We perform estimations of compartment models for dengue transmission in rural Cambodia with increasing complexity regarding both model structure and the account for stochasticity. On the one hand, we successively account for three embedded sources of stochasticity: observation noise, demographic variability and environmental hazard. On the other hand, complexity in the model structure is increased by introducing vector-borne transmission, explicit asymptomatic infections and interacting virus serotypes. Using two sources of case data from dengue epidemics in Kampong Cham (Cambodia), models are estimated in the bayesian framework, with Markov Chain Monte Carlo and Particle Markov Chain Monte Carlo. We highlight the advantages and drawbacks of the different formulations in a practical setting. Although in this case the deterministic models provide a good approximation of the mean trajectory for a low computational cost, the stochastic frameworks better reflect and account for parameter and simulation uncertainty.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.mbs.2019.01.010 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Unveiling the role of miRNAs in Diminished Ovarian Reserve: an in silico network approach.
Syst Biol Reprod Med
December 2025
Department of Biosciences and Technology for Food, Agriculture and Environment, University of Teramo, Teramo, Italy.
MicroRNAs (miRNAs) have acquired an increased recognition to unravel the complex molecular mechanisms underlying Diminished Ovarian Reserve (DOR), one of the main responsible for infertility. To investigate the impact of miRNA profiles in granulosa cells and follicular fluid, crucial players in follicle development, this study employed a computational network theory approach to reconstruct potential pathways regulated by miRNAs in granulosa cells and follicular fluid of women suffering from DOR. Available data from published research were collected to create the FGC_MiRNome_MC, a representation of miRNA target genes and their interactions.
View Article and Find Full Text PDFOxidative and Excitatory Neurotoxic Stresses in CRISPR/Cas9-Induced Kynurenine Aminotransferase Knockout Mice: A Novel Model for Despair-Based Depression and Post-Traumatic Stress Disorder.
Front Biosci (Landmark Ed)
January 2025
HUN-REN-SZTE Neuroscience Research Group, Hungarian Research Network, University of Szeged (HUN-REN-SZTE), Danube Neuroscience Research Laboratory, H-6725 Szeged, Hungary.
Backgrounds: Memory and emotion are especially vulnerable to psychiatric disorders such as post-traumatic stress disorder (PTSD), which is linked to disruptions in serotonin (5-HT) metabolism. Over 90% of the 5-HT precursor tryptophan (Trp) is metabolized via the Trp-kynurenine (KYN) metabolic pathway, which generates a variety of bioactive molecules. Dysregulation of KYN metabolism, particularly low levels of kynurenic acid (KYNA), appears to be linked to neuropsychiatric disorders.
View Article and Find Full Text PDFHP1 Promotes the Centromeric Localization of ATRX and Protects Cohesion by Interfering Wapl Activity in Mitosis.
Front Biosci (Landmark Ed)
January 2025
The Key Laboratory of Model Animals and Stem Cell Biology in Hunan Province, Hunan Normal University Health Science Center, 410013 Changsha, Hunan, China.
Background: α thalassemia/mental retardation syndrome X-linked (ATRX) serves as a part of the sucrose nonfermenting 2 (SNF2) chromatin-remodeling complex. In interphase, ATRX localizes to pericentromeric heterochromatin, contributing to DNA double-strand break repair, DNA replication, and telomere maintenance. During mitosis, most ATRX proteins are removed from chromosomal arms, leaving a pool near the centromere region in mammalian cells, which is critical for accurate chromosome congression and sister chromatid cohesion protection.
View Article and Find Full Text PDFBSN Learning Pathways: A Leadership Collaboration to Prepare and Retain New Nurses in Specialized Practice Areas.
Nurs Leadersh (Tor Ont)
June 2025
Current nursing shortages, particularly in complex practice or specialty areas, coupled with high attrition rates of both seasoned and new graduate nurses, have required nursing leaders to consider creative approaches to recruit, prepare and retain nurses in specialty areas. This article describes a collaborative partnership between post-secondary institutions and health authorities in one province to address the need to prepare and retain nurses in high-priority specialized areas, such as the intensive care unit or the emergency department. This partnership allows for a proactive connection that leverages the strengths and resources of both healthcare and educational institutions.
View Article and Find Full Text PDFDevelopment and Validation of a GULP-Based Predictive Model for Dehydration in Elderly Patients with Post-Stroke Dysphagia.
Br J Hosp Med (Lond)
January 2025
Speech and Language Rehabilitation Department, Beijing Rehabilitation Hospital Affiliated with Capital Medical University, Beijing, China.
The background for establishing and verifying a dehydration prediction model for elderly patients with post-stroke dysphagia (PSD) based on General Utility for Latent Process (GULP) is as follows: For elderly patients with PSD, GULP technology is utilized to build a dehydration prediction model. This aims to improve the accuracy of dehydration risk assessment and provide clinical intervention, thereby offering a scientific basis and enhancing patient prognosis. This research highlights the innovative application of GULP technology in constructing complex medical prediction models and addresses the special health needs of elderly stroke patients.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!