In Africa, Cancer is an emerging health problem where in 2012 new cancer cases were about 847,00 and around 519,00 deaths, three quarters of those deaths occurred in sub-Saharan region. In 2018, cancer was ranked as the third leading cause of deaths in Kenya after infectious and cardiovascular diseases. In 2018 cancer incidences were estimated to be 47,887 new cancer cases and 32,987 deaths. According to data from World Health Organization in 2020, cervical cancer is the second most prevalent cancer among women while breast cancer is the first. In this study, data collected by the Nairobi Cancer Registry (NCR) was used to produce spatial-temporal distribution of the cervical cancer in counties in Kenya. The results showed that counties where data was available among them Embu, Meru, Machakos, Mombasa, Nyeri, Kiambu, Kakamega, Nairobi and Bomet respectively had high risk of cervical cancer. Availability of county-based estimates and spatial-temporal distribution of cervical cancer cases will aide development of targeted county strategies, enhance early detection, promote awareness and implementation of universal coverage of major control interventions which will be crucial in reducing and halting the rising burden of the cancer cases in Kenya. In counties where data was not available the model showed relative risks for cervical cancer disease was minute but it was present, therefore spatial temporal models are very appropriate to estimate relative risks of diseases even when there is a small sample (and possibly without a sample) in a given area by borrowing information from other neighboring regions.
| Published in | American Journal of Theoretical and Applied Statistics (Volume 10, Issue 3) |
| DOI | 10.11648/j.ajtas.20211003.14 |
| Page(s) | 158-166 |
| 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), 2024. Published by Science Publishing Group |
Small Area Estimation, Spatial Temporal, Integrated Nested Laplace Approximation, Generalized Linear Mixed Models
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APA Style
Joseph Kuria Waitara, Gregory Kerich, John Kihoro, Anne Korir. (2021). Poisson-Gamma and Spatial-Temporal Models: with Application to Cervical Cancer in Kenya’s Counties. American Journal of Theoretical and Applied Statistics, 10(3), 158-166. https://doi.org/10.11648/j.ajtas.20211003.14
ACS Style
Joseph Kuria Waitara; Gregory Kerich; John Kihoro; Anne Korir. Poisson-Gamma and Spatial-Temporal Models: with Application to Cervical Cancer in Kenya’s Counties. Am. J. Theor. Appl. Stat. 2021, 10(3), 158-166. doi: 10.11648/j.ajtas.20211003.14
AMA Style
Joseph Kuria Waitara, Gregory Kerich, John Kihoro, Anne Korir. Poisson-Gamma and Spatial-Temporal Models: with Application to Cervical Cancer in Kenya’s Counties. Am J Theor Appl Stat. 2021;10(3):158-166. doi: 10.11648/j.ajtas.20211003.14
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Download@article{10.11648/j.ajtas.20211003.14,
author = {Joseph Kuria Waitara and Gregory Kerich and John Kihoro and Anne Korir},
title = {Poisson-Gamma and Spatial-Temporal Models: with Application to Cervical Cancer in Kenya’s Counties},
journal = {American Journal of Theoretical and Applied Statistics},
volume = {10},
number = {3},
pages = {158-166},
doi = {10.11648/j.ajtas.20211003.14},
url = {https://doi.org/10.11648/j.ajtas.20211003.14},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20211003.14},
abstract = {In Africa, Cancer is an emerging health problem where in 2012 new cancer cases were about 847,00 and around 519,00 deaths, three quarters of those deaths occurred in sub-Saharan region. In 2018, cancer was ranked as the third leading cause of deaths in Kenya after infectious and cardiovascular diseases. In 2018 cancer incidences were estimated to be 47,887 new cancer cases and 32,987 deaths. According to data from World Health Organization in 2020, cervical cancer is the second most prevalent cancer among women while breast cancer is the first. In this study, data collected by the Nairobi Cancer Registry (NCR) was used to produce spatial-temporal distribution of the cervical cancer in counties in Kenya. The results showed that counties where data was available among them Embu, Meru, Machakos, Mombasa, Nyeri, Kiambu, Kakamega, Nairobi and Bomet respectively had high risk of cervical cancer. Availability of county-based estimates and spatial-temporal distribution of cervical cancer cases will aide development of targeted county strategies, enhance early detection, promote awareness and implementation of universal coverage of major control interventions which will be crucial in reducing and halting the rising burden of the cancer cases in Kenya. In counties where data was not available the model showed relative risks for cervical cancer disease was minute but it was present, therefore spatial temporal models are very appropriate to estimate relative risks of diseases even when there is a small sample (and possibly without a sample) in a given area by borrowing information from other neighboring regions.},
year = {2021}
}
TY - JOUR T1 - Poisson-Gamma and Spatial-Temporal Models: with Application to Cervical Cancer in Kenya’s Counties AU - Joseph Kuria Waitara AU - Gregory Kerich AU - John Kihoro AU - Anne Korir Y1 - 2021/06/26 PY - 2021 N1 - https://doi.org/10.11648/j.ajtas.20211003.14 DO - 10.11648/j.ajtas.20211003.14 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 - 158 EP - 166 PB - Science Publishing Group SN - 2326-9006 UR - https://doi.org/10.11648/j.ajtas.20211003.14 AB - In Africa, Cancer is an emerging health problem where in 2012 new cancer cases were about 847,00 and around 519,00 deaths, three quarters of those deaths occurred in sub-Saharan region. In 2018, cancer was ranked as the third leading cause of deaths in Kenya after infectious and cardiovascular diseases. In 2018 cancer incidences were estimated to be 47,887 new cancer cases and 32,987 deaths. According to data from World Health Organization in 2020, cervical cancer is the second most prevalent cancer among women while breast cancer is the first. In this study, data collected by the Nairobi Cancer Registry (NCR) was used to produce spatial-temporal distribution of the cervical cancer in counties in Kenya. The results showed that counties where data was available among them Embu, Meru, Machakos, Mombasa, Nyeri, Kiambu, Kakamega, Nairobi and Bomet respectively had high risk of cervical cancer. Availability of county-based estimates and spatial-temporal distribution of cervical cancer cases will aide development of targeted county strategies, enhance early detection, promote awareness and implementation of universal coverage of major control interventions which will be crucial in reducing and halting the rising burden of the cancer cases in Kenya. In counties where data was not available the model showed relative risks for cervical cancer disease was minute but it was present, therefore spatial temporal models are very appropriate to estimate relative risks of diseases even when there is a small sample (and possibly without a sample) in a given area by borrowing information from other neighboring regions. VL - 10 IS - 3 ER -
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