scholarly journals Gentrification, mobility patterns and health in Lisbon: a time series’ analysis from 2008 to 2018

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
R Sá ◽  
E Soares dos Santos ◽  
T Gabriel ◽  
A Moreira ◽  
P Giraldo

Abstract Background Mobility patterns have a great impact on health. The use of cars is known to be related with increasing air pollution, noise and accidents, and less active transportation, leading to cardiovascular, oncological or respiratory diseases, among others. Gentrification is a process through which the rising value of a geographical area displaces low-income inhabitants, mostly due to rising rents, mortgages and property taxes. This change has the potential for relocating long-time residents and businesses. The aim of this study was to quantify the effect of gentrification in the car influx in the city of Lisbon. Methods A time series' analysis was performed using public ecological data, from 2008 to 2018, of habitation costs per square meter (as a proxy of gentrification) and the number of cars that entered Lisbon through accessing highways. The model was adjusted for confounding factors such as Lisbon's gross income and fuel prices. Results We verified the effect of seasonality in the car influx, with peaks before and after summer - july and october - and a downward trend until 2013 that then inflected and started an upward trend from 2014 to 2018. Habitation costs were positively correlated with car influx into the city (R2=0.773; p < 0.001). In the model, 1€/m2 of increment in housing prices corresponded to 200 more cars that entered the city. Conclusions In Lisbon, gentrification was associated with the increasing number of cars entering the city. These findings may have implications in future policies that regulate housing and mobility. Further research is needed to fully understand the causal pathways of this phenomenon. Key messages Mobility patterns have a great influence on health, and gentrification may influence them. The increase of 1€ per square meter in housing prices lead to an increase of the influx of cars of 200.

PLoS ONE ◽  
2014 ◽  
Vol 9 (8) ◽  
pp. e105130 ◽  
Author(s):  
Pierre Fournier ◽  
Alexandre Dumont ◽  
Caroline Tourigny ◽  
Aline Philibert ◽  
Aliou Coulibaly ◽  
...  

Author(s):  
Ravindra S. Kembhavi ◽  
Saurabha U. S.

Background: Dengue fever is a major public health problem, the concern is high as the disease is closely related to climate change.Methods: This was a retrospective study, conducted for 1 year in a tertiary care hospital in the city of Mumbai. Data of Dengue cases and climate for the city of Mumbai between 2011 and 2015 were obtained. Data was analysed using SPSS- time series analysis and forecasting model.Results: 33% cases belonged to the 21-30 years, proportion of men affected were more than women. A seasonal distribution of cases was observed. A strong correlation was noted between the total number of cases reported and (a) mean monthly rainfall and (b) number of days of rainfall. ARIMA model was used for forecasting.Conclusions: The trend analysis along with forecasting model helps in being prepared for the year ahead. 


2010 ◽  
Vol 41 (1/2) ◽  
pp. 90 ◽  
Author(s):  
Simone Andrea Pozza ◽  
Ed Pinheiro Lima ◽  
Tatiane Tagino Comin ◽  
Marcelino Luiz Gimenes ◽  
Jose Renato Coury

2021 ◽  
Vol 56 (3) ◽  
pp. 398-412
Author(s):  
Mauricio Do Nascimento Moura ◽  
Maria Isabel Vitorino ◽  
Glauber Guimarães Cirino da Silva ◽  
Valdir Soares de Andrade Filho

This study examines the relationship between the time-series analysis of climate, deforestation, wildfire, Aerosol Optical Depth (AOD), and hospital admissions for respiratory diseases in the Eastern Amazon. Through a descriptive study with an ecological approach of an 18-year time-series analysis, we made a statistical analysis of two pre-established periods, namely, the rainy season and the dry season. On a decadal scale, analyzing the signals of climate indices [i.e., the Southern Oscillation Index (SOI) and the Atlantic Meridional Mode (AMM)], the city of Marabá presents correlations between hospital admissions, wildfire, and AOD. This is not observed with the same accuracy in Santarém. On a seasonal scale, our analysis demonstrated how both cities in this research presented an increase in the number of hospital admissions during the dry season: Marabá, 3%; Santarém, 5%. The same season also presented a higher number of fire outbreaks, AOD, and higher temperatures. The AOD monthly analysis showed that the atmosphere of Marabá may be under the influence of other types of aerosols, such as those from mining activities. There is a time lag of approximately 2 months in the records of wildfire in the city. Such lag is not found in Santarém. The linear regression analysis shows that there is a correlation above 64% (Marabá) and 50% (Santarém), which is statistically significant because it proves that the number of hospital admissions for respiratory diseases is dependable on the AOD value. From the cities in the study, Marabá presents the highest incidence of wildfire, with an average of 188.5— the average in Santarém is 68.7—, and therefore the highest AOD value, with an average of 0.66 (Santarém, 0.47), both during the dry season. It is evident that the climate component has a relevant contribution to the increase in the number of hospital admissions, especially during the rainy season, where there are few or no records of wildfires.


2021 ◽  
Vol 31 (3) ◽  
pp. 496-506
Author(s):  
Andre Evaristo Marcondes Cesar ◽  
Blanca Elena Guerrero Daboin ◽  
Tassiane Cristina Morais ◽  
Isabella Portugal ◽  
Jorge De Oliveira Echeimberg ◽  
...  

Introduction: Inserted in the vulnerable context of the Brazilian Amazon, the state of Tocantins has suffered damages with the dissemination of COVID-19 in its territory; however, little evidence is published from this state. Objective: This study aims to analyze the case-fatality, mortality, and incidence of COVID-19 in Tocantins. Methods: This is an ecological study, population-based, time-series analysis of COVID-19 cases and deaths in the state of Tocantins from March 2020 to August 2021. Results: During the examined period, 219,031 COVID-19 cases, and 3,594 deaths were registered due to disease. Two possible occurrence peaks were characterized in this time-series analysis. Remarkably, the Second Wave had the highest lethality rates (3.02% - April 2021), mortality (39.81 deaths per 100,000 inhabitants – March 2021), and incidence (1,938.88 cases per 100,000 inhabitants – March 2021). At the end of the period, mortality, incidence, and lethality showed flat trends, suggesting a positive outcome of the vaccination program. Conclusion: The prevention, surveillance, and control actions of COVID-19 cases in Tocantins State have been directed to mitigate the deleterious effects of the pandemic. Nevertheless, efforts are still needed to decrease lethality, mortality, and incidence trends, and ultimately to achieve control of the COVID-19 pandemic in the region.


2020 ◽  
Author(s):  
Marta Ellena ◽  
Joan Ballester ◽  
Paola Mercogliano ◽  
Elisa Ferracin ◽  
Giuliana Barbato ◽  
...  

Abstract The authors have withdrawn this preprint due to author disagreement.


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