Spatio-temporal trends in the risk of adolescent pregnancy in Minas Gerais, Brazil, 2000–2015

Abstract Purpose To investigate, through a spatio-temporal analysis, the association between the percentages of live births of adolescent mothers (LBAM) and the human development index (HDI), including the three components: income, education and longevity. Methods The percentage of LBAM was obtained from the Brazilian Live Births Information System for the state of Minas Gerais, Brazil in the period 2000–2015 and the HDI data and its components were obtained from United Nations Development Program’s (UNDP) Human Development Reports. A generalized additive model (GAM) was used to estimate the relative risk of LBAM in relation to the HDI and to identify spatial clusters of the geographical distribution of LBAM, the Moran global and local index was used. Results There is an association between the HDI and its components with LBAM. The high values of relative risk are spatially concentrated in the northern part of the state of Minas Gerais. The graphs indicated a nonlinear relationship between LBAM over the years. Conclusions There is a strong spatial dependence of LBAM in Minas Gerais, which suggests that a geographical location plays a fundamental role in understanding it. The regional disparity confirmed in this study is inherent in the process of human development, it is important for planning actions aimed at the development of these regions in order to minimize existing disparities.

Download Full-text

Spatio-temporal analysis between the incidence of COVID-19 and human development in Mato Grosso do Sul, Brazil

10.1101/2021.01.19.21250106 ◽

2021 ◽

Author(s):

Amaury de Souza ◽

Marcel Carvalho Abreu ◽

José Francisco de Oliveira-Júnior

Keyword(s):

Human Development ◽

Human Development Index ◽

Temporal Analysis ◽

The State ◽

Metropolitan Region ◽

Spatial Correlations ◽

Mato Grosso ◽

Development Index ◽

Spatio Temporal ◽

Mato Grosso Do Sul

AbstractObjetiveTo analyze the spatial distribution of the Covid-19 incidence and its correlation with the municipal human development index (IDHM) in the state of Mato Grosso do Sul (MS), Brazil.MethodsThis is an ecological, exploratory and analytical study whose units of analysis were the 79 municipalities that make up the state of MS. Covid-19 incidence coefficients, death numbers, lethality rate, mortality rate and Human Development Index for municipalities (IDHM) in the period from March 2020 to December 31, 2020 were used. spatial correlations between the variables mentioned above.ResultsThe incidence of Covid-19 has spatial dependence with moderate positive correlation and formation of clusters located in the Metropolitan Region of Campo Grande (RMCG) and municipalities in the region.ConclusionThe uneven mapping of Covid-19 and its relationship with IDHM in the Ministry of Health can contribute to actions to address the regional pandemic.

Download Full-text

Spatio-temporal analysis of the state of sports facilities in Slovenia from 1975 to 2012

Geodetski vestnik ◽

10.15292/geodetski-vestnik.2013.03.544-560 ◽

2013 ◽

Vol 57 (03) ◽

pp. 544-560

Author(s):

Simon Starček ◽

Dušan Petrovič

Keyword(s):

Temporal Analysis ◽

The State ◽

Sports Facilities ◽

Spatio Temporal

Download Full-text

Mapping Evapotranspiration, Vegetation and Precipitation Trends in the Catchment of the Shrinking Lake Poopó

Remote Sensing ◽

10.3390/rs12010073 ◽

2019 ◽

Vol 12 (1) ◽

pp. 73 ◽

Cited By ~ 1

Author(s):

Juan Torres-Batlló ◽

Belén Martí-Cardona ◽

Ramiro Pillco-Zolá

Keyword(s):

Land Cover ◽

Vegetation Index ◽

Temporal Trends ◽

Temporal Analysis ◽

Mountain Range ◽

Water Losses ◽

Essential Information ◽

General Decline ◽

Increasing Trend ◽

Spatio Temporal

Lake Poopó is located in the Andean Mountain Range Plateau or Altiplano. A general decline in the lake water level has been observed in the last two decades, coinciding roughly with an intensification of agriculture exploitation, such as quinoa crops. Several factors have been linked with the shrinkage of the lake, including climate change, increased irrigation, mining extraction and population growth. Being an endorheic catchment, evapotranspiration (ET) losses are expected to be the main water output mechanism and previous studies demonstrated ET increases using Earth observation (EO) data. In this study, we seek to build upon these earlier findings by analyzing an ET time series dataset of higher spatial and temporal resolution, in conjunction with land cover and precipitation data. More specifically, we performed a spatio-temporal analysis, focusing on wet and dry periods, that showed that ET changes occur primarily in the wet period, while the dry period is approximately stationary. An analysis of vegetation trends performed using 500 MODIS vegetation index products (NDVI) also showed an overall increasing trend during the wet period. Analysis of NDVI and ET across land cover types showed that only croplands had experienced an increase in NDVI and ET losses, while natural covers showed either constant or decreasing NDVI trends together with increases in ET. The larger increase in vegetation and ET losses over agricultural regions, strongly suggests that cropping practices exacerbated water losses in these areas. This quantification provides essential information for the sustainable planning of water resources and land uses in the catchment. Finally, we examined the spatio-temporal trends of the precipitation using the newly available Climate Hazards Group Infrared Precipitation with Stations (CHIRPS-v2) product, which we validated with onsite rainfall measurements. When integrated over the entire catchment, precipitation and ET showed an average increasing trend of 5.2 mm yr−1 and 4.3 mm yr−1, respectively. This result suggests that, despite the increased ET losses, the catchment-wide water storage should have been offset by the higher precipitation. However, this result is only applicable to the catchment-wide water balance, and the location of water may have been altered (e.g., by river abstractions or by the creation of impoundments) to the detriment of the Lake Poopó downstream.

Download Full-text

Spatio-Temporal Patterns of the 2019-nCoV Epidemic at the County Level in Hubei Province, China

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17072563 ◽

2020 ◽

Vol 17 (7) ◽

pp. 2563 ◽

Cited By ~ 8

Author(s):

Wentao Yang ◽

Min Deng ◽

Chaokui Li ◽

Jincai Huang

Keyword(s):

Temporal Dynamics ◽

Spatial Interaction ◽

Temporal Trends ◽

Temporal Patterns ◽

Temporal Analysis ◽

Hubei Province ◽

Incidence Rates ◽

County Level ◽

Spatial Clusters ◽

Spatio Temporal

Understanding the spatio-temporal characteristics or patterns of the 2019 novel coronavirus (2019-nCoV) epidemic is critical in effectively preventing and controlling this epidemic. However, no research analyzed the spatial dependency and temporal dynamics of 2019-nCoV. Consequently, this research aims to detect the spatio-temporal patterns of the 2019-nCoV epidemic using spatio-temporal analysis methods at the county level in Hubei province. The Mann–Kendall and Pettitt methods were used to identify the temporal trends and abrupt changes in the time series of daily new confirmed cases, respectively. The local Moran’s I index was applied to uncover the spatial patterns of the incidence rate, including spatial clusters and outliers. On the basis of the data from January 26 to February 11, 2020, we found that there were 11 areas with different types of temporal patterns of daily new confirmed cases. The pattern characterized by an increasing trend and abrupt change is mainly attributed to the improvement in the ability to diagnose the disease. Spatial clusters with high incidence rates during the period were concentrated in Wuhan Metropolitan Area due to the high intensity of spatial interaction of the population. Therefore, enhancing the ability to diagnose the disease and controlling the movement of the population can be confirmed as effective measures to prevent and control the regional outbreak of the epidemic.

Download Full-text

Spatio-temporal analysis and visualisation of the anthrax epidemic situation in livestock in Kazakhstan over the period 1933-2016

Geospatial health ◽

10.4081/gh.2017.589 ◽

2017 ◽

Cited By ~ 1

Author(s):

Sarsenbay K. Abdrakhmanov ◽

Yersyn Y. Mukhanbetkaliyev ◽

Fedor I. Korennoy ◽

Bolat Sh. Karatayev ◽

Aizada A. Mukhanbetkaliyeva ◽

...

Keyword(s):

Temporal Trends ◽

Small Ruminants ◽

Temporal Analysis ◽

Space Time ◽

Decision Makers ◽

Annual Number ◽

Spatio Temporal ◽

The Republic ◽

Increasing Trends ◽

Historical Periods

An analysis of the anthrax epidemic situation among livestock animals in the Republic of Kazakhstan over the period 1933-2016 is presented. During this time, 4,064 anthrax outbreaks (mainly in cattle, small ruminants, pigs and horses) were recorded. They fall into five historical periods of increase and decrease in the annual anthrax incidence (1933-1953; 1954-1968; 1969-1983; 1984- 2001; and 2002-2016), which has been associated with changes in economic activity and veterinary surveillance. To evaluate the temporal trends of incidence variation for each of these time periods, the following methods were applied: i) spatio-temporal analysis using a space-time cube to assess the presence of hotspots (i.e., areas of outbreak clustering) and the trends of their emergence over time; and ii) a linear regression model that was used to evaluate the annual numbers of outbreaks as a function of time. The results show increasing trends during the first two periods followed by a decreasing trend up to now. The peak years of anthrax outbreaks occurred in 1965-1968 but outbreaks still continue with an average annual number of outbreaks of 1.2 (95% confidence interval: 0.6-1.8). The space-time analysis approach enabled visualisation of areas with statistically significant increasing or decreasing trends of outbreak clustering providing a practical opportunity to inform decision-makers and allowing the veterinary services to concentrate their efforts on monitoring the possible risk factors in the identified locations.

Download Full-text

Measuring multidimensional poverty in the state of Minas Gerais, Brazil: looking beyond income

Revista de Administração Pública ◽

10.1590/0034-7612154852 ◽

2018 ◽

Vol 52 (3) ◽

pp. 386-416

Author(s):

Murilo Fahel ◽

Leticia Ribeiro Teles

Keyword(s):

Health Education ◽

Human Development ◽

Multidimensional Poverty ◽

Minas Gerais ◽

The State ◽

Standard Of Living ◽

Sample Survey ◽

Amartya Sen ◽

Poverty Index ◽

Multidimensional Poverty Index

Abstract The multidimensional poverty index (MPI) was developed by the Oxford Poverty & Human Development Initiative (Ophi) in 2010. The MPI is established on indicators of health, education and standard of living. The concept of multidimensionality is anchored on the theory of poverty and human development elaborated by the indian economist Amartya Sen in the 1980s. The methodology used for the modeling of this study is based on Alkire and Foster - AF (2011) and analyzes the incidence and intensity of poverty. The purpose of this paper focuses on the application of the MPI in the state of Minas Gerais, Brazil and uses the Household Sample Survey produced by João Pinheiro Foundation (FJP) in 2009, 2011 and 2013. The results indicate that the MPI is relativaly low, 0.0329 (2009), 0.0226 (2011) and 0.0155 (2013), indicating there is a tendency for decreasing along the years.

Download Full-text

Analysis of the spatio-temporal dynamics of incidence, mortality and test rates (rapid and RT-PCR) of COVID-19 in the state of Minas Gerais, Brazil

Revista de Epidemiologia e Controle de Infecção ◽

10.17058/reci.v1i1.15605 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Milton José Da Silva-Júnior ◽

Kaio Saramago Mendonça ◽

Caio Augusto De Lima ◽

Priscilla Larissa Silva Pires ◽

Tatiany Calegari ◽

...

Keyword(s):

Temporal Dynamics ◽

Minas Gerais ◽

The State ◽

Rt Pcr ◽

Spatio Temporal

Download Full-text

Spatio-Temporal Analysis of Heating and Cooling Degree-Days Over Iran

10.21203/rs.3.rs-441421/v1 ◽

2021 ◽

Author(s):

Amin Sadeqi ◽

Hossein Tabari ◽

Yagob Dinpashoh

Keyword(s):

Time Series ◽

Energy Demand ◽

Temporal Trends ◽

Temporal Analysis ◽

Degree Days ◽

Heating And Cooling ◽

Cooling Degree Days ◽

Spatio Temporal ◽

Heating Degree Days ◽

Cooling Energy Demand

Abstract Climate change affects the energy demand in different sectors of the society. To investigate this possible impact, in this research, temporal trends and change points in heating degree-days (HDD), cooling degree-days (CDD), and their simultaneous combination (HDD+CDD) were analysed for a 60-year period (1960-2019) in Iran. The results show that less than 20% of the study stations had significant trends (either upward or downward) in HDD time series, while more than 80% of the stations had significant increasing trends in CDD and HDD+CDD time series. Abrupt changes in HDD time series mostly occurred in the early 1980s, but those in CDD time series were mostly observed in the 1990s. The cooling energy demand in Iran has dramatically increased as CDD values have raised up from 690 ºC-days to 1010 ºC-days in the last 60 years. HDD, however, almost remained constant in the same period. The results suggest that if global warming continues with the current pace, cooling energy demand in the residential sector will considerably increase in the future, calling for a change in residential energy consumption policies.

Download Full-text