ArticleInfectious Disease Modelling2020
Using statistics and mathematical modelling to understand infectious disease outbreaks: COVID-19 as an example.
Article in Infectious Disease Modelling, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
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Who cites it
35 citing papers in PubMed.
- Variant-Specific Viral Kinetics in Acute COVID-19.The Journal of infectious diseases · 2023Trial
- Characterising non-household contact patterns relevant to respiratory transmission in the USA: analysis of a cross-sectional survey.The Lancet. Digital health · 2025Article
- Data fitting and optimal control strategies for HBV acute patient cases in the United States.Infectious Disease Modelling · 2025Article
- Forecasting the Monkeypox Outbreak Using Limited Data: A Case Study of Thailand.Interdisciplinary perspectives on infectious diseases · 2025Article
- How mathematical modelling can inform outbreak response vaccination.BMC infectious diseases · 2024Review
- Open-sourced modeling and simulating tools for decision-makers during an emerging pandemic or epidemic - Systematic evaluation of utility and usability: A scoping review update.Dialogues in health · 2024Article
- Spatiotemporal Cluster Detection for COVID-19 Outbreak Surveillance: Descriptive Analysis Study.JMIR public health and surveillance · 2024Article
- Best practices for estimating and reporting epidemiological delay distributions of infectious diseases.PLoS computational biology · 2024Article
- Mathematical modeling of contact tracing and stability analysis to inform its impact on disease outbreaks; an application to COVID-19.Infectious Disease Modelling · 2024Article
- Understanding the infection severity and epidemiological characteristics of mpox in the UK.Nature communications · 2024Article
- Time series analysis and short-term forecasting of monkeypox outbreak trends in the 10 major affected countries.BMC infectious diseases · 2024Article
- Nowcasting the 2022 mpox outbreak in England.PLoS computational biology · 2023Article
- Modelling the impact of repeat asymptomatic testing policies for staff on SARS-CoV-2 transmission potential.Journal of theoretical biology · 2023Article
- Article
- Evaluating COVID-19 risk under the estimation of population mean using two attributes.Concurrency and computation : practice & experience · 2022Article
- The challenges of data in future pandemics.Epidemics · 2022Review
- A computational framework for modelling infectious disease policy based on age and household structure with applications to the COVID-19 pandemic.PLoS computational biology · 2022Article
- Bayesian Modeling of COVID-19 to Classify the Infection and Death Rates in a Specific Duration: The Case of Algerian Provinces.International journal of environmental research and public health · 2022Article
- Challenges in estimation, uncertainty quantification and elicitation for pandemic modelling.Epidemics · 2022Article
- Microfluidic Point-of-Care (POC) Devices in Early Diagnosis: A Review of Opportunities and Challenges.Sensors (Basel, Switzerland) · 2022Review
Corrections and comments
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Authors and funding
19 authors.
Funding
Abstract
During an infectious disease outbreak, biases in the data and complexities of the underlying dynamics pose significant challenges in mathematically modelling the outbreak and designing policy. Motivated by the ongoing response to COVID-19, we provide a toolkit of statistical and mathematical models beyond the simple SIR-type differential equation models for analysing the early stages of an outbreak and assessing interventions. In particular, we focus on parameter estimation in the presence of known biases in the data, and the effect of non-pharmaceutical interventions in enclosed subpopulations, such as households and care homes. We illustrate these methods by applying them to the COVID-19 pandemic.
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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.