Integer time series models for tuberculosis in Africa

Tuberculosis, an airborne disease, is the deadliest human infectious disease caused by one single agent. The African region is among the most affected and most burdensome area in terms of tuberculosis cases. In this paper, we modeled the number of new cases of tuberculosis for 2000–2021 by integer t...

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Bibliographic Details
Published in:Scientific reports 2023-07, Vol.13 (1), p.11443-11443, Article 11443
Main Authors: Ojo, Oluwadare O., Nadarajah, Saralees, Kebe, Malick
Format: Article
Language:English
Subjects:
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Acquired immune deficiency syndrome
Africa - epidemiology
AIDS
Binomial distribution
COVID-19
HIV
Human immunodeficiency virus
Humanities and Social Sciences
Humans
Infectious diseases
Models, Statistical
Mortality
multidisciplinary
Neural networks
Pandemics
Science
Science (multidisciplinary)
Statistical analysis
Statistical methods
Time Factors
Time series
Tuberculosis
Tuberculosis - epidemiology
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Summary:Tuberculosis, an airborne disease, is the deadliest human infectious disease caused by one single agent. The African region is among the most affected and most burdensome area in terms of tuberculosis cases. In this paper, we modeled the number of new cases of tuberculosis for 2000–2021 by integer time series. For each African country, we fitted twenty different models and selected the model that best fitted the data. The twenty models were mostly based on the number of new cases following either the Poisson or negative binomial distribution with the rate parameter allowed to vary linearly or quadratically with respect to year. The best fitted models were used to give predictions for 2022–2031.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-023-38707-4