Table 1. RSV-SIRS model parameter estimates and model selection using a Poisson sampling model.

Finland
Model	P
Classic	3	−1647.400	3300.8000	3308.9290	2.1948e+03	8.6808e+01	4.2847e+01	2.9136e−01	NA
LHD	4	−1589.048	3186.0950	3196.9330	2.1858e+03	9.4965e+01	4.2878e+01 (±4.5816E−11)	2.7076e−01 (±3.2131E−10)	5.8830e−03

Maximum likelihood (ML) parameter estimates for both models and two time series of the number of reported syncytial virus cases in two different localities: Gambia and Finland. The statistical model for the observation error is the Poisson distribution. The letter denotes the number of model parameters in each case. denotes the value negative log-likelihood function evaluated at the ML estimates. The AIC and BIC scores for each model vs. data set combination are also reported. The model selection decision rule is to pick the model with lowest information criterion value. Accordingly, the LHD model seems to be the best choice in Finland whereas the Classical model seems to be a sufficient explanation for the observed time series patterns in Gambia. Confidence intervals for and are shown in parentheses for the best model for each locality.