Journal of the Korean Data and Information Science Society

한국데이터정보과학회 (The Korean Data and Information Science Society)
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실시간 에볼라 바이러스 전염병 모형의 전염확률분포추정

A transmission distribution estimation for real time Ebola virus disease epidemic model

  • Choi, Ilsu (Department of Statistics, Chonnam National University) ;
  • Rhee, Sung-Suk (Department of Business Administration, Seowon University)
  • 투고 : 2014.12.21
  • 심사 : 2015.01.10
  • 발행 : 2015.01.31
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초록

전염병은 기초 감염 재생산 수가 시간에 따라 달라져서 상황을 관리하기 어렵기 때문에 확산을 통제하기 어려울 뿐 아니라 정확한 예측은 더욱 어렵다고 알려져 있다. 최근에 많은 모형들이 새롭게 제시되고 있으며 그에 따라 현저하게 다른 결과가 도출되고 있다. 연속된 시간에서 기초 감염 재생산 수는 일반적으로 확률과정이론이 적용되고 있다. 본 논문에서는 에볼라 바이러스 전염병 모형에서 전염확률분포의 추정 방법을 제시하였다. 이 방법은 대규모 전염병 발생에서 실시간 추정을 가능하게 함으로 적절한 질병관리를 용이하게 한다. 기니에서 발생한 에볼라 바이러스 자료를 제시한 방법으로 분석하였다.

The epidemic is seemed to be extremely difficult for accurate predictions. The new models have been suggested that show quite different results. The basic reproductive number of epidemic for consequent time intervals are estimated based on stochastic processes. In this paper, we proposed a transmission distribution estimation for Ebola virus disease epidemic model. This estimation can be easier to obtain in real time which is useful for informing an appropriate public health response to the outbreak. Finally, we implement our proposed method with data from Guinea Ebola disease outbreak.

키워드

참고문헌

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  1. 베이지안 음이항 분기과정을 이용한 한국 메르스 발생 연구 vol.28, pp.1, 2015, https://doi.org/10.7465/jkdi.2017.28.1.153
  2. 절삭 혼합모형을 이용한 우리나라 삼일열 말라리아 장단기 잠복기 비율 추정 vol.29, pp.4, 2015, https://doi.org/10.7465/jkdi.2018.29.4.1025