Table 2.
Match between identified models with requirements of HTA programme
| Paper | Model Type | Simplicity | Can adapt to epidemiological changes | Can adapt to environmental changes | Centre Recruitment | Could inform commissioning Decisions |
|---|---|---|---|---|---|---|
| Carter (2004) | Simulation using Poisson distribution | Y | P | Y | Y | Y |
| Carter (2005) | Unconditional | Y | Y | N | N | Y |
| Conditional | Y | Y | Y | Y | Y | |
| Simulation using Poisson distribution | Y | P | Y | Y | Y | |
| Simulation using Poisson distribution with average recruitment rates (λ) varied according to a uniform distribution | Y | P | Y | Y | Y | |
| Anisimov (2007) | Poisson process with recruitment rates (λ) viewed as a sample from a gamma distribution | N | Y | Y | N | P |
| Moussa (1984) | Conditional | Y | Y | Y | N | Y |
| Williford (1987) | Poisson | N | Y | Y | N | N |
| Negative binomial (Poisson process with recruitment rates (λ) viewed as a sample from a gamma distribution) | N | Y | Y | Y | N | |
| Lees contagious poisson | N | Y | Y | Y | N | |
| Bayesian - prior distribution is possion-gamma, posterior is gamma | N | Y | Y | N | N | |
| Gajewski (2007) | Bayesian - prior distribution is the inverse gamma, likelihood is the exponential distribution, posterior distribution is the inverse gamma | N | Y | Y | P | Y |
| Abbas (2007) | Markov | N | P | Y | N | Y |
| Hadich (2001) | Time series | N | P | N | N | N |
Y = Criterion met
N = Criterion not met
P = Posssibly: Criteron could be met, dependent on circumstance