scholarly journals Monitoring Murder Crime in Namibia Using Bayesian Space-Time Models

2012 ◽  
Vol 2012 ◽  
pp. 1-12
Author(s):  
Isak Neema ◽  
Dankmar Böhning
Keyword(s):  
Relative Risk ◽  
Population Density ◽  
Temporal Trends ◽  
Space Time ◽  
Time Interaction ◽  
Time Space ◽  
Northern Regions ◽  
Gibbs Sampling Algorithm ◽  
Population Sizes ◽  
Regional Clustering

This paper focuses on the analysis of murder in Namibia using Bayesian spatial smoothing approach with temporal trends. The analysis was based on the reported cases from 13 regions of Namibia for the period 2002–2006 complemented with regional population sizes. The evaluated random effects include space-time structured heterogeneity measuring the effect of regional clustering, unstructured heterogeneity, time, space and time interaction and population density. The model consists of carefully chosen prior and hyper-prior distributions for parameters and hyper-parameters, with inference conducted using Gibbs sampling algorithm and sensitivity test for model validation. The posterior mean estimate of the parameters from the model using DIC as model selection criteria show that most of the variation in the relative risk of murder is due to regional clustering, while the effect of population density and time was insignificant. The sensitivity analysis indicates that both intrinsic and Laplace CAR prior can be adopted as prior distribution for the space-time heterogeneity. In addition, the relative risk map show risk structure of increasing north-south gradient, pointing to low risk in northern regions of Namibia, while Karas and Khomas region experience long-term increase in murder risk.

scholarly journals Bayesian modeling of spatiotemporal patterns of TB-HIV co-infection risk in Kenya

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Verrah Otiende ◽  
Thomas Achia ◽  
Henry Mwambi
Keyword(s):  
Relative Risk ◽  
Temporal Trends ◽  
Control Program ◽  
Infection Risk ◽  
Space Time ◽  
Geographical Variations ◽  
Hiv Coinfection ◽  
Notification Data ◽  
Best Fit ◽  
Case Notification

Abstract Background Tuberculosis (TB) and Human Immunodeficiency Virus (HIV) diseases are globally acknowledged as a public health challenge that exhibits adverse bidirectional relations due to the co-epidemic overlap. To understand the co-infection burden we used the case notification data to generate spatiotemporal maps that described the distribution and exposure hypotheses for further epidemiologic investigations in areas with unusual case notification levels. Methods We analyzed the TB and TB-HIV case notification data from the Kenya national TB control program aggregated for forty-seven counties over a seven-year period (2012–2018). Using spatiotemporal poisson regression models within the Integrated Nested Laplace Approach (INLA) paradygm, we modeled the risk of TB-HIV co-infection. Six competing models with varying space-time formulations were compared to determine the best fit model. We then assessed the geographic patterns and temporal trends of coinfection risk by mapping the posterior marginal from the best fit model. Results Of the total 608,312 TB case notifications, 194,129 were HIV co-infected. The proportion of TB-HIV co-infection was higher in females (39.7%) than in males (27.0%). A significant share of the co-infection was among adults aged 35 to 44 years (46.7%) and 45 to 54 years (42.1%). Based on the Bayesian Defiance Information (DIC) and the effective number of parameters (pD) comparisons, the spatiotemporal model allowing space-time interaction was the best in explaining the geographical variations in TB-HIV coinfection. The model results suggested that the risk of TB-HIV coinfection was influenced by infrastructure index (Relative risk (RR) = 5.75, Credible Interval (Cr.I) = (1.65, 19.89)) and gender ratio (RR = 5.81e−04, Cr. I = (1.06e−04, 3.18e−03). The lowest and highest temporal relative risks were in the years 2016 at 0.9 and 2012 at 1.07 respectively. The spatial pattern presented an increased co-infection risk in a number of counties. For the spatiotemporal interaction, only a few counties had a relative risk greater than 1 that varied in different years. Conclusions We identified elevated risk areas for TB/HIV co-infection and fluctuating temporal trends which could be because of improved TB case detection or surveillance bias caused by spatial heterogeneity in the co-infection dynamics. Focused interventions and continuous TB-HIV surveillance will ensure adequate resource allocation and significant reduction of HIV burden amongst TB patients.

scholarly journals Global statistical tests for clustered earthquake pattern discovery in Italy

2012 ◽  
Vol 2 (2) ◽  
pp. 9 ◽  
Author(s):  
Renata Rotondi ◽  
Elisa Varini
Keyword(s):  
Point Processes ◽  
Statistical Tests ◽  
Stress Transfer ◽  
Eastern Alps ◽  
Space Time ◽  
Data Sets ◽  
Seismogenic Sources ◽  
Time Interaction ◽  
Time Space ◽  
Stochastic Point Processes

It is a widely shared opinion that not only secondary earthquakes (aftershocks) but also main earthquakes tend to occur in time-space clusters. The importance of this assumption requires the application of statistical tools to objectively evaluate its coherence with the reality at different scales of size-space-time. Global tests allow us to select the data sets with significant space-time clustering in order to perform more in-depth analyses to detect cluster locations. According to different fixed magnitude thresholds, we perform two global statistical tests, the Knox test and the Jacquez test, based on the space-time distance between pairs of earthquakes under the null hypothesis of uniform distribution in time and space, and evaluate the significance of the possible clusters. We analyze subsets of historical Italian earthquakes drawn from the Parametric Catalog of Italian Earthquakes (CPTI04) with magnitude thresholds 4.5, 5.3 and 6.0, associated with the composite seismogenic sources of the Database of Individual Seismogenic Sources. Each subset is related to one of the eight tectonically homogeneous macroregions in which the Italian territory has been divided. Significant space-time clustering is found for all sets with a magnitude threshold of 4.5. This tendency decreases drastically or disappears when the cut off rises to 5.3, with the exception of two macroregions located in the Eastern Alps and the Calabrian Arc, respectively, where evidence of space-time interaction may refer to stress transfer among consecutive or adjacent faults. The link between clustering effect and tectonic behavior could guide the choice of different stochastic point processes to model the seismic activity.

scholarly journals Estimating relative risk for dengue disease in Peninsular Malaysia using INLA

2017 ◽  
Vol 13 (4) ◽  
pp. 721-727 ◽  
Author(s):  
Nurul Syafiah Abd Naeeim ◽  
Nuzlinda Abdul Rahman
Keyword(s):  
Relative Risk ◽  
Disease Mapping ◽  
Peninsular Malaysia ◽  
Space Time ◽  
Dengue Disease ◽  
Temporal Effects ◽  
Space And Time ◽  
Time Interaction ◽  
Spatio Temporal ◽  
Mapping Models

Study in spatio-temporal disease mapping models give a great worth in epidemiology, in describing the pattern of disease incidence across geographical space and time. This paper studies generalized linear mixed models (GLMM) for the analysis of spatial and temporal variability of dengue disease rates. For spatio-temporal study, the models accommodate spatially correlated random effects as well as temporal effects together with the space time interaction. The space time interaction is used to capture any additional effects that are not explained by the main factors of space and time. However, as study including time dimension is quite complex for disease mapping, the temporal effects that only relate to structured and unstructured time pattern are considered in these models as initial screening in studying disease pattern and time trend. The models are fitted within a hierarchical Bayesian framework using Integrated Nested Laplace Approximation (INLA) methodology. For this study, there are three main objectives. First, to choose the best model that represent the disease phenomenon. Second, to estimate the relative risk of disease based on the model selected and lastly, to visualize the risk spatial pattern and temporal trend using graphical representation. The models are applied to monthly dengue fever data in Peninsular Malaysia reported to Ministry of Health Malaysia for year 2015 by district level.

CASIMIR EFFECT FOR THE ROBIN SURFACES IN STATIC ROBERTSON–WALKER SPACE–TIME

2011 ◽  
Vol 20 (02) ◽  
pp. 161-168 ◽  
Author(s):  
MOHAMMAD R. SETARE ◽  
M. DEHGHANI
Keyword(s):  
Scalar Field ◽  
Energy Momentum Tensor ◽  
Casimir Effect ◽  
Vacuum Expectation ◽  
Robin Boundary Condition ◽  
Momentum Tensor ◽  
Space Time ◽  
Conformally Invariant ◽  
Time Space ◽  
Robin Boundary

We investigate the energy–momentum tensor for a massless conformally coupled scalar field in the region between two curved surfaces in k = -1 static Robertson–Walker space–time. We assume that the scalar field satisfies the Robin boundary condition on the surfaces. Robertson–Walker space–time space is conformally related to Rindler space; as a result we can obtain vacuum expectation values of the energy–momentum tensor for a conformally invariant field in Robertson–Walker space–time space from the corresponding Rindler counterpart by the conformal transformation.

scholarly journals The Impact of Health Policies and Sociodemographic Factors on Doubling Time of the COVID-19 Pandemic in Mexico

2021 ◽  
Vol 18 (5) ◽  
pp. 2354
Author(s):  
Lina Díaz-Castro ◽  
Héctor Cabello-Rangel ◽  
Kurt Hoffman
Keyword(s):  
Population Density ◽  
Doubling Time ◽  
Sociodemographic Factors ◽  
Health Policies ◽  
Government Response ◽  
University Of Oxford ◽  
Negative Effect ◽  
Population Sizes ◽  
The University ◽  
The Impact

Background. The doubling time is the best indicator of the course of the current COVID-19 pandemic. The aim of the present investigation was to determine the impact of policies and several sociodemographic factors on the COVID-19 doubling time in Mexico. Methods. A retrospective longitudinal study was carried out across March–August, 2020. Policies issued by each of the 32 Mexican states during each week of this period were classified according to the University of Oxford Coronavirus Government Response Tracker (OxCGRT), and the doubling time of COVID-19 cases was calculated. Additionally, variables such as population size and density, poverty and mobility were included. A panel data model was applied to measure the effect of these variables on doubling time. Results. States with larger population sizes issued a larger number of policies. Delay in the issuance of policies was associated with accelerated propagation. The policy index (coefficient 0.60, p < 0.01) and the income per capita (coefficient 3.36, p < 0.01) had a positive effect on doubling time; by contrast, the population density (coefficient −0.012, p < 0.05), the mobility in parks (coefficient −1.10, p < 0.01) and the residential mobility (coefficient −4.14, p < 0.01) had a negative effect. Conclusions. Health policies had an effect on slowing the pandemic’s propagation, but population density and mobility played a fundamental role. Therefore, it is necessary to implement policies that consider these variables.

In quest of higher dimensions – Superstring Theory and the Calabi – Yau manifolds

2021 ◽  
Author(s):  
Deep Bhattacharjee ◽  
Sanjeevan Singha Roy
Keyword(s):  
String Theory ◽  
Higher Dimensions ◽  
Physical Reality ◽  
Space Time ◽  
Superstring Theory ◽  
Real Nature ◽  
Time Space ◽  
Klein Theory ◽  
Relative Notion ◽  
Definition Of

Higher dimensions are impossible to visualize as the size of dimension varies inversely proportional to its level. The more the dimension ranges, the least its size. We are a set of points living in a particular point of space and a particular frame of time. i.e, we live in space-time. The space has more dimensions that meets the human eye. We are living in a world of hyper-space. Our world being a smaller dimension is floating in higher dimensions. The quest for the visually of higher dimensions has been a fantasy to mankind but this aspect of nature is completely locked. We can transform dimensions i.e., from higher to lower dimensions, or from lower to higher dimensions, but only through mathematics. The relative notion of mathematics helps us to do the thing, which is perhaps impossible in the experimental part of physical reality. Humans being an element of 3 Dimensions – length, breath, height can only perceive one higher dimensions, that is space-time. but beyond that the notion of dimension itself changes. The dimensions got curled up in every intersection of the coordinates of space in such a way that the higher dimensions remain stable to us. But in reality it is highly unstable. In the higher dimensions, above 4, the space is tearing apart and joining again spontaneously, but the tearing portion itself covered by 2 dimensional Branes which acts as a stabilizer for the unstable dimensions. Dimensions will get smaller and smaller with the space-time interwoven in it. But at Planks length that is 10^-33 meter, the notion of space-time itself breaks down thereby making impossible for the higher dimensions to coexist along with space. Without space, there will be no identity of any dimension. The space itself is the fabric for the milestone of residing higher dimensions. Imagine our room, which is 3 dimensional. But what is there inside the room. The space and of course the time. Space-time being a totally separate entity is not quite separate when compared with other dimensions because it makes the residing place for the higher dimensions or the hyperspace itself. We all are confined within a lower dimensional world within a randomness of higher dimensions. Time being alike like space is an arrow which has the capability of slicing space into different forms. Thereby taking a snapshot of our every nano-second we vibrate within space-time. As each slice of time represents each slice of space, similarly each slice of space represents each slice of time. The nature of space-time is beyond human consciousness. It is the identity by which we breathe, we play, we survive. It is the whole localization of species that encompasses itself with space thereby making space-time a relative quantity depending upon the reference frame. The only thing that can encompass space-time or even change the relative definition of space-time is the speed, the speed far beyond the speed of light. The more the speed, the less the array of time flows. Space-time being an invisible entity makes the other dimensions visible residing in it only into the level of 3, that is l, b, h. After that there is a infamous structure formed by the curling of higher dimensions called CALABI-YAU manifold. This manifold depicts the usual nature of the dimensional quadrants of the higher order by containing a number of small spherical spheres inside it. The mathematics of string theory is still unable to solve the genus and the containing spheres of the manifold which can be the ultimate quest for the hidden dimensions. Hidden, as, the higher dimensions are hidden from human perspective of macro level but if we probe deeper into the fabric of the space-time of General Relativity then we will find the 5th dimension according to the Kaluza-Klein theory. And if we probe even deeper into it at the perspective of string theory we will be amazed to see the real nature of quantum world. They are so marvelously beautiful, they contain so many forms of higher dimensions ranging from 6 to 10. And even many more of that, but we are still not sure about it where they may exist in a ghost state. After all, the quantum nature is far more beautiful that one can even imagine with a full faze of weirdness.

scholarly journals Mapping current and future European public water withdrawals and consumption

2014 ◽  
Vol 18 (2) ◽  
pp. 407-416 ◽  
Author(s):  
I. Vandecasteele ◽  
A. Bianchi ◽  
F. Batista e Silva ◽  
C. Lavalle ◽  
O. Batelaan
Keyword(s):  
Population Density ◽  
Temporal Trends ◽  
Absolute Error ◽  
Reference Scenario ◽  
Total Water ◽  
Country Level ◽  
European Public ◽  
Density Map ◽  
Per Capita ◽  
Water Withdrawals

Abstract. In Europe, public water withdrawals make up on average 30% and in some cases up to 60% of total water withdrawals. These withdrawals are becoming increasingly important with growing population density; hence there is a need to understand the spatial and temporal trends involved. Pan-European public/municipal water withdrawals and consumption were mapped for 2006 and forecasted for 2030. Population and tourism density were assumed to be the main driving factors for withdrawals. Country-level statistics on public water withdrawals were disaggregated to a combined population and tourism density map (the "user" density map) computed for 2006. The methodology was validated using actual regional withdrawal statistics from France for 2006. The total absolute error (TAE) calculated was proven to be reduced by taking into account the tourism density in addition to the population density. In order to forecast the map to 2030 we considered a reference scenario where per capita withdrawals were kept constant in time. Although there are large variations from region to region, this resulted in a European average increase of water withdrawals of 16%. If we extrapolate the average reduction in per capita withdrawals seen between 2000 and 2008, we forecast a reduction in average total water withdrawals of 4%. Considering a scenario where all countries converge to an optimal water use efficiency, we see an average decrease of 28%.

scholarly journals Clustering of equine grass sickness cases in the United Kingdom: a study considering the effect of position-dependent reporting on the space–time K-function

2004 ◽  
Vol 133 (2) ◽  
pp. 343-348 ◽  
Author(s):  
N. P. FRENCH ◽  
H. E. McCARTHY ◽  
P. J. DIGGLE ◽  
C. J. PROUDMAN
Keyword(s):  
United Kingdom ◽  
Management Practices ◽  
Space Time ◽  
Pasture Management ◽  
Local Climate ◽  
Temporal Properties ◽  
Time Interaction ◽  
The United Kingdom ◽  
Grass Sickness ◽  
Type C

Equine grass sickness (EGS) is a largely fatal, pasture-associated dysautonomia. Although the aetiology of this disease is unknown, there is increasing evidence that Clostridium botulinum type C plays an important role in this condition. The disease is widespread in the United Kingdom, with the highest incidence believed to occur in Scotland. EGS also shows strong seasonal variation (most cases are reported between April and July). Data from histologically confirmed cases of EGS from England and Wales in 1999 and 2000 were collected from UK veterinary diagnostic centres. The data did not represent a complete census of cases, and the proportion of all cases reported to the centres would have varied in space and, independently, in time. We consider the variable reporting of this condition and the appropriateness of the space–time K-function when exploring the spatial-temporal properties of a ‘thinned’ point process. We conclude that such position-dependent under-reporting of EGS does not invalidate the Monte Carlo test for space–time interaction, and find strong evidence for space–time clustering of EGS cases (P<0·001). This may be attributed to contagious or other spatially and temporally localized processes such as local climate and/or pasture management practices.

Space, Time, Space-Time and Society

1993 ◽  
Vol 63 (4) ◽  
pp. 406-424 ◽  
Author(s):  
Patrick L. Baker
Keyword(s):  
Space Time ◽  
Time Space
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