Literature DB >> 33648578

Predicting the incidence of brucellosis in Western Iran using Markov switching model.

Maryam Mohammadian-Khoshnoud1, Majid Sadeghifar2, Zahra Cheraghi3,4, Zahra Hosseinkhani5.   

Abstract

OBJECTIVE: Brucellosis is a zoonosis almost chronic disease. Brucellosis bacteria can remain in the environment for a long time. Thus, climate irregularities could pave the way for the survival of the bacterium brucellosis. Brucellosis is more common in men 25 to 29 years of age, in the western provinces, and in the spring months. The aim of this study is to investigate the effect of climatic factors as well as predicting the incidence of brucellosis in Qazvin province using the Markov switching model (MSM). This study is a secondary study of data collected from 2010 to 2019 in Qazvin province. The data include brucellosis cases and climatic parameters. Two state MSM with time lags of 0, 1 and 2 was fitted to the data. The Bayesian information criterion (BIC) was used to evaluate the models.
RESULTS: According to the BIC, the two-state MSM with a 1-month lag is a suitable model. The month, the average-wind-speed, the minimum-temperature have a positive effect on the number of brucellosis, the age and rainfall have a negative effect. The results show that the probability of an outbreak for the third month of 2019 is 0.30%.

Entities:  

Mesh:

Year:  2021        PMID: 33648578      PMCID: PMC7923320          DOI: 10.1186/s13104-020-05415-5

Source DB:  PubMed          Journal:  BMC Res Notes        ISSN: 1756-0500


  17 in total

1.  Human brucellosis.

Authors:  Brodie Ramin; Paul Macpherson
Journal:  BMJ       Date:  2010-09-10

Review 2.  The new global map of human brucellosis.

Authors:  Georgios Pappas; Photini Papadimitriou; Nikolaos Akritidis; Leonidas Christou; Epameinondas V Tsianos
Journal:  Lancet Infect Dis       Date:  2006-02       Impact factor: 25.071

3.  Brucellosis presenting as septic shock.

Authors:  Mehandi Haran; Amit Agarwal; Yizhak Kupfer; Chanaka Seneviratne; Kabu Chawla; Sidney Tessler
Journal:  BMJ Case Rep       Date:  2011-03-10

4.  Time series analysis of human and bovine brucellosis in South Korea from 2005 to 2010.

Authors:  Hu Suk Lee; Moon Her; Michael Levine; George E Moore
Journal:  Prev Vet Med       Date:  2012-12-29       Impact factor: 2.670

5.  [Characteristics on spatial and temporal distribution as well as the driving effect of meteorological factors on brucellosis in Datong city, Shanxi province, 2005-2015].

Authors:  Z R Yang; X Li; Z J Shao; W T Ma; X J Yuan; K J Wu; K Liu
Journal:  Zhonghua Liu Xing Bing Xue Za Zhi       Date:  2018-09-10

Review 6.  Laboratory animal models for brucellosis research.

Authors:  Teane M A Silva; Erica A Costa; Tatiane A Paixão; Renée M Tsolis; Renato L Santos
Journal:  J Biomed Biotechnol       Date:  2011-02-20

7.  Time series and trend analysis of brucellosis in Oskou county, East Azerbaijan: 2007-2016.

Authors:  Hosein Rafiemanesh; Yousef Alimohamadi; Seyed Rasoul Hashemi Aghdam; Avaz Safarzadeh; Abolghasem Shokri; Alireza Zemestani
Journal:  Health Promot Perspect       Date:  2019-10-24

8.  Epidemiological features and risk factors associated with the spatial and temporal distribution of human brucellosis in China.

Authors:  Yin-Jun Li; Xin-Lou Li; Song Liang; Li-Qun Fang; Wu-Chun Cao
Journal:  BMC Infect Dis       Date:  2013-11-16       Impact factor: 3.090

9.  Forecasting the monthly incidence rate of brucellosis in west of Iran using time series and data mining from 2010 to 2019.

Authors:  Hadi Bagheri; Leili Tapak; Manoochehr Karami; Zahra Hosseinkhani; Hamidreza Najari; Safdar Karimi; Zahra Cheraghi
Journal:  PLoS One       Date:  2020-05-12       Impact factor: 3.240

10.  Effect of climatic factors on the seasonal fluctuation of human brucellosis in Yulin, northern China.

Authors:  Kun Liu; Zurong Yang; Weifeng Liang; Tianci Guo; Yong Long; Zhongjun Shao
Journal:  BMC Public Health       Date:  2020-04-16       Impact factor: 3.295

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