Branching process models for surveillance of infectious diseases controlled by mass vaccination.
Biostatistics
; 4(2): 279-95, 2003 Apr.
Article
in En
| MEDLINE
| ID: mdl-12925522
ABSTRACT
Mass vaccination programmes aim to maintain the effective reproduction number R of an infection below unity. We describe methods for monitoring the value of R using surveillance data. The models are based on branching processes in which R is identified with the offspring mean. We derive unconditional likelihoods for the offspring mean using data on outbreak size and outbreak duration. We also discuss Bayesian methods, implemented by Metropolis-Hastings sampling. We investigate by simulation the validity of the models with respect to depletion of susceptibles and under-ascertainment of cases. The methods are illustrated using surveillance data on measles in the USA.
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Collection:
01-internacional
Database:
MEDLINE
Main subject:
Mass Vaccination
/
Communicable Diseases
/
Models, Immunological
Type of study:
Prognostic_studies
/
Screening_studies
Limits:
Humans
Language:
En
Journal:
Biostatistics
Year:
2003
Document type:
Article
Affiliation country: