README.md

In mrc-ide/drep: Dengue reproduction number calculation

drep

drep allows calculation of the reproduction number (R0) of the dengue virus from force of infection using the at-equilibrium number of primary, secondary, tertiary and quaternary infections in a population and their relative infectiousness. This is done assuming that dengue transmission is at endemic equilibrium.

Installation

You can install the development version of the drep package using devtools. First install devtools, if you don't already have it.

install.packages("devtools")
library(devtools)

Then, in a fresh R session, install the drep package.

devtools::install_github("mrc-ide/drep")

Background

Reliable estimates of transmission intensity of dengue are needed to quantify the global burden of the disease and assess the impact of control strategies. Transmission intensity of an infectious disease can be measured using the force of infection (the per capita rate at which susceptible individuals acquire infection, FOI) or the basic reproduction number (the average number of secondary infections generated by one primary case entering a susceptible population, R0). While FOI is driven by birth rates of the human population, R0 is not. Both these measures can be used to estimate the global burden of dengue using a set of climatic and environmental predictors and a geostatistical model to produce a continuous surface of transmission intensity and calculate burden outputs (infections, symptomatic cases, hospitalizations). The DENVfoiMap R package allows to use FOI or RO estimates and make global projections using a set of environmental and demographic variables. As a first step towards making global maps of dengue FOI and predicting global annual dengue burden, drep provides a set of functions to translate average dengue FOI (per serotype) into R0 and burden estimates.

We make a number of assumptions:

1. four dengue serotypes are in circulation
2. there is a maxiumum number of four dengue infections per individual
3. dengue transmission is at equilibrium
4. force of infection is constant through time

Example

This is a basic example which shows how to convert FOI into R0. To do this we need:

• the proportion of the human population in different age groups
• the relative infectiousness of the four dengue infections.

We assume that the human population is divided up into 20 age groups and define the following parameters:

• number of age groups in the country human population (n_age_groups)
• the force of infection estimate (FOI)
• the relative infectiousness of the four dengue infections (phis)

We asssume, as a starting point, that all four infections have the same infectiousness.

n_age_groups <- 20
FOI <- 0.0235
phis <- c(1, 1, 1, 1)

We then simulate some data, including

• the lower and upper age limits (l_lim and u_lim) of the country age groups
• the proportion of individuals in each age gorup (f_j)

l_lim <- seq(0, 95, length.out = n_age_groups)
u_lim <- seq(5, 100, length.out = n_age_groups)
n_j <- sample(1:50, n_age_groups, replace = TRUE)
f_j <- n_j / sum(n_j)
f_j
#>  [1] 0.038383838 0.096969697 0.028282828 0.012121212 0.046464646
#>  [6] 0.020202020 0.012121212 0.008080808 0.068686869 0.024242424
#> [11] 0.028282828 0.038383838 0.076767677 0.056565657 0.078787879
#> [16] 0.092929293 0.058585859 0.070707071 0.064646465 0.078787879

The R0 can be calculated using the calculate_R0 function. The calculate_R0 function takes six arguments:

• FOI: a numeric value of the force of infection estimate, which represents the average estimate per serotype
• f_j: a numeric vector of the proportions of individuals in each age group
• l_lim: a numeric vector of the lower limits of the country age groups
• u_lim: a numeric vector of the upper limits of the country age groups
• phis: a numeric vector of the relative infectiousness of the numbers of primary, secondary, tertiary and quaternary dengue infections.

R0 <- drep::calculate_R0(FOI, f_j, u_lim, l_lim, phis)
R0
#> [1] 2.970795

mrc-ide/drep documentation built on Jan. 6, 2020, 11:06 p.m.