While campaigns of vaccination against SARS-CoV-2 are underway across the world, communities face the challenge of a fair and effective distribution of a limited supply of doses. Current vaccine allocation strategies are based on criteria such as age or risk. In the light of strong spatial heterogeneities in disease history and transmission, we explore spatial allocation strategies as a complement to existing approaches. Given the practical constraints and complex epidemiological dynamics, designing effective vaccination strategies at a country scale is an intricate task. We propose a novel optimal control framework to derive the best possible vaccine allocation for given disease transmission projections and constraints on vaccine supply and distribution logistics. As a proof-of-concept, we couple our framework with an existing spatially explicit compartmental COVID-19 model tailored to the Italian geographic and epidemiological context. We optimize the vaccine allocation on scenarios of unfolding disease transmission across the 107 provinces of Italy, from January to April 2021. For each scenario, the optimal solution significantly outperforms alternative strategies that prioritize provinces based on incidence, population distribution, or prevalence of susceptibles. Our results suggest that the complex interplay between the mobility network and the spatial heterogeneities implies highly non-trivial prioritization strategies for effective vaccination campaigns. Our work demonstrates the potential of optimal control for complex and heterogeneous epidemiological landscapes at country, and possibly global, scales.
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http://dx.doi.org/10.1371/journal.pcbi.1010237 | DOI Listing |
J Biomater Sci Polym Ed
January 2025
Department of Microbiology, University of Central Punjab, Lahore, Pakistan.
Infected burn wounds present significant clinical challenges due to delayed healing and risk of infection, necessitating advanced treatments that offer both antimicrobial and regenerative properties. This study aimed to develop and evaluate multifunctional electrospun nanofiber films incorporating rhamnose (as an angiogenic agent) and therapeutic agents, namely fluticasone, mupirocin, ciprofloxacin, and silver sulfadiazine, for the enhanced healing of infected burn wounds. Nanofibers containing rhamnose, polyacrylonitrile, polyvinyl alcohol and therapeutic agents were fabricated electrospinning.
View Article and Find Full Text PDFXi Bao Yu Fen Zi Mian Yi Xue Za Zhi
January 2025
National Key Laboratory of Bioreactors, School of Biological Engineering, East China University of Science and Technology, Shanghai 200237, China. *Corresponding author, E-mail:
BMC Oral Health
January 2025
Sub-Institute of Public Safety Standardization, China National Institute of Standardization, No.4 Zhichun Road, Haidian District, Beijing, 100191, PR China.
Background: This study aimed to establish a model for predicting the difficulty of mandibular third molar extraction based on a Bayesian network to meet following requirements: (1) analyse the interaction of the primary risk factors; (2) output quantitative difficulty-evaluation results based on the patient's personal situation; and (3) identify key surgical points and propose surgical protocols to decrease complications.
Methods: Relevant articles were searched to identify risk factors. Clinical knowledge and experience were used to analyse the risk factors to establish the Bayesian network.
Mikrochim Acta
January 2025
Shanxi Key Laboratory of Micro Nano Sensors & Artificial Intelligence Perception, College of Integrated Circuits, Taiyuan University of Technology, Taiyuan, 030024, China.
African swine fever (ASF) is an acute hemorrhagic disease in pigs caused by the African swine fever virus (ASFV), which has a high mortality rate and brought great damage to global pig farming industry. At present, there is no effective treatment or vaccine to combat ASFV infection, so early detection of ASFV has become particularly important. Therefore, the PDMS/chitosan/MPMs composite film was proposed to detect ASFV P72.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Orthopaedics, Traditional Chinese Medical Hospital of Gansu Province, Qilihe District, Guazhou Street 418, Lanzhou, 730050,, Gansu, China.
Knee osteoarthritis (KOA) represents a progressive degenerative disorder characterized by the gradual erosion of articular cartilage. This study aimed to develop and validate biomarker-based predictive models for KOA diagnosis using machine learning techniques. Clinical data from 2594 samples were obtained and stratified into training and validation datasets in a 7:3 ratio.
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