On the heterogeneous spread of COVID-19 in Chile

Freire-Flores, Danton; Llanovarced-Kawles, Nyna; Sanchez-Daza, Anamaria; Olivera-Nappa, Álvaro

doi:10.1016/j.chaos.2021.111156

Cited by 14 publications

(7 citation statements)

References 37 publications

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“…7b). Therefore, most decisions have been based on trends of the current reproduction number, which, however, does not capture the spreading dynamics of VoCs [27][28][29][30][31]. The situation is similar in other countries in Latin America and the global south, where countries have not reached a sequencing rate of 1 % of their positive tests [22].…”

Section: Discussionmentioning

confidence: 99%

“…Therefore, vaccination was not considered an essential variable in this modelling. There is also no spatial resolution in the model (as in, e.g., [30,42]) as we assume sampling to be representative, and these would only affect wave patterns (which do not compromise our results). Besides, we excluded contact tracing from our model; samples collected within the same infection chain are likely caused by the same SARS-CoV-2 variant (thus, including them would induce selection biases in our analyses).…”

Section: Discussionmentioning

confidence: 99%

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Model-based assessment of sampling protocols for infectious disease genomic surveillance

Contreras,

Oróstica,

Daza-Sanchez

et al. 2023

Preprint

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Genomic surveillance of infectious diseases allows monitoring circulating and emerging variants and quantifying their epidemic potential. However, due to the high costs associated with genomic sequencing, only a limited number of samples can be analysed. Thus, it is critical to understand how sampling impacts the information generated. Here, we combine a compartmental model for the spread of COVID-19 (distinguishing several SARS-CoV-2 variants) with different sampling strategies to assess their impact on genomic surveillance. In particular, we compare adaptive sampling, i.e., dynamically reallocating resources between screening at points of entry and inside communities, and constant sampling, i.e., assigning fixed resources to the two locations. We show that adaptive sampling uncovers new variants up to five weeks earlier than constant sampling, significantly reducing detection delays and estimation errors. This advantage is most prominent at low sequencing rates. Although increasing the sequencing rate has a similar effect, the marginal benefits of doing so may not always justify the associated costs. Consequently, it is convenient for countries with comparatively few resources to operate at lower sequencing rates, thereby profiting the most from adaptive sampling. Finally, our methodology can be readily adapted to study undersampling in other dynamical systems.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Model-based assessment of sampling protocols for infectious disease genomic surveillance

Contreras,

Oróstica,

Daza-Sanchez

et al. 2023

Preprint

View full text Add to dashboard Cite

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“…One of the important ideas is to study the spread of COVID-19 through mathematical models. To that end, a number of mathematical models have been developed over the past two years to study local infections, estimate peaks in the number of people infected, and suggest ways to control the spread of the disease [7] , [8] , [9] , [10] , [11] , [12] , [13] , [14] , [15] , [16] , [28] , [29] , [30] , [31] , [32] , [33] , [34] , [35] , [36] , [37] , [38] , [39] , [40] .…”

Section: Introductionmentioning

confidence: 99%

Modeling and optimal control of mutated COVID-19 (Delta strain) with imperfect vaccination

Guo

2022

Chaos, Solitons & Fractals

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As people around the world work to stop the COVID-19 pandemic, mutated COVID-19 (Delta strain) that are more contagious are emerging in many places. How to develop effective and reasonable plans to prevent the spread of mutated COVID-19 is an important issue. In order to simulate the transmission of mutated COVID-19 (Delta strain) in China with a certain proportion of vaccination, we selected the epidemic situation in Jiangsu Province as a case study. To solve this problem, we develop a novel epidemic model with a vaccinated population. The basic properties of the model is analyzed, and the expression of the basic reproduction number is obtained. We collect data on the Delta strain epidemic in Jiangsu Province, China from July 20 to August 5, 2021. The weighted nonlinear least square estimation method is used to fit the daily asymptomatic infected people, common infected people and severe infected people. The estimated parameter values are obtained, the approximate values of the basic reproduction number are calculated . Through the global sensitivity analysis, we identify some parameters that have a greater impact on the prevalence of the disease. Finally, according to the evaluation results of parameter influence, we consider three control measures (vaccination, isolation and nucleic acid testing) to control the spread of the disease. The results of the study found that the optimal control measure is to dynamically adjust the three control measures to achieve the lowest number of infections at the lowest cost. The research in this paper can not only enrich theoretical research on the transmission of COVID-19, but also provide reliable control suggestions for countries and regions experiencing mutated COVID-19 epidemics.

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“…The spread of COVID-19 in Chile has been remarkably heterogeneous, not only because of its geography and sparse urbanization but also because of the pronounced social inequalities [16][17][18][19][20][21]. The Chilean government has deployed an ambitious vaccination program [22,23], so that, to date, almost 60% of the total population has been fully vaccinated [24].…”

Section: Introductionmentioning

confidence: 99%

Mutational signatures and transmissibility of SARS-CoV-2 Gamma and Lambda variants

Oróstica,

Contreras,

Mohr

et al. 2021

Preprint

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The emergence of SARS-CoV-2 variants of concern endangers the long-term control of COVID-19, especially in countries with limited genomic surveillance. In this work, we explored genomic drivers of contagion in Chile. We sequenced 3443 SARS-CoV-2 genomes collected between January and July 2021, where the Gamma (P.1), Lambda (C.37), Alpha (B.1.1.7), B.1.1.348, and B.1.1 lineages were predominant. Using a Bayesian model tailored for limited genomic surveillance, we found that Lambda and Gamma variants' reproduction numbers were about 5% and 16% larger than Alpha's, respectively. We observed an overabundance of mutations in the Spike gene, strongly correlated with the variant's transmissibility. Furthermore, the variants' mutational signatures featured a breakpoint concurrent with the beginning of vaccination (mostly CoronaVac, an inactivated virus vaccine), indicating an additional putative selective pressure. Thus, our work provides a reliable method for quantifying novel variants' transmissibility under subsampling (as newly-reported Delta, B.1.617.2) and highlights the importance of continuous genomic surveillance.

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On the heterogeneous spread of COVID-19 in Chile

Cited by 14 publications

References 37 publications

Model-based assessment of sampling protocols for infectious disease genomic surveillance

Model-based assessment of sampling protocols for infectious disease genomic surveillance

Modeling and optimal control of mutated COVID-19 (Delta strain) with imperfect vaccination

Mutational signatures and transmissibility of SARS-CoV-2 Gamma and Lambda variants

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