scholarly journals Using Markov assumption with covariates to assess the Plasmodium falciparum malaria serological markers evolution

2020 ◽  
Vol 7 (`) ◽  
pp. 915-932
Author(s):  
Oumy Niass ◽  
Abdou Kâ Diongue ◽  
Philippe Saint-Pierre ◽  
Aissatou Touré
Keyword(s):  
Markov Model ◽  
Markov Models ◽  
Homogeneous Model ◽  
Control Program ◽  
Plasmodium Falciparum Malaria ◽  
Waiting Time Distribution ◽  
Piecewise Constant ◽  
Malaria Control Program ◽  
Markov Assumption ◽  
Two State Model

In this study, we develop Three Markov models which are continuous time-homogeneous Model, time piecewise constant intensities Markov model and semi-Markov model with Weibull distribution as the waiting time distribution to evaluate malaria serology evolution. We consider two-state model describing antibody reactivity defined by immunologists. We discuss in detail the application of these models to identify relationships between malaria control program and serological measurements of malaria transmission

scholarly journals Using Markov assumption with covariates to assess the Plasmodium falciparum malaria serological markers evolution

2020 ◽  
Vol 7 (`) ◽  
pp. 913-929
Author(s):  
Oumy Niass ◽  
Abdou Kâ Diongue ◽  
Philippe Saint-Pierre ◽  
Aissatou Touré
Keyword(s):  
Markov Model ◽  
Markov Models ◽  
Homogeneous Model ◽  
Control Program ◽  
Plasmodium Falciparum Malaria ◽  
Waiting Time Distribution ◽  
Piecewise Constant ◽  
Malaria Control Program ◽  
Markov Assumption ◽  
Two State Model

In this study, we develop Three Markov models which are continuous time-homogeneous Model, time piecewise constant intensities Markov model and semi-Markov model with Weibull distribution as the waiting time distribution to evaluate malaria serology evolution. We consider two-state model describing antibody reactivity defined by immunologists. We discuss in detail the application of these models to identify relationships between malaria control program and serological measurements of malaria transmission

scholarly journals Therapeutic efficacy of artemether-lumefantrine and artesunate-amodiaquine for the treatment of uncomplicated Plasmodium falciparum malaria in Mali, 2015–2016

2020 ◽  
Author(s):  
Youssouf Diarra ◽  
Oumar Koné ◽  
Lansana Sangaré ◽  
Lassina Doumbia ◽  
Dade Bouye Ben Haidara ◽  
...  
Keyword(s):  
Plasmodium Falciparum ◽  
Uncomplicated Malaria ◽  
Artemisinin Resistance ◽  
Control Program ◽  
Plasmodium Falciparum Malaria ◽  
Malaria Control Program ◽  
National Malaria Control Program ◽  
Pre Treatment ◽  
Better Than

Abstract Background The current first-line treatments for uncomplicated malaria recommended by the National Malaria Control Program in Mali are artemether–lumefantrine (AL) and artesunate–amodiaquine (ASAQ). From 2015–2016, we conducted an in vivo study to assess the clinical and parasitological responses to AL and ASAQ in Sélingué, Mali. Methods Children between 6 and 59 months of age with uncomplicated Plasmodium falciparum infection and 2,000–200,000 asexual parasites/µL of blood were enrolled, randomly assigned to either AL or ASAQ, and followed up for 42 days. Uncorrected and PCR-corrected efficacy results at days 28 and 42 were calculated. Known markers of resistance in the Pfk13, Pfmdr1, and Pfcrt genes were assessed using Sanger sequencing. Results A total of 449 patients were enrolled: 225 in the AL group and 224 in the ASAQ group. Uncorrected efficacy at day 28 was 83.4% (95% CI: 78.5–88.4%) in the AL arm and 93.1% (95% CI: 89.7–96.5%) in the ASAQ arm. The per protocol PCR-corrected efficacy at day 28 was 91.0% (86.0–95.9%) in the AL arm and 97.1% (93.6–100%) in the ASAQ arm. ASAQ was significantly (p < 0.05) better than AL for each of the aforementioned efficacy outcomes. No mutations associated with artemisinin resistance were identified in the Pfk13 gene. Overall, for Pfmdr1, the N86 allele and the NFD haplotype were the most common. The NFD haplotype was significantly more prevalent in the post-treatment than in the pre-treatment isolates in the AL arm (p < 0.01) but not in the ASAQ arm. For Pfcrt, the CVIET haplotype was the most common. Conclusions Our findings indicate that both AL and ASAQ remain effective for the treatment of uncomplicated malaria in Sélingué, Mali.

scholarly journals A copula-based multivariate hidden Markov model for modelling momentum in football

2021 ◽  
Author(s):  
Marius Ötting ◽  
Roland Langrock ◽  
Antonello Maruotti
Keyword(s):  
Markov Model ◽  
Hidden Markov Models ◽  
Markov Models ◽  
Hidden Markov ◽  
State Dependence ◽  
Change Points ◽  
Sports Fans ◽  
Modelling Framework ◽  
State Dependent ◽  
Different Levels

AbstractWe investigate the potential occurrence of change points—commonly referred to as “momentum shifts”—in the dynamics of football matches. For that purpose, we model minute-by-minute in-game statistics of Bundesliga matches using hidden Markov models (HMMs). To allow for within-state dependence of the variables, we formulate multivariate state-dependent distributions using copulas. For the Bundesliga data considered, we find that the fitted HMMs comprise states which can be interpreted as a team showing different levels of control over a match. Our modelling framework enables inference related to causes of momentum shifts and team tactics, which is of much interest to managers, bookmakers, and sports fans.

Projecting demands for renal replacement therapy in the Northern Territory: a stochastic Markov model

2018 ◽  
Vol 42 (4) ◽  
pp. 380 ◽  
Author(s):  
Jiqiong You ◽  
Yuejen Zhao ◽  
Paul Lawton ◽  
Steven Guthridge ◽  
Stephen P. McDonald ◽  
...  
Keyword(s):  
Renal Replacement Therapy ◽  
Markov Model ◽  
Replacement Therapy ◽  
Management Practices ◽  
Markov Models ◽  
Self Care ◽  
Potential Effect ◽  
Northern Territory ◽  
Baseline Scenario ◽  
On Demand

Objective The aim of the present study was to evaluate the potential effects of different health intervention strategies on demand for renal replacement therapy (RRT) services in the Northern Territory (NT). Methods A Markov chain simulation model was developed to estimate demand for haemodialysis (HD) and kidney transplantation (Tx) over the next 10 years, based on RRT registry data between 2002 and 2013. Four policy-relevant scenarios were evaluated: (1) increased Tx; (2) increased self-care dialysis; (3) reduced incidence of end-stage kidney disease (ESKD); and (4) reduced mortality. Results There were 957 new cases of ESKD during the study period, with most patients being Indigenous people (85%). The median age was 50 years at onset and 57 years at death, 12 and 13 years younger respectively than Australian medians. The prevalence of RRT increased 5.6% annually, 20% higher than the national rate (4.7%). If current trends continue (baseline scenario), the demand for facility-based HD (FHD) would approach 100 000 treatments (95% confidence interval 75 000–121 000) in 2023, a 5% annual increase. Increasing Tx (0.3%), increasing self-care (5%) and reducing incidence (5%) each attenuate demand for FHD to ~70 000 annually by 2023. Conclusions The present study demonstrates the effects of changing service patterns to increase Tx, self-care and prevention, all of which will substantially attenuate the growth in FHD requirements in the NT. What is known about the topic? The burden of ESKD is projected to increase in the NT, with demand for FHD doubling every 15 years. Little is known about the potential effect of changes in health policy and clinical practice on demand. What does this paper add? This study assessed the usefulness of a stochastic Markov model to evaluate the effects of potential policy changes on FHD demand. What are the implications for practitioners? The scenarios simulated by the stochastic Markov models suggest that changes in current ESKD management practices would have a large effect on future demand for FHD.

scholarly journals Computing Optimal Properties of Drugs Using Mathematical Models of Single Channel Dynamics

2018 ◽  
Vol 6 (1) ◽  
pp. 41-64 ◽  
Author(s):  
Aslak Tveito ◽  
Mary M. Maleckar ◽  
Glenn T. Lines
Keyword(s):  
Differential Equations ◽  
Markov Model ◽  
Stochastic Models ◽  
Markov Models ◽  
Single Channel ◽  
Probability Density Functions ◽  
Density Functions ◽  
Mathematical Framework ◽  
Wild Type ◽  
Channel Dynamics

AbstractSingle channel dynamics can be modeled using stochastic differential equations, and the dynamics of the state of the channel (e.g. open, closed, inactivated) can be represented using Markov models. Such models can also be used to represent the effect of mutations as well as the effect of drugs used to alleviate deleterious effects of mutations. Based on the Markov model and the stochastic models of the single channel, it is possible to derive deterministic partial differential equations (PDEs) giving the probability density functions (PDFs) of the states of the Markov model. In this study, we have analyzed PDEs modeling wild type (WT) channels, mutant channels (MT) and mutant channels for which a drug has been applied (MTD). Our aim is to show that it is possible to optimize the parameters of a given drug such that the solution of theMTD model is very close to that of the WT: the mutation’s effect is, theoretically, reduced significantly.We will present the mathematical framework underpinning this methodology and apply it to several examples. In particular, we will show that it is possible to use the method to, theoretically, improve the properties of some well-known existing drugs.

scholarly journals PAC-Bayes Bounds on Variational Tempered Posteriors for Markov Models

Entropy ◽  
2021 ◽  
Vol 23 (3) ◽  
pp. 313
Author(s):  
Imon Banerjee ◽  
Vinayak A. Rao ◽  
Harsha Honnappa
Keyword(s):  
Markov Model ◽  
Markov Models ◽  
Model Misspecification ◽  
Dependence Structure ◽  
Posterior Distributions ◽  
Ergodic Properties ◽  
Variational Approximations ◽  
Popular View ◽  
Probably Approximately Correct ◽  
Risk Bounds

Datasets displaying temporal dependencies abound in science and engineering applications, with Markov models representing a simplified and popular view of the temporal dependence structure. In this paper, we consider Bayesian settings that place prior distributions over the parameters of the transition kernel of a Markov model, and seek to characterize the resulting, typically intractable, posterior distributions. We present a Probably Approximately Correct (PAC)-Bayesian analysis of variational Bayes (VB) approximations to tempered Bayesian posterior distributions, bounding the model risk of the VB approximations. Tempered posteriors are known to be robust to model misspecification, and their variational approximations do not suffer the usual problems of over confident approximations. Our results tie the risk bounds to the mixing and ergodic properties of the Markov data generating model. We illustrate the PAC-Bayes bounds through a number of example Markov models, and also consider the situation where the Markov model is misspecified.

scholarly journals The Application of Baum-Welch Algorithm in Multistep Attack

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Yanxue Zhang ◽  
Dongmei Zhao ◽  
Jinxing Liu
Keyword(s):  
Markov Model ◽  
Hidden Markov Model ◽  
Hidden Markov Models ◽  
Viterbi Algorithm ◽  
Markov Models ◽  
Hidden Markov ◽  
Simulation Experiments ◽  
Forward Algorithm ◽  
Better Than

The biggest difficulty of hidden Markov model applied to multistep attack is the determination of observations. Now the research of the determination of observations is still lacking, and it shows a certain degree of subjectivity. In this regard, we integrate the attack intentions and hidden Markov model (HMM) and support a method to forecasting multistep attack based on hidden Markov model. Firstly, we train the existing hidden Markov model(s) by the Baum-Welch algorithm of HMM. Then we recognize the alert belonging to attack scenarios with the Forward algorithm of HMM. Finally, we forecast the next possible attack sequence with the Viterbi algorithm of HMM. The results of simulation experiments show that the hidden Markov models which have been trained are better than the untrained in recognition and prediction.

scholarly journals A Markov model of urban evolution: Neighbourhood change as a complex process

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0245357
Author(s):  
Daniel Silver ◽  
Thiago H. Silva
Keyword(s):  
Markov Model ◽  
Markov Models ◽  
Past Research ◽  
Hierarchical Approach ◽  
Evolutionary Trajectory ◽  
Complex Process ◽  
Trajectories Of Change ◽  
Neighbourhood Change ◽  
The Impact ◽  
Complexity Theories

This paper seeks to advance neighbourhood change research and complexity theories of cities by developing and exploring a Markov model of socio-spatial neighbourhood evolution in Toronto, Canada. First, we classify Toronto neighbourhoods into distinct groups using established geodemographic segmentation techniques, a relatively novel application in this geographic setting. Extending previous studies, we pursue a hierarchical approach to classifying neighbourhoods that situates many neighbourhood types within the city’s broader structure. Our hierarchical approach is able to incorporate a richer set of types than most past research and allows us to study how neighbourhoods’ positions within this hierarchy shape their trajectories of change. Second, we use Markov models to identify generative processes that produce patterns of change in the city’s distribution of neighbourhood types. Moreover, we add a spatial component to the Markov process to uncover the extent to which change in one type of neighbourhood depends on the character of nearby neighbourhoods. In contrast to the few studies that have explored Markov models in this research tradition, we validate the model’s predictive power. Third, we demonstrate how to use such models in theoretical scenarios considering the impact on the city’s predicted evolutionary trajectory when existing probabilities of neighbourhood transitions or distributions of neighbourhood types would hypothetically change. Markov models of transition patterns prove to be highly accurate in predicting the final distribution of neighbourhood types. Counterfactual scenarios empirically demonstrate urban complexity: small initial changes reverberate throughout the system, and unfold differently depending on their initial geographic distribution. These scenarios show the value of complexity as a framework for interpreting data and guiding scenario-based planning exercises.

scholarly journals Utilizing Gaze Behavior for Inferring Task Transitions Using Abstract Hidden Markov Models

2016 ◽  
Vol 19 (58) ◽  
pp. 1
Author(s):  
Daniel Fernando Tello Gamarra
Keyword(s):  
Markov Model ◽  
Hidden Markov Model ◽  
Hidden Markov Models ◽  
Markov Models ◽  
Hidden Markov ◽  
Hand Movement ◽  
Gaze Behavior ◽  
Improved Method ◽  
The Relationship

We demonstrate an improved method for utilizing observed gaze behavior and show that it is useful in inferring hand movement intent during goal directed tasks. The task dynamics and the relationship between hand and gaze behavior are learned using an Abstract Hidden Markov Model (AHMM). We show that the predicted hand movement transitions occur consistently earlier in AHMM models with gaze than those models that do not include gaze observations.

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