scholarly journals Assessing the impact of feline immunodeficiency virus and bovine tuberculosis co-infection in African lions

2012 ◽  
Vol 279 (1745) ◽  
pp. 4206-4214 ◽  
Author(s):  
M. Maas ◽  
D. F. Keet ◽  
V. P. M. G. Rutten ◽  
J. A. P. Heesterbeek ◽  
M. Nielen
Keyword(s):  
Feline Immunodeficiency Virus ◽  
Bovine Tuberculosis ◽  
Temporal Analysis ◽  
Blood Chemistry ◽  
The North ◽  
Conservation Problem ◽  
Immunodeficiency Virus ◽  
Spatio Temporal ◽  
The Impact ◽  
African Lions

Bovine tuberculosis (BTB), caused by Mycobacterium bovis , is a disease that was introduced relatively recently into the Kruger National Park (KNP) lion population. Feline immunodeficiency virus (FIV ple ) is thought to have been endemic in lions for a much longer time. In humans, co-infection between Mycobacterium tuberculosis and human immunodeficiency virus increases disease burden. If BTB were to reach high levels of prevalence in lions, and if similar worsening effects would exist between FIV ple and BTB as for their human equivalents, this could pose a lion conservation problem. We collected data on lions in KNP from 1993 to 2008 for spatio-temporal analysis of both FIV ple and BTB, and to assess whether a similar relationship between the two diseases exists in lions. We found that BTB prevalence in the south was higher than in the north (72 versus 19% over the total study period) and increased over time in the northern part of the KNP (0–41%). No significant spatio-temporal differences were seen for FIV ple in the study period, in agreement with the presumed endemic state of the infection. Both infections affected haematology and blood chemistry values, FIV ple in a more pronounced way than BTB. The effect of co-infection on these values, however, was always less than additive. Though a large proportion (31%) of the lions was co-infected with FIV ple and M. bovis , there was no evidence for a synergistic relation as in their human counterparts. Whether this results from different immunopathogeneses remains to be determined.

scholarly journals Modelling local patterns of child mortality risk: a Bayesian Spatio-temporal analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Alejandro Lome-Hurtado ◽  
Jacques Lartigue-Mendoza ◽  
Juan C. Trujillo
Keyword(s):  
High Risk ◽  
Mexico City ◽  
Child Mortality ◽  
Mortality Risk ◽  
Temporal Analysis ◽  
Health Concern ◽  
The North ◽  
Greater Mexico ◽  
Spatio Temporal ◽  
Child Mortality Rate

Abstract Background Globally, child mortality rate has remained high over the years, but the figure can be reduced through proper implementation of spatially-targeted public health policies. Due to its alarming rate in comparison to North American standards, child mortality is particularly a health concern in Mexico. Despite this fact, there remains a dearth of studies that address its spatio-temporal identification in the country. The aims of this study are i) to model the evolution of child mortality risk at the municipality level in Greater Mexico City, (ii) to identify municipalities with high, medium, and low risk over time, and (iii) using municipality trends, to ascertain potential high-risk municipalities. Methods In order to control for the space-time patterns of data, the study performs a Bayesian spatio-temporal analysis. This methodology permits the modelling of the geographical variation of child mortality risk across municipalities, within the studied time span. Results The analysis shows that most of the high-risk municipalities were in the east, along with a few in the north and west areas of Greater Mexico City. In some of them, it is possible to distinguish an increasing trend in child mortality risk. The outcomes highlight municipalities currently presenting a medium risk but liable to become high risk, given their trend, after the studied period. Finally, the likelihood of child mortality risk illustrates an overall decreasing tendency throughout the 7-year studied period. Conclusions The identification of high-risk municipalities and risk trends may provide a useful input for policymakers seeking to reduce the incidence of child mortality. The results provide evidence that supports the use of geographical targeting in policy interventions.

Physical factors of influence in the interactions between rainfall, evapotranspiration and soil moisture driving the spatio-temporal evolution of drought patterns in the Ebro Basin (NE Spain).

2021 ◽  
Author(s):  
Jaime Gaona ◽  
Pere Quintana-Seguí ◽  
Maria José Escorihuela
Keyword(s):  
Soil Moisture ◽  
Land Cover ◽  
Iberian Peninsula ◽  
Land Surface ◽  
Temporal Analysis ◽  
Drought Indices ◽  
Surface Model ◽  
Physical Factors ◽  
Spatio Temporal ◽  
The Impact

<p>Droughts in the Iberian Peninsula are a natural hazard of great relevance due to their recurrence, severity and impact on multiple environmental and socioeconomic aspects. The Ebro Basin, located in the NE of the Iberian Peninsula, is particularly vulnerable to drought with consequences on agriculture, urban water supply and hydropower. This study, performed within the Project HUMID (CGL2017-85687-R), aims at evaluating the influence of the climatic, land cover and soil characteristics on the interactions between rainfall, evapotranspiration and soil moisture anomalies which define the spatio-temporal drought patterns in the basin.</p><p>The onset, propagation and mitigation of droughts in the Iberian Peninsula is driven by anomalies of rainfall, evapotranspiration and soil moisture, which are related by feedback processes. To test the relative importance of such anomalies, we evaluate the contribution of climatic, land-cover and geologic heterogeneity on the definition of the spatio-temporal patterns of drought. We use the Köppen-Geiger climatic classification to assess how the contrasting climatic types within the basin determine differences on drought behavior. Land-cover types that govern the partition between evaporation and transpiration are also of great interest to discern the influence of vegetation and crop types on the anomalies of evapotranspiration across the distinct regions of the basin (e.g. forested mountains vs. crop-dominated areas). The third physical characteristic whose effect on drought we investigate is the impact of soil properties on soil moisture anomalies.</p><p>The maps and time series used for the spatio-temporal analysis are based on drought indices calculated with high-resolution datasets from remote sensing (MOD16A2ET and SMOS1km) and the land-surface model SURFEX-ISBA. The Standardized Precipitation Index (SPI), the EvapoTranspiration Deficit Index (ETDI) and the Soil Moisture Deficit Index (SMDI) are the three indices chosen to characterize the anomalies of the corresponding rainfall (atmospheric), evapotranspiration (atmosphere-land interface) and soil moisture (land) anomalies (components of the water balance). The comparison of the correlations of the indices (with different time lags) between contrasting regions offers insights about the impact of climate, land-cover and soil properties in the dominance, the timing of the response and memory aspects of the interactions. The high spatial and temporal resolution of remote sensing and land-surface model data allows adopting time and spatial scales suitable to investigate the influence of these physical factors with detail beyond comparison with ground-based datasets.</p><p>The spatial and temporal analysis prove useful to investigate the physical factors of influence on the anomalies between rainfall, evapotranspiration and soil moisture. This approach facilitates the physical interpretation of the anomalies of drought indices aiming to improve the characterization of drought in heterogeneous semi-arid areas like the Ebro River Basin.</p>

scholarly journals Nepal, a multi-hazard risk country: Spatio-temporal analysis

2019 ◽  
Vol 58 ◽  
pp. 145-152
Author(s):  
Ganesh Kumar Jimee ◽  
Kimiro Meguro ◽  
Amod Mani Dixit
Keyword(s):  
Temporal Analysis ◽  
Significant Loss ◽  
Climatic Conditions ◽  
Decision Makers ◽  
Economic Conditions ◽  
Tectonic Processes ◽  
Active Tectonic ◽  
Spatio Temporal ◽  
The Impact ◽  
Complex Geology

Nepal, though covers small area of the earth, exposes complex geology with active tectonic processes, high peaks, sloppy terrain and climatic variation. Combination of such geo-physical and climatic conditions with existing poor socio-economic conditions, unplanned settlements, rapidly increasing population and low level of awareness has put the country in highest risk to multi-hazard events. Fires, floods, landslides and epidemics are the most frequent hazard events, which have cumulatively caused a significant loss of lives and property every year. However, due to diversity in physiographic, climatic and socio-economic conditions within the country, the type, frequency and degree of the impact of such events differs in different places. During the period of 46 years (1971-2016), an average of 2 events have been occurred causing 3 deaths/missing every day. Disaster events occurred most frequently during the months of April, July and August, while relatively lesser number of events have been reported during January, November and December. However, earthquakes have been reported in different months, regardless with the season. This paper is an effort to analyse the spatial distribution and temporal variation of disaster events in Nepal. Further it has drawn a trend of disasters occurrence in Nepal, which will help the decision makers and other stakeholders for formulating Disaster Risk Management (DRM) plan and policies on one hand and heighten citizens’ awareness of against disasters on the other.

scholarly journals Pathological manifestations of feline immunodeficiency virus (FIV) infection in wild African lions

Virology ◽  
2009 ◽  
Vol 390 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Melody E. Roelke ◽  
Meredith A. Brown ◽  
Jennifer L. Troyer ◽  
Hanlie Winterbach ◽  
Christiaan Winterbach ◽  
...  
Keyword(s):  
Feline Immunodeficiency Virus ◽  
Immunodeficiency Virus ◽  
African Lions

A FEATURE-BASED SCHEME FOR DETECTING AND CLASSIFYING VIDEO-SHOT TRANSITIONS BASED ON SPATIO-TEMPORAL ANALYSIS AND FUZZY CLASSIFICATION

2009 ◽  
Vol 23 (06) ◽  
pp. 1179-1200 ◽  
Author(s):  
GUO-SHIANG LIN ◽  
MIN-KUAN CHANG ◽  
SHIEN-TANG CHIU
Keyword(s):  
Feature Extraction ◽  
Temporal Analysis ◽  
Fuzzy Classification ◽  
Model Parameters ◽  
Fuzzy Classifier ◽  
Video Shot ◽  
Feature Based ◽  
Spatio Temporal ◽  
Shot Transitions ◽  
The Impact

In this paper, we propose a feature-based scheme for detecting different genres of video shot transitions based on spatio-temporal analysis and model parameter estimation. In feature extraction, the histogram difference and its modified versions are calculated from the effectiveness of detecting cuts and reducing the impact of fleeting lights. We propose a hybrid algorithm composed of adaptive thresholding, parameter calculation, and transition duration refinement to measure model parameters. Some properties of the associated model parameters of each transition are computed as features. A feature measuring the time gap between two consecutive shots is also adopted. After feature extraction, a fuzzy classifier integrates these features to distinguish nontransitions, cuts, and dissolve-type features from one to another. Many test videos having different types of shots are used for performance evaluation. The experimental results demonstrate that the proposed scheme not only detects cuts, dissolves, and fades well, but also accurately locates the duration of each dissolve-type transition. In addition, the proposed scheme outperforms some existing methods in terms of cut and dissolve detection.

scholarly journals Modelling Local Patterns of Children Mortality. A Bayesian Spatio-Temporal Analysis.

2019 ◽  
Author(s):  
Alejandro Lome-Hurtado ◽  
Jacques Lartigue Mendoza ◽  
Juan Carlos Trujillo
Keyword(s):  
High Risk ◽  
Mortality Risk ◽  
Temporal Analysis ◽  
Health Concern ◽  
North West ◽  
The North ◽  
Policy Interventions ◽  
Medium Risk ◽  
Spatio Temporal ◽  
Over Time

Abstract Background: The number of death children at the international scale are still high, but with proper spatially-targeted health public policies this number could be reduced. In Mexico, children mortality is a particular health concern due to its alarming rate all throughout North America. The aims of this study are i) to model the change of children mortality risk at the municipality level, (ii) to identify municipalities with high, medium and low risk over time and (iii) to ascertain potential high-risk municipalities across time, using local trends of each municipality in Greater Mexico City. Methods: The study uses Bayesian spatio-temporal analysis to control for space-time patterns of data. This allow to model the geographical variation of the municipalities within the time span studied. Results: The analysis shows that most of the high-risk municipalities are in the north, west, and some in the east; some of such municipalities show an increasing children mortality risk over time. The outcomes highlight some municipalities which show a medium risk currently but are likely to become high risk along the study period. Finally, the odds of children mortality risk illustrate a decreasing tendency over the 7-year framework. Conclusions: Identification of high-risk municipalities may provide a useful input to policy-makers seeking out to reduce the incidence of children mortality, since it would provide evidence to support geographical targeting for policy interventions.

scholarly journals Arabian Sea Tropical Cyclones: A Spatio-Temporal Analysis in Support of Natural Hazard Risk Appraisal in Oman

2021 ◽  
Author(s):  
Suad Al-Manji ◽  
Gordon Mitchell ◽  
Amna Al Ruheili
Keyword(s):  
High Risk ◽  
Tropical Cyclones ◽  
Natural Hazard ◽  
Temporal Distribution ◽  
Storm Surges ◽  
Temporal Analysis ◽  
The North ◽  
Risk Areas ◽  
Spatio Temporal ◽  
Extreme Winds

Tropical cyclones [TCs] are a common natural hazard that have significantly impacted Oman. Over the period 1881–2019, 41 TC systems made landfall in Oman, each associated with extreme winds, storm surges and significant flash floods, often resulting in loss of life and substantial damage to infrastructure. TCs affect Omani coastal areas from Muscat in the north to Salalah in the south. However, developing a better understanding of the high-risk regions is needed, and is of particular interest in disaster risk reduction institutions in Oman. This study aims to find and map TC tracks and their spatio-temporal distribution to landfall in Oman to identify the high-risk areas. The analysis uses Kernel Density Estimation [KDE] and Linear Direction Mean [LDM] methods to better identify the spatio-temporal distribution of TC tracks and their landfall in Oman. The study reveals clear seasonal and monthly patterns. This knowledge will help to improve disaster planning for the high-risk areas.

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