ArticleApplied network science2020
Network model and analysis of the spread of Covid-19 with social distancing.
Article in Applied network science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
16 citing papers in PubMed, 3 citations in OpenAlex.
- Remarks on a Scaling Theory of Spread of COVID-19 with an Application to the Case of Bulgaria.Entropy (Basel, Switzerland) · 2026Article
- Designing network based intervention strategies for epidemics of infectious diseases from edge based infection probability.Scientific reports · 2026Article
- Anxiety and Depressive Symptoms Before and During the COVID-19 Pandemic: A Longitudinal Network Analysis.Depression and anxiety · 2026Article
- Modeling the Dynamics of Dengue Transmission with Awareness and Optimal Control Analysis.PloS one · 2025Article
- Beyond scale-free networks: integrating multilayer social networks with molecular clusters in the local spread of COVID-19.Scientific reports · 2023Article
- Strategies and Trends in COVID-19 Vaccination Delivery: What We Learn and What We May Use for the Future.Vaccines · 2023Article
- Epidemic Diffusion Network of Spain: A Mobility Model to Characterize the Transmission Routes of Disease.International journal of environmental research and public health · 2023Article
- Transmission Analysis of COVID-19 Outbreaks Associated with Places of Worship, Arkansas, May 2020-December 2020.Journal of religion and health · 2023Article
- The effects of momentary loneliness and COVID-19 stressors on hypothalamic-pituitary adrenal (HPA) axis functioning: A lockdown stage changes the association between loneliness and salivary cortisol.Psychoneuroendocrinology · 2022Article
- Occupations and their impact on the spreading of COVID-19 in urban communities.Scientific reports · 2022Article
- COVID-19 epidemic under the K-quarantine model: Network approach.Chaos, solitons, and fractals · 2022Article
- Article
- Prioritizing vaccination based on analysis of community networks.Applied network science · 2022Article
- Socio-demographic and health factors drive the epidemic progression and should guide vaccination strategies for best COVID-19 containment.Results in physics · 2021Article
- Mathematical modeling applied to epidemics: an overview.The Sao Paulo journal of mathematical sciences · 2021Article
- Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The first mitigation response to the Covid-19 pandemic was to limit person-to-person interaction as much as possible. This was implemented by the temporary closing of many workplaces and people were required to follow social distancing. Networks are a great way to represent interactions among people and the temporary severing of these interactions. Here, we present a network model of human-human interactions that could be mediators of disease spread. The nodes of this network are individuals and different types of edges denote family cliques, workplace interactions, interactions arising from essential needs, and social interactions. Each individual can be in one of four states: susceptible, infected, immune, and dead. The network and the disease parameters are informed by the existing literature on Covid-19. Using this model, we simulate the spread of an infectious disease in the presence of various mitigation scenarios. For example, lockdown is implemented by deleting edges that denote non-essential interactions. We validate the simulation results with the real data by matching the basic and effective reproduction numbers during different phases of the spread. We also simulate different possibilities of the slow lifting of the lockdown by varying the transmission rate as facilities are slowly opened but people follow prevention measures like wearing masks etc. We make predictions on the probability and intensity of a second wave of infection in each of these scenarios.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.