Parameter estimation of tuberculosis transmission model using Ensemble Kalman filter across Indian states and union territories

被引：11
|
作者：
Narula, Pankaj [1 ]
Piratla, Vihari [2 ]
Bansal, Ankit [3 ]
Azad, Sarita [1 ]
Lio, Pietro [4 ]
机构：
[1] Indian Inst Technol Mandi, Sch Basic Bas Sci, Mandi 175001, Himachal Prades, India
[2] Indian Inst Technol Mandi, Sch Comp & Elect Engn, Mandi 175001, Himachal Prades, India
[3] Indian Inst Technol Roorkee, Dept Mech & Ind Engn, Roorkee 247667, Uttarakhand, India
[4] Univ Cambridge, Comp Lab, William Gates Bldg,15 JJ Thomson Ave, Cambridge CB3 0FD, England
来源：
INFECTION DISEASE & HEALTH | 2016年 / 21卷 / 04期
关键词：
Tuberculosis; India; Infection;
D O I：
10.1016/j.idh.2016.11.001
中图分类号：
R1 [预防医学、卫生学];
学科分类号：
1004 ; 120402 ;
摘要：
Background: Tuberculosis (TB) is one of the main causes of mortality on the globe. Besides the full implementation of Revised National Tuberculosis Control Programme (RNTCP), TB continues to be a major public health problem in India. Methods: In the present study, parameters of a TB model are estimated using Ensemble Kalman filter (EnKf) approach. Infection rate and fraction of smear positive cases of TB are estimated in context of India. Results and Conclusions: Results reveal that the infection rate is highest in Manipur and the ratio of smear positive cases is highest in Pondicherry. The infection rate of TB in Manipur is found to be 2.57 per quarter for the period 2006-2011. (C) 2016 Australasian College for Infection Prevention and Control. Published by Elsevier B.V. All rights reserved.
引用
收藏
页码：184 / 191
页数：8
相关论文
共 50 条
  • [21] Combined state and parameter estimation for a landslide model using Kalman filter
    Mishra, Mohit
    Besancon, Gildas
    Chambon, Guillaume
    Baillet, Laurent
    IFAC PAPERSONLINE, 2021, 54 (07): : 304 - 309
  • [22] Spatial variability of geomechanical parameter, estimation via ensemble kalman filter
    Zhao, Hong-Liang
    Feng, Xia-Ting
    Zhang, Dong-Xiao
    Zhou, Hui
    Yantu Lixue/Rock and Soil Mechanics, 2007, 28 (10): : 2219 - 2223
  • [23] Spatial variability of geomechanical parameter estimation via ensemble kalman filter
    Zhao Hong-liang
    Feng Xia-ting
    Zhang Dong-xiao
    Zhou Hui
    ROCK AND SOIL MECHANICS, 2007, 28 (10) : 2219 - +
  • [24] Groundwater parameter estimation via ensemble kalman filter with covariance localization
    Nan, T. C.
    Wu, J. C.
    CALIBRATION AND RELIABILITY IN GROUNDWATER MODELING: MANAGING GROUNDWATER AND THE ENVIRONMENT, 2009, : 51 - 54
  • [25] A Bayesian Adaptive Ensemble Kalman Filter for Sequential State and Parameter Estimation
    Stroud, Jonathan R.
    Katzfuss, Matthias
    Wikle, Christopher K.
    MONTHLY WEATHER REVIEW, 2018, 146 (01) : 373 - 386
  • [26] Application of Ensemble Kalman filter in parameter calibration of Muskingum model
    Yue Yanbing
    Li Zhijia
    HYDRAULIC ENGINEERING, 2012 SREE CONFERENCE, 2013, : 55 - 58
  • [27] Research and application of parameter estimation method in hydrological model based on dual ensemble Kalman filter
    Lu, Mengtian
    Lu, Sicheng
    Liao, Weihong
    Lei, Xiaohui
    Yin, Zhaokai
    Wang, Hao
    HYDROLOGY RESEARCH, 2022, 53 (01): : 65 - 84
  • [28] Short-term forecast and dual state-parameter estimation for Japanese Encephalitis transmission using ensemble Kalman filter
    Riad, Mahbubul H.
    Scoglio, Caterina M.
    Cohnstaedt, Lee W.
    McVey, D. Scott
    2019 AMERICAN CONTROL CONFERENCE (ACC), 2019, : 3444 - 3449
  • [29] Constrained state estimation using the ensemble Kalman filter
    Prakash, J.
    Patwardhan, Sachin C.
    Shah, Sirish L.
    2008 AMERICAN CONTROL CONFERENCE, VOLS 1-12, 2008, : 3542 - +
  • [30] Dual State parameter Estimation of One Dimensional Sediment Transport Using Ensemble Kalman Filter
    Lai Ruixun
    Yu Xin
    Yang Ming
    Zhang Fangxiu
    Zhang Xiaojing
    PROCEEDINGS OF THE 5TH INTERNATIONAL YELLOW RIVER FORUM ON ENSURING WATER RIGHT OF THE RIVER'S DEMAND AND HEALTHY RIVER BASIN MAINTENANCE, VOL IV, 2015, : 297 - 304
12345