Volume 4(6); December

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Osong Public Health Res Perspect > Volume 4(6); 2013
Cho and Chu: What is Next for HIV/AIDS in Korea?
According to the United Nations Programme on human immunodeficiency virus (HIV)/AIDS (UNAIDS), the estimated number of people living with HIV/AIDS (PLWHA) worldwide is 35.3 million as of 2012 [1]. Since the first diagnosis of HIV infection in 1985 to 2012, a total of 9410 PLWHA cases have been diagnosed in Korea, which is relatively low compared to the global standard [2]. However, the number of the HIV-infected people has increased sharply in Korea since 2000 [2].
In Korea, various studies have been conducted on HIV/AIDS. The Korea National Institute of Health regularly conducts laboratory-based research on HIV patients receiving highly active antiretroviral therapy [3]. Since the establishment of the Korean HIV/AIDS Cohort in 2006, various papers on the incidence and seroprevalence of HIV/AIDS in Korea have been published [4,5]. Social science approaches deal with the status of PLWHA under a social context in various social settings [6–8].
Since 1985, Korea has been active in developing HIV/AIDS prevention policies and expanding the target/risk groups for HIV testing. However, since 1998, there has been a reduction in the number of tests carried out due to a change in the national policy from mandatory to voluntary HIV testing, with more emphasis on supporting the cost of treatment for HIV-infected persons and on prevention education. These are the initiatives taken by the Korean government to prevent and treat HIV/AIDS. In addition, it is necessary to estimate the future incidence of HIV/AIDS in Korea to secure the budget for the HIV/AIDS prevention policy.
In the current issue of the Osong Public Health and Research Perspectives, one paper presents the estimation and projection of HIV/AIDS incidence in Korea [9]. The authors have adopted an autoregressive integrated moving average (ARIMA) model. The ARIMA model has previously been used for the estimation of influenza mortality [10], malaria incidence [11], and the incidence of other infectious diseases [12–14].
However, the back calculation, EPI-info, and EPP models cannot be applied to estimate the number of HIV-infected Koreans because of limitations such as a lack of exact statistics on AIDS cases and the unavailability of specific information on commercial sex workers, intravenous drug users, and sexually transmitted infection risk groups. However, the time series method can utilize the autocorrelation functions and produce an estimation model based on the data of HIV cases identified yearly or monthly [9].
This study aims to construct an estimation model using data on HIV cases diagnosed in Korea on a yearly basis since 1985, and forecast the number of HIV-infected persons and changes in the epidemiological characteristics of the infection.
In this study, one interesting trend has been observed with respect to the gender ratio for HIV/AIDS infection in Korea. As the number of HIV-infected persons increases, the current gender ratio (HIV-infected men: HIV-infected women, 11:1) also increases. This ratio for newly diagnosed HIV infection is projected to be 20:1 in 2017, suggesting an increase in the current male dominance in the ratio. Another interesting point is that by 2012, the majority of the HIV-infected persons will be in their 30s (28%); however, at present, the rate of HIV infection is increasing in persons who are in their 20s. Thus, as the results of this study suggest, we can expect a sharp increase in the number of HIV-infected people who are in their 20s in the upcoming 5 years. Hence, people in their 20s form the target group for HIV prevention in Korea. In a previous study on HIV prevalence and herpes simplex virus type 2 seroprevalence, the Koreans in their 20s have been found to have a low rate of infection for both these sexually transmitted diseases [15,16]; however, it is necessary to monitor this age group more carefully, keeping in mind the current trend change.
Despite many studies on HIV/AIDS in Korea, we would still like to see a viral dynamic study on HIV/AIDS, estimating the incidence of the infection using a robust mathematical model. This may provide another interesting perspective on the gender ratio for HIV/AIDS in Korea.

Notes

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

References

1. UNAIDS . UNAIDS report on the global AIDS epidemic 2013. 2013. UNAIDS; Geneva:

2. Korea Center for Disease Control and Prevention. The surveillance reports for HIV/AIDS in Korea 2011. 2013. KCDC; Osong:

3. Kwon O.-K., Choi J.-Y., Kim E.-J., Kim S.S.. Infectivity of homologous recombinant HIV-1 pseudo-virus with reverse transcriptase inhibitor-related mutations from highly active antiretroviral therapy experienced patients. Osong Public Health Res Perspect 2(1):2011 Jun;23−28.
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4. Kee M.K., Lee J.H., Wang J., Kim S.S.. Ten-year trends in HIV prevalence among visitors to public health centers under the National HIV Surveillance System in Korea, 2000 to 2009. BMC Public Health 12:2012 Sep;831.
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5. Kee M.-Y., Hwang D.Y., Lee J.K.. Estimation of HIV seroprevalence in colorectal hospitals by questionnaire survey in Korea, 2002–2007. Osong Public Health Res Perspect 2(2):2011 Sep;104−108.
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7. Sohn A., Park S.. Changes in human immunodeficiency virus-related knowledge and stigmatizing attitudes among Korean adolescents from 2006 to 2011. Osong Public Health Res Perspect 3(2):2012 Mar;107−112.
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8. Sohn A., Cho B.. Knowledge, attitudes and sexual behaviors in HIV/AIDS and predictors affecting condom use among men who have sex with men in South Korea. Osong Public Health Res Perspect 3(3):2012 Jun;156−164.
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9. Yu H.-K., Kim N.-Y., Kim S.S.. Forecasting the number of HIV infection in Korean population using ARIMA model. Osong Public Health Res Perspect 4(6):2013 Dec;358−362.
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10. Reichert T.A., Simonsen L., Sharma A.. Influenza and the winter increase in mortality in the United States, 1959–1999. Am J Epidemiol 160(5):2004 Sep;492−502.
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11. Gaudart J., Toure O., Dessay N.. Modelling malaria incidence with environmental dependency in a locality of Sudanese savannah area, Mali. Malaria J 8:2009 Apr;61.
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12. Luz P.M., Mendes B.V., Codeco C.T.. Time series analysis of dengue incidence in Rio de Janeiro, Brazil. Am J Trop Med Hyg 79(6):2008 Dec;933−939.
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13. Yi J., Du C.T., Wang R.H., Liu L.. Applications of multiple seasonal autoregressive integrated moving average (ARIMA) model on predictive incidence of tuberculosis. Chin J Prev Med 41(2):2007;118−121.

14. Liu Q., Liu X., Jiang B., Yang W.. Forecasting incidence of hemorrhagic fever with renal syndrome in China using ARIMA model. BMC Infect Dis 11:2011 Aug;218.
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15. Kee M.K., Lee J.H., Chu C.. Characteristics of HIV seroprevalence of visitors to public health centers under the national HIV surveillance system in Korea: cross sectional study. BMC Public Health 9:2009 May;123.
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16. Shin H.S., Park J.J., Chu C.. Herpes simplex virus type 2 seroprevalence in Korea: rapid increase of HSV-2 seroprevalence in the 30s in the southern part. J Korean Med Sci. 22(6):2007 Dec;957−962.
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