Inferring the COVID-19 infection fatality rate in the community-dwelling population: a simple Bayesian evidence synthesis of seroprevalence study data and imprecise mortality data
- EconomicsEpidemiology and Infection
The results suggest that, as one might expect, lower IFRs are associated with younger populations (and may also be associated with wealthier populations) and with the age and wealth of the United States and European Union.
COVID-19 has illuminated the need for clearer AI-based risk management strategies
- Computer ScienceJournal of Risk Research
A lack of consistency in the reporting and availability of disaggregated, detailed data on COVID-19 in the US has limited the application of artificial intelligence methods and the effectiveness of those methods for projecting the spread and subsequent impacts of this disease in communities.
There are no equal opportunity infectors: Epidemiological modelers must rethink our approach to inequality in infection risk
- MedicinePLoS Comput. Biol.
This review evaluating potential historical and political explanations for the exclusion of drivers of disparity in infectious disease models for emerging infections, which have often been characterized as “equal opportunity infectors” despite ample evidence to the contrary, outlines principles to guide modeling of emerging infections in ways that represent the causes of inequity in infection as central rather than peripheral mechanisms.
Time-dependent SI model for epidemiology and applications to Covid-19
- MathematicsRevista Mexicana de Física
A generalisation of the Susceptible-Infectious model is made to include a time-dependent transmission rate, which leads to a close analytical expression in terms of a logistic function. The solution…
Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations
- Environmental SciencemedRxiv
Background: Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in…
The Problem of Semantic Shift in Longitudinal Monitoring of Social Media: A Case Study on Mental Health During the COVID-19 Pandemic
Social media allows researchers to track societal and cultural changes over time based on language analysis tools. Many of these tools rely on statistical algorithms which need to be tuned to…
How to improve the quality of comparisons using external control cohorts in single-arm clinical trials?
This paper presents a meta-analyses of the immune system’s response to infectious disease and its role in promoting physical and mental well-being in patients.
La modélisation (principalement par régression)
- Éducation et didactique
SHOWING 1-10 OF 90 REFERENCES
Avoidable errors in the modelling of outbreaks of emerging pathogens, with special reference to Ebola
- Environmental ScienceProceedings of the Royal Society B: Biological Sciences
An alternative based on stochastic models fit to raw data from an early phase of 2014 West Africa Ebola virus disease outbreak is demonstrated, showing not only that bias is reduced, but that uncertainty in estimates and forecasts is better quantified and that, critically, lack of model fit is more readily diagnosed.
Caution Warranted: Using the Institute for Health Metrics and Evaluation Model for Predicting the Course of the COVID-19 Pandemic
- MedicineAnnals of Internal Medicine
The Institute for Health Metrics and Evaluation model for predicting the course of the coronavirus disease 2019 pandemic has attracted considerable attention, but caution is warranted regarding the validity and usefulness of the model projections for policymakers.
Tail risk of contagious diseases
The COVID-19 pandemic has been a sobering reminder of the extensive damage brought about by epidemics, phenomena that play a vivid role in our collective memory, and that have long been identified as…
Bayesian workflow for disease transmission modeling in Stan
- Computer ScienceStatistics in medicine
This tutorial shows how to build, fit, and criticize disease transmission models in Stan, and should be useful to researchers interested in modeling the severe acute respiratory syndrome coronavirus…
Estimating SARS-CoV-2 seroprevalence and epidemiological parameters with uncertainty from serological surveys
A flexible framework that integrates uncertainty from test characteristics, sample size, and heterogeneity in seroprevalence across tested subpopulations to compare estimates from sampling schemes is used and it is found that sampling schemes informed by demographics and contact networks outperform uniform sampling.
Bayesian analysis of tests with unknown specificity and sensitivity
H hierarchical regression and post‐stratification models with code in Stan are demonstrated and their application to a controversial recent study of SARS‐CoV‐2 antibodies in a sample of people from the Stanford University area is discussed.
Superspreading and the effect of individual variation on disease emergence
It is shown that contact tracing data from eight directly transmitted diseases shows that the distribution of individual infectiousness around R0 is often highly skewed, and implications for outbreak control are explored, showing that individual-specific control measures outperform population-wide measures.
State-level tracking of COVID-19 in the United States
This work jointly modelled the US epidemic at the state-level, using publicly available death data within a Bayesian hierarchical semi-mechanistic framework, and demonstrated that good model forecasts of deaths for the next 3 weeks with low error and good coverage of credible intervals are demonstrated.
Report 20: Using Mobility to Estimate the Transmission Intensity of COVID-19 in Italy: A Subnational Analysis with Future Scenarios
The incidence of death reported across the 20 Italian regions is analyzed, and along with the observed relative changes in regional movement, how interventions have impacted the transmissibility of SARS-CoV-2 is assessed.
COVID-19 Epidemic in Switzerland: Growth Prediction and Containment Strategy Using Artificial Intelligence and Big Data
Through the use of a digital tool, such as Enerpol, to evaluate in a data-driven manner the impacts of various policy scenarios, the most effective measures to mitigate a spread of COVID-19 can be devised while the authors await the deployment of large-scale vaccination for the population globally.