COVID-19 moderates the association between to-metro and by-metro accessibility and house prices

Previous studies extensively examined the role of accessibility to metro in shaping house prices but largely overlooked the contribution of accessibility by metro. In addition, limited studies examined the moderating effect of COVID-19 on the price effects of to-metro and by-metro accessibility. Based on multilevel hedonic price and quantile regression models, this study scrutinizes the association between to-metro accessibility, by-metro accessibility, and house prices in Chengdu, China, and examines the moderating role of COVID-19 in this association. We show that by-metro accessibility significantly influences house prices. COVID-19 significantly influences the value of to-metro accessibility but marginally affects that of by-metro accessibility. The value of to-metro accessibility is disproportionately affected by the pandemic. Specifically, small or low-priced houses are less affected than big or high-priced houses. In other words, the flattening of the to-metro price gradient is more discernible for big or high-priced houses. The changing preference of residents has also been verified by the decreases in house transaction volume in metro-adjacent areas. © 2022 Elsevier Ltd

Changing Food Patterns during the Pandemic: Exploring the Role of Household Dynamics and Income Stabilization Strategies

COVID-19 still looms as the largest risk to the agriculture, energy, and health sectors, threatening sustainable global economic development. The literature shows that the COVID-19 pandemic can divert governments' attention away from climate change, renewable energy, and food security challenges that are necessary to address for sustainable economic growth. The COVID-19 pandemic has consistently influenced environmental behaviors, as it has primarily decreased income levels and disrupted food systems worldwide. This study examined the impacts of COVID-19 on food consumption patterns, food diversity, and income challenges and explored the factors affecting food consumption patterns during the pandemic. The data collected through an online survey from 1537 Chinese households were analyzed through a paired t-test, a mixed-design ANOVA, and a logistic regression analysis. The results revealed that the consumption of the majority of individual food commodities decreased during the COVID-19 pandemic. Among the individual food items, the consumption of pork witnessed the greatest decrease during the COVID-19 pandemic compared to the normal period. The decrease in food diversity was higher for the households whose income was affected compared to the households whose income was not affected during the COVID-19 pandemic. Furthermore, the consumption quantities of various food groups declined more for highly income-affected households than for medium and slightly affected households during the pandemic. Households that adopted a dissaving income-stabilizing strategy were 47% points more likely to maintain their food consumption patterns during the pandemic. Farmers were 17% points and 19% points less likely to suffer worsened food consumption compared to self-employed and wage workers, respectively, during the pandemic. Thus, self-production methods such as kitchen gardening can assist households to maintain and improve their consumption of food commodities during the COVID-19 pandemic. © 2022 by the authors.

School and community reopening during the COVID-19 pandemic: a mathematical modelling study.

Operating schools safely during the COVID-19 pandemic requires a balance between health risks and the need for in-person learning. Using demographic and epidemiological data between 31 July and 23 November 2020 from Toronto, Canada, we developed a compartmental transmission model with age, household and setting structure to study the impact of schools reopening in September 2020. The model simulates transmission in the home, community and schools, accounting for differences in infectiousness between adults and children, and accounting for work-from-home and virtual learning. While we found a slight increase in infections among adults (2.2%) and children (4.5%) within the first eight weeks of school reopening, transmission in schools was not the key driver of the virus resurgence in autumn 2020. Rather, it was community spread that determined the outbreak trajectory, primarily due to increases in contact rates among adults in the community after school reopening. Analyses of cross-infection among households, communities and schools revealed that home transmission is crucial for epidemic progression and safely operating schools, while the degree of in-person attendance has a larger impact than other control measures in schools. This study suggests that safe school reopening requires the strict maintenance of public health measures in the community.

Capturing Household Structure and Mobility within and between Remote Aboriginal Communities in Northern Australia Using Longitudinal Data: A Pilot Study.

Cultural practices and development level can influence a population's household structures and mixing patterns. Within some populations, households can be organized across multiple dwellings. This likely affects the spread of infectious disease through these communities; however, current demographic data collection tools do not record these data. METHODS: Between June and October 2018, the Contact And Mobility Patterns in remote Aboriginal Australian communities (CAMP-remote) pilot study recruited Aboriginal mothers with infants in a remote northern Australian community to complete a monthly iPad-based contact survey. RESULTS: Thirteen mother-infant pairs (participants) completed 69 study visits between recruitment and the end of May 2019. Participants reported they and their other children slept in 28 dwellings during the study. The median dwelling occupancy, defined as people sleeping in the same dwelling on the previous night, was ten (range: 3.5-25). Participants who completed at least three responses (n = 8) slept in a median of three dwellings (range: 2-9). Each month, a median of 28% (range: 0-63%) of the participants travelled out of the community. Including these data in disease transmission models amplified estimates of infectious disease spread in the study community, compared to models parameterized using census data. CONCLUSIONS: The lack of data on mixing patterns in populations where households can be organized across dwellings may impact the accuracy of infectious disease models for these communities and the efficacy of public health actions they inform.

Household Structure Projection: A Monte-Carlo based Approach

The kernel of an agent based simulation system for spreading of infectious disease needs a so called household structure (HSD) of the area being simulated which contains a list of households with the age of each member in the household being recorded. Such a household structure is available in a Census that is usually released every 10 years. Previous researches have shown the changing of the household structure has a great impact on disease spreading patterns. It is observed that the changing of the household structure e.g., the average citizen ages and household size, is at a faster speed. However, serious infectious diseases, such as SARS (year 2002), H1N1 (year 2009) and COVID-19 (year 2019), occur with a higher frequency now than previous eras. For example, it would be bad to use HSD2010 built using Census 2010 to simulate COVID-19. In view of this situation, we need a better way to obtain a good household structure in between the Census years in order for an agent-based simulation system to be effective. Note that though a detailed Census is not available every year, aggregated information such as the number of households with a particular size, and the number of people of a particular age are usually available almost monthly. Given HSDx, the household structure for year x, and the aggregated information from year y where y > x, we propose a Monte-Carlo based approach "patching" HSDx to get an approximated HSDy. To validate our algorithm, we pick x and y - x + 10 which both Censuses are available and find out the root-mean-square error (RMSE) between Census's HSDy and generated HSDy is fairly small for x = 1990 and 2000. The spreading patterns obtained by our simulation system have good matches. We hence obtain HSD2020 to be used in your system for studying the spreading of COVID-19.

The impact of spatial and social structure on an SIR epidemic on a weighted multilayer network.

A key factor in the transmission of infectious diseases is the structure of disease transmitting contacts. In the context of the current COVID-19 pandemic and with some data based on the Hungarian population we develop a theoretical epidemic model (susceptible-infected-removed, SIR) on a multilayer network. The layers include the Hungarian household structure, with population divided into children, adults and elderly, as well as schools and workplaces, some spatial embedding and community transmission due to sharing communal spaces, service and public spaces. We investigate the sensitivity of the model (via the time evolution and final size of the epidemic) to the different contact layers and we map out the relation between peak prevalence and final epidemic size. When compared to the classic compartmental model and for the same final epidemic size, we find that epidemics on multilayer network lead to higher peak prevalence meaning that the risk of overwhelming the health care system is higher. Based on our model we found that keeping cliques/bubbles in school as isolated as possible has a major effect while closing workplaces had a mild effect as long as workplaces are of relatively small size.

Working from Home and Work-Family Balance: A Study of Women Educators during Lockdown

Covid-19 has had an overwhelming effect on lives and livelihoods alike. We have all embraced the new normal, including working from home, although it has come as an abrupt change. While not all jobs lend themselves to be shifted online, teaching is one profession that could witness such a change with relative ease. Technology eased the process, but it was not easy for those who had to do so, especially for women educators who faced very demanding sets of circumstances for managing work and home with limited domestic support. This paper attempts to study the impact of the mandatory lockdown on women educators, their work-life balance, and their experiences. The study was conducted in two phases, quantitative and qualitative. The quantitative phase was composed of 150 responses from women educators teaching online during the lockdown in PostGraduate Diploma in Management (PGDM) programs in Jaipur, India. Thirty respondents volunteered to participate in the qualitative phase, which was conducted using semi-structured in-depth interviews. Five themes emerged from the qualitative phase: Structuring the home environment for work, workplace social support, personal social support, household structure, and feelings of isolation. There was substantial evidence backing up all these themes in the existing literature and this has been discussed comprehensively in the findings section. © 2021, Research Institute of Asian Women. All rights reserved.

The potential impact of co-residence structures on socio-demographic inequalities in COVID-19 mortality.

During the COVID-19 pandemic, confinement measures were adopted across the world to limit the spread of the virus. In France, these measures were applied between March 17 and May 10. Using high-quality population census data and focusing on co-residence structures on French territory, this article analyzes how co-residence patterns unevenly put different socio-demographic groups at risk of being infected and dying from COVID-19. The research ambition is to quantify the possible impact of co-residence structures heterogeneity on socio-economic inequalities in mortality stemming from within-household transmission of the virus. Using a simulation approach, the article highlights the existence of theoretical pronounced inequalities of vulnerability to COVID-19 related to cohabitation structures as well as a reversal of the social gradient of vulnerability when the age of the infected person increases. Among young age categories, infection is simulated to lead to more deaths in the less educated or foreign-born populations. Among the older ones, the inverse holds with infections having a greater potential to provoke deaths through the transmission of the virus within households headed by a highly educated or a native-born person. Demographic patterns such as the cohabitation of multiple generations and the survival of both partners of a couple help to explain these results. Even though inter-generational co-residence and large households are more common among the lower educated and foreign born in general, the higher educated are more likely to still live with their partner at higher ages.