportunity to compare with the sectors most affected by the Covid-19 crisis highlighted in the literature will be obtained. In the research, Location Coefficient technique, Herfindahl Index, Diversity Index Level-3 (province) scale will be calculated on the basis of employment, the number of workplaces and sectoral patent data. In the next step of the project, in line with this flexibility capacity, it will be determined whether there is a spatial difference between the sectors of the crisis in the district of Antalya province. The Covid-19 crisis differs spatially in the city of Antalya on a sectoral scale.

Philip S. Morrison (p), Stephanie Rossouw, Talita Greyling

M.Tahsin Şahin

As COVID-19 (Delta and Omicron) continue to disrupt the lives and livelihood of millions across the globe and there remains controversy over the effect of lockdowns on people’s wellbeing. Both negative and positive effects of lockdown have been documented within and between countries using a range of measures.
In 2020 New Zealand introduced different lockdown levels in the Auckland Region compared to the Rest of New Zealand. We take advantage of this ‘natural experiment’ to assess the effect of differential levels of lockdown severity on people’s subjective wellbeing. Using a difference-in-difference methodology we compare average levels of wellbeing based on sentiment analysis which synthesizes wellbeing emotions from hundreds of Tweets from the two regions on a daily basis.

Please note. I've attached a closely related paper in place of an extended abstract - due to delays in preparing the latter. We are continuing to work on the extended abstract. Apologies.