scholarly journals Variation in use of Caesarean section in Norway: An application of spatio-temporal Gaussian random fields

2021 ◽  
pp. 140349482110085
Author(s):  
Janne Mannseth ◽  
Geir D. Berentsen ◽  
Hans J. Skaug ◽  
Rolv T. Lie ◽  
Dag Moster
Keyword(s):  
Caesarean Section ◽  
Spatial Correlation ◽  
Medical Intervention ◽  
Gaussian Random Fields ◽  
Fair Use ◽  
Model Parameters ◽  
Birth Registry ◽  
R Packages ◽  
Spatio Temporal ◽  
Homogenous Population

Aims: Caesarean section (CS) is a medical intervention performed in Norway when a surgical delivery is considered more beneficial than a vaginal. Because deliveries with higher risk are centralized to larger hospitals, use of CS varies considerably between hospitals. We describe how the use of CS varies geographically by municipality. Since indications for CS should have little variation across the relatively homogenous population of Norway, we expect fair use of CS to be evenly distributed across the municipalities. Methods: Data from the Medical Birth Registry of Norway were used in our analyses (810,914 total deliveries, 133,746 CSs, 440 municipalities). We propose a spatial correlation model that takes the location into account to describe the variation in use of CS across the municipalities. The R packages R-INLA and TMB are used to estimate the yearly municipal CS rate and the spatial correlation between the municipalities. We also apply stratified models for different categories of delivering women (Robson groups). Estimated rates are displayed in maps and model parameters are shown in tables. Results: The CS rate varies substantially between the different municipalities. As expected, there was strong correlation between neighbouring municipalities. Similar results were found for different Robson groups. Conclusions: The substantial difference in CS use across municipalities in Norway is not likely to be due to specific medical reasons, but rather to hospitals’ different policies towards the use of CS. The policy to be either more or less restrictive to CS was not specific to any category of deliveries.

Comparison of Nonlinear Spatial Correlation Models by the Influence of the Data Augmentation to the Classification Risk

2002 ◽  
Vol 7 (1) ◽  
pp. 31-42
Author(s):  
J. Šaltytė ◽  
K. Dučinskas
Keyword(s):  
Spatial Correlation ◽  
Random Fields ◽  
Data Augmentation ◽  
Gaussian Random Fields ◽  
Classification Rule ◽  
Numerical Comparison ◽  
First Order ◽  
Bayesian Risk ◽  
Correlation Models

The Bayesian classification rule used for the classification of the observations of the (second-order) stationary Gaussian random fields with different means and common factorised covariance matrices is investigated. The influence of the observed data augmentation to the Bayesian risk is examined for three different nonlinear widely applicable spatial correlation models. The explicit expression of the Bayesian risk for the classification of augmented data is derived. Numerical comparison of these models by the variability of Bayesian risk in case of the first-order neighbourhood scheme is performed.

scholarly journals Spatio-temporal modeling of surface runoff in ungauged sub-catchments of Subarnarekha river basin using SWAT

MAUSAM ◽  
2021 ◽  
Vol 72 (3) ◽  
pp. 597-606
Author(s):  
CHINMAYA PANDA ◽  
DWARIKA MOHAN DAS ◽  
B. C. SAHOO ◽  
B. PANIGRAHI ◽  
K. K. SINGH
Keyword(s):  
Surface Runoff ◽  
Assessment Tool ◽  
Nutrient Loss ◽  
Coefficient Of Determination ◽  
Annual Rainfall ◽  
Model Parameters ◽  
Runoff Generation ◽  
Temporal Modeling ◽  
Spatio Temporal ◽  
R Factors

In this present study, Soil and Water Assessment Tool (SWAT) embedded with ArcGIS interface has been used to simulate the surface runoff from the un-gauged sub-catchments in the upper catchment of Subarnarekha basin. Model calibration and validation were performed with the help of Sequential Uncertainty Fitting (SUFI-2) in-built in the SWAT-CUP package (SWAT Calibration Uncertainty Programs). The model was calibrated for a period from 1996 to 2008 with 3 years warm up period (1996-1998) and validated for a period of 5 years from 2009 to 2013. The model evaluation was performed by Nash - Sutcliffe coefficient (NSE), Coefficient of determination (R2) and Percentage Bias (PBIAS). The degree of uncertainty was evaluated by P and R factors. Basing upon the R2, NSE and PBIAS values respectively, of the order of 0.90, 0.90 and -12%, during calibration and 0.85, 0.83 and -15% during validation, substantiate performance of the model. All uncertainties of model parameters have been well taken by the P and R factors respectively, of the order of 0.95 and 0.77 during calibration and 0.82 and 0.87 during validation. The runoff generation from 19 sub-catchments of Adityapur catchment varies from 29.2-44.1% of the annual rainfall and average surface runoff simulated for the entire catchment is 545 mm. As the surface runoff generated in most of the sub-catchments amounts to above 30% of rainfall, it is recommended for adequate number of structural interventions at appropriate locations in the catchment to store the rainfall excess for providing irrigation, recharging groundwater and restricting the sediment and nutrient loss.

scholarly journals MODELLING THE RESPONSE OF VASCULAR TUMOURS TO CHEMOTHERAPY: A MULTISCALE APPROACH

2006 ◽  
Vol 16 (supp01) ◽  
pp. 1219-1241 ◽  
Author(s):  
HELEN M. BYRNE ◽  
MARKUS R. OWEN ◽  
TOMAS ALARCON ◽  
JAMES MURPHY ◽  
PHILIP K. MAINI
Keyword(s):  
Cell Density ◽  
Tumour Cell ◽  
Drug Transport ◽  
Angiogenic Factors ◽  
Future Research ◽  
Model Parameters ◽  
Multiscale Approach ◽  
Proliferating Cells ◽  
Vascular Adaptation ◽  
Spatio Temporal

An existing multiscale model is extended to study the response of a vascularised tumour to treatment with chemotherapeutic drugs which target proliferating cells. The underlying hybrid cellular automaton model couples tissue-level processes (e.g. blood flow, vascular adaptation, oxygen and drug transport) with cellular and subcellular phenomena (e.g. competition for space, progress through the cell cycle, natural cell death and drug-induced cell kill and the expression of angiogenic factors). New simulations suggest that, in the absence of therapy, vascular adaptation induced by angiogenic factors can stimulate spatio-temporal oscillations in the tumour's composition. Numerical simulations are presented and show that, depending on the choice of model parameters, when a drug which kills proliferating cells is continuously infused through the vasculature, three cases may arise: the tumour is eliminated by the drug; the tumour continues to expand into the normal tissue; or, the tumour undergoes spatio-temporal oscillations, with regions of high vascular and tumour cell density alternating with regions of low vascular and tumour cell density. The implications of these results and possible directions for future research are also discussed.

Turing and Benjamin–Feir instability mechanisms in non-autonomous systems

2020 ◽  
Vol 476 (2238) ◽  
pp. 20200003 ◽  
Author(s):  
Robert A. Van Gorder
Keyword(s):  
Autonomous Systems ◽  
Reaction Diffusion ◽  
Reaction Rates ◽  
Time Dependent ◽  
Model Parameters ◽  
Time Varying ◽  
Reaction Diffusion Systems ◽  
Diffusion Systems ◽  
Dependent Model ◽  
Spatio Temporal

The Turing and Benjamin–Feir instabilities are two of the primary instability mechanisms useful for studying the transition from homogeneous states to heterogeneous spatial or spatio-temporal states in reaction–diffusion systems. We consider the case when the underlying reaction–diffusion system is non-autonomous or has a base state which varies in time, as in this case standard approaches, which rely on temporal eigenvalues, break down. We are able to establish respective criteria for the onset of each instability using comparison principles, obtaining inequalities which involve the in general time-dependent model parameters and their time derivatives. In the autonomous limit where the base state is constant in time, our results exactly recover the respective Turing and Benjamin–Feir conditions known in the literature. Our results make the Turing and Benjamin–Feir analysis amenable for a wide collection of applications, and allow one to better understand instabilities emergent due to a variety of non-autonomous mechanisms, including time-varying diffusion coefficients, time-varying reaction rates, time-dependent transitions between reaction kinetics and base states which change in time (such as heteroclinic connections between unique steady states, or limit cycles), to name a few examples.

scholarly journals Maternal Characteristics and Temporal Trends in Birth Outcomes: Comparison between Spanish and Migrant Mothers

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Carlos Varea ◽  
Cristina Bernis ◽  
Antonio González González
Keyword(s):  
Birth Weight ◽  
Caesarean Section ◽  
Low Birth Weight ◽  
Birth Outcomes ◽  
Common Factor ◽  
Mode Of Delivery ◽  
Temporal Trends ◽  
Medical Intervention ◽  
Future Research ◽  
Reproductive Pattern

Low birth weight and preterm babies have been increasing in Spain since 1980, coinciding with important changes in the social and demographic structure of childbearing populations—including the contribution of a 25% of foreign mothers—and with increasing medical intervention in births. This study, based on 5,990,613 births, compares the temporary trends in reproductive patterns and birth outcomes in Spanish and foreign mothers during the period 1996–2009 and evaluates for the years 2007 to 2009 the relative contribution of mother's origin and Caesarean section to birth weight variability. Foreign mothers maintain their own reproductive pattern, whereas negative birth outcomes increase in all groups. Results from logistic regression analysis show that besides late maternity and primiparity also Caesarean section increases the risk for low birth weight. The reduction in Caesarean section rates between 2007 and 2009 might explain the reduction of low birth weight detected. A change of tendency simultaneously appears in most maternal and newborn characteristics, and in the mode of delivery in all ethnic groups since 2008. Coincidence in the timing of the change of trends points to a common factor. We suggest that the current world financial crisis could be this common cause, a hypothesis to be contrasted in future research.

A Dynamic and Flexible State Model for Rainfall Nowcasting

2020 ◽  
Author(s):  
Marc Schleiss ◽  
Venkat Roy
Keyword(s):  
Temporal Evolution ◽  
Weather Prediction ◽  
Radar Reflectivity ◽  
State Model ◽  
Dynamic State ◽  
Model Parameters ◽  
Target Area ◽  
Stochastic Perturbations ◽  
Spatio Temporal ◽  
Linear State

<p>We present a dynamic state model estimation method for rainfall nowcasting in which we assume that the short term spatio-temporal evolution of rainfall can be approximated by a linear state model with stochastic perturbations.  We estimate the model parameters using radar reflectivity measurements for one-step as well as multiple-step ahead rainfall nowcasting. If the rainfall intensity at location <strong>x</strong> and time index t is given by u<sub>t</sub>(<strong>x</strong>), then the overall rainfall field intensity vector at any time t over N pixels (of the target area) can be represented by <strong>u</strong><sub>t</sub> = [u<sub>t</sub>(<strong>x</strong><sub>N</sub>),...u<sub>t</sub>(<strong>x</strong><sub>N</sub>)]<sup>T</sup><sub>.</sub> Following the aforementioned formalism, the spatio-temporal evolution of the rainfall field can be described by the following linear state model given by<br><strong>u</strong><sub>t</sub> = <strong>H</strong><sub>t</sub><strong>u</strong><sub>t-1</sub> + <strong>q</strong><sub>t</sub><br>where <strong>H</strong><sub>t</sub> is an unknown time-varying state-transition matrix of dimensions NxN and <strong>q</strong><sub>t</sub> is a stochastic process noise vector of length N. We present an iterative least squares based method to estimate <strong>H</strong><sub>t </sub>and explore simpler algebraic structures (e.g., scaled affine transformations) to reduce the numbers of unknown parameters during estimation. We evaluate the performances of the proposed model using simulations and radar reflectivity data from the Royal Netherlands Meteorological Institute (KNMI). We observe that the nowcasting performances strongly depend on the size of the target area (number of pixels N), the type of events as well as the parameterization of <strong>H</strong><sub>t</sub>. The key advantage of the proposed approach over classical nowcasting methods based on Lagrangian persistence is the possibility to incorporate prior information about future rainfall evolution from external sources of information such as satellites or numerical weather prediction models during the estimation of the parameters.</p>

Evaluation of allergic response using dynamic thermography

2015 ◽  
Vol 23 (1) ◽  
Author(s):  
E. Rokita ◽  
T. Rok ◽  
G. Tatoń
Keyword(s):  
Allergic Reaction ◽  
Skin Prick Test ◽  
High Sensitivity ◽  
Allergic Response ◽  
Coefficient Of Determination ◽  
Model Parameters ◽  
Prick Test ◽  
Skin Reactivity ◽  
Heated Area ◽  
Spatio Temporal

AbstractSkin dynamic termography supplemented by a mathematical model is presented as an objective and sensitive indicator of the skin prick test result. Termographic measurements were performed simultaneously with routine skin prick tests. The IR images were acquired every 70 s up to 910 s after skin prick. In the model histamine is treated as the principal mediator of the allergic reaction. Histamine produces vasolidation and the engorged vessels are responsible for an increase in skin temperature. The model parameters were determined by fitting the analytical solutions to the spatio-temporal distributions of the differences between measured and baseline temperatures. The model reproduces experimental data very well (coefficient of determination = 0.805÷0.995). The method offers a set of parameters to describe separately skin allergic reaction and skin reactivity. The release of histamine after allergen injection is the best indicator of allergic response. The diagnostic parameter better correlates with the standard evaluation of a skin prick test (correlation coefficient = 0.98) than the result of the thermographic planimetric method based on temperature and heated area determination (0.81). The high sensitivity of the method allows for determination of the allergic response in patients with the reduced skin reactivity.

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 Spatio-temporal modeling of COVID-19 epidemic

2021 ◽  
pp. 23-37
Author(s):  
V.L. Sokolovsky ◽  
◽  
G.B. Furman ◽  
D.A. Polyanskaya ◽  
E.G. Furman ◽  
...  
Keyword(s):  
Numerical Solutions ◽  
Mass Vaccination ◽  
Reaction Diffusion Equations ◽  
Disease Spread ◽  
Correct Prediction ◽  
Model Parameters ◽  
Population Mobility ◽  
Personal Protection Equipment ◽  
Infected People ◽  
Spatio Temporal

In autumn and winter 2020–2021 there was a growth in morbidity with COVID-19. Since there are no efficient medications and mass vaccination has only just begun, quarantine, limitations on travels and contacts between people as well as use of personal protection equipment (masks) still remain priority measures aimed at preventing the disease from spreading. In this work we have analyzed how the epidemic developed and what impacts quarantine measures exerted on the disease spread; to do that we applied various mathematical models. It was shown that simple models belonging to SIR-type (S means susceptible; I, infected; and R, recovered or removed from the infected group) allowed estimating certain model parameters such as morbidity and recovery coefficients that could be used in more complicated models. We examined spatio-temporal epidemiologic models based on finding solutions to non-stationary two-dimensional reaction-diffusion equations. Such models allow taking into account uneven distribution of population, changes in population mobility, and changes in frequency of contacts between susceptible and infected people due to quarantine. We applied obtained analytical and numerical solutions to analyze different stages in the epidemic as well as its wave-like development influenced by imposing and canceling quarantine limitations. To take into account ultimate rate at which the disease spreads and its incubation period (when an infected person is not a source of contagion), we suggest using equations similar to the Cattaneo-Vernotte one. The suggested model allows predicting where the front of morbidity spread is going to occur, that is, a moving frontier between areas where there are infected people and areas where they are absent. Use of such models provides an opportunity to introduce differential quarantine measures basing on more objective grounds. At the end of 2020 mass vaccination started in some countries. We estimated a necessary number of people that had to be vaccinated so that new waves of COVID-19 epidemic would be prevented; in our estimates, not less than 80% of the country population should be vaccinated. Correct prediction of epidemic development is becoming more and more vital at the moment due to new and more contagious COVID-19 virus strains occurring in England, South Africa, and some other countries. Our research results can be used for predicting spread of COVID-19 and other communicable diseases; they can make for taking the most efficient measures for successful control over epidemics.

scholarly journals Trend in female genital mutilation and its associated adverse birth outcomes: A 10-year retrospective birth registry study in Northern Tanzania

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0244888
Author(s):  
Issa Rashid Suleiman ◽  
Eusebious Maro ◽  
Benjamin C. Shayo ◽  
Julius Pius Alloyce ◽  
Gileard Masenga ◽  
...  
Keyword(s):  
Caesarean Section ◽  
Hospital Stay ◽  
Birth Outcomes ◽  
Apgar Score ◽  
Female Genital Mutilation ◽  
Adverse Birth Outcomes ◽  
Birth Registry ◽  
Genital Mutilation ◽  
Northern Tanzania ◽  
Female Genital

Background Approximately 200 million women and girls were reported to have undergone female genital mutilation worldwide in 2015.UNICEF’s data based on household survey estimates 15% of women from 15–49 years have undergone FGM from year 2004–2015. Despite this, reliable data on trend of prevalence of female genital mutilation and its associated birth outcomes have not been documented in Tanzania. This study aimed at determining the trends of female genital mutilation and associated maternal and neonatal adverse outcomes in northern Tanzania. Methods A cross-sectional study was conducted using maternally-linked data from Kilimanjaro Christian Medical birth registry involving 30,286 women who gave birth to singletons from 2004–2014. The prevalence of female genital mutilation was computed as proportion of women with female genital mutilation yearly over 10 years. Odds ratios with 95% confidence intervals for adverse birth outcomes associated with female genital mutilation were estimated using multivariable logistic regression model. Results Over the 10-year period, the prevalence of female genital mutilation averaged 15.4%. Female genital mutilation decreased from 23.6% in 2005 to 10.6% in 2014. Female genital mutilation was associated with increased odds for caesarean section (aOR1.26; 95% CI: 1.18–1.34), post-partum haemorrhage (aOR 1.31; 95% CI: 1.10–1.57) and long hospital stay (aOR 1.21; 95% CI: 1.14–1.29). Female genital mutilation also increased women’s likelihood of delivering an infant with low Apgar score at 5th minute (aOR 1.60; 95% CI: 1.37–1.89).FGM type III and IV had increased odds of caesarean section, episiotomy and prolonged duration of hospital stay as compared to FGM type I and II, although the association was statistically insignificant. Conclusion Female genital mutilation prevalence has declined over the study period. Our study has demonstrated that postpartum haemorrhage, delivery by caesarean section, long maternal hospital stays and low APGAR score are associated with FGM. Initiatives to mitigate FGM practice should be strengthened further to reduce/eliminate this practice. Moreover, surgical interventions to improve severe form FGM are welcomed to improve the aforementioned aspects of obstetric outcome in this locality.

Sign in / Sign up

Export Citation Format

Share Document