apply.leos.method: Method to generate estimates based on notification...

Description Usage Arguments Details Value Author(s) Examples

View source: R/apply.leos.method.R

Description

Function apply.leos.method applies the following method for the estimates: Notification delay modelling by Leo Bastos

Usage

1
2
apply.leos.method(df.in, current.epiyearweek, quantile.target = 0.95,
  low.activity = NULL, generate.plots = F)

Arguments

df.in

Data frame with the FIRST THREE columns refering to [,1] location id, [,2] notification date, [,3] digitization date, unless all(c('ID_MUNICIP', 'DT_NOTIFIC', 'DT_DIGITA') %in% names(df.in)) == T

current.epiyearweek

Most recent epidemiological week to be considered and estimated. Expected format YYYY*WW, e.g., 2010W03

quantile.target

Quantile to be used to determine Dmax from delay profile. Default: 0.95

low.activity

List of location id's not to be estimated due to low activity. Default: NULL

generate.plots

Boolean object to determine wether function should generate and save plots or not. Default: F

Details

N_t - number of notified cases at time t

Y_t,d - number of notified cases from time t with notification delay d

D - maximum acceptable time delay

N_t = Y_t,0 + sum_d=1^D Y_t,d

Y_0,t is known forall t

If T is today, Y_t,d is unknown for all (t,d) such that t+d > T

Contributtors: Claudia T Codeço and Marcelo F C Gomes

Value

Function apply.leos.method returns a list containing the following components:

estimated.data.frame

Data frame containing the weekly aggregate of df.in, plus columns with estimate mean, quantiles 2.5%, 50% and 97.5% and other relevant info

delay.cutoff

Data frame with Dmax obtained for each locality, epiyearweek used as cutoff and execution date

estimated.epiyearweek

Epidemiological week requested

model.pars

List with model's WAIC, DIC and hyperparameters from the INLA, for each locality (as character)

call

Function call

Author(s)

Marcelo F C Gomes [email protected]

Examples

1
2
3
data(opportunity.example.data)
res <- apply.leos.method(opportunity.example.data, current.epiyearweek='2014W52',
 quantile.target=0.95)

Opportunity-Estimator-EpiSurveillance/leos.opportunity.estimator documentation built on Nov. 20, 2019, 10:07 p.m.