Against the current COVID-19 pandemic, governments worldwide have devised a variety of non-pharmaceutical interventions to mitigate it. However, it is generally difficult to estimate the joint impact of different control strategies. In this paper, we tackle this question with an extended epidemic SEIR model, informed by a socio-political classification of different interventions. First, we inquire the conceptual effect of mitigation parameters on the infection curve. Then, we illustrate the potential of our model to reproduce and explain empirical data from a number of countries, to perform cross-country comparisons. This gives information on the best synergies of interventions to control epidemic outbreaks while minimising impact on socio-economic needs. For instance, our results suggest that, while rapid and strong lockdown is an effective pandemic mitigation measure, a combination of social distancing and early contact tracing can achieve similar mitigation synergistically, while keeping lower isolation rates. This quantitative understanding can support the establishment of mid- and long-term interventions, to prepare containment strategies against further outbreaks. This paper also provides an online tool that allows researchers and decision makers to interactively simulate diverse scenarios with our model.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8139462 | PMC |
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0252019 | PLOS |
Postgrad Med J
January 2025
Proof of Concept Center, Eastern Hepatobiliary Surgery Hospital, Third Affiliated Hospital, Second Military Medical University, Naval Medical University, No. 255, Yangpu District, Shanghai, 200433, China.
Objectives: The objective was to investigate the role of double extraction in reducing data errors in evidence synthesis for pharmaceutical and non-pharmaceutical interventions.
Design: Crossover randomized controlled trial (RCT).
Setting: University and hospital with teaching programs in evidence-based medicine.
Math Biosci
January 2025
Biocomplexity Institute, University of Virginia, VA, USA; Department of Computer Science, University of Virginia, VA, USA.
Public health interventions reduce infection risk, while imposing significant costs on both individuals and the society. Interventions can also lead to behavioral changes, as individuals weigh the cost and benefits of avoiding infection. Aggregate epidemiological models typically focus on the population-level consequences of interventions, often not incorporating the mechanisms driving behavioral adaptations associated with interventions compliance.
View Article and Find Full Text PDFInj Prev
January 2025
Traffic Injury Research Foundation, Ottawa, Ontario, Canada.
Introduction: Understanding the impact of non-pharmaceutical COVID-19 interventions (NPIs) on road safety has become increasingly important to uncover the unintended consequences of the pandemic. This study explores how NPIs influenced alcohol-related and speed-related traffic collisions, including fatalities and serious injuries, in five cities of the province of Québec, Canada: Montréal, Québec, Laval, Longueuil and Sherbrooke.
Methods: We performed Poisson interrupted time-series analyses using daily traffic fatality and injury data from 2015 to 2022, to assess the change in rate expressed per 10 000 population.
Adv Gerontol
January 2025
V.M.Bekhterev National Research Medical Center for Psychiatry and Neurology, 3 Bekhterev str., St. Petersburg 192019, Russian Federation, e-mail:
The article describes the forms, causes and consequences of insomnia in the elderly. It shows the clinical features of dyssomnic disorders in comorbid depressive and anxiety disorders, as the most common mental pathology of old age. The approaches of Russian and foreign authors to the diagnosis and treatment of insomnia in the elderly are considered.
View Article and Find Full Text PDFSci Rep
December 2024
DIME, University of Genova, via all'Opera Pia 15, 16145, Genova, Italy.
During the COVID-19 pandemic, effective public policy interventions have been crucial in combating virus transmission, sparking extensive debate on crisis management strategies and emphasizing the necessity for reliable models to inform governmental decisions, particularly at the local level. Leveraging disaggregated socio-demographic microdata, including social determinants, age-specific strata, and mobility patterns, we design a comprehensive network model of Catalonia's population and, through numerical simulation, assess its response to the outbreak of COVID-19 over the two-year period 2020-21. Our findings underscore the critical importance of timely implementation of broad non-pharmaceutical measures and effective vaccination campaigns in curbing virus spread; in addition, the identification of high-risk groups and their corresponding maps of connections within the network paves the way for tailored and more impactful interventions.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!