Estimation of parasitic infection dynamics when detectability is imperfect.
The simultaneous estimation of infection rate, cure rate and detectability of parasitic infections is considered. A new method for this estimation based on a simple statistical model assuming constant transition rates between parasite states is proposed. Repeated observations on the infection status of the same individuals is required for this method. A maximum likelihood approach is used for parameter estimation and the calculation of standard errors of the estimates. The method is illustrated by a longitudinal study of the presence of Giardia lamblia infection in Kenyan children.
Nagelkerke
N J
NJ
Medical Research Centre, Kenya Medical Research Institute, Nairobi.
Chunge
R N
RN
Kinoti
S N
SN
D005243:Feces / Q000469:parasitology; D005873:Giardiasis / Q000453:epidemiology* / Q000469:parasitology; D006801:Humans; D007223:Infant; D007630:Kenya / Q000453:epidemiology; D008137:Longitudinal Studies; D008390:Markov Chains; D008432:Mathematical Computing; D015233:Models, Statistical; D011157:Population Dynamics; D015995:Prevalence; D012984:Software