Literature DB >> 26116617

CUSUM control charts to monitor series of Negative Binomial count data.

Airlane Pereira Alencar1, Linda Lee Ho2, Orlando Yesid Esparza Albarracin1.   

Abstract

To detect outbreaks of diseases in public health, several control charts have been proposed in the literature. In this context, the usual generalized linear model may be fitted for counts under a Negative Binomial distribution with a logarithm link function and the population size included as offset to model hospitalization rates. Different statistics are used to build CUSUM control charts to monitor daily hospitalizations and their performances are compared in simulation studies. The main contribution of the current paper is to consider different statistics based on transformations and the deviance residual to build control charts to monitor counts with seasonality effects and evaluate all the assumptions of the monitored statistics. The monitoring of daily number of hospital admissions due to respiratory diseases for people aged over 65 years in the city São Paulo-Brazil is considered as an illustration of the current proposal.

Entities:  

Keywords:  Surveillance; deviance residual; likelihood ratio; seasonal effect

Mesh:

Year:  2015        PMID: 26116617     DOI: 10.1177/0962280215592427

Source DB:  PubMed          Journal:  Stat Methods Med Res        ISSN: 0962-2802            Impact factor:   3.021


  2 in total

1.  The burden of seasonal respiratory infections on a national telehealth service in England.

Authors:  R A Morbey; S Harcourt; R Pebody; M Zambon; J Hutchison; J Rutter; H Thomas; G E Smith; A J Elliot
Journal:  Epidemiol Infect       Date:  2017-04-17       Impact factor: 4.434

2.  Monitoring the Zero-Inflated Time Series Model of Counts with Random Coefficient.

Authors:  Cong Li; Shuai Cui; Dehui Wang
Journal:  Entropy (Basel)       Date:  2021-03-20       Impact factor: 2.524

  2 in total

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