Parameters: Model parameters
In jc-castillo/vaccineEarlyInvest: Investment in Early Manufacturing Capacity for Vaccines
Description
Public fields
Methods
Examples
Description
Class to handle parameters of the model for investment in early vaccine capacity
Public fields
inputfileWorld or US input file
poverallProbability that no problem at the overall level prevents vaccine feasibility
pvectorProbability that there's no problem at the viral vector platform level
psubunitProbability that there's no problem at the protein subunit platform level
prnaProbability that there's no problem at the RNA platform level
pdnaProbability that there's no problem at the DNA platform level
pattenuatedProbability that there's no problem at the live attenuated platform level
pinactivatedProbability that there's no problem at the inactivated platform level
pvlpProbability that there's no problem at the virus-like particle platform level
ppreclinicalProbability that there's no problem at the candidate level when a vaccine is in preclincal trials
plivebacProbability that there's no problem at the live attenuated bacteria platform level
paapcProbability that there's no problem at the artificial antigen presenting cells platform level
pdendriticProbability that there's no problem at the dendritic cells platform level
psavProbability that there's no problem at the self-assembling vaccine platform level
punknownProbability that there's no problem for unknown platform
prepurposedProbability that there's no problem with a repurposed candidate
pphase1Probability that there's no problem at the candidate level when a vaccine is in phase 1 trials
pphase2Probability that there's no problem at the candidate level when a vaccine is in phase 2 trials
pphase3Probability that there's no problem at the candidate level when a vaccine is in phase 3 trials
psubcatProbability that there's no problem at subcategory level
pspikeProbability that there's no problem at the candidate level when a vaccine targets spike proten
precombinantProbability that there's no problem at the candidate level when a vaccine targets recombinant proten
potherproteinProbability that there's no problem at the candidate level when a vaccine targets some other proten
popshareShare of world population accounted for by country / coalition
gdpshareShare of world GDP accounted for by country /coalition
econlossratioRatio of economic losses in the country / coalition as a percent relative to world
spilloversHow much do countries in the country /coalition care about spillovers
outlifefactorExtent to which countries care about international lives
outlivesratioFraction of world that lives outside country /coalition
fracHighRiskFraction of population in the country /coalition at high risk
TTTime that the vaccine is brought forward (months)
tauPeriod of analysis (months)
damageshareFraction of damage accounted for by some fraction of the population
vaccshareFraction of population that accounts for some fraction of damage
monthbenEconomic benefit for the whole world per month (in billion $)
worldmortalityWorld mortality
mortalityMonthly internal mortality
statLifeValue of statistical life in million $
lifeExpLife expectancy
yearsLostYears lost per covid death
sharmExpected share of harm avoided due to an alternative drug being developed
maxcandNumber of candidates to consider
hbenMonthly health benefits
damageintIntegral that measures fraction of damages
totmonthbenTotal benefit of bringing forward vaccine for one month
alphaParameter for heterogeneity of benefits of vaccination with a smooth functional form.
a=1 corresponds to perfectly homogeneous benefits, a=0 corresponds to all benefits to the first person.
benefitdistString describing the form of the benefit distribution
piecewiseparParameters of a piecewise linear benefit distribution
fracneededFraction of population needed to reopen economy
effpopEffective world population that needs to be vaccinated to
get all (100 percent) of benefits
simplebenefitsWhether the benefit function is a simple function with one single kink
kink2locLocation of the second kink in the benefit function
slopefactormaxMaximum ratio between the benefits from vaccinating high risk people and
next population group
slopefactorminMinimum ratio between the benefits from vaccinating high risk people and
next population group
maxgdpratioMaximum ratio between share of GDP and share of population
benefitshapeParameter that specifies the shape of the benefit function. It's linear if it
is one, it's equal to health benefits if it is zero.
cCost of capacity per dose / year
capacityConstraint on capacity (doses / month)
capkinkCapacity at which marginal cost has a kink (doses / month)
capkink_nucleicCapacity at which marginal cost has a kink for RNA and DNA (doses / month)
capkink_subunitsCapacity at which marginal cost has a kink for protein subunit and viral vector (doses / month)
capkink_liveCapacity at which marginal cost has a kink for live attenuated and deactivated (doses / month)
mgcostelastElasticity of marginal cost after kink
afterCapacityWorldwide capacity after the end of the program (doses / month)
counterCapacityWorldwide capacity in the counterfactual (doses / month)
popWorld population population (billions)
cprodProduction cost per vaccine ($)
replicationsNumber of replications for Monte Carlo
fcapacityFraction of capacity cost that must be borne by the firm
fcostredFraction of cost reduction after the second vaccine within a platform
outsidefactorHow much more likely are firms to be successful in an outside market
pearlyPrice of early batch of vaccines
platePrice of late batch of vaccines
nearlyNumber or vaccines in early batch
nlateNumber or vaccines in late batch
riskPremiumPremium that must given to candidates to participate despite risk (bn $)
overallFungFraction of capacity cost that is fungible across platforms
platFungFraction of capacity cost that is fungible within platforms
subcatFungFraction of capacity cost that is fungible within subcategory
protVectorFungFraction of capacity cost that is fungible between protein and viral vectors
fracScrapFraction of cost that can be saved if a candidate is not successful
budgetProgram budget
capcostTotal capacity cost per candidate
globalWhether the the analysis is for the whole wolrd
outcapCapacity to build in an outside market
outprobProbability that copy vaccine will be successful, conditional on own success
outquantityAmount of outside vaccines that will be sold at high prices
Methods
Public methods
Method new()
Create a new Parameters object.
Usage
Parameters$new(
input = NULL,
population = NULL,
gdp_pc = NULL,
frac_high_risk = NULL,
loss2yr = NULL,
worldLoss2yr = 0.138,
benefitKinks = NULL,
...
)
Arguments
inputDetermines how to initialize object. Can be a string telling
which default parameters to use. Can also be the input object
(of class reactivevalues) with the inputs from a Shiny app,
in which case all inputs are copied into fields.
populationCountry population (in millions)
gdp_pcCountry GDP per capita (in thousand USD)
frac_high_riskFraction of population that is high risk
loss2yrCumulative percent of GDP lost because of pandemic over two years
worldLoss2yrCumulative percent of GDP lost worldwide because of pandemic over two years
benefitKinksLocation of the kinks in the benefit function. List with two vectors; the first
vector has the fractions vaccinated, the second has the fractions of benefits obtained.
...Set fields at non-default values
Returns
A new Parameters object.
Examples
par <- Parameters$new(global = TRUE)
Method setDerivedParameters()
Compute additional parameters that are functions of the input parameters
Usage
Parameters$setDerivedParameters(benefitKinks = NULL)
Arguments
benefitKinksLocation of the kinks in the benefit function. List with two vectors; the first
vector has the fractions vaccinated, the second has the fractions of benefits obtained.
Method clone()
The objects of this class are cloneable with this method.
Usage
Parameters$clone(deep = FALSE)
Arguments
deepWhether to make a deep clone.
Examples
1
2
3
4
5
## ------------------------------------------------
## Method `Parameters$new`
## ------------------------------------------------
par <- Parameters$new(global = TRUE)
jc-castillo/vaccineEarlyInvest documentation built on Sept. 29, 2020, 12:48 p.m.
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Description Public fields Methods Examples
Description
Class to handle parameters of the model for investment in early vaccine capacity
Public fields
inputfileWorld or US input file
poverallProbability that no problem at the overall level prevents vaccine feasibility
pvectorProbability that there's no problem at the viral vector platform level
psubunitProbability that there's no problem at the protein subunit platform level
prnaProbability that there's no problem at the RNA platform level
pdnaProbability that there's no problem at the DNA platform level
pattenuatedProbability that there's no problem at the live attenuated platform level
pinactivatedProbability that there's no problem at the inactivated platform level
pvlpProbability that there's no problem at the virus-like particle platform level
ppreclinicalProbability that there's no problem at the candidate level when a vaccine is in preclincal trials
plivebacProbability that there's no problem at the live attenuated bacteria platform level
paapcProbability that there's no problem at the artificial antigen presenting cells platform level
pdendriticProbability that there's no problem at the dendritic cells platform level
psavProbability that there's no problem at the self-assembling vaccine platform level
punknownProbability that there's no problem for unknown platform
prepurposedProbability that there's no problem with a repurposed candidate
pphase1Probability that there's no problem at the candidate level when a vaccine is in phase 1 trials
pphase2Probability that there's no problem at the candidate level when a vaccine is in phase 2 trials
pphase3Probability that there's no problem at the candidate level when a vaccine is in phase 3 trials
psubcatProbability that there's no problem at subcategory level
pspikeProbability that there's no problem at the candidate level when a vaccine targets spike proten
precombinantProbability that there's no problem at the candidate level when a vaccine targets recombinant proten
potherproteinProbability that there's no problem at the candidate level when a vaccine targets some other proten
popshareShare of world population accounted for by country / coalition
gdpshareShare of world GDP accounted for by country /coalition
econlossratioRatio of economic losses in the country / coalition as a percent relative to world
spilloversHow much do countries in the country /coalition care about spillovers
outlifefactorExtent to which countries care about international lives
outlivesratioFraction of world that lives outside country /coalition
fracHighRiskFraction of population in the country /coalition at high risk
TTTime that the vaccine is brought forward (months)
tauPeriod of analysis (months)
damageshareFraction of damage accounted for by some fraction of the population
vaccshareFraction of population that accounts for some fraction of damage
monthbenEconomic benefit for the whole world per month (in billion $)
worldmortalityWorld mortality
mortalityMonthly internal mortality
statLifeValue of statistical life in million $
lifeExpLife expectancy
yearsLostYears lost per covid death
sharmExpected share of harm avoided due to an alternative drug being developed
maxcandNumber of candidates to consider
hbenMonthly health benefits
damageintIntegral that measures fraction of damages
totmonthbenTotal benefit of bringing forward vaccine for one month
alphaParameter for heterogeneity of benefits of vaccination with a smooth functional form. a=1 corresponds to perfectly homogeneous benefits, a=0 corresponds to all benefits to the first person.
benefitdistString describing the form of the benefit distribution
piecewiseparParameters of a piecewise linear benefit distribution
fracneededFraction of population needed to reopen economy
effpopEffective world population that needs to be vaccinated to get all (100 percent) of benefits
simplebenefitsWhether the benefit function is a simple function with one single kink
kink2locLocation of the second kink in the benefit function
slopefactormaxMaximum ratio between the benefits from vaccinating high risk people and next population group
slopefactorminMinimum ratio between the benefits from vaccinating high risk people and next population group
maxgdpratioMaximum ratio between share of GDP and share of population
benefitshapeParameter that specifies the shape of the benefit function. It's linear if it is one, it's equal to health benefits if it is zero.
cCost of capacity per dose / year
capacityConstraint on capacity (doses / month)
capkinkCapacity at which marginal cost has a kink (doses / month)
capkink_nucleicCapacity at which marginal cost has a kink for RNA and DNA (doses / month)
capkink_subunitsCapacity at which marginal cost has a kink for protein subunit and viral vector (doses / month)
capkink_liveCapacity at which marginal cost has a kink for live attenuated and deactivated (doses / month)
mgcostelastElasticity of marginal cost after kink
afterCapacityWorldwide capacity after the end of the program (doses / month)
counterCapacityWorldwide capacity in the counterfactual (doses / month)
popWorld population population (billions)
cprodProduction cost per vaccine ($)
replicationsNumber of replications for Monte Carlo
fcapacityFraction of capacity cost that must be borne by the firm
fcostredFraction of cost reduction after the second vaccine within a platform
outsidefactorHow much more likely are firms to be successful in an outside market
pearlyPrice of early batch of vaccines
platePrice of late batch of vaccines
nearlyNumber or vaccines in early batch
nlateNumber or vaccines in late batch
riskPremiumPremium that must given to candidates to participate despite risk (bn $)
overallFungFraction of capacity cost that is fungible across platforms
platFungFraction of capacity cost that is fungible within platforms
subcatFungFraction of capacity cost that is fungible within subcategory
protVectorFungFraction of capacity cost that is fungible between protein and viral vectors
fracScrapFraction of cost that can be saved if a candidate is not successful
budgetProgram budget
capcostTotal capacity cost per candidate
globalWhether the the analysis is for the whole wolrd
outcapCapacity to build in an outside market
outprobProbability that copy vaccine will be successful, conditional on own success
outquantityAmount of outside vaccines that will be sold at high prices
Methods
Public methods
Method new()
Create a new Parameters object.
Usage
Parameters$new( input = NULL, population = NULL, gdp_pc = NULL, frac_high_risk = NULL, loss2yr = NULL, worldLoss2yr = 0.138, benefitKinks = NULL, ... )
Arguments
inputDetermines how to initialize object. Can be a string telling which default parameters to use. Can also be the
inputobject (of classreactivevalues) with the inputs from a Shiny app, in which case all inputs are copied into fields.populationCountry population (in millions)
gdp_pcCountry GDP per capita (in thousand USD)
frac_high_riskFraction of population that is high risk
loss2yrCumulative percent of GDP lost because of pandemic over two years
worldLoss2yrCumulative percent of GDP lost worldwide because of pandemic over two years
benefitKinksLocation of the kinks in the benefit function. List with two vectors; the first vector has the fractions vaccinated, the second has the fractions of benefits obtained.
...Set fields at non-default values
Returns
A new Parameters object.
Examples
par <- Parameters$new(global = TRUE)
Method setDerivedParameters()
Compute additional parameters that are functions of the input parameters
Usage
Parameters$setDerivedParameters(benefitKinks = NULL)
Arguments
benefitKinksLocation of the kinks in the benefit function. List with two vectors; the first vector has the fractions vaccinated, the second has the fractions of benefits obtained.
Method clone()
The objects of this class are cloneable with this method.
Usage
Parameters$clone(deep = FALSE)
Arguments
deepWhether to make a deep clone.
Examples
1 2 3 4 5 | ## ------------------------------------------------
## Method `Parameters$new`
## ------------------------------------------------
par <- Parameters$new(global = TRUE)
|
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