Dataset Information

Characterizing the COVID-19 dynamics with a new epidemic model: Susceptible-exposed-asymptomatic-symptomatic-active-removed.

ABSTRACT: The coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread stealthily and presented a tremendous threat to the public. It is important to investigate the transmission dynamics of COVID-19 to help understand the impact of the disease on public health and the economy. In this article, we develop a new epidemic model that utilizes a set of ordinary differential equations with unknown parameters to delineate the transmission process of COVID-19. The model accounts for asymptomatic infections as well as the lag between symptom onset and the confirmation date of infection. To reflect the transmission potential of an infected case, we derive the basic reproduction number from the proposed model. Using the daily reported number of confirmed cases, we describe an estimation procedure for the model parameters, which involves adapting the iterated filter-ensemble adjustment Kalman filter (IF-EAKF) algorithm. To illustrate the use of the proposed model, we examine the COVID-19 data from Quebec for the period from 2 April 2020 to 10 May 2020 and carry out sensitivity studies under a variety of assumptions. Simulation studies are used to evaluate the performance of the proposed model under a variety of settings.

SUBMITTER: Yi GY

PROVIDER: S-EPMC9087003 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Characterizing the COVID-19 dynamics with a new epidemic model: Susceptible-exposed-asymptomatic-symptomatic-active-removed.

Yi Grace Y GY Hu Pingbo P He Wenqing W

The Canadian journal of statistics = Revue canadienne de statistique 20220415 2

The coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread stealthily and presented a tremendous threat to the public. It is important to investigate the transmission dynamics of COVID-19 to help understand the impact of the disease on public health and the economy. In this article, we develop a new epidemic model that utilizes a set of ordinary differential equations with unknown parameters to delineate the transmission proces ...[more]

PMID: 35573897

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Project description:Grapevine trunk diseases (GTDs) have become a major concern to viticulture worldwide, causing a high economic impact on yield and vineyard longevity in all growing areas. The prevalence of GTDs is increasing and, together with the absence of effective treatments, is currently one of the major challenges for viticulture sustainability. Given the urgent need to identify and develop new sustainable and effective protection strategies, a better understanding of grapevine defence mechanisms is crucial to develop more tolerant plants and provide new insights for disease management. This study explored the transcriptomic profile of GTDs symptomatic and asymptomatic plants of ‘Trincadeira’, a tolerant cultivar, and ‘Alicante Bouschet’, a susceptible cultivar to GTDs, using next-generation sequencing technology. RNA-seq yielded 1 598 differentially expressed genes (DEGs) between the two cultivars, and 64 DEGs between the groups with different symptomatology, regardless of the cultivar. Transport was revealed as the main biological process involved, generally activated in the susceptible cultivar ‘Alicante Bouschet’, suggesting that the DEGs associated with these processes may play an important role in disease development. Contrarily, the relative tolerance of ‘Trincadeira’ to this disease complex might be supported by the activation of secondary and hormonal metabolism and the differential expression of a set of defence-related genes, including resistance genes, which may act as key factors to limit GTDs infection. Furthermore, this study points to an important role of PER42 gene in the inhibition of GTDs symptoms. Our results provide new insights into the resistance mechanisms of grapevine to GTDs and may help to explain the different susceptibilities of grapevine plants to GTDs. To the best of our knowledge, this is the first time that the expression of grapevine defence-related gene expression has been studied in response to different GTDs-associated fungal infections under natural field conditions. We highlight the importance of these studies for the identification of candidate genes that may allow the development of new strategies to incorporate new sources of resistance. The activation or inhibition of potential plant response regulators can be used to promote resistance, thus providing sustainable and effective alternatives to successfully manage GTDs.

Dataset Information

Characterizing the COVID-19 dynamics with a new epidemic model: Susceptible-exposed-asymptomatic-symptomatic-active-removed.

Publications

Characterizing the COVID-19 dynamics with a new epidemic model: Susceptible-exposed-asymptomatic-symptomatic-active-removed.

Similar Datasets

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