Model Parameters Classes

This page contains information about the different classes which contain parameters used for the forward simulation of the Warwick-Lancaster model.

Overview:

• Initial Conditions Classes:

  • ICs

• Regional and Time Dependent Parameters Classes:

  • RegParameters

• Disease Specific Parameters Classes:

  • DiseaseParameters

  • Transmission

• Simulation Method Parameters Classes:

  • SimParameters

• Vaccine Specific Parameters Classes:

  • VaccineParameters

• Social Distancing Parameters Classes:

  • SocDistParameters

• Parameters Controller Classes:

  • ParametersController

Parameter Classes for the Warwick-Lancaster Model

Below we list the methods for all the parameter classes associated with the forward simulation of the Warwick-Lancaster model.

Initial Conditions Parameters

class warwickmodel.ICs(model, susceptibles_IC, exposed1_IC, exposed2_IC, exposed3_IC, exposed4_IC, exposed5_IC, infectives_sym_IC, infectives_asym_IC, recovered_IC)

ICs: Base class for the ICs of the model: a deterministic SEIR used by the Universities of Warwick and Lancaster to model the Covid-19 epidemic and the effects of vaccines and waning immunity on the epidemic trajectory in different countries.

Parameters:

• susceptibles_IC (list of lists) – Initial number of susceptibles classifed by age (column name) and region (row name) for different vaccination statuses (unvaccinated, fully-vaccinated, boosted, partially-waned, fully-waned, previous-variant immunity) (column name II).

• exposed1_IC (list of lists) – Initial number of exposed of the first type classifed by age (column name) and region (row name) for different vaccination statuses (unvaccinated, fully-vaccinated, boosted, partially-waned, fully-waned, previous-variant immunity) (column name II).

• exposed2_IC (list of lists) – Initial number of exposed of the second type classifed by age (column name) and region (row name) for different vaccination statuses (unvaccinated, fully-vaccinated, boosted, partially-waned, fully-waned, previous-variant immunity) (column name II).

• exposed3_IC (list of lists) – Initial number of exposed of the third type classifed by age (column name) and region (row name) for different vaccination statuses (unvaccinated, fully-vaccinated, boosted, partially-waned, fully-waned, previous-variant immunity) (column name II).

• exposed4_IC (list of lists) – Initial number of exposed of the forth type classifed by age (column name) and region (row name) for different vaccination statuses (unvaccinated, fully-vaccinated, boosted, partially-waned, fully-waned, previous-variant immunity) (column name II).

• exposed5_IC (list of lists) – Initial number of exposed of the fifth type classifed by age (column name) and region (row name) for different vaccination statuses (unvaccinated, fully-vaccinated, boosted, partially-waned, fully-waned, previous-variant immunity) (column name II).

• infectives_sym_IC (list of lists) – Initial number of symptomatic infectives classifed by age (column name) and region (row name) for different vaccination statuses (unvaccinated, fully-vaccinated, boosted, partially-waned, fully-waned, previous-variant immunity) (column name II).

• infectives_asym_IC (list of lists) – Initial number of asymptomatic infectives classifed by age (column name) and region (row name) for different vaccination statuses (unvaccinated, fully-vaccinated, boosted, partially-waned, fully-waned, previous-variant immunity) (column name II).

• recovered_IC (list of lists) – Initial number of recovered classifed by age (column name) and region (row name).

total_population()

Returns the country-specific total number of individuals in each age group.

Returns:

List of the ountry-specific total number of individuals in each age group using the initial conditions of the WarwickLancSEIRModel the class relates to.

Return type:

List of lists

Regional and Time Dependent Parameters

class warwickmodel.RegParameters(model, region_index)

RegParameters: Base class for the regional and time dependent parameters of the model: a deterministic SEIR used by the Universities of Warwick and Lancaster to model the Covid-19 epidemic and the effects of vaccines and waning immunity on the epidemic trajectory in different countries.

Parameters:

region_index (int) – Index of region for which we wish to simulate.

Disease Specific Parameters

class warwickmodel.DiseaseParameters(model, d, tau, we, omega)

DiseaseParameters: Base class for the disease-specific parameters of the model: a deterministic SEIR used by the Universities of Warwick and Lancaster to model the Covid-19 epidemic and the effects of vaccines and waning immunity on the epidemic trajectory in different countries.

Parameters:

• d (int or float or list) – Age-dependent probabilities of dispalying symptoms.

• tau (int or float) – Reduction in transmission for an asymptomatic infectious compared to the symptomatic case.

• we (list) – Rates of waning of immunity for current and an older variant.

• omega (int or float) – Change in susceptibility due to the variant.

Transmission Specific Parameters

class warwickmodel.Transmission(model, beta, alpha, gamma)

Transmission: Base class for the transmission-specific parameters of the model: a deterministic SEIR used by the Universities of Warwick and Lancaster to model the Covid-19 epidemic and the effects of vaccines and waning immunity on the epidemic trajectory in different countries.

Parameters:

• beta (int or float or list) – Age-dependent susceptibility to infection.

• alpha (int or float) – Rate of progression to infection from exposed.

• gamma (int or float or list) – Age-dependent rate of recovery.

Simulation Method Parameters

class warwickmodel.SimParameters(model, method, times, eps=False)

SimParameters: Base class for the simulation method’s parameters of the model: a deterministic SEIR used by the Universities of Warwick and Lancaster to model the Covid-19 epidemic and the effects of vaccines and waning immunity on the epidemic trajectory in different countries.

Parameters:

• method (str) – The type of solver implemented by the simulator.

• times (list) – List of time points at which we wish to evaluate the ODEs system.

• eps (boolean) – Indicator parameter for deploying boosters to the recovered compartment.

Vaccination Parameters

class warwickmodel.VaccineParameters(model, vac, vacb, adult, nu_tra, nu_symp, nu_inf, nu_sev_h, nu_sev_d)

VaccineParameters: Base class for the vaccination-specific parameters of the model: a deterministic SEIR used by the Universities of Warwick and Lancaster to model the Covid-19 epidemic and the effects of vaccines and waning immunity on the epidemic trajectory in different countries.

Parameters:

• vac (int or float or list) – Country-specific vaccination rate of the susceptible population.

• vacb (int or float or list) – Country-specific booster vaccination rate.

• adult (list) – List of the proportions of each age-group that are boosted or vaccinated.

• nu_tra (int or float or list) – Vaccine effects on transmission for infected individuals of different vaccination statuses (unvaccinated, fully-vaccinated, boosted, partially-waned, fully-waned, previous-variant immunity).

• nu_symp (int or float or list) – Vaccine effects on symptom development for different vaccination statuses (unvaccinated, fully-vaccinated, boosted, partially-waned, fully-waned, previous-variant immunity).

• nu_inf (int or float or list) – Vaccine effects on susceptability for susceptible individuals of different vaccination statuses (unvaccinated, fully-vaccinated, boosted, partially-waned, fully-waned, previous-variant immunity).

• nu_sev_h (int or float or list) – Vaccine effects on hospitalised severe outcomes for different vaccination statuses (unvaccinated, fully-vaccinated, boosted, partially-waned, fully-waned, previous-variant immunity).

• nu_sev_d (int or float or list) – Vaccine effects on dead severe outcomes for different vaccination statuses (unvaccinated, fully-vaccinated, boosted, partially-waned, fully-waned, previous-variant immunity).

Social Distancing Parameters

class warwickmodel.SocDistParameters(model, phi=1)

SocDistParameters: Base class for the social distancing parameters of the model: a deterministic SEIR used by the Universities of Warwick and Lancaster to model the Covid-19 epidemic and the effects of vaccines and waning immunity on the epidemic trajectory in different countries.

Parameters:

phi (int or float or list) – Country-specific control factor.

Parameters Controller

class warwickmodel.ParametersController(model, regional_parameters, ICs_parameters, disease_parameters, transmission_parameters, simulation_parameters, vaccine_parameters, soc_dist_parameters=None)

ParametersController Class: Base class for the paramaters of the model: a deterministic SEIR used by the Universities of Warwick and Lancaster to model the Covid-19 epidemic and the effects of vaccines and waning immunity on the epidemic trajectory in different countries.

In order to simulate using the Warwick model, the following parameters are required, which are stored as part of this class.

Parameters:

• model (WarwickLancSEIRModel) – The model whose parameters are stored.

• regional_parameters (RegParameters) – Class of the regional and time dependent parameters used in the simulation of the model.

• ICs_parameters (ICs) – Class of the Ics used in the simulation of the model.

• disease_parameters (DiseaseParameters) – Class of the disease-specific parameters used in the simulation of the model.

• transmission_parameters (Transmission) – Class of the rates of progression parameters used in the simulation of the model.

• simulation_parameters (SimParameters) – Class of the simulation method’s parameters used in the simulation of the model.

• vaccine_parameters (VaccineParameters) – Class of the vaccine-specific parameters used in the simulation of the model.

• soc_dist_parameters (SocDistParameters) – Class of the social distancing parameters used in the simulation of the model.