Ordinal Regression Modeling of Mother to Infant HIV Transmission in Nyeri County, Kenya

Agnes Njoki; Anthony Wanjoya; Antony Waititu

doi:doi:10.11648/j.ijdsa.20200605.14

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Ordinal Regression Modeling of Mother to Infant HIV Transmission in Nyeri County, Kenya

Agnes Njoki, Anthony Wanjoya, Antony Waititu

Published in International Journal of Data Science and Analysis (Volume 6, Issue 5)

Received: 30 September 2020 Accepted: 20 October 2020 Published: 23 October 2020

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Abstract

The transmission rates of HIV from a HIV-positive mother to her child during pregnancy, delivery or breastfeeding remains of much concern. Various governments and non-governmental organizations have aimed at coming up with policies aimed at minimizing the transmissions. For this to be achievable, there is a need for sound statistical procedures in the analysis of the mother to infant HIV transmission data. The study gives an application of the ordinal regression to the modeling of such data, a case of Nyeri County-Kenya. The logistic regression has been described as the best methodology for modeling binary response variables. However it does not provide a best fit for an ordered categorical variable with more than two categories. This calls for the extensions of the logistic regression which can be used when modeling such kind of variables, such an extension is the ordinal regression methodology. This study proposes the use of the ordinal regression methodology with probit and logit link functions to model infant feeding, arv regimen, maternal cell count and maternal viral load effect on mother to infant HIV transmission in Nyeri county, Kenya a case of Karatina sub-county referral hospital. An aspect of the ordinal link models, which can be useful for this implementation is particularly emphasized as it is in their interpretation that the classes of the dependent variable can be considered from the partition of the variation interval of an underlying continuous random variable. Data to be used shall be secondary data collected from Karatina sub-county referral hospital. Inference on parameters and model diagnostics is also provided.

Published in	International Journal of Data Science and Analysis (Volume 6, Issue 5)
DOI	10.11648/j.ijdsa.20200605.14
Page(s)	145-152
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

Ordinal Regression, Logistic and Probit Link Functions, HIV Transmission

References

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[3]	Fondoh, V. N. & Mom, N. A. (2017) Mother-to-child transmission of HIV and its predictors among HIV-exposed infants at the Bamenda Regional Hospital, Cameroon. Africa. Afr J Lab Med; 6 (1). doi: 10.4102/ajlm.v6i1.589.
[4]	Rutagwera, David & Molès, jean-pierre & Kankasa, Chipepo & Mwiya, Mwiya & Tuaillon, Edouard & Peries, Marianne & Nagot, Nicolas & Van de Perre, Philippe & Tylleskär& Thorkild. (2019). Prevalence and determinants of HIV shedding in breast milk during continued breastfeeding among Zambian mothers not on antiretroviral treatment (ART): A cross-sectional study. Medicine; 98 (44). doi: 10.1097/MD.0000000000017383.
[5]	Manji, Karim & Duggan, Christopher & Liu, Enju & Bosch, Ronald & Kisenge, Rodrick & Aboud, Said & Kupka, Ronald & Fawzi & Wafaie. (2016). Exclusive Breast-feeding Protects against Mother-to-Child Transmission of HIV-1 through 12 Months of Age in Tanzania. Journal of Tropical Pediatrics; 62 (4). doi: 10.1093/tropej/fmw012.
[6]	Potty, Rajaram & Sinha, Anju & Sethumadhavan, Rajeev & Isac, Shajy & Washington, Reynold. (2019). Incidence, prevalence and associated factors of mother-to-child transmission of HIV, among children exposed to maternal HIV, in Belgaum district, Karnataka, India. BMC Public Health; 19 (386). doi: 10.1186/s12889-019-6707-3.
[7]	Lumbanraja, S. N. & Sanusi, S. R. (2016) Triple antiretroviral therapy effectively eliminates HIV transmission from mother to child. International Journal of Pharm Tech Research; 9 (11), 68-71.
[8]	Obsa, Siyum & Dabsu, Regea & Ejeta & Eyasu (2018). Rate of mother to child transmission of HIV and factors associated among HIV exposed infants in OromiaRegional State, Ethiopia: Retrospective study. Egyptian Pediatric Association Gazette; 66 (3), 61-65. doi: 10.1016/j.epag.2018.07.002.
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[10]	Thomas, T. K., Masaba, R., Borkowf, C. B., Ndivo, R., Zeh, C., Misore, A., Otieno, J., Jamieson, D., Thigpen, M. C., Bulterys, M., Slutsker, L., De Cock, K. M., Amornkul, P. N., Greenberg, A. E., Fowler, M. G. & KIBS Study Team (2011). PLoS Med; 8 (3). doi: 10.1371/journal.pmed.1001015.
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APA Style

Agnes Njoki, Anthony Wanjoya, Antony Waititu. (2020). Ordinal Regression Modeling of Mother to Infant HIV Transmission in Nyeri County, Kenya. International Journal of Data Science and Analysis, 6(5), 145-152. https://doi.org/10.11648/j.ijdsa.20200605.14

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ACS Style

Agnes Njoki; Anthony Wanjoya; Antony Waititu. Ordinal Regression Modeling of Mother to Infant HIV Transmission in Nyeri County, Kenya. Int. J. Data Sci. Anal. 2020, 6(5), 145-152. doi: 10.11648/j.ijdsa.20200605.14

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AMA Style

Agnes Njoki, Anthony Wanjoya, Antony Waititu. Ordinal Regression Modeling of Mother to Infant HIV Transmission in Nyeri County, Kenya. Int J Data Sci Anal. 2020;6(5):145-152. doi: 10.11648/j.ijdsa.20200605.14

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@article{10.11648/j.ijdsa.20200605.14,
  author = {Agnes Njoki and Anthony Wanjoya and Antony Waititu},
  title = {Ordinal Regression Modeling of Mother to Infant HIV Transmission in Nyeri County, Kenya},
  journal = {International Journal of Data Science and Analysis},
  volume = {6},
  number = {5},
  pages = {145-152},
  doi = {10.11648/j.ijdsa.20200605.14},
  url = {https://doi.org/10.11648/j.ijdsa.20200605.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijdsa.20200605.14},
  abstract = {The transmission rates of HIV from a HIV-positive mother to her child during pregnancy, delivery or breastfeeding remains of much concern. Various governments and non-governmental organizations have aimed at coming up with policies aimed at minimizing the transmissions. For this to be achievable, there is a need for sound statistical procedures in the analysis of the mother to infant HIV transmission data. The study gives an application of the ordinal regression to the modeling of such data, a case of Nyeri County-Kenya. The logistic regression has been described as the best methodology for modeling binary response variables. However it does not provide a best fit for an ordered categorical variable with more than two categories. This calls for the extensions of the logistic regression which can be used when modeling such kind of variables, such an extension is the ordinal regression methodology. This study proposes the use of the ordinal regression methodology with probit and logit link functions to model infant feeding, arv regimen, maternal cell count and maternal viral load effect on mother to infant HIV transmission in Nyeri county, Kenya a case of Karatina sub-county referral hospital. An aspect of the ordinal link models, which can be useful for this implementation is particularly emphasized as it is in their interpretation that the classes of the dependent variable can be considered from the partition of the variation interval of an underlying continuous random variable. Data to be used shall be secondary data collected from Karatina sub-county referral hospital. Inference on parameters and model diagnostics is also provided.},
 year = {2020}
}

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TY  - JOUR
T1  - Ordinal Regression Modeling of Mother to Infant HIV Transmission in Nyeri County, Kenya
AU  - Agnes Njoki
AU  - Anthony Wanjoya
AU  - Antony Waititu
Y1  - 2020/10/23
PY  - 2020
N1  - https://doi.org/10.11648/j.ijdsa.20200605.14
DO  - 10.11648/j.ijdsa.20200605.14
T2  - International Journal of Data Science and Analysis
JF  - International Journal of Data Science and Analysis
JO  - International Journal of Data Science and Analysis
SP  - 145
EP  - 152
PB  - Science Publishing Group
SN  - 2575-1891
UR  - https://doi.org/10.11648/j.ijdsa.20200605.14
AB  - The transmission rates of HIV from a HIV-positive mother to her child during pregnancy, delivery or breastfeeding remains of much concern. Various governments and non-governmental organizations have aimed at coming up with policies aimed at minimizing the transmissions. For this to be achievable, there is a need for sound statistical procedures in the analysis of the mother to infant HIV transmission data. The study gives an application of the ordinal regression to the modeling of such data, a case of Nyeri County-Kenya. The logistic regression has been described as the best methodology for modeling binary response variables. However it does not provide a best fit for an ordered categorical variable with more than two categories. This calls for the extensions of the logistic regression which can be used when modeling such kind of variables, such an extension is the ordinal regression methodology. This study proposes the use of the ordinal regression methodology with probit and logit link functions to model infant feeding, arv regimen, maternal cell count and maternal viral load effect on mother to infant HIV transmission in Nyeri county, Kenya a case of Karatina sub-county referral hospital. An aspect of the ordinal link models, which can be useful for this implementation is particularly emphasized as it is in their interpretation that the classes of the dependent variable can be considered from the partition of the variation interval of an underlying continuous random variable. Data to be used shall be secondary data collected from Karatina sub-county referral hospital. Inference on parameters and model diagnostics is also provided.
VL  - 6
IS  - 5
ER  -

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Author Information

Agnes Njoki

Department of Statistics and Actuarial Science, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya
Anthony Wanjoya

Department of Statistics and Actuarial Science, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya
Antony Waititu

Department of Statistics and Actuarial Science, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya

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APA Style

Agnes Njoki, Anthony Wanjoya, Antony Waititu. (2020). Ordinal Regression Modeling of Mother to Infant HIV Transmission in Nyeri County, Kenya. International Journal of Data Science and Analysis, 6(5), 145-152. https://doi.org/10.11648/j.ijdsa.20200605.14

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ACS Style

Agnes Njoki; Anthony Wanjoya; Antony Waititu. Ordinal Regression Modeling of Mother to Infant HIV Transmission in Nyeri County, Kenya. Int. J. Data Sci. Anal. 2020, 6(5), 145-152. doi: 10.11648/j.ijdsa.20200605.14

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AMA Style

Agnes Njoki, Anthony Wanjoya, Antony Waititu. Ordinal Regression Modeling of Mother to Infant HIV Transmission in Nyeri County, Kenya. Int J Data Sci Anal. 2020;6(5):145-152. doi: 10.11648/j.ijdsa.20200605.14

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@article{10.11648/j.ijdsa.20200605.14,
  author = {Agnes Njoki and Anthony Wanjoya and Antony Waititu},
  title = {Ordinal Regression Modeling of Mother to Infant HIV Transmission in Nyeri County, Kenya},
  journal = {International Journal of Data Science and Analysis},
  volume = {6},
  number = {5},
  pages = {145-152},
  doi = {10.11648/j.ijdsa.20200605.14},
  url = {https://doi.org/10.11648/j.ijdsa.20200605.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijdsa.20200605.14},
  abstract = {The transmission rates of HIV from a HIV-positive mother to her child during pregnancy, delivery or breastfeeding remains of much concern. Various governments and non-governmental organizations have aimed at coming up with policies aimed at minimizing the transmissions. For this to be achievable, there is a need for sound statistical procedures in the analysis of the mother to infant HIV transmission data. The study gives an application of the ordinal regression to the modeling of such data, a case of Nyeri County-Kenya. The logistic regression has been described as the best methodology for modeling binary response variables. However it does not provide a best fit for an ordered categorical variable with more than two categories. This calls for the extensions of the logistic regression which can be used when modeling such kind of variables, such an extension is the ordinal regression methodology. This study proposes the use of the ordinal regression methodology with probit and logit link functions to model infant feeding, arv regimen, maternal cell count and maternal viral load effect on mother to infant HIV transmission in Nyeri county, Kenya a case of Karatina sub-county referral hospital. An aspect of the ordinal link models, which can be useful for this implementation is particularly emphasized as it is in their interpretation that the classes of the dependent variable can be considered from the partition of the variation interval of an underlying continuous random variable. Data to be used shall be secondary data collected from Karatina sub-county referral hospital. Inference on parameters and model diagnostics is also provided.},
 year = {2020}
}

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TY  - JOUR
T1  - Ordinal Regression Modeling of Mother to Infant HIV Transmission in Nyeri County, Kenya
AU  - Agnes Njoki
AU  - Anthony Wanjoya
AU  - Antony Waititu
Y1  - 2020/10/23
PY  - 2020
N1  - https://doi.org/10.11648/j.ijdsa.20200605.14
DO  - 10.11648/j.ijdsa.20200605.14
T2  - International Journal of Data Science and Analysis
JF  - International Journal of Data Science and Analysis
JO  - International Journal of Data Science and Analysis
SP  - 145
EP  - 152
PB  - Science Publishing Group
SN  - 2575-1891
UR  - https://doi.org/10.11648/j.ijdsa.20200605.14
AB  - The transmission rates of HIV from a HIV-positive mother to her child during pregnancy, delivery or breastfeeding remains of much concern. Various governments and non-governmental organizations have aimed at coming up with policies aimed at minimizing the transmissions. For this to be achievable, there is a need for sound statistical procedures in the analysis of the mother to infant HIV transmission data. The study gives an application of the ordinal regression to the modeling of such data, a case of Nyeri County-Kenya. The logistic regression has been described as the best methodology for modeling binary response variables. However it does not provide a best fit for an ordered categorical variable with more than two categories. This calls for the extensions of the logistic regression which can be used when modeling such kind of variables, such an extension is the ordinal regression methodology. This study proposes the use of the ordinal regression methodology with probit and logit link functions to model infant feeding, arv regimen, maternal cell count and maternal viral load effect on mother to infant HIV transmission in Nyeri county, Kenya a case of Karatina sub-county referral hospital. An aspect of the ordinal link models, which can be useful for this implementation is particularly emphasized as it is in their interpretation that the classes of the dependent variable can be considered from the partition of the variation interval of an underlying continuous random variable. Data to be used shall be secondary data collected from Karatina sub-county referral hospital. Inference on parameters and model diagnostics is also provided.
VL  - 6
IS  - 5
ER  -

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