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

页码：184 / 191

页数：8

共 50 条

[41] Dual state-parameter optimal estimation of one-dimensional open channel model using ensemble Kalman filter
Rui-xun Lai
Hong-wei Fang
Guo-jian He
Xin Yu
Ming Yang
Ming Wang
Journal of Hydrodynamics, 2013, 25 : 564 - 571
[42] Nonglobal Parameter Estimation Using Local Ensemble Kalman Filtering
Bellsky, Thomas
Berwald, Jesse
Mitchell, Lewis
MONTHLY WEATHER REVIEW, 2014, 142 (06) : 2150 - 2164
[43] Shape and distributed parameter estimation for history matching using a modified Ensemble Kalman filter and level sets
Villegas, Rossmary
Etienam, Clement
Dorn, Oliver
Babaei, Masoud
INVERSE PROBLEMS IN SCIENCE AND ENGINEERING, 2020, 28 (02) : 175 - 195
[44] Estimation of geothermal reservoir properties using the Ensemble Kalman Filter
Marquart, Gabriele
Vogt, Christian
Klein, Christoph
Widera, Andre
EUROPEAN GEOSCIENCES UNION GENERAL ASSEMBLY 2013, EGUDIVISION ENERGY, RESOURCES & THE ENVIRONMENT, ERE, 2013, 40 : 117 - 126
[45] Position Estimation of Touristant ASV Using Ensemble Kalman Filter
Nurhadi, Hendro
Herlambang, Teguh
Adzkiya, Dieky
INNOVATIVE SCIENCE AND TECHNOLOGY IN MECHANICAL ENGINEERING FOR INDUSTRY 4.0, 2019, 2187
[46] Geospatial state space estimation using an ensemble Kalman Filter
Sallis, Philip
Hernandez, Sergio
International Journal of Simulation: Systems, Science and Technology, 2010, 11 (06): : 56 - 60
[47] Estimation of a Stochastic Burgers' Equation Using an Ensemble Kalman Filter
Domzalski, Mariusz
Kowalczuk, Zdzislaw
2018 23RD INTERNATIONAL CONFERENCE ON METHODS & MODELS IN AUTOMATION & ROBOTICS (MMAR), 2018, : 736 - 740
[48] A Parameter-Estimation Method Using the Ensemble Kalman Filter for Flow and Thermal Simulation in an Engine Compartment
Kusano, Kazuya
Yamakawa, Hironobu
Hano, Kenich
JOURNAL OF HEAT TRANSFER-TRANSACTIONS OF THE ASME, 2018, 140 (12):
[49] State estimation of tidal hydrodynamics using ensemble Kalman filter
Tamura, Hitoshi
Bacopoulos, Peter
Wang, Dingbao
Hagen, Scott C.
Kubatko, Ethan J.
ADVANCES IN WATER RESOURCES, 2014, 63 : 45 - 56
[50] Estimation of spray flow characteristics using ensemble Kalman filter
Takahashi, Shun
Misaka, Takashi
Nara, Shotaro
Sugiyama, Naoki
Nohara, Tetsuo
Kawamoto, Yuki
Kuramoto, Yuiki
Obara, Akira
Osada, Rina
Kikuchi, Asuka
Ochiai, Masayuki
Osumi, Kazuo
Ishikawa, Naoya
FLOW MEASUREMENT AND INSTRUMENTATION, 2022, 88

← 1 2 3 4 5 →