ArticleBiology2020
Using Early Data to Estimate the Actual Infection Fatality Ratio from COVID-19 in France.
Article in Biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
46 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review and meta-analysis of published research data on COVID-19 infection fatality rates.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2020Pooled it
- Early COVID-19 Pandemic Preparedness: Informing Public Health Interventions and Hospital Capacity Planning Through Participatory Hybrid Simulation Modeling.International journal of environmental research and public health · 2024Article
- Article
- Exploring COVID-19 transmission patterns and key factors during epidemics caused by three major strains in Asia.Journal of theoretical biology · 2023Article
- Coronavirus covid-19 detection by means of explainable deep learning.Scientific reports · 2023Article
- Effect of sojourn time distributions on the early dynamics of COVID-19 outbreak.Nonlinear dynamics · 2023Article
- Using a latent Hawkes process for epidemiological modelling.PloS one · 2023Article
- Data-driven multiscale dynamical framework to control a pandemic evolution with non-pharmaceutical interventions.PloS one · 2023Article
- Mathematical modeling to study the impact of immigration on the dynamics of the COVID-19 pandemic: A case study for Venezuela.Spatial and spatio-temporal epidemiology · 2022Article
- From individual-based epidemic models to McKendrick-von Foerster PDEs: a guide to modeling and inferring COVID-19 dynamics.Journal of mathematical biology · 2022Article
- EKF-SIRD model algorithm for predicting the coronavirus (COVID-19) spreading dynamics.Scientific reports · 2022Article
- Evaluating the mitigation strategies of COVID-19 by the application of the COEnvironmental research · 2022Article
- Influence of state reopening policies in COVID-19 mortality.Scientific reports · 2022Article
- SARS-CoV-2: Molecular Structure, Pathogenesis, Potential Therapeutic Targets, and Immune Response of the Infected Subject.Interdisciplinary perspectives on infectious diseases · 2022Review
- COVID-19 second wave: District level study of concentration of confirmed cases and fatality in India.Environmental challenges (Amsterdam, Netherlands) · 2021Article
- How Good is the Science That Informs Government Policy? A Lesson From the U.K.'s Response to 2020 CoV-2 Outbreak.Journal of bioethical inquiry · 2021Article
- Pathogenesis, Symptomatology, and Transmission of SARS-CoV-2 through Analysis of Viral Genomics and Structure.mSystems · 2021Article
- A Bayesian estimate of the early COVID-19 infection fatality ratio in Brazil based on a random seroprevalence survey.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2021Article
- Plateaus, rebounds and the effects of individual behaviours in epidemics.Scientific reports · 2021Article
- Analysis of Delayed Vaccination Regimens: A Mathematical Modeling Approach.Epidemiologia (Basel, Switzerland) · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
The number of screening tests carried out in France and the methodology used to target the patients tested do not allow for a direct computation of the actual number of cases and the infection fatality ratio (IFR). The main objective of this work is to estimate the actual number of people infected with COVID-19 and to deduce the IFR during the observation window in France. We develop a `mechanistic-statistical' approach coupling a SIR epidemiological model describing the unobserved epidemiological dynamics, a probabilistic model describing the data acquisition process and a statistical inference method. The actual number of infected cases in France is probably higher than the observations: we find here a factor ×8 (95%-CI: 5-12) which leads to an IFR in France of 0.5% (95%-CI: 0.3-0.8) based on hospital death counting data. Adjusting for the number of deaths in nursing homes, we obtain an IFR of 0.8% (95%-CI: 0.45-1.25). This IFR is consistent with previous findings in China (0.66%) and in the UK (0.9%) and lower than the value previously computed on the Diamond Princess cruse ship data (1.3%).
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.