Finite-time scaling for epidemic processes with power-law superspreading events

Falcó, Carles; Corral, √Ålvaro

doi:10.1103/physreve.105.064122

Cited by 4 publications

(2 citation statements)

References 51 publications

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“…Hence, ensuring a precise diagnosis is paramount to preventing superspreading events after successful exposure and, therefore, RT-qPCR must be used. Assuming a power-law structure in the distribution of superspreaders [61], the number of test required remains approximately constant for a fixed population size and interaction structure. Were the stratified structure to broaden at the top, the national guides of antigen-based test with confirmatory RT-qPCR become the next reasonable choice.…”

Section: Covid-19 In Costa Rica: Reactive Testing With Rt-qpcrmentioning

confidence: 99%

Estimating the performance of mass testing strategies for COVID-19: a case study for Costa Rica

Solís

Pasquier

Núñez-Corrales

et al. 2022

Preprint

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Devising effective mass testing strategies to control and suppress COVID-19 pandemic waves make up a complex sociotechnical challenge. It requires a trade-off between performing detection technologies in terms of specificity and sensitivity, and the availability and cost of individual tests per technology. Overcoming this trade-off requires first predicting the level of risk of exposure across the population available. Then selecting testing strategies that match resources to maximize positive case detection and optimize the number of tests and their total cost during sustained mass testing campaigns. In this article, we derive the behavior of four different mass testing strategies, grounded in guidelines and public health policies issued by the Costa Rican public healthcare system. We assume a (privacy-preserving) pre-classifier applied to patient data, Capable of partitioning suspected individuals into low-risk and high-risk groups. We consider the impact of three testing technologies, RT-qPCR, antigen-based testing and saliva-based testing (RT-LAMP). When available, we introduced a category of essential workers. Numerical simulation results confirm that strategies using only RT-qPCR tests cannot achieve sufficient stock capacity to provide efficient detection regardless of prevalence, sensitivity, or specificity. Strategies that harness the power of both pooling and RT-LAMP either maximize stock capacity or detection, efficiency, or both. Our work reveals that investing both in data quality and classification accuracy can improve the odds of achieving pandemic control and mitigation. Future work will concentrate, based on our findings, on constructing representative synthetic data through agent-based modeling and studying the properties of specific pre-classifiers under various scenarios.

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Section: Covid-19 In Costa Rica: Reactive Testing With Rt-qpcrmentioning

confidence: 99%

Estimating the performance of mass testing strategies for COVID-19: a case study for Costa Rica

Solís

Pasquier

Núñez-Corrales

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…More recently, these methods have been used to model the spread of COVID cases in communities during the early stages of the pandemic [5,6]. As time progressed, varying local containment efforts caused changes in the number of infected members in each community [7,8], leading to periods of increase and decrease. In this paper, we describe a stochastic process model built on a branching process in random environments (BPRE) that explicitly takes into account periods of growth and decrease in the transmission rate of the virus.…”

Section: Introductionmentioning

confidence: 99%

Branching processes in random environments with thresholds

Francisci,

Vidyashankar

2023

Adv. Appl. Probab.

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Motivated by applications to COVID dynamics, we describe a model of a branching process in a random environment $\{Z_n\}$ whose characteristics change when crossing upper and lower thresholds. This introduces a cyclical path behavior involving periods of increase and decrease leading to supercritical and subcritical regimes. Even though the process is not Markov, we identify subsequences at random time points $\{(\tau_j, \nu_j)\}$ —specifically the values of the process at crossing times, viz. $\{(Z_{\tau_j}, Z_{\nu_j})\}$ —along which the process retains the Markov structure. Under mild moment and regularity conditions, we establish that the subsequences possess a regenerative structure and prove that the limiting normal distributions of the growth rates of the process in supercritical and subcritical regimes decouple. For this reason, we establish limit theorems concerning the length of supercritical and subcritical regimes and the proportion of time the process spends in these regimes. As a byproduct of our analysis, we explicitly identify the limiting variances in terms of the functionals of the offspring distribution, threshold distribution, and environmental sequences.

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Moments of undersampled distributions: Application to the size of epidemics

Corral

2024

Chaos, Solitons & Fractals

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Finite-time scaling for epidemic processes with power-law superspreading events

Cited by 4 publications

References 51 publications

Estimating the performance of mass testing strategies for COVID-19: a case study for Costa Rica

Estimating the performance of mass testing strategies for COVID-19: a case study for Costa Rica

Branching processes in random environments with thresholds

Moments of undersampled distributions: Application to the size of epidemics

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