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| http://dx.doi.org/10.1016/j.bja.2020.04.001 | DOI Listing |
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Global infectious disease early warning models: An updated review and lessons from the COVID-19 pandemic.
Infect Dis Model
June 2025
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Beijing, 100191, China.
An early warning model for infectious diseases is a crucial tool for timely monitoring, prevention, and control of disease outbreaks. The integration of diverse multi-source data using big data and artificial intelligence techniques has emerged as a key approach in advancing these early warning models. This paper presents a comprehensive review of widely utilized early warning models for infectious diseases around the globe.
View Article and Find Full Text PDFG-quadruplex-forming small RNA inhibits coronavirus and influenza A virus replication.
Commun Biol
January 2025
Division of Microbiology, Faculty of Pharmaceutical Sciences, Tohoku Medical and Pharmaceutical University, 4-4-1, Komatsuhima, Aoba-ku, Sendai, Miyagi, 981-8558, Japan.
Future pandemic threats may be caused by novel coronaviruses and influenza A viruses. Here we show that when directly added to a cell culture, 12mer guanine RNA (G12) and its phosphorothioate-linked derivatives (G12(S)), rapidly entered cytoplasm and suppressed the propagation of human coronaviruses and influenza A viruses to between 1/100 and nearly 1/1000 of normal virus infectivity without cellular toxicity and induction of innate immunity. Moreover, G12(S) alleviated the weight loss caused by coronavirus infection in mice.
View Article and Find Full Text PDFThe co-occurrence of multimorbidity and polypharmacy among middle-aged and older adults in Canada: A cross-sectional study using the Canadian Longitudinal Study on Aging (CLSA) and the Canadian Primary Care Sentinel Surveillance Network (CPCSSN).
PLoS One
January 2025
Department of Family Medicine, McMaster University, Hamilton, Ontario, Canada.
Background: There is an increasing prevalence of multiple conditions (multimorbidity) and multiple medications (polypharmacy) across many populations. Previous literature has focused on the prevalence and impact of these health states separately, but there is a need to better understand their co-occurrence.
Methods And Findings: This study reported on multimorbidity and polypharmacy among middle-aged and older adults in two national datasets: the Canadian Longitudinal Study on Aging (CLSA) and the Canadian Primary Care Sentinel Surveillance Network (CPCSSN).
Barriers and drivers influencing people's behaviour towards COVID-19 public health and social measures in the Netherlands.
Public Health Pract (Oxf)
June 2025
Erasmus MC, Pandemic and Disaster Preparedness Center, Delft, Rotterdam, the Netherlands.
Background: The disease burden of COVID-19 infection, morbidity, and mortality was unevenly distributed across different population subgroups. A one-size-fits-all approach may not reach all groups. Identifying barriers and drivers that influence behaviour towards COVID-19 public health and social measures (PHSM) is an important step when designing tailored interventions.
View Article and Find Full Text PDFImpacts, Adaptations, and Preparedness Among SNAP-Ed Implementers During the COVID-19 Pandemic: A Multistate Study.
J Public Health Manag Pract
November 2024
Author Affiliations: Department of Health Promotion, Education, and Behavior, University of South Carolina, Columbia, South Carolina (Ms Draper, Dr Younginer, and Mr Samin); Center for Excellence in Public Health, University of New England, Portland, Maine (Dr Rodriguez and Ms Bruno); and Department of Nutrition and Food Sciences, University of Rhode Island, Providence, Rhode Island (Dr Balestracci).
Objective: The study examines: 1) impacts of COVID-19 on the work of Supplemental Nutrition Assistance Program - Education (SNAP-Ed) implementers, 2) facilitators and barriers experienced in making adaptations, and 3) factors that would have helped with preparedness to adapt.
Design, Setting, And Participants: A purposive sample of 181 SNAP-Ed program implementers from across five states completed a survey or interview based on the study aims. Quantitative data was summarized with descriptive statistics and qualitative data was analyzed thematically.
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