Predicting Chlamydia Trachomatis Infection in a Mining Community in Western Ghana

Christiana Cynthia Nyarko; Nicholas Nicodemus Nana Nsowah-Nuamah; Mettle Felix Oko; Peter Kwesi Nyarko

doi:doi:10.11648/j.ajtas.20200906.17

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Predicting Chlamydia Trachomatis Infection in a Mining Community in Western Ghana

Christiana Cynthia Nyarko, Nicholas Nicodemus Nana Nsowah-Nuamah, Mettle Felix Oko, Peter Kwesi Nyarko

Published in American Journal of Theoretical and Applied Statistics (Volume 9, Issue 6)

Received: 7 October 2020 Accepted: 6 November 2020 Published: 22 December 2020

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Abstract

Chlamydia Trachomatis (CT) infection among females in a mining community in Western Ghana is a major medical issue. Screening using laboratory test results have been the usual control and prevention of STI globally but have been found to have its own limitations due to delay in test results leading to further transmission of genital infections. Consequently, a statistical model is formulated to predict the incidence of Chlamydia Trachomatis (CT) infection among females in the community. The model used a Modified Univariate Normal Discriminant Function, a Logistic Regression Model and specific symptoms associated with Chlamydial infection as part of the explanatory variables. Samples were taken from 186 patients consisting of 40 males and 146 females from two hospitals in the Tarkwa Nsuaem Municipality, a mining community in Western Ghana. The model was validated using a sensitivity analysis test and Apparent Error Rate (APER). The model predicted decreasing infection rate of patients with increasing age. The most reported and significant symptoms among the female patients diagnosed was vaginal discharge, (p<0.05). The study predicted a patient as positive or infected with Chlamydial, if the result of the model evaluated gave a positive value, otherwise the patient was declared free of infection. Further analysis of the proposed Statistical Chlamydia Trachomatis (SCT) model gave a sensitivity of 84% which was consistent with other research findings like the rapid point of care (POC) diagnostic test for Chlamydial infection with sensitivity range of 55–85% for high prevalence populations. The study observed that young females in mining communities are at risk of acquiring Chlamydial T infection if presenting with vaginal discharge. Identifying these risk factors associated with Chlamydial infection among young women in the mining communities would help inform health care officials the rate of infection in the Municipality, and accordingly mount public educational health campaign in the Municipality aimed at minimizing the spread of chlamydial infections and any other STI.

Published in	American Journal of Theoretical and Applied Statistics (Volume 9, Issue 6)
DOI	10.11648/j.ajtas.20200906.17
Page(s)	312-318
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2020. Published by Science Publishing Group

Keywords

Chlamydia Trachomatis, Symptoms, Univariate, Discriminant, Logistic, Sensitivity, Prediction

References

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APA Style

Christiana Cynthia Nyarko, Nicholas Nicodemus Nana Nsowah-Nuamah, Mettle Felix Oko, Peter Kwesi Nyarko. (2020). Predicting Chlamydia Trachomatis Infection in a Mining Community in Western Ghana. American Journal of Theoretical and Applied Statistics, 9(6), 312-318. https://doi.org/10.11648/j.ajtas.20200906.17

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ACS Style

Christiana Cynthia Nyarko; Nicholas Nicodemus Nana Nsowah-Nuamah; Mettle Felix Oko; Peter Kwesi Nyarko. Predicting Chlamydia Trachomatis Infection in a Mining Community in Western Ghana. Am. J. Theor. Appl. Stat. 2020, 9(6), 312-318. doi: 10.11648/j.ajtas.20200906.17

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AMA Style

Christiana Cynthia Nyarko, Nicholas Nicodemus Nana Nsowah-Nuamah, Mettle Felix Oko, Peter Kwesi Nyarko. Predicting Chlamydia Trachomatis Infection in a Mining Community in Western Ghana. Am J Theor Appl Stat. 2020;9(6):312-318. doi: 10.11648/j.ajtas.20200906.17

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@article{10.11648/j.ajtas.20200906.17,
  author = {Christiana Cynthia Nyarko and Nicholas Nicodemus Nana Nsowah-Nuamah and Mettle Felix Oko and Peter Kwesi Nyarko},
  title = {Predicting Chlamydia Trachomatis Infection in a Mining Community in Western Ghana},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {9},
  number = {6},
  pages = {312-318},
  doi = {10.11648/j.ajtas.20200906.17},
  url = {https://doi.org/10.11648/j.ajtas.20200906.17},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20200906.17},
  abstract = {Chlamydia Trachomatis (CT) infection among females in a mining community in Western Ghana is a major medical issue. Screening using laboratory test results have been the usual control and prevention of STI globally but have been found to have its own limitations due to delay in test results leading to further transmission of genital infections. Consequently, a statistical model is formulated to predict the incidence of Chlamydia Trachomatis (CT) infection among females in the community. The model used a Modified Univariate Normal Discriminant Function, a Logistic Regression Model and specific symptoms associated with Chlamydial infection as part of the explanatory variables. Samples were taken from 186 patients consisting of 40 males and 146 females from two hospitals in the Tarkwa Nsuaem Municipality, a mining community in Western Ghana. The model was validated using a sensitivity analysis test and Apparent Error Rate (APER). The model predicted decreasing infection rate of patients with increasing age. The most reported and significant symptoms among the female patients diagnosed was vaginal discharge, (p<0.05). The study predicted a patient as positive or infected with Chlamydial, if the result of the model evaluated gave a positive value, otherwise the patient was declared free of infection. Further analysis of the proposed Statistical Chlamydia Trachomatis (SCT) model gave a sensitivity of 84% which was consistent with other research findings like the rapid point of care (POC) diagnostic test for Chlamydial infection with sensitivity range of 55–85% for high prevalence populations. The study observed that young females in mining communities are at risk of acquiring Chlamydial T infection if presenting with vaginal discharge. Identifying these risk factors associated with Chlamydial infection among young women in the mining communities would help inform health care officials the rate of infection in the Municipality, and accordingly mount public educational health campaign in the Municipality aimed at minimizing the spread of chlamydial infections and any other STI.},
 year = {2020}
}

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TY  - JOUR
T1  - Predicting Chlamydia Trachomatis Infection in a Mining Community in Western Ghana
AU  - Christiana Cynthia Nyarko
AU  - Nicholas Nicodemus Nana Nsowah-Nuamah
AU  - Mettle Felix Oko
AU  - Peter Kwesi Nyarko
Y1  - 2020/12/22
PY  - 2020
N1  - https://doi.org/10.11648/j.ajtas.20200906.17
DO  - 10.11648/j.ajtas.20200906.17
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
SP  - 312
EP  - 318
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20200906.17
AB  - Chlamydia Trachomatis (CT) infection among females in a mining community in Western Ghana is a major medical issue. Screening using laboratory test results have been the usual control and prevention of STI globally but have been found to have its own limitations due to delay in test results leading to further transmission of genital infections. Consequently, a statistical model is formulated to predict the incidence of Chlamydia Trachomatis (CT) infection among females in the community. The model used a Modified Univariate Normal Discriminant Function, a Logistic Regression Model and specific symptoms associated with Chlamydial infection as part of the explanatory variables. Samples were taken from 186 patients consisting of 40 males and 146 females from two hospitals in the Tarkwa Nsuaem Municipality, a mining community in Western Ghana. The model was validated using a sensitivity analysis test and Apparent Error Rate (APER). The model predicted decreasing infection rate of patients with increasing age. The most reported and significant symptoms among the female patients diagnosed was vaginal discharge, (p<0.05). The study predicted a patient as positive or infected with Chlamydial, if the result of the model evaluated gave a positive value, otherwise the patient was declared free of infection. Further analysis of the proposed Statistical Chlamydia Trachomatis (SCT) model gave a sensitivity of 84% which was consistent with other research findings like the rapid point of care (POC) diagnostic test for Chlamydial infection with sensitivity range of 55–85% for high prevalence populations. The study observed that young females in mining communities are at risk of acquiring Chlamydial T infection if presenting with vaginal discharge. Identifying these risk factors associated with Chlamydial infection among young women in the mining communities would help inform health care officials the rate of infection in the Municipality, and accordingly mount public educational health campaign in the Municipality aimed at minimizing the spread of chlamydial infections and any other STI.
VL  - 9
IS  - 6
ER  -

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Author Information

Christiana Cynthia Nyarko

Department of Mathematical Sciences, Faculty of Engineering, University of Mines and Technology (UMaT), Tarkwa, Ghana
Nicholas Nicodemus Nana Nsowah-Nuamah

Office of the President, Dominion University College, Accra, Ghana
Mettle Felix Oko

Department of Statistics and Actuarial Science, School of Physical and Mathematical Science, University of Ghana, Legon, Accra, Ghana
Peter Kwesi Nyarko

Department of Mathematical Sciences, Faculty of Engineering, University of Mines and Technology (UMaT), Tarkwa, Ghana

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APA Style

Christiana Cynthia Nyarko, Nicholas Nicodemus Nana Nsowah-Nuamah, Mettle Felix Oko, Peter Kwesi Nyarko. (2020). Predicting Chlamydia Trachomatis Infection in a Mining Community in Western Ghana. American Journal of Theoretical and Applied Statistics, 9(6), 312-318. https://doi.org/10.11648/j.ajtas.20200906.17

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ACS Style

Christiana Cynthia Nyarko; Nicholas Nicodemus Nana Nsowah-Nuamah; Mettle Felix Oko; Peter Kwesi Nyarko. Predicting Chlamydia Trachomatis Infection in a Mining Community in Western Ghana. Am. J. Theor. Appl. Stat. 2020, 9(6), 312-318. doi: 10.11648/j.ajtas.20200906.17

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AMA Style

Christiana Cynthia Nyarko, Nicholas Nicodemus Nana Nsowah-Nuamah, Mettle Felix Oko, Peter Kwesi Nyarko. Predicting Chlamydia Trachomatis Infection in a Mining Community in Western Ghana. Am J Theor Appl Stat. 2020;9(6):312-318. doi: 10.11648/j.ajtas.20200906.17

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@article{10.11648/j.ajtas.20200906.17,
  author = {Christiana Cynthia Nyarko and Nicholas Nicodemus Nana Nsowah-Nuamah and Mettle Felix Oko and Peter Kwesi Nyarko},
  title = {Predicting Chlamydia Trachomatis Infection in a Mining Community in Western Ghana},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {9},
  number = {6},
  pages = {312-318},
  doi = {10.11648/j.ajtas.20200906.17},
  url = {https://doi.org/10.11648/j.ajtas.20200906.17},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20200906.17},
  abstract = {Chlamydia Trachomatis (CT) infection among females in a mining community in Western Ghana is a major medical issue. Screening using laboratory test results have been the usual control and prevention of STI globally but have been found to have its own limitations due to delay in test results leading to further transmission of genital infections. Consequently, a statistical model is formulated to predict the incidence of Chlamydia Trachomatis (CT) infection among females in the community. The model used a Modified Univariate Normal Discriminant Function, a Logistic Regression Model and specific symptoms associated with Chlamydial infection as part of the explanatory variables. Samples were taken from 186 patients consisting of 40 males and 146 females from two hospitals in the Tarkwa Nsuaem Municipality, a mining community in Western Ghana. The model was validated using a sensitivity analysis test and Apparent Error Rate (APER). The model predicted decreasing infection rate of patients with increasing age. The most reported and significant symptoms among the female patients diagnosed was vaginal discharge, (p<0.05). The study predicted a patient as positive or infected with Chlamydial, if the result of the model evaluated gave a positive value, otherwise the patient was declared free of infection. Further analysis of the proposed Statistical Chlamydia Trachomatis (SCT) model gave a sensitivity of 84% which was consistent with other research findings like the rapid point of care (POC) diagnostic test for Chlamydial infection with sensitivity range of 55–85% for high prevalence populations. The study observed that young females in mining communities are at risk of acquiring Chlamydial T infection if presenting with vaginal discharge. Identifying these risk factors associated with Chlamydial infection among young women in the mining communities would help inform health care officials the rate of infection in the Municipality, and accordingly mount public educational health campaign in the Municipality aimed at minimizing the spread of chlamydial infections and any other STI.},
 year = {2020}
}

Copy | Download

TY  - JOUR
T1  - Predicting Chlamydia Trachomatis Infection in a Mining Community in Western Ghana
AU  - Christiana Cynthia Nyarko
AU  - Nicholas Nicodemus Nana Nsowah-Nuamah
AU  - Mettle Felix Oko
AU  - Peter Kwesi Nyarko
Y1  - 2020/12/22
PY  - 2020
N1  - https://doi.org/10.11648/j.ajtas.20200906.17
DO  - 10.11648/j.ajtas.20200906.17
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
SP  - 312
EP  - 318
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20200906.17
AB  - Chlamydia Trachomatis (CT) infection among females in a mining community in Western Ghana is a major medical issue. Screening using laboratory test results have been the usual control and prevention of STI globally but have been found to have its own limitations due to delay in test results leading to further transmission of genital infections. Consequently, a statistical model is formulated to predict the incidence of Chlamydia Trachomatis (CT) infection among females in the community. The model used a Modified Univariate Normal Discriminant Function, a Logistic Regression Model and specific symptoms associated with Chlamydial infection as part of the explanatory variables. Samples were taken from 186 patients consisting of 40 males and 146 females from two hospitals in the Tarkwa Nsuaem Municipality, a mining community in Western Ghana. The model was validated using a sensitivity analysis test and Apparent Error Rate (APER). The model predicted decreasing infection rate of patients with increasing age. The most reported and significant symptoms among the female patients diagnosed was vaginal discharge, (p<0.05). The study predicted a patient as positive or infected with Chlamydial, if the result of the model evaluated gave a positive value, otherwise the patient was declared free of infection. Further analysis of the proposed Statistical Chlamydia Trachomatis (SCT) model gave a sensitivity of 84% which was consistent with other research findings like the rapid point of care (POC) diagnostic test for Chlamydial infection with sensitivity range of 55–85% for high prevalence populations. The study observed that young females in mining communities are at risk of acquiring Chlamydial T infection if presenting with vaginal discharge. Identifying these risk factors associated with Chlamydial infection among young women in the mining communities would help inform health care officials the rate of infection in the Municipality, and accordingly mount public educational health campaign in the Municipality aimed at minimizing the spread of chlamydial infections and any other STI.
VL  - 9
IS  - 6
ER  -

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