pomp (version 2.4)

dacca: Model of cholera transmission for historic Bengal.

Description

dacca constructs a ‘pomp’ object containing census and cholera mortality data from the Dacca district of the former British province of Bengal over the years 1891 to 1940 together with a stochastic differential equation transmission model. The model is that of King et al. (2008). The parameters are the MLE for the SIRS model with seasonal reservoir.

Usage

dacca(gamma = 20.8, eps = 19.1, rho = 0, delta = 0.02,
  deltaI = 0.06, clin = 1, alpha = 1, beta_trend = -0.00498,
  logbeta = c(0.747, 6.38, -3.44, 4.23, 3.33, 4.55),
  logomega = log(c(0.184, 0.0786, 0.0584, 0.00917, 0.000208, 0.0124)),
  sd_beta = 3.13, tau = 0.23, S_0 = 0.621, I_0 = 0.378, Y_0 = 0,
  R1_0 = 0.000843, R2_0 = 0.000972, R3_0 = 1.16e-07)

Arguments

gamma

recovery rate

eps

rate of waning of immunity for severe infections

rho

rate of waning of immunity for inapparent infections

delta

baseline mortality rate

deltaI

cholera mortality rate

clin

fraction of infections that lead to severe infection

alpha

transmission function exponent

beta_trend

slope of secular trend in transmission

logbeta

seasonal transmission rates

logomega

seasonal environmental reservoir parameters

sd_beta

environmental noise intensity

tau

measurement error s.d.

S_0

initial susceptible fraction

I_0

initial fraction of population infected

Y_0

initial fraction of the population in the Y class

R1_0, R2_0, R3_0

initial fractions in the respective R classes

Value

dacca returns a ‘pomp’ object containing the model, data, and MLE parameters, as estimated by King et al. (2008).

Details

Data are provided courtesy of Dr. Menno J. Bouma, London School of Tropical Medicine and Hygiene.

References

A. A. King, E. L. Ionides, M. Pascual, and M. J. Bouma, Inapparent infections and cholera dynamics, Nature, 454:877-880, 2008

See Also

Other pomp examples: blowflies, ebola, gompertz, measles, ou2, ricker, rw2, sir_models, verhulst

Other datasets: blowflies, bsflu, ebola, measles, parus

Examples

# NOT RUN {
po <- dacca()
plot(po)
## MLE:
coef(po)
plot(simulate(po))
# }