The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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Estimating Infection Distribution and Prevalence of Malaria in South Korea Using a Back-calculation Formula

후향연산식을 활용한 국내 삼일열 말라리아의 감염분포와 유병자수 추정

  • Jang, Hyun-Gap (Dept. of Education and Training, Korea Cancer Center Hospital) ;
  • Park, Jeong-Soo (Dept. of Statistics, Chonnam National University) ;
  • Jun, Mi-Jeong (Korea Red Cross, Gwangju-Chonnam Blood-Bank) ;
  • Rhee, Jeong-Ae (Dept. of Preventive Medicine, Chonnam National University) ;
  • Kim, Han-Me-Ury (Dept. of Statistics, Chonnam National University)
  • Published : 2008.12.31
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Abstract

Incidence of Plasmodium vivax malaria in South Korea have been reemerged from mid-1990 and infected around 1600 patients annually recent years. The authors calculated the distribution of malaria infection and prevalence in South Korea using incidence (2001-2006) and incubation period distributions by a back-calculation formula and the least squares estimation method. The estimated infection has a normal distribution with a mean 207 and a standard deviation 30.7 days. In addition, the authors found the estimated daily average prevalence is 628.8 patients.

국내 삼일열 말라리아는 1990년대 중반부터 급격히 증가하여 2000년대에는 연평균 1600여명이 발병하고 있다. 본 연구에서는 이미 알려진 잠복기 분포와 2001년부터 2006년까지의 발병자수 자료에 바탕하여 후향연산식을 활용하여 국내 삼일열 말라리아의 감염분포를 최소제곱법으로 추정하였다. 추정된 감염분포는 평균이 207일이고 표준편차가 30.7일인 정규분포를 이루었다. 이를 이용하여 연간 유병자수 분포를 산출한 결과, 말라리아의 하루 평균 유병자수는 628.8명 이었다.

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References

  1. 이정희, 이영생, 박정수 (2008). 국내 신증후군 출혈열의 감염자 분포와 유병자수 추정, Journal of the Korean Data Analysis Society, 10, 1915-1922
  2. 이주영, 황진수, 고운영, 기미경, 김지연 (2002). 후향연산 모형 (Back-calculation model)을 이용한 국내 HIV 감염자와 AIDS 환자의 추계, <예방의학회지>, 35, 65-71
  3. 장현갑 (2008). 감염확률밀도함수를 이용한 말라리아 유병률 추정, <전남대학교 대학원 보건학 협동과정 석사학위 논문>. 광주
  4. 질병관리본부, 홈페이지: http://stat.cdc.go.kr
  5. Bacchetti, P., Segal, M. R. and Jewell, N. P. (1993). Backcalculation of HIV infection rate, Statistical Science, 8, 82-119 https://doi.org/10.1214/ss/1177010994
  6. Becker, N. G., Watson, L. F. and Carlin, J. B. (1991). A method of non-parametric back-projection and its application to AIDS data, Statistics in Medicine, 10, 1527-1542 https://doi.org/10.1002/sim.4780101005
  7. Brookmeyer, R. (1991). Reconstruction and future trends of the AIDS epidemic in the United States, Science, 253, 37-42 https://doi.org/10.1126/science.2063206
  8. Brookmeyer, R. and Gail, M. H. (1986). Minimum size of the acquired immunodeficiency syndrome (AIDS) epidemic in the United States, Lancet, 2, 1320-1322
  9. Brookmeyer, R. and Gail, M. H. (1988). A method for obtaining short-term projections and lower bounds on the size of the AIDS epidemic, Journal of the American Statistical Association, 83, 301-308 https://doi.org/10.2307/2288844
  10. Brookmeyer, R. and Liao, J. (1992). Statistical methods for reconstructing infection curves, AIDS Epidemi- ology: Methodologic Issues, Jewell N., Dietz K., Farewell V.(eds), 36-60, Birkhauser, Boston
  11. Day, N. E., Gore, S. M., McGee, M. A. and South, M. (1989). Predictions of the AIDS epidemic in the U.K.: The use of the back projection method, Philosophical Transactions of the Royal Society of London, Series B, Biological Sciences, 325, 123-134 https://doi.org/10.1098/rstb.1989.0077
  12. De Angelis, D., Hickman, M. and Yang, S. (2004). Estimating long-term trends in the incidence and preva- lence of opiate use/injecting drug use and the number of former users: Back-calculation methods and opiate overdose deaths, American Journal of Epidemiology, 160, 994-1004 https://doi.org/10.1093/aje/kwh306
  13. Jang, H. G., Lee, J. A. and Park, J. S. (2008). Estimating infection distribution and prevalence with para- sitemia of Plasmodium vivax malaria using incidence and incubation period, Technical report, Depart- ment of Statistics, Chonnam National University, Gwangju
  14. Kim, M. B. (2001). Epidemiologic characteristics of malaria in non-malarious area, Jeollabuk-do, Korea in 2000, The Korean Journal of Parasitology, 39, 223-226 https://doi.org/10.3347/kjp.2001.39.3.223
  15. Lee, J. S., Lee, W. J., Cho, S. H., and Ree, H. I. (2002). Outbreak of vivax malaria in areas adjacent to the demilitarized zone, South Korea, 1998, The American Journal of Tropical Medicine and Hygiene, 66, 13-17 https://doi.org/10.4269/ajtmh.2002.66.13
  16. Nishiura, H., Lee, H. W., Cho, S. H., Lee, W. G., In, T. S., Moon, S. U., Gyung, T. C. and Kim, T. S. (2007). Estimates of short- and long-term incubation periods of Plasmodium vivax malaria in the Republic of Korea, Transactions of the Royal Society of Tropical Medicine and Hygiene, 101, 338-343 https://doi.org/10.1016/j.trstmh.2006.11.002
  17. O'Sullivan, F. A. (1986). A statistical perspective on ill-posed inverse problems, Statistical Science, 1, 502-527 https://doi.org/10.1214/ss/1177013525
  18. Park, J. W., Klein, T. A., Lee, H. C., Pach, L. A., Ryu, S. H., Yeom, J.S., Moon, S. H., Kim, T. S., Chal, J. Y. Oh, M. D. and Choe, K. W. (2003). Vivax malaria: A continuing health threat to the Republic of Korea, The American Journal of Tropical Medicine and Hygiene, 69, 159-167
  19. WHO (2005). World Malaria Report