University of Oulu

Balogun OS, Gao X-Z, Jolayemi ET, Olaleye SA (2020) Generalized cure rate model for infectious diseases with possible co-infections. PLoS ONE 15(9): e0239003. https://doi.org/10.1371/journal.pone.0239003

Generalized cure rate model for infectious diseases with possible co-infections

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Author: Balogun, Oluwafemi Samson1; Gao, Xiao-Zhi1; Jolayem, Emmanuel Teju2;
Organizations: 1School of Computing, University of Eastern Finland, Kuopio, Finland
2Department of Statistics, Faculty of Science, University of Ilorin, Ilorin, Kwara State, Nigeria
3Department of Marketing, Management and International Business, University of Oulu, Oulu, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 1.3 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2020092170199
Language: English
Published: Public Library of Science, 2020
Publish Date: 2020-09-21
Description:

Abstract

This research mainly aims to develop a generalized cure rate model, estimate the proportion of cured patients and their survival rate, and identify the risk factors associated with infectious diseases. The generalized cure rate model is based on bounded cumulative hazard function, which is a non-mixture model, and is developed using a two-parameter Weibull distribution as the baseline distribution, to estimate the cure rate using maximum likelihood method and real data with R and STATA software. The results showed that the cure rate of tuberculosis (TB) patients was 26.3%, which was higher than that of TB patients coinfected with human immunodeficiency virus (HIV; 23.1%). The non-parametric median survival time of TB patients was 51 months, while that of TB patients co-infected with HIV was 33 months. Moreover, no risk factors were associated with TB patients co-infected with HIV, while age was a significant risk factor for TB patients among the suspected risk factors considered. Furthermore, the bounded cumulative hazard function was extended to accommodate infectious diseases with co-infections by deriving an appropriate probability density function, determining the distribution, and using real data. Governments and related health authorities are also encouraged to take appropriate actions to combat infectious diseases with possible co-infections.

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Series: PLoS one
ISSN: 1932-6203
ISSN-E: 1932-6203
ISSN-L: 1932-6203
Volume: 15
Issue: 9
Article number: e0239003
DOI: 10.1371/journal.pone.0239003
OADOI: https://oadoi.org/10.1371/journal.pone.0239003
Type of Publication: A1 Journal article – refereed
Field of Science: 3141 Health care science
3142 Public health care science, environmental and occupational health
Subjects:
Copyright information: © 2020 Balogun et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
  https://creativecommons.org/licenses/by/4.0/