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Multiple Linear Regression Model of Meningococcal Disease in Ukraine: 1992–2015

Estimating the rates of invasive meningococcal disease (IMD) from epidemiologic data remains critical for making public health decisions. In Ukraine, such estimations have not been performed. We used epidemiological data to develop a national database. These data were used to estimate the population...

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Autor principal: Mokhort, Hennadii
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7036103/
https://www.ncbi.nlm.nih.gov/pubmed/32104202
http://dx.doi.org/10.1155/2020/5105120
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author Mokhort, Hennadii
author_facet Mokhort, Hennadii
author_sort Mokhort, Hennadii
collection PubMed
description Estimating the rates of invasive meningococcal disease (IMD) from epidemiologic data remains critical for making public health decisions. In Ukraine, such estimations have not been performed. We used epidemiological data to develop a national database. These data were used to estimate the population susceptible to IMD and identify the prevalence of asymptomatic carriers of N. meningitidis using simple epidemiological models of meningococcal disease that may be used by the national policy makers. The goal was to create simple, easily understood analysis of patterns of the infection within Ukraine that would capture the major features of the infection dynamics. Studies used nationally reported data during 1992–2015. A logic model identified the prevalence of carriage and the proportion of the population susceptible to IMD as key drivers of IMD incidence. Multiple linear regression models for all ages (total population) and for children ≤14 years old were fit to national-level data. Linear models with the incidence of IMD as an outcome were highly associated with carriage and estimated susceptible population in both total population and children (R(2) = 0.994 and R(2) = 0.978, respectively). The susceptibility rate to IMD in the study total population averaged 0.0034 ± 0.0009% annually. At the national level, IMD can be characterized by the simple interaction between the prevalence of asymptomatic carriage and the proportion of the susceptible population. IMD association with prevalence rates of carriage and the proportion of susceptible population is sufficiently strong for national-level planning of intervention strategies for IMD.
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spelling pubmed-70361032020-02-26 Multiple Linear Regression Model of Meningococcal Disease in Ukraine: 1992–2015 Mokhort, Hennadii Comput Math Methods Med Research Article Estimating the rates of invasive meningococcal disease (IMD) from epidemiologic data remains critical for making public health decisions. In Ukraine, such estimations have not been performed. We used epidemiological data to develop a national database. These data were used to estimate the population susceptible to IMD and identify the prevalence of asymptomatic carriers of N. meningitidis using simple epidemiological models of meningococcal disease that may be used by the national policy makers. The goal was to create simple, easily understood analysis of patterns of the infection within Ukraine that would capture the major features of the infection dynamics. Studies used nationally reported data during 1992–2015. A logic model identified the prevalence of carriage and the proportion of the population susceptible to IMD as key drivers of IMD incidence. Multiple linear regression models for all ages (total population) and for children ≤14 years old were fit to national-level data. Linear models with the incidence of IMD as an outcome were highly associated with carriage and estimated susceptible population in both total population and children (R(2) = 0.994 and R(2) = 0.978, respectively). The susceptibility rate to IMD in the study total population averaged 0.0034 ± 0.0009% annually. At the national level, IMD can be characterized by the simple interaction between the prevalence of asymptomatic carriage and the proportion of the susceptible population. IMD association with prevalence rates of carriage and the proportion of susceptible population is sufficiently strong for national-level planning of intervention strategies for IMD. Hindawi 2020-02-11 /pmc/articles/PMC7036103/ /pubmed/32104202 http://dx.doi.org/10.1155/2020/5105120 Text en Copyright © 2020 Hennadii Mokhort. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Mokhort, Hennadii
Multiple Linear Regression Model of Meningococcal Disease in Ukraine: 1992–2015
title Multiple Linear Regression Model of Meningococcal Disease in Ukraine: 1992–2015
title_full Multiple Linear Regression Model of Meningococcal Disease in Ukraine: 1992–2015
title_fullStr Multiple Linear Regression Model of Meningococcal Disease in Ukraine: 1992–2015
title_full_unstemmed Multiple Linear Regression Model of Meningococcal Disease in Ukraine: 1992–2015
title_short Multiple Linear Regression Model of Meningococcal Disease in Ukraine: 1992–2015
title_sort multiple linear regression model of meningococcal disease in ukraine: 1992–2015
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7036103/
https://www.ncbi.nlm.nih.gov/pubmed/32104202
http://dx.doi.org/10.1155/2020/5105120
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