A Discrete Model for the Evolution of Infection Prior to Symptom Onset

Ripoll, Jordi; Font, J.

doi:10.3390/math11051092

Cited by 10 publications

(4 citation statements)

References 28 publications

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“…S4B). Moreover, there is no relationship between transmission rate (i.e., average shedding) prior to symptoms and the time until symptom onset, which belies the expected tradeoff between transmission and duration for the initial latent (pre-symptomatic) phase of infection, commonly assumed in theory [3][4][5]62]. While such a transmission-duration tradeoff is highly relevant for some viruses (e.g., HIV, [8,13]), other constraints may be needed to explain the lack of evolution towards ever faster replication in less deadly viral infections [63].…”

Section: Discussionmentioning

confidence: 86%

Using models to identify the causes of pre-symptomatic transmission from human infection data

Zhang,

Pak,

Greischar

2024

Preprint

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When disease transmission can precede symptom onset, containing outbreaks requires distinct strategies, like active surveillance. Yet it is rarely clear in advance when such interventions are needed, especially for emerging pathogens. Predicting pre-symptomatic transmission would be easier with knowledge of the within-host dynamics that enable presymptomatic transmission. To investigate those dynamics, we survey controlled human infection (CHI) trials with viral agents, which contain data on incubation times, infection duration, and transmission potential following inoculation with a known dose. We find that all studies report information on the duration of viral shedding, but few report the timing of symptoms. Only one study provided data on the timing of shedding and symptoms for individual participants, following norovirus inoculation. We apply a statistical model to individual time series to show significantly greater potential for pre-symptomatic transmission with faster viral replication, but no evidence for a tradeoff between transmission rate and duration during the pre-symptomatic phase. We then compare within-host models of pathogen replication, immune clearance, and symptom onset to identify plausible assumptions about the causes of pre-symptomatic transmission. We recover the pattern that peak shedding can precede symptom onset if we assume that symptoms are triggered by immune responses rather than pathogen abundance. Only by relaxing the standard assumption of exponential growth can we recover the pattern that faster viral replication enables pre-symptomatic transmission. Thus, data on symptom onset in CHI trials, paired with models, can illuminate the within-host dynamics underpinning pre-symptomatic transmission, guiding efforts to improve control strategies.

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Section: Discussionmentioning

confidence: 86%

Using models to identify the causes of pre-symptomatic transmission from human infection data

Zhang,

Pak,

Greischar

2024

Preprint

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“…[21,[25][26][27][28] and references therein. We remark that, in Equation (3) the term s(t) − β(t) s(t) i(t) is an approximation of the actual term e −β(t) i(t) s(t), corresponding to a Poisson distribution for the number of contacts per unit of time (e.g., day), see [29,30].…”

Section: The Sir Discrete Modelmentioning

confidence: 99%

Probabilistic Procedures for SIR and SIS Epidemic Dynamics on Erdös-Rényi Contact Networks

Rocha,

Carvalho,

Coimbra

2023

AppliedMath

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This paper introduces the mathematical formalization of two probabilistic procedures for susceptible-infected-recovered (SIR) and susceptible-infected-susceptible (SIS) infectious diseases epidemic models, over Erdös-Rényi contact networks. In our approach, we consider the epidemic threshold, for both models, defined by the inverse of the spectral radius of the associated adjacency matrices, which expresses the network topology. The epidemic threshold dynamics are analyzed, depending on the global dynamics of the network structure. The main contribution of this work is the relationship established between the epidemic threshold and the topological entropy of the Erdös-Rényi contact networks. In addition, a relationship between the basic reproduction number and the topological entropy is also stated. The trigger of the infectious state is studied, where the probability value of the stability of the infected state after the first instant, depending on the degree of the node in the seed set, is proven. Some numerical studies are included and illustrate the implementation of the probabilistic procedures introduced, complementing the discussion on the choice of the seed set.

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“…Indeed, transmission due to asymptomatic infections cannot be effectively identified, making it more difficult to contain and control [6][7][8][9]. New and complex mathematical models are needed to represent epidemic dynamics due to asymptomatic carriers [10][11][12][13][14][15], also considering infection transmission prior to symptom onset [16]. Most importantly, early detection of aberrations becomes a crucial point [1,17].…”

Section: Introductionmentioning

confidence: 99%

A Low-Cost Early Warning Method for Infectious Diseases with Asymptomatic Carriers

Gaspari

2024

Healthcare

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At the beginning of 2023, the Italian former prime minister, the former health minister and 17 others including the current president of the Lombardy region were placed under investigation on suspicion of aggravated culpable epidemic in connection with the government’s response at the start of the COVID-19 pandemic. The charges revolve around the failure by authorities to take adequate measures to prevent the spread of the virus in the Bergamo area, which experienced a significant excess of deaths during the initial outbreak. The aim of this paper is to analyse the pandemic data of Italy and the Lombardy region in the first 10 days of the pandemic, spanning from the 24th of February 2020 to the 4th of March 2020. The objective is to determine whether the use of early warning indicators could have facilitated the identification of a critical increase in infections. This identification, in turn, would have enabled the timely formulation of strategies for pandemic containment, thereby reducing the number of deaths. In conclusion, to translate our findings into practical guidelines, we propose a low-cost early warning method for infectious respiratory diseases with asymptomatic carriers.

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A Discrete Model for the Evolution of Infection Prior to Symptom Onset

Cited by 10 publications

References 28 publications

Using models to identify the causes of pre-symptomatic transmission from human infection data

Using models to identify the causes of pre-symptomatic transmission from human infection data

Probabilistic Procedures for SIR and SIS Epidemic Dynamics on Erdös-Rényi Contact Networks

A Low-Cost Early Warning Method for Infectious Diseases with Asymptomatic Carriers

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