Since the start of the COVID-19 pandemic in China many models have appeared in the literature, trying to simulate its dynamics. Focusing on modeling the biological and sociological mechanisms which influence the disease spread, the basic reference example is the SIR model. However, it is too simple to be able to model those mechanisms (including the three main types of control measures: social distancing, contact tracing and health system measures) to fit real data and to simulate possible future scenarios. A question, then, arises: how much and how do we need to complexify a SIR model? We develop a -SEIHQRD model, which may be the simplest one satisfying the mentioned requirements for arbitrary territories and can be simplified in particular cases. We show its very good performance in the Italian case and study different future scenarios.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7775262 | PMC |
http://dx.doi.org/10.1016/j.physd.2020.132839 | DOI Listing |
Palliat Support Care
January 2025
Department of Theology and Religious Education, College of Liberal Arts, Manila, Philippines.
Teaching death, spirituality, and palliative care equips students with critical skills and perspectives for holistic patient care. This interdisciplinary approach fosters empathy, resilience, and personal growth while enhancing competence in end-of-life care. Using experiential methods like simulations and real patient interactions, educators bridge theory and practice.
View Article and Find Full Text PDFBrief Bioinform
November 2024
School of Engineering, Westlake University, No. 600 Dunyu Road, 310030 Zhejiang, P.R. China.
Single-cell RNA sequencing (scRNA-seq) offers remarkable insights into cellular development and differentiation by capturing the gene expression profiles of individual cells. The role of dimensionality reduction and visualization in the interpretation of scRNA-seq data has gained widely acceptance. However, current methods face several challenges, including incomplete structure-preserving strategies and high distortion in embeddings, which fail to effectively model complex cell trajectories with multiple branches.
View Article and Find Full Text PDFCirc Genom Precis Med
January 2025
Mary and Steve Wen Cardiovascular Division, Department of Medicine, University of California, Los Angeles. (W.F., N.D.W.).
Background: Lp(a; Lipoprotein[a]) is a predictor of atherosclerotic cardiovascular disease (ASCVD); however, there are few algorithms incorporating Lp(a), especially from real-world settings. We developed an electronic health record (EHR)-based risk prediction algorithm including Lp(a).
Methods: Utilizing a large EHR database, we categorized Lp(a) cut points at 25, 50, and 75 mg/dL and constructed 10-year ASCVD risk prediction models incorporating Lp(a), with external validation in a pooled cohort of 4 US prospective studies.
Zhonghua Yu Fang Yi Xue Za Zhi
January 2025
Immunization Program Institute of Shaanxi Provincial Center for Disease Control and Prevention, Xi'an 710054, China.
To investigate the safety of the tetravalent meningococcal conjugate vaccine (MPCV-ACYW) in combination with the inactivated poliomyelitis (IPV) vaccine and diphtheria-tetanus-acellular pertussis (DTaP) vaccine for infants aged 3-5 months and provide real-world evidence for the immunization strategy of vaccine combination. From June to October 2023, a total of 600 3-month-old infants were selected and divided into three groups: control group, mono-vaccination group and combined vaccination group. They were simultaneously or individually vaccinated with MPCV-ACYW, IPV and DTaP vaccines at 3, 4, and 5 months of age, respectively.
View Article and Find Full Text PDFJMIR Med Educ
January 2025
Centre for Digital Transformation of Health, University of Melbourne, Carlton, Australia.
Background: Learning health systems (LHS) have the potential to use health data in real time through rapid and continuous cycles of data interrogation, implementing insights to practice, feedback, and practice change. However, there is a lack of an appropriately skilled interprofessional informatics workforce that can leverage knowledge to design innovative solutions. Therefore, there is a need to develop tailored professional development training in digital health, to foster skilled interprofessional learning communities in the health care workforce in Australia.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!