A model for the emergence of drug resistance in the presence of asymptomatic infections

Robinson, Marguerite; Stilianakis, Nikolaos I.

doi:10.1016/j.mbs.2013.03.003

Cited by 66 publications

(93 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…19 and 20). Other research has focused on the formulation and analyses of mathematical models for host population epidemiological dynamics that include asymptomatic individuals (2,(21)(22)(23)(24). In all these epidemiological modeling studies, evolutionary dynamics of latency were ignored.…”

Section: Significancementioning

confidence: 99%

Dynamics in a simple evolutionary-epidemiological model for the evolution of an initial asymptomatic infection stage

Saad-Roy

Wingreen

Levin

et al. 2020

Proc. Natl. Acad. Sci. U.S.A.

View full text Add to dashboard Cite

Pathogens exhibit a rich variety of life history strategies, shaped by natural selection. An important pathogen life history characteristic is the propensity to induce an asymptomatic yet productive (transmissive) stage at the beginning of an infection. This characteristic is subject to complex trade-offs, ranging from immunological considerations to population-level social processes. We aim to classify the evolutionary dynamics of such asymptomatic behavior of pathogens (hereafter “latency”) in order to unify epidemiology and evolution for this life history strategy. We focus on a simple epidemiological model with two infectious stages, where hosts in the first stage can be partially or fully asymptomatic. Immunologically, there is a trade-off between transmission and progression in this first stage. For arbitrary trade-offs, we derive different conditions that guarantee either at least one evolutionarily stable strategy (ESS) at zero, some, or maximal latency of the first stage or, perhaps surprisingly, at least one unstable evolutionarily singular strategy. In this latter case, there is bistability between zero and nonzero (possibly maximal) latency. We then prove the uniqueness of interior evolutionarily singular strategies for power-law and exponential trade-offs: Thus, bistability is always between zero and maximal latency. Overall, previous multistage infection models can be summarized with a single model that includes evolutionary processes acting on latency. Since small changes in parameter values can lead to abrupt transitions in evolutionary dynamics, appropriate disease control strategies could have a substantial impact on the evolution of first-stage latency.

show abstract

Section: Significancementioning

confidence: 99%

Dynamics in a simple evolutionary-epidemiological model for the evolution of an initial asymptomatic infection stage

Saad-Roy

Wingreen

Levin

et al. 2020

Proc. Natl. Acad. Sci. U.S.A.

View full text Add to dashboard Cite

show abstract

“…Since, in the case of the COVID-19, there is a relevant percentage of the infected individuals that are asymptomatic, we split the class of infected individuals in symptomatic and asymptomatic 7 – 9 : where is the number of asymptomatic individuals, is the number of symptomatic individuals, and are the recovered individuals from the asymptomatic and symptomatic infection, respectively, and p is the proportion of individuals who develop symptoms. For ease of reference, we call this model “ SIRASD ” (Susceptible-Infected-Recovered for Asymptomatic-Symptomatic and Dead) model.…”

Section: Introductionmentioning

confidence: 99%

Modeling and forecasting the early evolution of the Covid-19 pandemic in Brazil

Bastos

Cajueiro

2020

Sci Rep

171

138

View full text Add to dashboard Cite

We model and forecast the early evolution of the COVID-19 pandemic in Brazil using Brazilian recent data from February 25, 2020 to March 30, 2020. This early period accounts for unawareness of the epidemiological characteristics of the disease in a new territory, sub-notification of the real numbers of infected people and the timely introduction of social distancing policies to flatten the spread of the disease. We use two variations of the SIR model and we include a parameter that comprises the effects of social distancing measures. Short and long term forecasts show that the social distancing policy imposed by the government is able to flatten the pattern of infection of the COVID-19. However, our results also show that if this policy does not last enough time, it is only able to shift the peak of infection into the future keeping the value of the peak in almost the same value. Furthermore, our long term simulations forecast the optimal date to end the policy. Finally, we show that the proportion of asymptomatic individuals affects the amplitude of the peak of symptomatic infected, suggesting that it is important to test the population.

show abstract

“…Modelling has also revealed the importance of accounting for asymptomatic carriers in epidemiological models. For example, under certain conditions, neglecting pre-symptomatic influenza transmission was shown to overestimate the impact of interventions targeting symptomatically infected hosts [ 12 ]. Neglecting asymptomatic carriers in a model of Ebola virus transmission was shown to significantly overestimate the projected cumulative incidence of symptomatic infections, as well as overestimate the population-level vaccination coverage needed to contain epidemics [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

Implications of asymptomatic carriers for infectious disease transmission and control

Chisholm

Campbell

et al. 2018

R. Soc. open sci.

View full text Add to dashboard Cite

For infectious pathogens such as Staphylococcus aureus and Streptococcus pneumoniae , some hosts may carry the pathogen and transmit it to others, yet display no symptoms themselves. These asymptomatic carriers contribute to the spread of disease but go largely undetected and can therefore undermine efforts to control transmission. Understanding the natural history of carriage and its relationship to disease is important for the design of effective interventions to control transmission. Mathematical models of infectious diseases are frequently used to inform decisions about control and should therefore accurately capture the role played by asymptomatic carriers. In practice, incorporating asymptomatic carriers into models is challenging due to the sparsity of direct evidence. This absence of data leads to uncertainty in estimates of model parameters and, more fundamentally, in the selection of an appropriate model structure. To assess the implications of this uncertainty, we systematically reviewed published models of carriage and propose a new model of disease transmission with asymptomatic carriage. Analysis of our model shows how different assumptions about the role of asymptomatic carriers can lead to different conclusions about the transmission and control of disease. Critically, selecting an inappropriate model structure, even when parameters are correctly estimated, may lead to over- or under-estimates of intervention effectiveness. Our results provide a more complete understanding of the role of asymptomatic carriers in transmission and highlight the importance of accurately incorporating carriers into models used to make decisions about disease control.

show abstract

A model for the emergence of drug resistance in the presence of asymptomatic infections

Cited by 66 publications

References 43 publications

Dynamics in a simple evolutionary-epidemiological model for the evolution of an initial asymptomatic infection stage

Dynamics in a simple evolutionary-epidemiological model for the evolution of an initial asymptomatic infection stage

Modeling and forecasting the early evolution of the Covid-19 pandemic in Brazil

Implications of asymptomatic carriers for infectious disease transmission and control

Contact Info

Product

Resources

About