MODELING TOWARDS PENTAVALENT VACCINE COVERAGE IN PAKISTAN

ABSTRACT OBJECTIVES: To expose the trend and proposing the forecasting model for monthly pentavalent infant immunization coverage a signiﬁcant concern in disease management and control. DESIGN: The reported data of monthly infant pentavalent immunization coverage to National institute of health, Isl...
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Autor*in:	Muhammad Imran [verfasserIn] Jamal Abdul Nasir [verfasserIn] Abid Ali Chohan [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2016

Schlagwörter:	Pakistan Pentavalent infant immunization time series

Übergeordnetes Werk:	In: Journal of University Medical & Dental College - University of Faisalabad, 2020, 7(2016), 1
Übergeordnetes Werk:	volume:7 ; year:2016 ; number:1

Links:	Link aufrufen Link aufrufen Journal toc Journal toc

Katalog-ID:	DOAJ058719296

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allfields	(DE-627)DOAJ058719296 (DE-599)DOAJe788c74674564db588f9c2e5f82f8ef4 DE-627 ger DE-627 rakwb eng Muhammad Imran verfasserin aut MODELING TOWARDS PENTAVALENT VACCINE COVERAGE IN PAKISTAN 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier ABSTRACT OBJECTIVES: To expose the trend and proposing the forecasting model for monthly pentavalent infant immunization coverage a signiﬁcant concern in disease management and control. DESIGN: The reported data of monthly infant pentavalent immunization coverage to National institute of health, Islamabad, Pakistan from January 2009 to October 2014 for the present study has been taken from Pakistan bureau of statistics with total time series entities 70. National institute of health, Islamabad took the record of per month number of doses administered (0-11 months) children by the registered health centre in Pakistan. PERIOD: January 2009 to October 2014. SETTING: Pakistan Bureau of Statistics (Statistics House) METHODS: Two time series techniques namely Box Jenkins and artiﬁcial neural network (ANN) has been carried out to develop a forecasting model. Results: ARIMA (1, 1, 1) model with RMSE (56998) and ANN 10-3-1 model with RMSE (34582) are selected after execution of various set of parameters of both techniques.Due to lower RMSE ANN 10-3-1 is an adequate model. The established ANN model revealed that the increment for infant pentavalent coverage is 4.14% expected in next six month. CONCLUSIONS: ANN 10-3-1 is an efﬁcient model for forecasting the monthly pentavalent infant immunization coverage in Pakistan. Pakistan Pentavalent infant immunization time series Medicine R Jamal Abdul Nasir verfasserin aut Abid Ali Chohan verfasserin aut In Journal of University Medical & Dental College University of Faisalabad, 2020 7(2016), 1 (DE-627)1694308081 23105542 nnns volume:7 year:2016 number:1 https://doaj.org/article/e788c74674564db588f9c2e5f82f8ef4 kostenfrei http://jumdc.com/index.php/jumdc/article/view/169 kostenfrei https://doaj.org/toc/2221-7827 Journal toc kostenfrei https://doaj.org/toc/2310-5542 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2016 1
spelling	(DE-627)DOAJ058719296 (DE-599)DOAJe788c74674564db588f9c2e5f82f8ef4 DE-627 ger DE-627 rakwb eng Muhammad Imran verfasserin aut MODELING TOWARDS PENTAVALENT VACCINE COVERAGE IN PAKISTAN 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier ABSTRACT OBJECTIVES: To expose the trend and proposing the forecasting model for monthly pentavalent infant immunization coverage a signiﬁcant concern in disease management and control. DESIGN: The reported data of monthly infant pentavalent immunization coverage to National institute of health, Islamabad, Pakistan from January 2009 to October 2014 for the present study has been taken from Pakistan bureau of statistics with total time series entities 70. National institute of health, Islamabad took the record of per month number of doses administered (0-11 months) children by the registered health centre in Pakistan. PERIOD: January 2009 to October 2014. SETTING: Pakistan Bureau of Statistics (Statistics House) METHODS: Two time series techniques namely Box Jenkins and artiﬁcial neural network (ANN) has been carried out to develop a forecasting model. Results: ARIMA (1, 1, 1) model with RMSE (56998) and ANN 10-3-1 model with RMSE (34582) are selected after execution of various set of parameters of both techniques.Due to lower RMSE ANN 10-3-1 is an adequate model. The established ANN model revealed that the increment for infant pentavalent coverage is 4.14% expected in next six month. CONCLUSIONS: ANN 10-3-1 is an efﬁcient model for forecasting the monthly pentavalent infant immunization coverage in Pakistan. Pakistan Pentavalent infant immunization time series Medicine R Jamal Abdul Nasir verfasserin aut Abid Ali Chohan verfasserin aut In Journal of University Medical & Dental College University of Faisalabad, 2020 7(2016), 1 (DE-627)1694308081 23105542 nnns volume:7 year:2016 number:1 https://doaj.org/article/e788c74674564db588f9c2e5f82f8ef4 kostenfrei http://jumdc.com/index.php/jumdc/article/view/169 kostenfrei https://doaj.org/toc/2221-7827 Journal toc kostenfrei https://doaj.org/toc/2310-5542 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2016 1
allfields_unstemmed	(DE-627)DOAJ058719296 (DE-599)DOAJe788c74674564db588f9c2e5f82f8ef4 DE-627 ger DE-627 rakwb eng Muhammad Imran verfasserin aut MODELING TOWARDS PENTAVALENT VACCINE COVERAGE IN PAKISTAN 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier ABSTRACT OBJECTIVES: To expose the trend and proposing the forecasting model for monthly pentavalent infant immunization coverage a signiﬁcant concern in disease management and control. DESIGN: The reported data of monthly infant pentavalent immunization coverage to National institute of health, Islamabad, Pakistan from January 2009 to October 2014 for the present study has been taken from Pakistan bureau of statistics with total time series entities 70. National institute of health, Islamabad took the record of per month number of doses administered (0-11 months) children by the registered health centre in Pakistan. PERIOD: January 2009 to October 2014. SETTING: Pakistan Bureau of Statistics (Statistics House) METHODS: Two time series techniques namely Box Jenkins and artiﬁcial neural network (ANN) has been carried out to develop a forecasting model. Results: ARIMA (1, 1, 1) model with RMSE (56998) and ANN 10-3-1 model with RMSE (34582) are selected after execution of various set of parameters of both techniques.Due to lower RMSE ANN 10-3-1 is an adequate model. The established ANN model revealed that the increment for infant pentavalent coverage is 4.14% expected in next six month. CONCLUSIONS: ANN 10-3-1 is an efﬁcient model for forecasting the monthly pentavalent infant immunization coverage in Pakistan. Pakistan Pentavalent infant immunization time series Medicine R Jamal Abdul Nasir verfasserin aut Abid Ali Chohan verfasserin aut In Journal of University Medical & Dental College University of Faisalabad, 2020 7(2016), 1 (DE-627)1694308081 23105542 nnns volume:7 year:2016 number:1 https://doaj.org/article/e788c74674564db588f9c2e5f82f8ef4 kostenfrei http://jumdc.com/index.php/jumdc/article/view/169 kostenfrei https://doaj.org/toc/2221-7827 Journal toc kostenfrei https://doaj.org/toc/2310-5542 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2016 1
allfieldsGer	(DE-627)DOAJ058719296 (DE-599)DOAJe788c74674564db588f9c2e5f82f8ef4 DE-627 ger DE-627 rakwb eng Muhammad Imran verfasserin aut MODELING TOWARDS PENTAVALENT VACCINE COVERAGE IN PAKISTAN 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier ABSTRACT OBJECTIVES: To expose the trend and proposing the forecasting model for monthly pentavalent infant immunization coverage a signiﬁcant concern in disease management and control. DESIGN: The reported data of monthly infant pentavalent immunization coverage to National institute of health, Islamabad, Pakistan from January 2009 to October 2014 for the present study has been taken from Pakistan bureau of statistics with total time series entities 70. National institute of health, Islamabad took the record of per month number of doses administered (0-11 months) children by the registered health centre in Pakistan. PERIOD: January 2009 to October 2014. SETTING: Pakistan Bureau of Statistics (Statistics House) METHODS: Two time series techniques namely Box Jenkins and artiﬁcial neural network (ANN) has been carried out to develop a forecasting model. Results: ARIMA (1, 1, 1) model with RMSE (56998) and ANN 10-3-1 model with RMSE (34582) are selected after execution of various set of parameters of both techniques.Due to lower RMSE ANN 10-3-1 is an adequate model. The established ANN model revealed that the increment for infant pentavalent coverage is 4.14% expected in next six month. CONCLUSIONS: ANN 10-3-1 is an efﬁcient model for forecasting the monthly pentavalent infant immunization coverage in Pakistan. Pakistan Pentavalent infant immunization time series Medicine R Jamal Abdul Nasir verfasserin aut Abid Ali Chohan verfasserin aut In Journal of University Medical & Dental College University of Faisalabad, 2020 7(2016), 1 (DE-627)1694308081 23105542 nnns volume:7 year:2016 number:1 https://doaj.org/article/e788c74674564db588f9c2e5f82f8ef4 kostenfrei http://jumdc.com/index.php/jumdc/article/view/169 kostenfrei https://doaj.org/toc/2221-7827 Journal toc kostenfrei https://doaj.org/toc/2310-5542 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2016 1
allfieldsSound	(DE-627)DOAJ058719296 (DE-599)DOAJe788c74674564db588f9c2e5f82f8ef4 DE-627 ger DE-627 rakwb eng Muhammad Imran verfasserin aut MODELING TOWARDS PENTAVALENT VACCINE COVERAGE IN PAKISTAN 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier ABSTRACT OBJECTIVES: To expose the trend and proposing the forecasting model for monthly pentavalent infant immunization coverage a signiﬁcant concern in disease management and control. DESIGN: The reported data of monthly infant pentavalent immunization coverage to National institute of health, Islamabad, Pakistan from January 2009 to October 2014 for the present study has been taken from Pakistan bureau of statistics with total time series entities 70. National institute of health, Islamabad took the record of per month number of doses administered (0-11 months) children by the registered health centre in Pakistan. PERIOD: January 2009 to October 2014. SETTING: Pakistan Bureau of Statistics (Statistics House) METHODS: Two time series techniques namely Box Jenkins and artiﬁcial neural network (ANN) has been carried out to develop a forecasting model. Results: ARIMA (1, 1, 1) model with RMSE (56998) and ANN 10-3-1 model with RMSE (34582) are selected after execution of various set of parameters of both techniques.Due to lower RMSE ANN 10-3-1 is an adequate model. The established ANN model revealed that the increment for infant pentavalent coverage is 4.14% expected in next six month. CONCLUSIONS: ANN 10-3-1 is an efﬁcient model for forecasting the monthly pentavalent infant immunization coverage in Pakistan. Pakistan Pentavalent infant immunization time series Medicine R Jamal Abdul Nasir verfasserin aut Abid Ali Chohan verfasserin aut In Journal of University Medical & Dental College University of Faisalabad, 2020 7(2016), 1 (DE-627)1694308081 23105542 nnns volume:7 year:2016 number:1 https://doaj.org/article/e788c74674564db588f9c2e5f82f8ef4 kostenfrei http://jumdc.com/index.php/jumdc/article/view/169 kostenfrei https://doaj.org/toc/2221-7827 Journal toc kostenfrei https://doaj.org/toc/2310-5542 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2016 1
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DESIGN: The reported data of monthly infant pentavalent immunization coverage to National institute of health, Islamabad, Pakistan from January 2009 to October 2014 for the present study has been taken from Pakistan bureau of statistics with total time series entities 70. National institute of health, Islamabad took the record of per month number of doses administered (0-11 months) children by the registered health centre in Pakistan. PERIOD: January 2009 to October 2014. SETTING: Pakistan Bureau of Statistics (Statistics House) METHODS: Two time series techniques namely Box Jenkins and artiﬁcial neural network (ANN) has been carried out to develop a forecasting model. Results: ARIMA (1, 1, 1) model with RMSE (56998) and ANN 10-3-1 model with RMSE (34582) are selected after execution of various set of parameters of both techniques.Due to lower RMSE ANN 10-3-1 is an adequate model. The established ANN model revealed that the increment for infant pentavalent coverage is 4.14% expected in next six month. 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author	Muhammad Imran
spellingShingle	Muhammad Imran misc Pakistan misc Pentavalent infant immunization misc time series misc Medicine misc R MODELING TOWARDS PENTAVALENT VACCINE COVERAGE IN PAKISTAN
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topic_title	MODELING TOWARDS PENTAVALENT VACCINE COVERAGE IN PAKISTAN Pakistan Pentavalent infant immunization time series
topic	misc Pakistan misc Pentavalent infant immunization misc time series misc Medicine misc R
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title	MODELING TOWARDS PENTAVALENT VACCINE COVERAGE IN PAKISTAN
ctrlnum	(DE-627)DOAJ058719296 (DE-599)DOAJe788c74674564db588f9c2e5f82f8ef4
title_full	MODELING TOWARDS PENTAVALENT VACCINE COVERAGE IN PAKISTAN
author_sort	Muhammad Imran
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title_sort	modeling towards pentavalent vaccine coverage in pakistan
title_auth	MODELING TOWARDS PENTAVALENT VACCINE COVERAGE IN PAKISTAN
abstract	ABSTRACT OBJECTIVES: To expose the trend and proposing the forecasting model for monthly pentavalent infant immunization coverage a signiﬁcant concern in disease management and control. DESIGN: The reported data of monthly infant pentavalent immunization coverage to National institute of health, Islamabad, Pakistan from January 2009 to October 2014 for the present study has been taken from Pakistan bureau of statistics with total time series entities 70. National institute of health, Islamabad took the record of per month number of doses administered (0-11 months) children by the registered health centre in Pakistan. PERIOD: January 2009 to October 2014. SETTING: Pakistan Bureau of Statistics (Statistics House) METHODS: Two time series techniques namely Box Jenkins and artiﬁcial neural network (ANN) has been carried out to develop a forecasting model. Results: ARIMA (1, 1, 1) model with RMSE (56998) and ANN 10-3-1 model with RMSE (34582) are selected after execution of various set of parameters of both techniques.Due to lower RMSE ANN 10-3-1 is an adequate model. The established ANN model revealed that the increment for infant pentavalent coverage is 4.14% expected in next six month. CONCLUSIONS: ANN 10-3-1 is an efﬁcient model for forecasting the monthly pentavalent infant immunization coverage in Pakistan.
abstractGer	ABSTRACT OBJECTIVES: To expose the trend and proposing the forecasting model for monthly pentavalent infant immunization coverage a signiﬁcant concern in disease management and control. DESIGN: The reported data of monthly infant pentavalent immunization coverage to National institute of health, Islamabad, Pakistan from January 2009 to October 2014 for the present study has been taken from Pakistan bureau of statistics with total time series entities 70. National institute of health, Islamabad took the record of per month number of doses administered (0-11 months) children by the registered health centre in Pakistan. PERIOD: January 2009 to October 2014. SETTING: Pakistan Bureau of Statistics (Statistics House) METHODS: Two time series techniques namely Box Jenkins and artiﬁcial neural network (ANN) has been carried out to develop a forecasting model. Results: ARIMA (1, 1, 1) model with RMSE (56998) and ANN 10-3-1 model with RMSE (34582) are selected after execution of various set of parameters of both techniques.Due to lower RMSE ANN 10-3-1 is an adequate model. The established ANN model revealed that the increment for infant pentavalent coverage is 4.14% expected in next six month. CONCLUSIONS: ANN 10-3-1 is an efﬁcient model for forecasting the monthly pentavalent infant immunization coverage in Pakistan.
abstract_unstemmed	ABSTRACT OBJECTIVES: To expose the trend and proposing the forecasting model for monthly pentavalent infant immunization coverage a signiﬁcant concern in disease management and control. DESIGN: The reported data of monthly infant pentavalent immunization coverage to National institute of health, Islamabad, Pakistan from January 2009 to October 2014 for the present study has been taken from Pakistan bureau of statistics with total time series entities 70. National institute of health, Islamabad took the record of per month number of doses administered (0-11 months) children by the registered health centre in Pakistan. PERIOD: January 2009 to October 2014. SETTING: Pakistan Bureau of Statistics (Statistics House) METHODS: Two time series techniques namely Box Jenkins and artiﬁcial neural network (ANN) has been carried out to develop a forecasting model. Results: ARIMA (1, 1, 1) model with RMSE (56998) and ANN 10-3-1 model with RMSE (34582) are selected after execution of various set of parameters of both techniques.Due to lower RMSE ANN 10-3-1 is an adequate model. The established ANN model revealed that the increment for infant pentavalent coverage is 4.14% expected in next six month. CONCLUSIONS: ANN 10-3-1 is an efﬁcient model for forecasting the monthly pentavalent infant immunization coverage in Pakistan.
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title_short	MODELING TOWARDS PENTAVALENT VACCINE COVERAGE IN PAKISTAN
url	https://doaj.org/article/e788c74674564db588f9c2e5f82f8ef4 http://jumdc.com/index.php/jumdc/article/view/169 https://doaj.org/toc/2221-7827 https://doaj.org/toc/2310-5542
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