In this paper we discussed about different types of Epedemic models. These models takes into account the total population amounts as desist for the illness transmission since its increase makes more difficult contacts among susceptible and infected. A mathematical model is often fitted to the data set while estimation of epidemiological parameter is done from disease outbreak data. The probable estimates of parameters are uncertain that may arise due to sum data errors. The estimates are dependent on structure models used in fitting process and the uncertainty leads to more uncertainty in estimation of parameter. We give maximum efforts in parameters value estimation from initial growth rate. In this setting parameter estimates may be sensible from detail course of infection.
People exposed to certain diseases are required to be treated with a safe and effective dose level of a drug. In epidemiological studies to find out an effective dose level, different dose levels are applied to the exposed and a certain number of cures is observed. Negative binomial distribution is considered to fit overdispersed Poisson count data. This study investigates the time effect on the response at different time points as well as at different dose levels. The point estimation and confidence bands for ED(100p)(t) and LT(100p)(d) are formulated in closed form for the proposed dose-time-response model with the negative binomial distribution. Numerical illustrations are carried out in order to check the performance level of the proposed model.
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