Estimation of SARS-CoV-2 mortality during the early stages of an epidemic: a modeling study in Hubei, China, and six regions in Europe

Hauser, Anthony; Counotte, Michel Jacques; Cc, Margossian; Konstantinoudis, G; Low, Nicola; Althaus, CL; Riou, Julien

doi:10.1101/2020.03.04.20031104

Cited by 93 publications

(117 citation statements)

References 36 publications

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“…While true case fatality rate (CFR) is difficult to assess early in an epidemic [24][25][26] , estimates from modeling studies range from 0.9% -3.3% 27,28 . Disease severity and mortality rates show a striking rise with age 29 , with CFR estimates ranging from <0.1% for patients under 30 years old to >10% for those over 70 24 , with a slightly higher incidence and mortality in men 4,30 . Children are significantly less likely than adults to develop severe disease, and reported pediatric deaths are rare 31 .…”

Section: Introductionmentioning

confidence: 99%

Integrated analyses of single-cell atlases reveal age, gender, and smoking status associations with cell type-specific expression of mediators of SARS-CoV-2 viral entry and highlights inflammatory programs in putative target cells

Muus

Luecken

Eraslan

et al. 2020

Preprint

251

326

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The COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, creates an urgent need for identifying molecular mechanisms that mediate viral entry, propagation, and tissue pathology. Cell membrane bound angiotensin-converting enzyme 2 (ACE2) and associated proteases, transmembrane protease serine 2 (TMPRSS2) and Cathepsin L (CTSL), were previously identified as mediators of SARS-CoV2 cellular entry. Here, we assess the cell type-specific RNA expression of ACE2, TMPRSS2, and CTSL through an integrated analysis of 107 single-cell and single-nucleus RNA-Seq studies, including 22 lung and airways datasets (16 unpublished), and 85 datasets from other diverse organs. Joint expression of ACE2 and the accessory proteases identifies specific subsets of respiratory epithelial cells as putative targets of viral infection in the nasal passages, airways, and alveoli. Cells that co-express ACE2 and proteases are also identified in cells from other organs, some of which have been associated with COVID-19 transmission or pathology, including gut enterocytes, corneal epithelial cells, cardiomyocytes, heart pericytes, olfactory sustentacular cells, and renal epithelial cells. Performing the first meta-analyses of scRNA-seq studies, we analyzed 1,176,683 cells from 282 nasal, airway, and lung parenchyma samples from 164 donors spanning fetal, childhood, adult, and elderly age groups, associate increased levels of ACE2, TMPRSS2, and CTSL in specific cell types with increasing age, male gender, and smoking, all of which are epidemiologically linked to COVID-19 susceptibility and outcomes. Notably, there was a particularly low expression of ACE2 in the few young pediatric samples in the analysis. Further analysis reveals a gene expression program shared by ACE2 + TMPRSS2 + cells in nasal, lung and gut tissues, including genes that may mediate viral entry, subtend key immune functions, and mediate epithelial-macrophage cross-talk. Amongst these are IL6, its receptor and co-receptor, IL1R, TNF response pathways, and complement genes. Cell type specificity in the lung and airways and smoking effects were conserved in mice. Our analyses suggest that differences in the cell type-specific expression of mediators of SARS-CoV-2 viral entry may be responsible for aspects of COVID-19 epidemiology and clinical course, and point to putative molecular pathways involved in disease susceptibility and pathogenesis.

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Section: Introductionmentioning

confidence: 99%

Integrated analyses of single-cell atlases reveal age, gender, and smoking status associations with cell type-specific expression of mediators of SARS-CoV-2 viral entry and highlights inflammatory programs in putative target cells

Muus

Luecken

Eraslan

et al. 2020

Preprint

251

326

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“…The more recent study about Sars-Cov-2 mortality on symptomatic and asymptomatic COVID-19 patients in the Hubei region shows the following Sars-Cov-2 mortality per age-groups [3] [ Table 2].…”

Section: Discussionmentioning

confidence: 99%

“…In Europe, COVID-19 cases are most dramatically started to increase from the first week of March 2020. Of these, Italy is grappling with the worst outbreak, with over 35,713 confirmed cases and around 3000 deaths by March 18, 2020 [1][2][3][4][5]. This exponential increase in COVID-19 positive cases in Italy raised turmoil, and the government decree to a lockdown of the entire country [1].…”

Section: Introductionmentioning

confidence: 99%

“…Article on modeling epidemic transition of COVID-19 have been published [1][2][3][4][5][6][7][8] and based on the previous publication from China, South Korea, Iran, and Japan presented the estimation of epidemic trends and transmission rates [1][2][3][4][5][6][7][8]. Through this research, we evaluated the consistency of the containment rules and identified possible SARS-CoV-2 local mutation using the S.E.I.R mathematical model.…”

Section: Introductionmentioning

confidence: 99%

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Modelling the epidemiological trend and behavior of COVID-19 in Italy

Rovetta¹,

Bhagavathula

2020

Preprint

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As of March 16, 2020, over 185,000 across the world, Italy became the red hotspot for the COVID-19 pandemic after China. With over 35,000 cases and 2900 deaths reported in the month of March in Italy, it is necessary to stimulate epidemic trend to understand the behavior of COVID-19 in Italy. By S.E.I.R. simulation, we estimated the most representative epidemic parameters occurred from March 1 to 14, 2020, thus being able to evaluate the consistency of the containment rules and identify possible Sars-Cov-2 local mutations. Our estimations are based on some assumptions and limitations exited.

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“…The exponential distribution or even Erlang(k = 2, λ = k/τ) distribution of the incubation period ( figure 4C) is not supported by data [1,2], which indicates much narrower distribution isolated from zero, so we think that our estimate of the basic reproduction number is closer to a real value. Data describing epidemic dynamics in China suggest that very strict quarantine and other preventive efforts imposed in the most affected China province, Hubei, [7,16] allowed to reduce R about 25-fold (which is on par with the estimated reduction of transmissibility of 97-100% [17]). This allowed the Chinese to reduce coefficient β from about 1.4 in the exponential growth phase to about β = 0.89 in the regression phase.…”

Section: Discussionmentioning

confidence: 99%

Dynamics of COVID-19 pandemic at constant and time-dependent contact rates

Kochańczyk

Grabowski

Lipniacki

2020

Preprint

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We constructed a simple Susceptible-Infected-Infectious-Excluded model of the spread of COVID-19. The model is parametrised only by the average incubation period, τ, and two rate parameters: contact rate, r C , and exclusion rate, r E . The rates can be manipulated by non-therapeutic interventions and determine the basic reproduction number, R = r C /r E , and, together with τ, the daily multiplication coefficient at the early exponential phase, β. Initial β determines the reduction of r C required to contain epidemic spread. In the long-term, we consider a scenario based on typical social behaviours, in which r C first decreases in response to a surge of daily new cases, forcing people to self-isolate, and then slowly increases when people gradually accept higher risk. Consequently, initial abrupt epidemic spread is followed by a plateau and slow regression. This scenario, although economically and socially devastating, will grant time to develop, produce, and distribute a vaccine, or at least limit daily cases to a manageable number.

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Estimation of SARS-CoV-2 mortality during the early stages of an epidemic: a modeling study in Hubei, China, and six regions in Europe

Cited by 93 publications

References 36 publications

Integrated analyses of single-cell atlases reveal age, gender, and smoking status associations with cell type-specific expression of mediators of SARS-CoV-2 viral entry and highlights inflammatory programs in putative target cells

Integrated analyses of single-cell atlases reveal age, gender, and smoking status associations with cell type-specific expression of mediators of SARS-CoV-2 viral entry and highlights inflammatory programs in putative target cells

Modelling the epidemiological trend and behavior of COVID-19 in Italy

Dynamics of COVID-19 pandemic at constant and time-dependent contact rates

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