scholarly journals An Environmental GIS-based Variable Analysis of SARS-CoV-2 in the City of Recife, Brazil

2020 ◽  
Author(s):  
Arthur Souza ◽  
Caroline Mota ◽  
Amanda Rosa ◽  
Ciro Figueiredo ◽  
Ana Lucia Candeias
Keyword(s):  
Low Income ◽  
Public Services ◽  
Spatial Regression ◽  
Case Fatality ◽  
Global Scale ◽  
Environmental Data ◽  
Data Sets ◽  
Spatial Regression Analysis ◽  
Effective Drugs ◽  
The City

Abstract Background: Given the increasing rates at which cases of people infected by Covid-19 have been evolving to case-fatality rates on a global scale and the context of there being a world-wide socio-economic crisis, decision-making must be undertaken based on prioritizing effective measures to control and combat the disease since there is a lack of effective drugs and as yet no vaccine. Method: This paper explores the determinant factors of the COVID-19 pandemic and its impacts on Recife, Pernambuco-Brazil by performing both local and global spatial regression analysis on two types of environmental data-sets. Data were obtained from ten specific days between late April and early July 2020, comprehending the ascending, peak and descending behaviours of the curve of infections.Results: This study highlights the importance of identifying and mapping clusters of the most affected neighbourhoods and their determinant effects. We have identified that it is increasingly common for there to be a phase in which hotspots of confirmed cases appear in a well-developed and heavily densely-populated neighbourhood of the city of Recife. From there, the disease is carried to areas characterised by having a precarious provision of public services and a low-income population and this quickly creates hotspots of case-fatality rates. The results also help to understand the influence of the age, income, level of education of the population and, additionally, of the extent to which they can access public services, on the behaviour of the virus across neighbourhoods.Conclusion: This study supports government measures against the spread of Covid-19 in heterogeneous cities, evidencing social inequality as a driver for a high incidence of fatal cases of the disease. Understanding the variables which influence the local dynamics of the virus spread becomes vital for identifying the most vulnerable regions for which prevention actions need to be developed.

scholarly journals An Environmental GIS-based Variable Analysis on SARS-CoV-2 in the City of Recife, Brazil

2020 ◽  
Author(s):  
Arthur Souza ◽  
Caroline Maria de Miranda Mota ◽  
Amanda Rosa ◽  
Ciro Figueiredo ◽  
Ana Lucia Candeias
Keyword(s):  
Low Income ◽  
Public Services ◽  
Spatial Regression ◽  
Case Fatality ◽  
Global Scale ◽  
Environmental Data ◽  
Data Sets ◽  
Spatial Regression Analysis ◽  
Effective Drugs ◽  
The City

Abstract Background: Given the increasing rates at which people have been infected by Covid-19 evolving to case-fatality rates on a global scale and the context of there being a world-wide socio-economic crisis, decision-making must be undertaken based on prioritizing effective measures to control and combat the disease since there is a lack of effective drugs. Method: This paper explores the determinant factors of the COVID-19 pandemic and its impacts on Recife, Pernambuco-Brazil by performing both local and global spatial regression analysis on two types of environmental data-sets. Data were obtained from ten specific days between late April and early July 2020, comprehending the ascending, peaking and descending behaviours of the curve of infections.Results: This study highlights clusters of the most affected neighbourhoods and their determinant effects. We have observed the increasing phase with hotspots of confirmed cases in a well-developed and heavily densely-populated neighbourhood of Recife city, then evolving for hotspots of case-fatality rates into areas characterised by having a precarious provision of public services and low-income population. The results also help to understand the influence of the age, income, level of education of the population and, additionally, the people’s access to public services, on the behaviour of the virus across neighbourhoods.Conclusion: This study supports government measures against the spread of Covid-19 in heterogeneous cities, evidencing social inequality as a driver for a high incidence of fatal cases of the disease. Understanding the variables which influence the local dynamics of the virus spread becomes vital for identifying the most vulnerable regions for which prevention actions need to be developed.

scholarly journals Informal Land Sale and Housing in the Periphery of Pointe-Noire

2016 ◽  
Vol 51 (1) ◽  
pp. 29-54
Author(s):  
Gabriel Tati
Keyword(s):  
Urban Sprawl ◽  
Low Income ◽  
Public Services ◽  
Spatial Differentiation ◽  
Pointe Noire ◽  
Customary Land ◽  
Congo Brazzaville ◽  
Land Transactions ◽  
The City

This article examines the relations between practices in informal land transactions under customary tenure and spatial differentiation among suburbs in the periphery of the city of Pointe-Noire, Congo-Brazzaville. Urban sprawl is a permanent feature of urbanisation in Congo-Brazzaville that not only propagates slums for low-income dwellers but also entails locally embedded ways of building the city in the absence of state-led planning. The case of Pointe-Noire shows that large tracts of customary land are sold without public control, a process accompanied by the emergence of new suburbs with different stylistic patterns of housing. While suburbanisation does carry the potential to improve the quality of housing by attracting wealthy residents, it exacerbates spatial fragmentation and the exclusion of certain groups in the population from access to both land for housing in upmarket suburbs and public services. Powerful actors tend to profit most from informality.

Discussing the determinants of online budget transparency based on a spatial regression analysis of Croatian cities and municipalities: Do good neighbours make you better?

2020 ◽  
Vol 23 (3) ◽  
pp. 268-287
Author(s):  
Paulo Reis Mourao ◽  
Mihaela Bronić ◽  
Branko Stanić
Keyword(s):  
Spatial Regression ◽  
Eastern European ◽  
Public Employees ◽  
Direct Effects ◽  
Spatial Lag ◽  
Goods And Services ◽  
European Democracy ◽  
Local Budget ◽  
Spatial Regression Analysis ◽  
The City

Taxpayers want to pay as little in taxes as possible to fund an adequate level of public goods and services in their local government, and so they need to keep their local incumbents accountable. Online local budget transparency (OLBT) facilitates this accountability, as it enables citizens to find information online about their local budgets that is timely, accurate, comprehensive and understandable. The aim of this article is to identify the most important determinants of OLBT for all 556 Croatian cities and municipalities from 2014 to 2017. Using a dynamic spatial lag Durbin model, the analysis explores the direct and indirect effects of potential determinants on OLBT. The main contribution is the pioneering use of a dynamic spatial lag Durbin model for researching local budget transparency determinants in a Central and Eastern European democracy. The results show that neighbours have an influence on OLBT but that direct effects dominate; that is, the major OLBT determinants come from within each city/municipality. Particularly important determinants are residents’ income, the local government’s wealth, the number of public employees in the city/municipality and the population size.

scholarly journals COVID-19 case-fatality rate and demographic and socioeconomic influencers: a worldwide spatial regression analysis based on country-level data

2020 ◽  
Author(s):  
Yang Cao ◽  
Ayako Hiyoshi ◽  
Scott Montgomery
Keyword(s):  
Population Size ◽  
Spatial Regression ◽  
Case Fatality ◽  
Country Level ◽  
Level Data ◽  
Lower Treatment ◽  
Active Testing ◽  
Large Populations ◽  
Spatial Regression Analysis ◽  
Testing Policies

We used the COVID-19 dataset obtained from the Our World in Data website and investigated the associations between COVID-19 CFR and nine country-level indices of 209 countries/territories using the Matern correlation regression model. Spatial dependence among the data was controlled using the latitude and longitude of the centroid of the countries/territories. Stratified analyses were conducted by economic level and COVID-19 testing policy. The average of country/territory-specific COVID-19 CFR is about 2-3% worldwide, which is higher than previously reported at 0.7-1.3%. Statistically significant associations were observed between COVID-19 CFR and population size and proportion of female smokers. The open testing policies are associated with decreased CFR. Strictness of anti-COVID-19 measures was not statistically significantly associated with CFR overall, but the higher stringency index was associated with higher CFR in higher income countries with active testing policies. The statistically significant association between population size and COVID-19 CRF suggests the healthcare strain and lower treatment efficiency in countries with large populations. The observed association between smoking in females and COVID-19 CFR might be due to that the proportion of female smokers reflected broadly income level of a country. When testing is warranted and healthcare resources are sufficient, strict quarantine and/or lockdown measures might result in excess deaths in underprivileged populations.

scholarly journals Comparing spatial regression to random forests for large environmental data sets

PLoS ONE ◽  
2020 ◽  
Vol 15 (3) ◽  
pp. e0229509
Author(s):  
Eric W. Fox ◽  
Jay M. Ver Hoef ◽  
Anthony R. Olsen
Keyword(s):  
Random Forests ◽  
Spatial Regression ◽  
Environmental Data ◽  
Data Sets

scholarly journals Will Households Invest in Safe Sanitation? Results from an Experimental Demand Trial in Nakuru, Kenya

2021 ◽  
Vol 18 (9) ◽  
pp. 4462
Author(s):  
Rachel Peletz ◽  
Caroline Delaire ◽  
Joan Kones ◽  
Clara MacLeod ◽  
Edinah Samuel ◽  
...  
Keyword(s):  
Low Income ◽  
Low Income Countries ◽  
Health Concern ◽  
High Quality ◽  
Market Prices ◽  
Price Point ◽  
Improved Sanitation ◽  
Sanitation Infrastructure ◽  
The City ◽  
Experimental Demand

Unsafe sanitation is an increasing public health concern for rapidly expanding cities in low-income countries. Understanding household demand for improved sanitation infrastructure is critical for planning effective sanitation investments. In this study, we compared the stated and revealed willingness to pay (WTP) for high-quality, pour-flush latrines among households in low-income areas in the city of Nakuru, Kenya. We found that stated WTP for high-quality, pour-flush latrines was much lower than market prices: less than 5% of households were willing to pay the full costs, which we estimated between 87,100–82,900 Kenyan Shillings (KES), or 871–829 USD. In addition, we found large discrepancies between stated and revealed WTP. For example, 90% of households stated that they would be willing to pay a discounted amount of 10,000 KES (100 USD) for a high-quality, pour-flush latrine, but only 10% of households redeemed vouchers at this price point (paid via six installment payments). Households reported that financial constraints (i.e., lack of cash, other spending priorities) were the main barriers to voucher redemption, even at highly discounted prices. Our results emphasize the importance of financial interventions that address the sizable gaps between the costs of sanitation products and customer demand among low-income populations.

scholarly journals Reproducing scientists’ mobility: a data-driven model

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Giacomo Vaccario ◽  
Luca Verginer ◽  
Frank Schweitzer
Keyword(s):  
Decision Rules ◽  
Migration Policy ◽  
Large Data ◽  
Global Scale ◽  
Global Network ◽  
Data Sets ◽  
Mobility Patterns ◽  
Agent Based ◽  
Hiring Process ◽  
Geographical Distances

AbstractHigh skill labour is an important factor underpinning the competitive advantage of modern economies. Therefore, attracting and retaining scientists has become a major concern for migration policy. In this work, we study the migration of scientists on a global scale, by combining two large data sets covering the publications of 3.5 million scientists over 60 years. We analyse their geographical distances moved for a new affiliation and their age when moving, this way reconstructing their geographical “career paths”. These paths are used to derive the world network of scientists’ mobility between cities and to analyse its topological properties. We further develop and calibrate an agent-based model, such that it reproduces the empirical findings both at the level of scientists and of the global network. Our model takes into account that the academic hiring process is largely demand-driven and demonstrates that the probability of scientists to relocate decreases both with age and with distance. Our results allow interpreting the model assumptions as micro-based decision rules that can explain the observed mobility patterns of scientists.

scholarly journals COVID-19 Pandemic in Rio de Janeiro, Brazil: A Social Inequality Report

Medicina ◽  
2021 ◽  
Vol 57 (6) ◽  
pp. 596
Author(s):  
Yago Bernardo ◽  
Denes do Rosario ◽  
Carlos Conte-Junior
Keyword(s):  
Observational Study ◽  
Social Inequality ◽  
Rio De Janeiro ◽  
Case Fatality Rate ◽  
Case Fatality ◽  
Mitigation Measures ◽  
Fatality Rate ◽  
Retrospective Report ◽  
The Social ◽  
The City

Background and Objectives: To perform a retrospective report on the lethality of COVID-19 in different realities in the city of Rio de Janeiro (RJ). Materials and Methods: We accomplished an observational study by collecting the data about total confirmed cases and deaths due to COVID-19 in the top 10 high social developed neighborhoods and top 10 most populous favelas in RJ to determine the case-fatality rate (CFR) and compare these two different realities. Results: CFR was significatively higher in poverty areas of RJ, reaching a mean of 9.08% in the most populous favelas and a mean of 4.87% in the socially developed neighborhoods. Conclusions: The social mitigation measures adopted in RJ have benefited only smaller portions of the population, excluding needy communities.

scholarly journals Spatial Accessibility to Local Public Services in an Unequal Place: An Analysis from Patterns of Residential Segregation in the Metropolitan Area of Santiago, Chile

2021 ◽  
Vol 13 (2) ◽  
pp. 442
Author(s):  
Yasna Cortés
Keyword(s):  
Residential Segregation ◽  
Metropolitan Area ◽  
Low Income ◽  
Public Services ◽  
Housing Prices ◽  
Spatial Association ◽  
Spatial Accessibility ◽  
Urban Systems ◽  
Local Public Services ◽  
Low Income Groups

The study of the relationship between the provision of local public services and residential segregation is critical when it might be the social manifestation of spatial income inequality. This paper analyzes how the spatial accessibility to local public services is distributed equitably among different social and economic groups in the Metropolitan Area of Santiago (MR), Chile. To accomplish this objective, I use accessibility measures to local public services such as transportation, public education, healthcare, kindergartens, parks, fire and police stations, cultural infrastructure, and information about housing prices and exempted housing units from local taxes by block, as well as quantile regressions and bivariate Local Indicators of Spatial Association (LISA). The main results confirm the accessibility to local public services is unequally distributed among residents. However, it affects more low-income groups who are suffering from significant deficits in the provision of local public services. In this scenario, poor residents face a double disadvantage due to their social exclusion from urban systems and their limited access to essential services such as education, healthcare, or transportation. In particular, I found that social residential segregation might be reinforced by insufficient access to local infrastructure that the most impoverished population should assume.

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