Dataset Information

Model-based prediction of SARS-CoV-2 in Ethiopia: Extended SEIR model

ABSTRACT: One of three models used to describe dynamics of COVID-19 spread in Ethiopia. Here the two investigated population groups healthcare workers and community members are modeled as separate but interacting groups. Results are published in https://www.thelancet.com/journals/langlo/article/PIIS2214-109X(21)00386-7/fulltext

SUBMITTER: Simon Merkt

PROVIDER: MODEL2212310001 | BioModels | 2023-01-04

REPOSITORIES: BioModels

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			Action	DRS
	MODEL2212310001?filename=covid_ethiopia_seir2x.yaml	Other
	MODEL2212310001?filename=covid_ethiopia_seir2x_conditions.tsv	Tabular
	MODEL2212310001?filename=covid_ethiopia_seir2x_measurements.tsv	Tabular
	MODEL2212310001?filename=covid_ethiopia_seir2x_model.sbml	Other
	MODEL2212310001?filename=covid_ethiopia_seir2x_observables.tsv	Tabular

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Project description:Variations in the susceptibility to SARS-CoV-2 infection and risk of severe disease are yet not well understood. The information on the human pathways and active members of the microbiome that can affect SARS-CoV-2 susceptibility and disease progression in the saliva is very scarce. Here, we studied 10 hospitalized patients with severe and moderate COVID-19 (Scov and Mcov) at an early stage of the disease during April to June 2020, compared to 10 uninfected individuals, including healthcare workers with repeated high-risk exposures to the virus but not infected (Non-susceptible, Nsus) and subjects who became infected during the follow-up (susceptible, Non-COVID, Ncov). We performed high-throughput proteomic profiling in saliva to determine the human pathways and active members of the microbiome across individuals. We detected differentially expressed proteins between groups, being the differences especially remarkable in the comparison between the non-infected vs the non-susceptible groups. In a functional analysis to correlate the putative protein biomarkers with relevant biological functions, we found increased expression of proteins related to inflammatory responses and central cellular processes and decreased expression of molecules involved in antiviral activity. The most noteworthy are the Cystatin family, protective molecules present at the oral cavity, the Calprotectin family involved in cell cycle progression, or the Histone family related to nucleosome functions. Furthermore, since proteomics allows checking microbiome functionality, we explored bacterial products and found in the COVID-19+ group 4 overrepresented genera and 2 phyla together with 4 main functional features (KOs) related to ribosomal proteins. Finally, we studied correlations with the plasma activity of the molecular target of SARS-CoV-2, ACE2, and found a link with two proteins related to protein transport through the microtubules in the cytoplasm (DYBC1 and MAPR1). Our study delineates new mechanisms of SARS-CoV-2 susceptibility and progression to severe disease that may help find better therapies for COVID-19.

Dataset Information

Model-based prediction of SARS-CoV-2 in Ethiopia: Extended SEIR model

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