State-Transition Model for Malaria Symptoms

Aims/ objectives: To develop a state-transition model for malaria symptoms. Study design: Longitudinal study. Place and Duration of Study: Department of Mathematics Masinde Muliro University of Science and Technology between January 2015 and December 2015. Methodology: We included 300 students (patients) with liver malaria disease, with or without the medical history of malaria disease, physical examination for signs and symptoms for both specific and non-specific symptom, investigation of the disease through laboratory test (BS test) and diagnostic test results. the focus of this study was to develop state-transition model for malaria symptoms. Bayesian method using Markov Chain Monte Carlo via Gibbs sampling algorithm was implemented for obtaining the parameter estimates. Results: The results of the study showed a significant association between malaria disease and observed symptoms Conclusion: The study findings provides a useful information that can be used for predicting malaria disease in areas where Blood slide test and rapid diagnostic test for malaria disease is not possible.

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Information processing systems. Open systems interconnection. Estelle: a formal description technique based on an extended state transition model

10.3403/00227838u ◽

2015 ◽

Keyword(s):

Information Processing ◽

State Transition ◽

Open Systems ◽

Transition Model ◽

Formal Description ◽

Extended State ◽

Formal Description Technique ◽

Open Systems Interconnection ◽

State Transition Model ◽

Description Technique

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Validation Support Tool to Cross-check the Behavioral Flows on a Requirements Analysis Model using the State Transition Model

2020 International Conference on Computational Science and Computational Intelligence (CSCI) ◽

10.1109/csci51800.2020.00326 ◽

2020 ◽

Author(s):

Hikaru Morita ◽

Saeko Matsuura

Keyword(s):

State Transition ◽

Requirements Analysis ◽

The State ◽

Transition Model ◽

Analysis Model ◽

Support Tool ◽

State Transition Model

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Exploring the Cost Effectiveness of Shared Decision Making for Choosing between Disease-Modifying Drugs for Relapsing-Remitting Multiple Sclerosis in the Netherlands: A State Transition Model

Medical Decision Making ◽

10.1177/0272989x20961091 ◽

2020 ◽

Vol 40 (8) ◽

pp. 1003-1019

Author(s):

Ingrid E. H. Kremer ◽

Mickael Hiligsmann ◽

Josh Carlson ◽

Marita Zimmermann ◽

Peter J. Jongen ◽

...

Keyword(s):

Decision Making ◽

Cost Effectiveness ◽

Shared Decision Making ◽

State Transition ◽

Transition Model ◽

Shared Decision ◽

Relapsing Remitting ◽

State Transition Model ◽

The Cost ◽

Relapsing Remitting Multiple Sclerosis

Background Up to 31% of patients with relapsing-remitting multiple sclerosis (RRMS) discontinue treatment with disease-modifying drug (DMD) within the first year, and of the patients who do continue, about 40% are nonadherent. Shared decision making may decrease nonadherence and discontinuation rates, but evidence in the context of RRMS is limited. Shared decision making may, however, come at additional costs. This study aimed to explore the potential cost-effectiveness of shared decision making for RRMS in comparison with usual care, from a (limited) societal perspective over a lifetime. Methods An exploratory economic evaluation was conducted by adapting a previously developed state transition model that evaluates the cost-effectiveness of a range of DMDs for RRMS in comparison with the best supportive care. Three potential effects of shared decision making were explored: 1) a change in the initial DMD chosen, 2) a decrease in the patient’s discontinuation in using the DMD, and 3) an increase in adherence to the DMD. One-way and probabilistic sensitivity analyses of a scenario that combined the 3 effects were conducted. Results Each effect separately and the 3 effects combined resulted in higher quality-adjusted life years (QALYs) and costs due to the increased utilization of DMD. A decrease in discontinuation of DMDs influenced the incremental cost-effectiveness ratio (ICER) most. The combined scenario resulted in an ICER of €17,875 per QALY gained. The ICER was sensitive to changes in several parameters. Conclusion This study suggests that shared decision making for DMDs could potentially be cost-effective, especially if shared decision making would help to decrease treatment discontinuation. Our results, however, may depend on the assumed effects on treatment choice, persistence, and adherence, which are actually largely unknown.

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