Although COVID-19 has caused severe suffering globally, the efficacy of nonpharmaceutical interventions has been greater than typical models have predicted. Meanwhile, evidence is mounting that the pandemic is characterized by superspreading. Capturing this phenomenon theoretically requires modeling at the scale of individuals. Using a mathematical model, we show that superspreading drastically enhances mitigations which reduce the overall personal contact number and that social clustering increases this effect.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1103/PhysRevLett.126.118301 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
State-space modelling using wastewater virus and epidemiological data to estimate reported COVID-19 cases and the potential infection numbers.
J R Soc Interface
January 2025
Department of Frontier Science for Advanced Environment, Graduate School of Environmental Studies, Tohoku University, Aoba 6-6-06, Aramaki, Aoba-ku, Sendai, Miyagi 980-8579, Japan.
The current situation of COVID-19 measures makes it difficult to accurately assess the prevalence of SARS-CoV-2 due to a decrease in reporting rates, leading to missed initial transmission events and subsequent outbreaks. There is growing recognition that wastewater virus data assist in estimating potential infections, including asymptomatic and unreported infections. Understanding the COVID-19 situation hidden behind the reported cases is critical for decision-making when choosing appropriate social intervention measures.
View Article and Find Full Text PDFComparative Evolutionary Epidemiology of SARS-CoV-2 Delta and Omicron Variants in Kuwait.
Viruses
November 2024
Department of Public Health, Ministry of Health, P.O. Box 24923, Kuwait City 13110, Kuwait.
Continuous surveillance is critical for early intervention against emerging novel SARS-CoV-2 variants. Therefore, we investigated and compared the variant-specific evolutionary epidemiology of all the Delta and Omicron sequences collected between 2021 and 2023 in Kuwait. We used Bayesian phylodynamic models to reconstruct, trace, and compare the two variants' demographics, phylogeographic, and host characteristics in shaping their evolutionary epidemiology.
View Article and Find Full Text PDFFractional modelling of COVID-19 transmission incorporating asymptomatic and super-spreader individuals.
Math Biosci
January 2025
Center for Research and Development in Mathematics and Applications (CIDMA), Department of Mathematics, University of Aveiro, Aveiro 3810-193, Portugal. Electronic address:
The COVID-19 pandemic has presented unprecedented challenges worldwide, necessitating effective modelling approaches to understand and control its transmission dynamics. In this study, we propose a novel approach that integrates asymptomatic and super-spreader individuals in a single compartmental model. We highlight the advantages of utilizing incommensurate fractional order derivatives in ordinary differential equations, including increased flexibility in capturing disease dynamics and refined memory effects in the transmission process.
View Article and Find Full Text PDFCOVID-19 outbreaks in endangered Indigenous groups from the Amazonia during the first wave of the COVID-19 pandemic in Ecuador: a retrospective cross-sectional study.
Rural Remote Health
September 2024
One Health Research Group, Universidad de las Américas, Quito, Ecuador.
Introduction: The COVID-19 pandemic has deeply affected Latin American countries, with countless COVID-19 cases and deaths. In countries like Mexico, Brazil, Peru, Colombia and Ecuador, the public health system collapsed and the lack of testing capacity did not allow control of the spread of SARS-CoV-2 during the first year of the COVID-19 pandemic. Moreover, rural and Indigenous communities in these countries, particularly isolated ones like those in the Amazon Basin, were neglected in terms of access to COVID-19 testing and medical aid.
View Article and Find Full Text PDFUnderstanding the progress of COVID-19 transmission in a rural district: a social network approach.
PeerJ
December 2024
Public Health Development Unit, Department of Public Health, Selangor State Health Department, Shah Alam, Selangor, Malaysia.
Background: Social interactions within and between communities influenced the spread of COVID-19. By using social network analysis (SNA), we aimed to understand the effect of social interaction on the spread of disease in a rural district.
Method: A retrospective record review study using positive COVID-19 cases and contact-tracing data from an area in Malaysia was performed and analysed using the SNA method through R software and visualised by Gephi software.
Want 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!