ArticlePhysica D. Nonlinear phenomena2021
Epidemic models with discrete state structures.
Article in Physica D. Nonlinear phenomena, 2021. 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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Who cites it
6 citing papers in PubMed.
- Modeling and control of Chikungunya with chronic infection.Infectious Disease Modelling · 2026Article
- Comparing the dynamics of COVID-19 infection and mortality in the United States, India, and Brazil.Physica D. Nonlinear phenomena · 2022Article
- Estimating a continuously varying offset between multivariate time series with application to COVID-19 in the United States.The European physical journal. Special topics · 2022Article
- The changing economic relationship between some of the major COVID-19 impacted countries with prominent wealth: a comparative study from the view point of stock markets.The European physical journal. Special topics · 2022Article
- Trends in COVID-19 prevalence and mortality: A year in review.Physica D. Nonlinear phenomena · 2021Article
- Nonlinear science against the COVID-19 pandemic.Physica D. Nonlinear phenomena · 2021Article
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Authors and funding
2 authors.
Funding
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Abstract
The state of an infectious disease can represent the degree of infectivity of infected individuals, or susceptibility of susceptible individuals, or immunity of recovered individuals, or a combination of these measures. When the disease progression is long such as for HIV, individuals often experience switches among different states. We derive an epidemic model in which infected individuals have a discrete set of states of infectivity and can switch among different states. The model also incorporates a general incidence form in which new infections are distributed among different disease states. We discuss the importance of the transmission-transfer network for infectious diseases. Under the assumption that the transmission-transfer network is strongly connected, we establish that the basic reproduction number
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