Systemic risk and spatiotemporal dynamics of the US housing market.
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ABSTRACT:
SUBMITTER: Meng H
PROVIDER: S-EPMC3888986 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:A survey, of sample size 224, is designed to include the different related-factors to housing location choice, such as; socioeconomic factors, housing characteristics, travel behavior, current self-selection factors, housing demand and future location preferences. It comprises 16 questions, categorized into three different sections; socioeconomic (5 Questions), current dwelling unit characteristics (7 Questions), and housing demand characteristics (4 Questions). The first part, socioeconomic, covers the basic information about the respondent, such as; age, gender, marital status, employment, and car ownership. While the second part, current dwelling unit characteristics, covers different aspect concerning the residential unit typology, financial aspects, and travel behavior of the respondent. It includes the tenure types of the residential unit, estimation of the unit price (in the case of ownership or renting), housing typologies, the main reason for choosing the unit, in case of working, the modes of travel to work, and time to reach it, residential mobility in the last decade, and the ownership of any other residential units. The last part, housing demand characteristics, covers the size of the demand for a residential unit, preference in living in a certain area and the reason to choose it, and the preference of residential unit׳s tenure. This survey is a representative sample for the population in Alexandria, Egypt. The data in this article is represented in: How do people select their residential locations in Egypt? The case of Alexandria; JCIT1757.
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Project description:ObjectivesWe determined the interactions between efficacy of antibiotic treatment, pathogen growth rates and between-organ spread during systemic Salmonella infections.MethodsWe infected mice with isogenic molecularly tagged subpopulations of either a fast-growing WT or a slow-growing ΔaroC Salmonella strain. We monitored viable bacterial numbers and fluctuations in the proportions of each bacterial subpopulation in spleen, liver, blood and mesenteric lymph nodes (MLNs) before, during and after the cessation of treatment with ampicillin and ciprofloxacin.ResultsBoth antimicrobials induced a reduction in viable bacterial numbers in the spleen, liver and blood. This reduction was biphasic in infections with fast-growing bacteria, with a rapid initial reduction followed by a phase of lower effect. Conversely, a slow and gradual reduction of the bacterial load was seen in infections with the slow-growing strain, indicating a positive correlation between bacterial net growth rates and the efficacy of ampicillin and ciprofloxacin. The viable numbers of either bacterial strain remained constant in MLNs throughout the treatment with a relapse of the infection with WT bacteria occurring after cessation of the treatment. The frequency of each tagged bacterial subpopulation was similar in the spleen and liver, but different from that of the MLNs before, during and after treatment.ConclusionsIn Salmonella infections, bacterial growth rates correlate with treatment efficacy. MLNs are a site with a bacterial population structure different to those of the spleen and liver and where the total viable bacterial load remains largely unaffected by antimicrobials, but can resume growth after cessation of treatment.
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Project description:Leptospirosis is an emerging neglected tropical disease with a worldwide significant global health burden. Between 2000 and 2016, there were 63,302 cases of human leptospirosis and 6,064 deaths reported in Brazil. We modeled the spatiotemporal risk dynamics of human leptospirosis morbidity and lethality, and attributed an easily interpretable risk-based priority index (PI) for all Brazilian federative units to suggest improvements to the national surveillance system. We also developed a conceptual framework of causality and estimated the effects of environmental and socioeconomic determinants of morbidity and lethality. Spatiotemporal risk patterns of morbidity and lethality differed. For morbidity, the pattern was mainly spatial, whereas lethality was mainly explained by the spatiotemporal interaction. The hypothesized causal model explained a relevant fraction of the heterogeneity in the spatial and spatiotemporal interaction patterns. The increase in soil moisture, precipitation, poverty, and the decrease in the proportion of urban households, acted as risk factors. The increase in the proportion of households in which waste is directly collected and in temperature were preventive factors. The structured temporal trend was increasing for morbidity and decreasing for lethality. In terms of morbidity, it was clear that the prioritization should be focused in a couple of states, mainly Acre. In terms of lethality, the allocation of resources need not be as asymmetric, but there was nonetheless a prioritization order. The proposed approach can be used to characterize spatiotemporal dynamics of other diseases and to inform decision makers.
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Project description:BackgroundHantavirus disease in humans is rare but frequently lethal in the Neotropics. Several abundant and widely distributed Sigmodontinae rodents are the primary hosts of Orthohantavirus and, in combination with other factors, these rodents can shape hantavirus disease. Here, we assessed the influence of host diversity, climate, social vulnerability and land use change on the risk of hantavirus disease in Brazil over 24 years.MethodsLandscape variables (native forest, forestry, sugarcane, maize and pasture), climate (temperature and precipitation), and host biodiversity (derived through niche models) were used in spatiotemporal models, using the 5570 Brazilian municipalities as units of analysis.ResultsAmounts of native forest and sugarcane, combined with temperature, were the most important factors influencing the increase of disease risk. Population at risk (rural workers) and rodent host diversity also had a positive effect on disease risk.ConclusionsLand use change-especially the conversion of native areas to sugarcane fields-can have a significant impact on hantavirus disease risk, likely by promoting the interaction between the people and the infected rodents. Our results demonstrate the importance of understanding the interactions between landscape change, rodent diversity, and hantavirus disease incidence, and suggest that land use policy should consider disease risk. Meanwhile, our risk map can be used to help allocate preventive measures to avoid disease.
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Project description:The Subprime Bubble preceding the Subprime Crisis of 2008 was fueled by risky lending practices, manifesting in the form of a large abrupt increase in the proportion of subprime mortgages issued in the US. This event also coincided with critical slowing down signals associated with instability, which served as evidence of a regime shift or phase transition in the US housing market. Here, we show that the US housing market underwent a regime shift between alternate stable states consistent with the observed critical slowing down signals. We modeled this regime shift on a universal transition path and validated the model by estimating when the bubble burst. Additionally, this model reveals loose monetary policy to be a plausible cause of the phase transition, implying that the bubble might have been deflatable by a timely tightening of monetary policy.
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Project description:Background and objectivesThe US housing market has experienced considerable fluctuations over the last decades. This study aimed to investigate the impacts of housing price dynamics on physical health, mental health, and health-related behaviors for older American outright owners, mortgaged owners, and renters.Research design and methodsWe drew longitudinal data from the 1992-2016 Health and Retirement Study and merged it to the 5-digit zip code-level Housing Price Index. The analytic sample comprised 34 182 persons and 174 759 person-year observations. We used a fixed-effects model to identify the health impacts of housing price dynamics separately for outright owners, mortgaged owners, and renters.ResultsA 100% increase in Housing Price Index was associated with a 2.81 and 3.50 percentage points (pp) increase in the probability of reporting excellent/very good/good health status for mortgage owners and renters, respectively. It was also related to a lower likelihood of obesity (1.82 pp) for outright owners and a lesser chance of obesity (2.85 pp) and smoking (3.03 pp) for renters. All of these relationships were statistically significant (p < .05). Renters also experienced significantly decreased depression scores (-0.24), measured by the Center for Epidemiologic Studies-Depression scale, associated with the same housing price changes.Discussion and implicationsHousing price dynamics have significant health impacts, and renters are more sensitive to fluctuations in the housing market. Our study rules out the wealth effect as the mechanism through which changes in housing prices affect older adults' health. Our findings may inform policies to promote older adults' health by investing in local area amenities and improving socioeconomic conditions.
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Project description:The database presented here was collected by Antoniucci and Marella to analyze the correlation between the housing price gradient and the immigrant population in Italy during 2016. It may also be useful in other statistical analyses, be they on the real estate market or in another branches of social science. The data sample relates to 112 Italian provincial capitals. It provides accurate information on urban structure, and specifically on urban density. The two most significant variables are original indicators constructed from official data sources: the housing price gradient, or the ratio between average prices in the center and suburbs by city; and building density, which is the average number of housing units per residential building. The housing price gradient is calculated for the two residential sub-markets, new-build and existing units, providing an original and detailed sample of the Italian residential market. Rather than average prices, the housing price gradient helps to identify potential divergences in residential market trends. As well as house prices, two other data clusters are considered: socio-economic variables, which provide a framework of each city, in terms of demographic and economic information; and various data on urban structure, which are rarely included in the same database.
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