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Forecasting the Monthly Reported Cases of Human Immunodeficiency Virus (HIV) at Minna Niger State, Nigeria

Forecasting the Monthly Reported Cases of Human Immunodeficiency Virus (HIV) at Minna Niger State, Nigeria
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摘要 There has been a moderate increase in newly diagnosed HIV-infected Minna populace, which calls for serious attention.<span style="font-family:;" "=""> </span><span style="font-family:Verdana;">This study</span><span style="font-family:;" "=""> </span><span style="font-family:Verdana;">used time series data based on monthly HIV cases from January 2007 to December 2018 taken from the statistical data document on HIV prevalence recorded in General Hospital Minna, Niger State.</span><span style="font-family:;" "=""> </span><span style="font-family:Verdana;">The methodology employed to analyze the data is base</span><span style="font-family:Verdana;">d</span><span style="font-family:;" "=""><span style="font-family:Verdana;"> on mathematical models of ARMA, ARIMA and SARIMA which were computed and diagnosed. From the results of parameter estimation of </span><span style="font-family:Verdana;">the models, ARMA(2, 1) model was the best model among the other ARMA models using information criteria (AIC). Diagnostic test was run on the ARMA(2, 1) model where the results show that the model was adequate and normally distributed using Box-Lung test and Q</span></span><span style="font-family:Verdana;">-</span><span style="font-family:Verdana;">Q plot respectively. Fur</span><span style="font-family:Verdana;">thermore, ARIMA of first and second differences w</span><span style="font-family:Verdana;">as</span><span style="font-family:Verdana;"> estimated and ARIMA(1,</span><span style="font-family:;" "=""> </span><span style="font-family:Verdana;">0,</span><span style="font-family:;" "=""> </span><span style="font-family:Verdana;">1) was the best model from the result of the AIC and diagnostic test carried out which revealed that the model was adequate and normally distributed using Box-Lung and Q-Q plot respectively. Furthermore, the results obtained in the ARMA and ARIMA models were used to arrive at a combined model given as ARIMA(1, 0, 1) </span><span style="font-family:;" "=""><span style="font-family:Verdana;">×</span><span><span style="font-family:Verdana;"> SARIMA(1, 0, 1)</span><sub><span style="font-family:Verdana;">12</span></sub></span></span><span style="font-family:;" "=""> </span><span style="font-family:Verdana;">which was subsequently estimated and found to be adequate from the result of the Box-Lung and Q-Q plot respectively. Post forecasting estimation and performance evolution were evaluated using the RMSE and MAE. The results showed that, ARIMA(1, 0, 1) </span><span style="font-family:;" "=""><span style="font-family:Verdana;">×</span><span><span style="font-family:Verdana;"> SARIMA(1, 0, 1)</span><sub><span style="font-family:Verdana;">12</span></sub><span style="font-family:Verdana;"> is the best forecasting model followed by ARIMA(1, 0, 2) on monthly HIV prevalence in Minna, Niger state.</span></span></span> There has been a moderate increase in newly diagnosed HIV-infected Minna populace, which calls for serious attention.<span style="font-family:;" "=""> </span><span style="font-family:Verdana;">This study</span><span style="font-family:;" "=""> </span><span style="font-family:Verdana;">used time series data based on monthly HIV cases from January 2007 to December 2018 taken from the statistical data document on HIV prevalence recorded in General Hospital Minna, Niger State.</span><span style="font-family:;" "=""> </span><span style="font-family:Verdana;">The methodology employed to analyze the data is base</span><span style="font-family:Verdana;">d</span><span style="font-family:;" "=""><span style="font-family:Verdana;"> on mathematical models of ARMA, ARIMA and SARIMA which were computed and diagnosed. From the results of parameter estimation of </span><span style="font-family:Verdana;">the models, ARMA(2, 1) model was the best model among the other ARMA models using information criteria (AIC). Diagnostic test was run on the ARMA(2, 1) model where the results show that the model was adequate and normally distributed using Box-Lung test and Q</span></span><span style="font-family:Verdana;">-</span><span style="font-family:Verdana;">Q plot respectively. Fur</span><span style="font-family:Verdana;">thermore, ARIMA of first and second differences w</span><span style="font-family:Verdana;">as</span><span style="font-family:Verdana;"> estimated and ARIMA(1,</span><span style="font-family:;" "=""> </span><span style="font-family:Verdana;">0,</span><span style="font-family:;" "=""> </span><span style="font-family:Verdana;">1) was the best model from the result of the AIC and diagnostic test carried out which revealed that the model was adequate and normally distributed using Box-Lung and Q-Q plot respectively. Furthermore, the results obtained in the ARMA and ARIMA models were used to arrive at a combined model given as ARIMA(1, 0, 1) </span><span style="font-family:;" "=""><span style="font-family:Verdana;">×</span><span><span style="font-family:Verdana;"> SARIMA(1, 0, 1)</span><sub><span style="font-family:Verdana;">12</span></sub></span></span><span style="font-family:;" "=""> </span><span style="font-family:Verdana;">which was subsequently estimated and found to be adequate from the result of the Box-Lung and Q-Q plot respectively. Post forecasting estimation and performance evolution were evaluated using the RMSE and MAE. The results showed that, ARIMA(1, 0, 1) </span><span style="font-family:;" "=""><span style="font-family:Verdana;">×</span><span><span style="font-family:Verdana;"> SARIMA(1, 0, 1)</span><sub><span style="font-family:Verdana;">12</span></sub><span style="font-family:Verdana;"> is the best forecasting model followed by ARIMA(1, 0, 2) on monthly HIV prevalence in Minna, Niger state.</span></span></span>
作者 Nwanne Christiana Umunna Samuel Olayemi Olanrewaju Nwanne Christiana Umunna;Samuel Olayemi Olanrewaju(Department of Statistics, University of Abuja, Abuja, Nigeria)
出处 《Open Journal of Statistics》 2020年第3期494-515,共22页 统计学期刊(英文)
关键词 Human Immunodeficiency Virus Autoregressive Moving Average Autoregressive Integrated Moving Average Seasonal Autoregressive Integrated Moving Average Forecasting Human Immunodeficiency Virus Autoregressive Moving Average Autoregressive Integrated Moving Average Seasonal Autoregressive Integrated Moving Average Forecasting
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  • 1王黎霞,施鸿生.我国结核病流行病学模型及疫情态势浅析[J].结核病与胸部肿瘤,1994(1):5-8. 被引量:3
  • 2Geoge E,Box P.时间序列分析:预测与控制.北京:中国统计出版社,1997。.
  • 3SAS公司.SAS/ETS软件使用手册.北京:中国统计出版社,1998.
  • 4Dye C, Fengzeng Z, Scheele S, et al. Evaluating the impact of tuberculosis control: number of deaths prevented by short-course chemotherapy in China. Int J Epidemiol,2000,29:558-564.
  • 5Shimao T. Tuberculosis and its control-lessons from the past and future prospect. Kekkaku, 2005,80:481-489.
  • 6Porter JD, McAdam KP. The re-emergence of tuberculosis. Annu Rev Public Health, 1994,15:303-323.
  • 7Nishiura H,Patanarapelert K, Tang IM. Predicting the future trend of drug-resistant tuberculosis in Thailand: assessing the impact of control strategies. Southeast Asian J Trop Med Public Health,2004,35:649-656.
  • 8Rios M, Garcia JM, Sanchez JA, et al. A statistical analysis of the seasonality in pulmonary tuberculosis. Eur J Epidemiol, 2000,16 :483-488.
  • 9West RW, Thompson JR. Modeling the impact of HIV on the spread of tuberculosis in the United States. Math Biosci, 1997,143:35-60.
  • 10Loytonen M, Maasilta P. Multi-drug resistant tuberculosis in Finland-a forecast. Soe Sci Med, 1998,46:695-702.

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