TY - JOUR
T1 - Forecasting future HIV infection cases
T2 - evidence from Indonesia
AU - Kurniasari, Maria Dyah
AU - Huruta, Andrian Dolfriandra
AU - Tsai, Hsiu Ting
AU - Lee, Cheng Wen
N1 - Publisher Copyright:
© 2020 Taylor & Francis Group, LLC.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2021
Y1 - 2021
N2 - Countries throughout the world, including Indonesia, are facing a complex problem with regards to HIV infection incidences and its prevalence. This is despite some local governments in some provinces of Indonesia working together with the Social Ministry of Indonesia to eradicate prostitution. There are high numbers of HIV sub-types in Indonesia such as HIV-1 (CRF01_AE and B). The forecast was conducted with the Autoregressive Integrated Moving Average model. The ARMA (1,1) was observed to be the best model for forecasting the number of HIV patients in Indonesia. This forecasting has been done since March 2019. Based on its dynamic forecasting with ARMA (1,1), this study proved the number of HIV-positive patients, from 2019 to 2030, had increased from 22,679 to 36,255, by almost 37% within 12 years. Indonesia is facing a growing trend in the number of new HIV cases, until 2030 which caused by stopped their follow-up treatments or they have ceased in consuming the Antiretroviral drugs even though the Indonesian government was provided national health insurance which covers the Antiretroviral drug and a limited number of health-care services providing the Antiretroviral therapy. Therefore, investigations focusing on estimate the number of HIV patients in Indonesia is an important finding. The information can be used as a resource for policy and decision making for plans and programs.
AB - Countries throughout the world, including Indonesia, are facing a complex problem with regards to HIV infection incidences and its prevalence. This is despite some local governments in some provinces of Indonesia working together with the Social Ministry of Indonesia to eradicate prostitution. There are high numbers of HIV sub-types in Indonesia such as HIV-1 (CRF01_AE and B). The forecast was conducted with the Autoregressive Integrated Moving Average model. The ARMA (1,1) was observed to be the best model for forecasting the number of HIV patients in Indonesia. This forecasting has been done since March 2019. Based on its dynamic forecasting with ARMA (1,1), this study proved the number of HIV-positive patients, from 2019 to 2030, had increased from 22,679 to 36,255, by almost 37% within 12 years. Indonesia is facing a growing trend in the number of new HIV cases, until 2030 which caused by stopped their follow-up treatments or they have ceased in consuming the Antiretroviral drugs even though the Indonesian government was provided national health insurance which covers the Antiretroviral drug and a limited number of health-care services providing the Antiretroviral therapy. Therefore, investigations focusing on estimate the number of HIV patients in Indonesia is an important finding. The information can be used as a resource for policy and decision making for plans and programs.
KW - antiretroviral
KW - autoregressive Integrated Moving Average
KW - forecasting
KW - Human Immunodeficiency Virus
KW - indonesia
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U2 - 10.1080/19371918.2020.1851332
DO - 10.1080/19371918.2020.1851332
M3 - Article
AN - SCOPUS:85097126925
SN - 1937-1918
VL - 36
SP - 12
EP - 25
JO - Social Work in Public Health
JF - Social Work in Public Health
IS - 1
ER -