Corpus overview


MeSH Disease

Infections (1)

Death (1)

Human Phenotype

There are no HP terms in the subcorpus


    displaying 1 - 1 records in total 1
    records per page

    Fundamental principles of epidemic spread highlight the immediate need forlarge-scale serological surveys to assess the stage of the SARS-CoV-2 epidemic

    Authors: Jose Lourenco; Robert Paton; Mahan Ghafari; Moritz Kraemer; Craig Thompson; Peter Simmonds; Paul Klenerman; Sunetra Gupta

    doi:10.1101/2020.03.24.20042291 Date: 2020-03-26 Source: medRxiv

    The spread of a novel pathogenic infectious agent eliciting protective immunity is typically characterised by three distinct phases: (I) an initial phase of slow accumulation of new infections (often undetectable), (II) a second phase of rapid growth in cases of infection MESHD, disease and death MESHD, and (III) an eventual slow down of transmission TRANS due to the depletion of susceptible individuals, typically leading to the termination of the (first) epidemic wave. Before the implementation of control measures (e.g. social distancing, travel TRANS bans, etc) and under the assumption that infection elicits protective immunity, epidemiological theory indicates that the ongoing epidemic of SARS-CoV-2 will conform to this pattern. Here, we calibrate a susceptible-infected-recovered (SIR) model to data on cumulative reported SARS-CoV-2 associated deaths from the United Kingdom (UK) and Italy under the assumption that such deaths MESHD are well reported events that occur only in a vulnerable fraction of the population. We focus on model solutions which take into consideration previous estimates of critical epidemiological parameters such as the basic reproduction number TRANS ( R0 TRANS), probability of death MESHD in the vulnerable fraction of the population, infectious period TRANS and time from infection MESHD to death, with the intention of exploring the sensitivity SERO of the system to the actual fraction of the population vulnerable to severe disease and death MESHD. Our simulations are in agreement with other studies that the current epidemic wave in the UK and Italy in the absence of interventions should have an approximate duration of 2-3 months, with numbers of deaths lagging behind in time relative to overall infections. Importantly, the results we present here suggest the ongoing epidemics in the UK and Italy started at least a month before the first reported death MESHD and have already led to the accumulation of significant levels of herd immunity in both countries. There is an inverse relationship between the proportion currently immune and the fraction of the population vulnerable to severe disease. This relationship can be used to determine how many people will require hospitalisation (and possibly die) in the coming weeks if we are able to accurately determine current levels of herd immunity. There is thus an urgent need for investment in technologies such as virus (or viral pseudotype) neutralization assays and other robust assays which provide reliable read-outs of protective immunity, and for the provision of open access to valuable data sources such as blood SERO banks and paired samples of acute and convalescent sera from confirmed cases TRANS of SARS-CoV-2 to validate these. Urgent development and assessment of such tests should be followed by rapid implementation at scale to provide real-time data. These data will be critical to the proper assessment of the effects of social distancing and other measures currently being adopted to slow down the case incidence and for informing future policy direction.

The ZB MED preprint Viewer preVIEW includes all COVID-19 related preprints from medRxiv and bioRxiv, from ChemRxiv, from ResearchSquare, from arXiv and from and is updated on a daily basis (7am CET/CEST).
The web page can also be accessed via API.



MeSH Disease
Human Phenotype

Export subcorpus as...

This service is developed in the project nfdi4health task force covid-19 which is a part of nfdi4health.

nfdi4health is one of the funded consortia of the National Research Data Infrastructure programme of the DFG.