Compartmental structures used in modeling COVID-19: a scoping review
Open Access
- 21 June 2022
- journal article
- review article
- Published by Springer Science and Business Media LLC in Infectious Diseases of Poverty
- Vol. 11 (1), 1-9
- https://doi.org/10.1186/s40249-022-01001-y
Abstract
The coronavirus disease 2019 (COVID-19) epidemic, considered as the worst global public health event in nearly a century, has severely affected more than 200 countries and regions around the world. To effectively prevent and control the epidemic, researchers have widely employed dynamic models to predict and simulate the epidemic’s development, understand the spread rule, evaluate the effects of intervention measures, inform vaccination strategies, and assist in the formulation of prevention and control measures. In this review, we aimed to sort out the compartmental structures used in COVID-19 dynamic models and provide reference for the dynamic modeling for COVID-19 and other infectious diseases in the future. A scoping review on the compartmental structures used in modeling COVID-19 was conducted. In this scoping review, 241 research articles published before May 14, 2021 were analyzed to better understand the model types and compartmental structures used in modeling COVID-19. Three types of dynamics models were analyzed: compartment models expanded based on susceptible-exposed-infected-recovered (SEIR) model, meta-population models, and agent-based models. The expanded compartments based on SEIR model are mainly according to the COVID-19 transmission characteristics, public health interventions, and age structure. The meta-population models and the agent-based models, as a trade-off for more complex model structures, basic susceptible-exposed-infected-recovered or simply expanded compartmental structures were generally adopted. There has been a great deal of models to understand the spread of COVID-19, and to help prevention and control strategies. Researchers build compartments according to actual situation, research objectives and complexity of models used. As the COVID-19 epidemic remains uncertain and poses a major challenge to humans, researchers still need dynamic models as the main tool to predict dynamics, evaluate intervention effects, and provide scientific evidence for the development of prevention and control strategies. The compartmental structures reviewed in this study provide guidance for future modeling for COVID-19, and also offer recommendations for the dynamic modeling of other infectious diseases.Keywords
Funding Information
- Natural Science Foundation of China (81973102, 81773487)
- Public Health Talents Training Program of Shanghai Municipality (GWV-10.2-XD21)
- Three-Side Innovation Projects for Aquaculture in Jiangsu Province (GWV-10.1-XK16)
- Major Project of Scientific and Technical Winter Olympics from National Key Research and Development Program of China (2021YFF0306000)
- 13th Five-Year National Science and Technology Major Project for Infectious Diseases (2018ZX10725-509)
- Key projects of the PLA logistics Scientific research Program (BHJ17J013)
- Fundamental Research Funds for the Central Universities (2021MS074)
- Natural Science Funds of Hebei (D2019502010)
This publication has 50 references indexed in Scilit:
- An evaluation of COVID-19 in Italy: A data-driven modeling analysisInfectious Disease Modelling, 2020
- Effects of non-pharmaceutical interventions on COVID-19 cases, deaths, and demand for hospital services in the UK: a modelling studyThe Lancet Public Health, 2020
- The role of furin cleavage site in SARS-CoV-2 spike protein-mediated membrane fusion in the presence or absence of trypsinSignal Transduction and Targeted Therapy, 2020
- Estimation of the Excess COVID-19 Cases in Seoul, South Korea by the Students Arriving from ChinaInternational Journal of Environmental Research and Public Health, 2020
- The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreakScience, 2020
- Prediction of COVID-19 transmission dynamics using a mathematical model considering behavior changesEpidemiology and Health, 2020
- Mathematical modelling of COVID-19 transmission and mitigation strategies in the population of Ontario, CanadaCMAJ : Canadian Medical Association Journal, 2020
- [An update on the epidemiological characteristics of novel coronavirus pneumonia(COVID-19)].2020
- Dynamics analysis of a delayed virus model with two different transmission methods and treatmentsAdvances in Difference Equations, 2020
- Multiscale mobility networks and the spatial spreading of infectious diseasesProceedings of the National Academy of Sciences of the United States of America, 2009