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

2020 ◽  
Vol 17 (7) ◽  
pp. 2563 ◽  
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.

THE NEW RADIOCARBON DATASET FOR TRILITH MONUMENTS OF SOUTHEASTERN ARABIA

Radiocarbon ◽  
2020 ◽  
pp. 1-11
Author(s):  
R Garba ◽  
P Demján ◽  
I Svetlik ◽  
D Dreslerová
Keyword(s):  
Iron Age ◽  
Temporal Patterns ◽  
Temporal Analysis ◽  
Coastal Plains ◽  
Spatial And Temporal Patterns ◽  
Two Phase ◽  
Stone Monuments ◽  
South Central ◽  
Geographical Expansion ◽  
Spatio Temporal

ABSTRACT Triliths are megalithic monuments scattered across the coastal plains of southern and southeastern Arabia. They consist of aligned standing stones with a parallel row of large hearths and form a space, the meaning of which is undoubtedly significant but nonetheless still unknown. This paper presents a new radiocarbon (14C) dataset acquired during the two field seasons 2018–2019 of the TSMO (Trilith Stone Monuments of Oman) project which investigated the spatial and temporal patterns of the triliths. The excavation and sampling of trilith hearths across Oman yielded a dataset of 30 new 14C dates, extending the use of trilith monuments to as early as the Iron Age III period (600–300 BC). The earlier dates are linked to two-phase trilith sites in south-central Oman. The three 14C pairs collected from the two-phase trilith sites indicated gaps between the trilith construction phases from 35 to 475 years (2 σ). The preliminary spatio-temporal analysis shows the geographical expansion of populations using trilith monuments during the 5th to 1st century BC and a later pull back in the 1st and 2nd century AD. The new 14C dataset for trilith sites will help towards a better understanding of Iron Age communities in southeastern Arabia.

scholarly journals Spatio-temporal dynamics of schistosomiasis in Rwanda between 2001 and 2012: impact of the national Neglected Tropical Disease control programme

2017 ◽  
Vol 12 (1) ◽  
Author(s):  
Elias Nyandwi ◽  
Tom Veldkamp ◽  
Frank Badu Osei ◽  
Sherif Amer
Keyword(s):  
Temporal Dynamics ◽  
Public Health Problem ◽  
Incidence Rates ◽  
Control Programme ◽  
Scan Statistics ◽  
Major Public Health Problem ◽  
Implementation Phase ◽  
Incidence Data ◽  
Spatio Temporal ◽  
The Impact

Schistosomiasis is recognised as a major public health problem in Rwanda. We aimed to identify the spatio-temporal dynamics of its distribution at a fine-scale spatial resolution and to explore the impact of control programme interventions. Incidence data of Schistosoma mansoni infection at 367 health facilities were obtained for the period 2001-2012. Disease cluster analyses were conducted using spatial scan statistics and geographic information systems. The impact of control interventions was assessed for three distinct sub-periods. Findings demonstrated persisting, emerging and re-emerging clusters of schistosomiasis infection across space and time. The control programme initially caused an abrupt increase in incidence rates during its implementation phase. However, this was followed by declining and disappearing clusters when the programme was fully in place. The findings presented should contribute to a better understanding of the dynamics of schistosomiasis distribution to be used when implementing future control activities, including prevention and elimination efforts.

scholarly journals Chlorophyll increases off the coasts of Japan after the 2011 tsunami using NASA/MODIS data

2014 ◽  
Vol 14 (8) ◽  
pp. 1999-2008 ◽  
Author(s):  
E. Sava ◽  
B. Edwards ◽  
G. Cervone
Keyword(s):  
Deep Water ◽  
Tsunami Wave ◽  
Temporal Patterns ◽  
Temporal Analysis ◽  
Maximum Force ◽  
Eastern Coast ◽  
Aqua Satellite ◽  
Spatio Temporal ◽  
Epicentral Region ◽  
Chlorophyll Concentrations

Abstract. Large chlorophyll anomalies are observed after the 2011 Japanese tsunami using the NASA MODIS instrument onboard the TERRA and AQUA satellites. These anomalies are observed both along the eastern coast of Japan, where the tsunami wave hit with maximum force, and in the deep water surrounding the epicentral region. Although both satellites show agreeing spatio-temporal patterns, larger anomalies are detected using the AQUA satellite. A temporal analysis shows increased chlorophyll concentrations immediately after the tsunami, and higher values are observed for nearly one month before reversing to pre-tsunami levels.

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

2019 ◽  
Vol 12 (1) ◽  
pp. 73 ◽  
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.

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

2017 ◽  
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.

Fog climatology analyses in coastal fog ecosystem at the Atacama Desert/Chile – spatio-temporal analysis of fog water characteristics and variability

2020 ◽  
Author(s):  
Juan Carlos Pastene ◽  
Alexander Siegmund ◽  
Camilo del Río ◽  
Pablo Osses
Keyword(s):  
Temporal Dynamics ◽  
Local Level ◽  
Global Radiation ◽  
Atacama Desert ◽  
Temporal Analysis ◽  
Local Network ◽  
Fog Water ◽  
Water Characteristics ◽  
Vertical Range ◽  
Spatio Temporal

<p>The coastal Chilean Atacama Desert comprise some of the driest areas of the world with anual mean precipitation partly less than 1 mm/year, like in the Tarapacá region. It is in these environments, where fog plays a relevant role for local ecosystems, like the so called <em>Tillandsia</em> Lomas. These fog ecosystems contain <em>Tillandsia landbeckii</em> as an endemic species, which covers a vertical range of about 800 to 1,250 m, related to fog availability. The study area “Oyarbide” (20°29’ S, 70°03’ W) is situated inland desert, over a range of 300 m elevation where the advective and orographic fog penetrate far enough to reach the east border of the site at around 1,200 m.</p> <p>On local level, the understanding of the fog climate characteristics and variability is still poor as well as knowledge about the driving parameters, the temporal dynamics and spatial gradients. For this reason, various parameters of fog climate are analysed and characterised on the basis of a local station network in order to determine the local fog climatology.</p> <p>From 2016, several high quality climatological stations (Thies Clima) were installed in “Oyarbide”, located in a transect from ca. 1,160 m to ca. 1,350 m in a distance between 10.3 km to 10.7 km from the coast. The local network of climate stations is generating a high temporal and spatial acquisition of climatological data of standard fog water (2 m), air temperature & humidity (2 m), surface temperature (5 cm), wind speed & direction (10 m & 2 m), air pressure, global radiation, leaf wetness and dew every 10 minutes until nowadays. Additionally, ten mini fog collectors (Mini FCs) were installed at the beginning 2019, covering a surface of ca. 3 km<sup>2</sup>, generating a monthly data of ground fog water collected (50 cm).</p> <p>First spatio-temporal analyses of different parameters of the local fog climate will be presented. The results of the study show a seasonal, monthly and daily variability, with altitudinal and vertical differences and oscillation. The results will serve as input for the understanding of the fog variability into hyperarid zones.</p>

scholarly journals Spatio-temporal dynamics of dengue in Brazil: seasonal travelling waves and determinants of regional synchrony

2018 ◽  
Author(s):  
Mikhail Churakov ◽  
Christian J. Villabona-Arenas ◽  
Moritz U.G. Kraemer ◽  
Henrik Salje ◽  
Simon Cauchemez
Keyword(s):  
Large Scale ◽  
Temporal Dynamics ◽  
Mosquito Control ◽  
Human Mobility ◽  
Travelling Waves ◽  
Seasonal Pattern ◽  
Temporal Analysis ◽  
Vector Ecology ◽  
Spatio Temporal ◽  
Dengue Epidemics

AbstractDengue continues to be the most important vector-borne viral disease globally and in Brazil, where more than 1.4 million cases and over 500 deaths were reported in 2016. Mosquito control programmes and other interventions have not stopped the alarming trend of increasingly large epidemics in the past few years.Here, we analyzed monthly dengue cases reported in Brazil between 2001 and 2016 to better characterize the key drivers of dengue epidemics. Spatio-temporal analysis revealed recurring travelling waves of disease occurrence. Using wavelet methods, we characterised the average seasonal pattern of dengue in Brazil, which starts in the western states of Acre and Rondônia, then travels eastward to the coast before reaching the northeast of the country. Only two states in the north of Brazil (Roraima and Amapá) did not follow the countrywide pattern and had inconsistent timing of dengue epidemics throughout the study period.We also explored epidemic synchrony and timing of annual dengue cycles in Brazilian regions. Using gravity style models combined with climate factors, we showed that both human mobility and vector ecology contribute to spatial patterns of dengue occurrence.This study offers a characterization of the spatial dynamics of dengue in Brazil and its drivers, which could inform intervention strategies against dengue and other arboviruses.Author summaryIn this paper we studied the synchronization of dengue epidemics in Brazilian regions. We found that a typical dengue season in Brazil can be described as a wave travelling from the western part of the country towards the east, with the exception of the two most northern equatorial states that experienced inconsistent seasonality of dengue epidemics.We found that the spatial structure of dengue cases is driven by both climate and human mobility patterns. In particular, precipitation was the most important factor for the seasonality of dengue at finer spatial resolutions.Our findings increase our understanding of large scale dengue patterns and could be used to enhance national control programs against dengue and other arboviruses.

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

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.

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

2018 ◽  
Vol 0 (0) ◽  
Author(s):  
Daiane Leite da Roza ◽  
Carla Maria Teixeira de Oliveira ◽  
Maria de Fátima Rodrigues Pereira de Pina ◽  
Denisa Maria de Melo Vasques de Mendonça ◽  
Edson Zangiacomi Martinez
Keyword(s):  
Relative Risk ◽  
Human Development ◽  
Adolescent Mothers ◽  
Temporal Trends ◽  
Temporal Analysis ◽  
Minas Gerais ◽  
The State ◽  
Local Index ◽  
Live Births ◽  
Spatio Temporal

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.

People and Mobile Robot Classification Through Spatio-Temporal Analysis of Optical Flow

2015 ◽  
Vol 29 (06) ◽  
pp. 1550021 ◽  
Author(s):  
Plinio Moreno ◽  
Dario Figueira ◽  
Alexandre Bernardino ◽  
José Santos-Victor
Keyword(s):  
Optical Flow ◽  
Temporal Patterns ◽  
Temporal Analysis ◽  
Feature Subset Selection ◽  
Classification Error ◽  
Support Vector ◽  
Feature Subset ◽  
People Detection ◽  
Mach Learn ◽  
Spatio Temporal

The goal of this work is to distinguish between humans and robots in a mixed human-robot environment. We analyze the spatio-temporal patterns of optical flow-based features along several frames. We consider the Histogram of Optical Flow (HOF) and the Motion Boundary Histogram (MBH) features, which have shown good results on people detection. The spatio-temporal patterns are composed of groups of feature components that have similar values on previous frames. The groups of features are fed into the FuzzyBoost algorithm, which at each round selects the spatio-temporal pattern (i.e. feature set) having the lowest classification error. The search for patterns is guided by grouping feature dimensions, considering three algorithms: (a) similarity of weights from dimensionality reduction matrices, (b) Boost Feature Subset Selection (BFSS) and (c) Sequential Floating Feature Selection (SFSS), which avoid the brute force approach. The similarity weights are computed by the Multiple Metric Learning for large Margin Nearest Neighbor (MMLMNN), a linear dimensionality algorithm that provides a type of Mahalanobis metric Weinberger and Saul, J. MaCh. Learn. Res.10 (2009) 207–244. The experiments show that FuzzyBoost brings good generalization properties, better than the GentleBoost, the Support Vector Machines (SVM) with linear kernels and SVM with Radial Basis Function (RBF) kernels. The classifier was implemented and tested in a real-time, multi-camera dynamic setting.

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