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Evidence that coronavirus superspreading is fat-tailed.

ABSTRACT: Superspreaders, infected individuals who result in an outsized number of secondary cases, are believed to underlie a significant fraction of total SARS-CoV-2 transmission. Here, we combine empirical observations of SARS-CoV and SARS-CoV-2 transmission and extreme value statistics to show that the distribution of secondary cases is consistent with being fat-tailed, implying that large superspreading events are extremal, yet probable, occurrences. We integrate these results with interaction-based network models of disease transmission and show that superspreading, when it is fat-tailed, leads to pronounced transmission by increasing dispersion. Our findings indicate that large superspreading events should be the targets of interventions that minimize tail exposure.

SUBMITTER: Wong F

PROVIDER: S-EPMC7703634 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Evidence that coronavirus superspreading is fat-tailed.

Wong Felix F Collins James J JJ

Proceedings of the National Academy of Sciences of the United States of America 20201102 47

Superspreaders, infected individuals who result in an outsized number of secondary cases, are believed to underlie a significant fraction of total SARS-CoV-2 transmission. Here, we combine empirical observations of SARS-CoV and SARS-CoV-2 transmission and extreme value statistics to show that the distribution of secondary cases is consistent with being fat-tailed, implying that large superspreading events are extremal, yet probable, occurrences. We integrate these results with interaction-based ...[more]

PMID: 33139561

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Project description:Tail fat content affects meat quality and varies significantly among different breeds of sheep. Ghezel (fat-tailed) and Zel (thin-tailed) are two important Iranian local sheep breeds with different patterns of fat storage. The current study presents the transcriptome characterization of tail fat using RNA sequencing in order to get a better comprehension of the molecular mechanism of lipid storage in the two mentioned sheep breeds. Seven (Zel  =  4 and Ghezel  =  3) 7-month-old male lambs were used for this experiment. The results of sequencing were analyzed with bioinformatics methods, including differentially expressed genes (DEGs) identification, functional enrichment analysis, structural classification of proteins, protein-protein interaction (PPI) and network and module analyses. Some of the DEGs, such as LIPG, SAA1, SOCS3, HIF-1 α , and especially IL-6, had a close association with lipid metabolism. Furthermore, functional enrichment analysis revealed pathways associated with fat deposition, including "fatty acid metabolism", "fatty acid biosynthesis" and "HIF-1 signaling pathway". The structural classification of proteins showed that major down-regulated DEGs in the Zel (thin-tailed) breed were classified under transporter class and that most of them belonged to the solute carrier transporter (SLC) families. In addition, DEGs under the transcription factor class with an important role in lipolysis were up-regulated in the Zel (thin-tailed) breed. Also, network analysis revealed that IL-6 and JUNB were hub genes for up-regulated PPI networks, and HMGCS1, VPS35 and VPS26A were hub genes for down-regulated PPI networks. Among the up-regulated DEGs, the IL-6 gene seems to play an important role in lipolysis of tail fat in thin-tailed sheep breeds via various pathways such as tumor necrosis factor (TNF) signaling and mitogen-activated protein kinase (MAPK) signaling pathways. Due to the probable role of the IL-6 gene in fat lipolysis and also due to the strong interaction of IL-6 with the other up-regulated DEGs, it seems that IL-6 accelerates the degradation of lipids in tail fat cells.

Project description:BackgroundNovel coronaviruses have emerged and caused major epidemics and pandemics in the past 2 decades, including SARS-CoV-1, MERS-CoV, and SARS-CoV-2, which led to the current COVID-19 pandemic. These coronaviruses are marked by their potential to produce disproportionally large transmission clusters from superspreading events (SSEs). As prompt action is crucial to contain and mitigate SSEs, real-time epidemic size estimation could characterize the transmission heterogeneity and inform timely implementation of control measures.ObjectiveThis study aimed to estimate the epidemic size of SSEs to inform effective surveillance and rapid mitigation responses.MethodsWe developed a statistical framework based on back-calculation to estimate the epidemic size of ongoing coronavirus SSEs. We first validated the framework in simulated scenarios with the epidemiological characteristics of SARS, MERS, and COVID-19 SSEs. As case studies, we retrospectively applied the framework to the Amoy Gardens SARS outbreak in Hong Kong in 2003, a series of nosocomial MERS outbreaks in South Korea in 2015, and 2 COVID-19 outbreaks originating from restaurants in Hong Kong in 2020.ResultsThe accuracy and precision of the estimation of epidemic size of SSEs improved with longer observation time; larger SSE size; and more accurate prior information about the epidemiological characteristics, such as the distribution of the incubation period and the distribution of the onset-to-confirmation delay. By retrospectively applying the framework, we found that the 95% credible interval of the estimates contained the true epidemic size after 37% of cases were reported in the Amoy Garden SARS SSE in Hong Kong, 41% to 62% of cases were observed in the 3 nosocomial MERS SSEs in South Korea, and 76% to 86% of cases were confirmed in the 2 COVID-19 SSEs in Hong Kong.ConclusionsOur framework can be readily integrated into coronavirus surveillance systems to enhance situation awareness of ongoing SSEs.

Project description:BACKGROUND:The level of fat deposition in carcass is a crucial factor influencing meat quality. Guangling Large-Tailed (GLT) and Small-Tailed Han (STH) sheep are important local Chinese fat-tailed breeds that show distinct patterns of fat depots. To gain a better understanding of fat deposition, transcriptome profiles were determined by RNA-sequencing of perirenal, subcutaneous, and tail fat tissues from both the sheep breeds. The common highly expressed genes (co-genes) in all the six tissues, and the genes that were differentially expressed (DE genes) between these two breeds in the corresponding tissues were analyzed. RESULTS:Approximately 47 million clean reads were obtained for each sample, and a total of 17,267 genes were annotated. Of the 47 highly expressed co-genes, FABP4, ADIPOQ, FABP5, and CD36 were the four most highly transcribed genes among all the known genes related to adipose deposition. FHC, FHC-pseudogene, and ZC3H10 were also highly expressed genes and could, thus, have roles in fat deposition. A total of 2091, 4233, and 4131 DE genes were identified in the perirenal, subcutaneous, and tail fat tissues between the GLT and STH breeds, respectively. Gene Ontology (GO) analysis showed that some DE genes were associated with adipose metabolism. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that PPAR signaling pathway and ECM-receptor interaction were specifically enriched. Four genes, namely LOC101102230, PLTP, C1QTNF7, and OLR1 were up-regulated and two genes, SCD and UCP-1, were down-regulated in all the tested tissues of STH. Among the genes involved in ECM-receptor interaction, the genes encoding collagens, laminins, and integrins were quite different depending on the depots or the breeds. In STH, genes such as LAMB3, RELN, TNXB, and ITGA8, were identified to be up regulated and LAMB4 was observed to be down regulated. CONCLUSIONS:This study unravels the complex transcriptome profiles in sheep fat tissues, highlighting the candidate genes involved in fat deposition. Further studies are needed to investigate the roles of the candidate genes in fat deposition and in determining the meat quality of sheep.

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Evidence that coronavirus superspreading is fat-tailed.

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Evidence that coronavirus superspreading is fat-tailed.

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