Fuzzy Logic Model to Forecast Environmental Related Health Diseases in Nigeria

Peter Adebayo Idowu; Olufemi Komolafe; Racheal Adefunke Oladejo

doi:doi:10.11648/j.ajmcm.20180301.14

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Fuzzy Logic Model to Forecast Environmental Related Health Diseases in Nigeria

Peter Adebayo Idowu, Olufemi Komolafe, Racheal Adefunke Oladejo

Published in American Journal of Mathematical and Computer Modelling (Volume 3, Issue 1)

Received: 13 February 2018 Accepted: 8 April 2018 Published: 10 May 2018

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Abstract

This paper identified the risk factors for environmental health related diseases and formulated a fuzzy logic based predictive model based on the identified variables. Related literatures were reviewed so as to understand the body of knowledge surrounding environmental health related diseases and their corresponding risk factors, interviews with community health officers were conducted in order to validate the identified variables. Fuzzy logic was used to formulate the predictive model using Matlab Fuzzy logic tool box. Data was collected from five different states in Nigeria. The result showed that there are cases of environmental related diseases in the areas where there is no potable water and in locations that lack good toilet facilities. In the areas where there is no toilet facility or where bucket and bush are used as toilet, there are always cases of cholera. In these areas during the rainy season cholera outbreaks are common occurrences. All these points to fact that, if there is a good environmental health tracking system with predictive features, then environmental health officers would be able to easily monitor, manage and track any area which may be prone to any of these environmental health diseases.

Published in	American Journal of Mathematical and Computer Modelling (Volume 3, Issue 1)
DOI	10.11648/j.ajmcm.20180301.14
Page(s)	27-37
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), 2018. Published by Science Publishing Group

Keywords

Environmental Health, Diseases, Forecast, Model, Fuzzy Logic

References

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[17]	Idowu P. A. (2012) A Spatial Data Model for HIV/AIDS Surveillance and Monitoring in Nigeria. International Journal of E-Health and Medical Communications. 3(2): 66-84.
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APA Style

Peter Adebayo Idowu, Olufemi Komolafe, Racheal Adefunke Oladejo. (2018). Fuzzy Logic Model to Forecast Environmental Related Health Diseases in Nigeria. American Journal of Mathematical and Computer Modelling, 3(1), 27-37. https://doi.org/10.11648/j.ajmcm.20180301.14

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ACS Style

Peter Adebayo Idowu; Olufemi Komolafe; Racheal Adefunke Oladejo. Fuzzy Logic Model to Forecast Environmental Related Health Diseases in Nigeria. Am. J. Math. Comput. Model. 2018, 3(1), 27-37. doi: 10.11648/j.ajmcm.20180301.14

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AMA Style

Peter Adebayo Idowu, Olufemi Komolafe, Racheal Adefunke Oladejo. Fuzzy Logic Model to Forecast Environmental Related Health Diseases in Nigeria. Am J Math Comput Model. 2018;3(1):27-37. doi: 10.11648/j.ajmcm.20180301.14

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@article{10.11648/j.ajmcm.20180301.14,
  author = {Peter Adebayo Idowu and Olufemi Komolafe and Racheal Adefunke Oladejo},
  title = {Fuzzy Logic Model to Forecast Environmental Related Health Diseases in Nigeria},
  journal = {American Journal of Mathematical and Computer Modelling},
  volume = {3},
  number = {1},
  pages = {27-37},
  doi = {10.11648/j.ajmcm.20180301.14},
  url = {https://doi.org/10.11648/j.ajmcm.20180301.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajmcm.20180301.14},
  abstract = {This paper identified the risk factors for environmental health related diseases and formulated a fuzzy logic based predictive model based on the identified variables. Related literatures were reviewed so as to understand the body of knowledge surrounding environmental health related diseases and their corresponding risk factors, interviews with community health officers were conducted in order to validate the identified variables. Fuzzy logic was used to formulate the predictive model using Matlab Fuzzy logic tool box. Data was collected from five different states in Nigeria. The result showed that there are cases of environmental related diseases in the areas where there is no potable water and in locations that lack good toilet facilities. In the areas where there is no toilet facility or where bucket and bush are used as toilet, there are always cases of cholera. In these areas during the rainy season cholera outbreaks are common occurrences. All these points to fact that, if there is a good environmental health tracking system with predictive features, then environmental health officers would be able to easily monitor, manage and track any area which may be prone to any of these environmental health diseases.},
 year = {2018}
}

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TY  - JOUR
T1  - Fuzzy Logic Model to Forecast Environmental Related Health Diseases in Nigeria
AU  - Peter Adebayo Idowu
AU  - Olufemi Komolafe
AU  - Racheal Adefunke Oladejo
Y1  - 2018/05/10
PY  - 2018
N1  - https://doi.org/10.11648/j.ajmcm.20180301.14
DO  - 10.11648/j.ajmcm.20180301.14
T2  - American Journal of Mathematical and Computer Modelling
JF  - American Journal of Mathematical and Computer Modelling
JO  - American Journal of Mathematical and Computer Modelling
SP  - 27
EP  - 37
PB  - Science Publishing Group
SN  - 2578-8280
UR  - https://doi.org/10.11648/j.ajmcm.20180301.14
AB  - This paper identified the risk factors for environmental health related diseases and formulated a fuzzy logic based predictive model based on the identified variables. Related literatures were reviewed so as to understand the body of knowledge surrounding environmental health related diseases and their corresponding risk factors, interviews with community health officers were conducted in order to validate the identified variables. Fuzzy logic was used to formulate the predictive model using Matlab Fuzzy logic tool box. Data was collected from five different states in Nigeria. The result showed that there are cases of environmental related diseases in the areas where there is no potable water and in locations that lack good toilet facilities. In the areas where there is no toilet facility or where bucket and bush are used as toilet, there are always cases of cholera. In these areas during the rainy season cholera outbreaks are common occurrences. All these points to fact that, if there is a good environmental health tracking system with predictive features, then environmental health officers would be able to easily monitor, manage and track any area which may be prone to any of these environmental health diseases.
VL  - 3
IS  - 1
ER  -

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Author Information

Peter Adebayo Idowu

Department of Computer Science and Engineering, Obafemi Awolowo University, Ile-Ife, Nigeria
Olufemi Komolafe

Engineering Materials Development Institute, Federal Ministry of Science & Technology, Akure, Nigeria
Racheal Adefunke Oladejo

Department of Computer Science, Ogun State Institute of Technology, Igbesa, Ogun State, Nigeria

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Plain Text BibTeX RIS

APA Style

Peter Adebayo Idowu, Olufemi Komolafe, Racheal Adefunke Oladejo. (2018). Fuzzy Logic Model to Forecast Environmental Related Health Diseases in Nigeria. American Journal of Mathematical and Computer Modelling, 3(1), 27-37. https://doi.org/10.11648/j.ajmcm.20180301.14

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ACS Style

Peter Adebayo Idowu; Olufemi Komolafe; Racheal Adefunke Oladejo. Fuzzy Logic Model to Forecast Environmental Related Health Diseases in Nigeria. Am. J. Math. Comput. Model. 2018, 3(1), 27-37. doi: 10.11648/j.ajmcm.20180301.14

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AMA Style

Peter Adebayo Idowu, Olufemi Komolafe, Racheal Adefunke Oladejo. Fuzzy Logic Model to Forecast Environmental Related Health Diseases in Nigeria. Am J Math Comput Model. 2018;3(1):27-37. doi: 10.11648/j.ajmcm.20180301.14

Copy | Download

@article{10.11648/j.ajmcm.20180301.14,
  author = {Peter Adebayo Idowu and Olufemi Komolafe and Racheal Adefunke Oladejo},
  title = {Fuzzy Logic Model to Forecast Environmental Related Health Diseases in Nigeria},
  journal = {American Journal of Mathematical and Computer Modelling},
  volume = {3},
  number = {1},
  pages = {27-37},
  doi = {10.11648/j.ajmcm.20180301.14},
  url = {https://doi.org/10.11648/j.ajmcm.20180301.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajmcm.20180301.14},
  abstract = {This paper identified the risk factors for environmental health related diseases and formulated a fuzzy logic based predictive model based on the identified variables. Related literatures were reviewed so as to understand the body of knowledge surrounding environmental health related diseases and their corresponding risk factors, interviews with community health officers were conducted in order to validate the identified variables. Fuzzy logic was used to formulate the predictive model using Matlab Fuzzy logic tool box. Data was collected from five different states in Nigeria. The result showed that there are cases of environmental related diseases in the areas where there is no potable water and in locations that lack good toilet facilities. In the areas where there is no toilet facility or where bucket and bush are used as toilet, there are always cases of cholera. In these areas during the rainy season cholera outbreaks are common occurrences. All these points to fact that, if there is a good environmental health tracking system with predictive features, then environmental health officers would be able to easily monitor, manage and track any area which may be prone to any of these environmental health diseases.},
 year = {2018}
}

Copy | Download

TY  - JOUR
T1  - Fuzzy Logic Model to Forecast Environmental Related Health Diseases in Nigeria
AU  - Peter Adebayo Idowu
AU  - Olufemi Komolafe
AU  - Racheal Adefunke Oladejo
Y1  - 2018/05/10
PY  - 2018
N1  - https://doi.org/10.11648/j.ajmcm.20180301.14
DO  - 10.11648/j.ajmcm.20180301.14
T2  - American Journal of Mathematical and Computer Modelling
JF  - American Journal of Mathematical and Computer Modelling
JO  - American Journal of Mathematical and Computer Modelling
SP  - 27
EP  - 37
PB  - Science Publishing Group
SN  - 2578-8280
UR  - https://doi.org/10.11648/j.ajmcm.20180301.14
AB  - This paper identified the risk factors for environmental health related diseases and formulated a fuzzy logic based predictive model based on the identified variables. Related literatures were reviewed so as to understand the body of knowledge surrounding environmental health related diseases and their corresponding risk factors, interviews with community health officers were conducted in order to validate the identified variables. Fuzzy logic was used to formulate the predictive model using Matlab Fuzzy logic tool box. Data was collected from five different states in Nigeria. The result showed that there are cases of environmental related diseases in the areas where there is no potable water and in locations that lack good toilet facilities. In the areas where there is no toilet facility or where bucket and bush are used as toilet, there are always cases of cholera. In these areas during the rainy season cholera outbreaks are common occurrences. All these points to fact that, if there is a good environmental health tracking system with predictive features, then environmental health officers would be able to easily monitor, manage and track any area which may be prone to any of these environmental health diseases.
VL  - 3
IS  - 1
ER  -

Copy | Download