Ho2019 - Mathematical models of transmission dynamics and vaccine strategies in Hong Kong during the 2017-2018 winter influenza season (Simple)

Model Identifier
BIOMD0000000851
Short description
This is the simple version of the two mathematical models presented by Ho et al. It is a model comprised of simple ordinary differential equations describing the overall epidemic dynamics of influenza infection in the 2017-2018 winter influenza season in Hong Kong.
Format
SBML
(L2V4)
Related Publication
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Mathematical models of transmission dynamics and vaccine strategies in Hong Kong during the 2017-2018 winter influenza season.
- Ho SH, He D, Eftimie R
- Journal of theoretical biology , 9/ 2019 , Volume 476 , pages: 74-94 , PubMed ID: 31128142
- Faculty of Education, University of Hong Kong, Pokfulam Road, Hong Kong. Electronic address: shingheiho@gmail.com.
- Two mathematical models described by simple ordinary differential equations are developed to investigate the Hong Kong influenza epidemic during 2017-2018 winter, based on overall epidemic dynamics and different influenza subtypes. The first model, describing the overall epidemic dynamics, provides the starting data for the second model which different influenza subtypes, and whose dynamics is further investigated. Weekly data from December 2017 to May 2018 are obtained from the data base of the Centre of Health Protection in Hong Kong, and used to parametrise the models. With the help of these models, we investigate the impact of different vaccination strategies and determine the corresponding critical vaccination coverage for different vaccine efficacies. The results suggest that at least 72% of Hong Kong population should have been vaccinated during 2017-2018 winter to prevent the seasonal epidemic by herd immunity (while data showed that only a maximum of 11.6% of the population were vaccinated). Our results also show that the critical vaccination coverage decreases with increasing vaccine efficacy, and the increase in one influenza subtype vaccine efficacy may lead to an increase in infections caused by a different subtype.
Contributors
Submitter of the first revision: Johannes Meyer
Submitter of this revision: Johannes Meyer
Modellers: Johannes Meyer
Submitter of this revision: Johannes Meyer
Modellers: Johannes Meyer
Metadata information
Curation status
Curated
Modelling approach(es)
Tags
Connected external resources
Name | Description | Size | Actions |
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Model files |
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Ho2019.xml | SBML L2V4 Representation of Ho2019 - Mathematical models of transmission dynamics and vaccine strategies in Hong Kong during the 2017–2018 winter influenza season (Simple) | 32.55 KB | Preview | Download |
Additional files |
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Ho2019.cps | COPASI file of Ho2019 - Mathematical models of transmission dynamics and vaccine strategies in Hong Kong during the 2017–2018 winter influenza season (Simple) | 63.37 KB | Preview | Download |
Ho2019.sedml | SED-ML file of Ho2019 - Mathematical models of transmission dynamics and vaccine strategies in Hong Kong during the 2017–2018 winter influenza season (Simple) | 3.67 KB | Preview | Download |
- Model originally submitted by : Johannes Meyer
- Submitted: Nov 12, 2019 12:15:22 PM
- Last Modified: Nov 12, 2019 12:15:22 PM
Revisions
Legends
: Variable used inside SBML models
: Variable used inside SBML models
Species
Species | Initial Concentration/Amount |
---|---|
V C17005 ; C28385 |
0.0565 item |
S C17005 ; Susceptibility |
0.9424 item |
I C17005 ; influenza infection |
0.0012 item |
R C17005 ; 0009785 |
0.0 item |
V e C17005 ; C49287 ; C28385 |
0.0565 item |
Reactions
Reactions | Rate | Parameters |
---|---|---|
V => I | compartment*k*I*V | k = 1.51338 |
S => V + V_e | compartment*r*(1-V_e/A) | r = 0.0155; A = 0.1155 |
S => I | compartment*beta*I*S | beta = 2.7516 |
I => R | compartment*gamma*I | gamma = 2.1272 |
Curator's comment:
(added: 12 Nov 2019, 12:15:16, updated: 12 Nov 2019, 12:15:16)
(added: 12 Nov 2019, 12:15:16, updated: 12 Nov 2019, 12:15:16)
Reproduced plot of Figure 7 in the original publication.
Model simulated and plot produced using COPASI 4.24 (Build 197).