ArticleInfectious Disease Modelling2017
How heterogeneous susceptibility and recovery rates affect the spread of epidemics on networks.
Article in Infectious Disease Modelling, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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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
6 citing papers in PubMed, 25 citations in OpenAlex.
- The spread of infectious diseases from a physics perspective.Biology methods & protocols · 2023Article
- Infectious Disease Modeling with Socio-Viral Behavioral Aspects-Lessons Learned from the Spread of SARS-CoV-2 in a University.Tropical medicine and infectious disease · 2022Article
- Characterizing tuberculosis transmission dynamics in high-burden urban and rural settings.Scientific reports · 2022Article
- Mitigating bias in estimating epidemic severity due to heterogeneity of epidemic onset and data aggregation.Annals of epidemiology · 2022Article
- Time-dependent heterogeneity leads to transient suppression of the COVID-19 epidemic, not herd immunity.Proceedings of the National Academy of Sciences of the United States of America · 2021Review
- Disease persistence on temporal contact networks accounting for heterogeneous infectious periods.Royal Society open science · 2019Article
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
In this paper, an extended heterogeneous SIR model is proposed, which generalizes the heterogeneous mean-field theory. Different from the traditional heterogeneous mean-field model only taking into account the heterogeneity of degree, our model considers not only the heterogeneity of degree but also the heterogeneity of susceptibility and recovery rates. Then, we analytically study the basic reproductive number and the final epidemic size. Combining with numerical simulations, it is found that the basic reproductive number depends on the mean of distributions of susceptibility and disease course when both of them are independent. If the mean of these two distributions is identical, increasing the variance of susceptibility may block the spread of epidemics, while the corresponding increase in the variance of disease course has little effect on the final epidemic size. It is also shown that positive correlations between individual susceptibility, course of disease and the square of degree make the population more vulnerable to epidemic and avail to the epidemic prevalence, whereas the negative correlations make the population less vulnerable and impede the epidemic prevalence.
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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.