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

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 efect of climatic factors as well as predicting the incidence of brucellosis in Qazvin prov‑ ince 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 ftted 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 efect on the number of brucellosis, the age and rainfall have a negative efect. The results show that the probability of an outbreak for the third month of 2019 is 0.30%

Predicting the Incidence of Brucellosis in Western Iran using Markov switching model

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 efect of climatic factors as well as predicting the incidence of brucellosis in Qazvin prov‑ ince 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 ftted 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 efect on the number of brucellosis, the age and rainfall have a negative efect. The results show that the probability of an outbreak for the third month of 2019 is 0.30%

Effect of occupational noise-induced sleep disturbance on worker's health

Aims: In addition to the noise, sleep disturbance (SD) as an outcome of the exposure to the wind turbine noises (WTNs) can adversely affect general health. This study aimed to investigate the effect of SD induced from WTNs on general health indicators. Materials and Methods: A total number of fifty tree workers from Manjil wind farm voluntarily participated in this study. Based on the job similarity and vicinity to the sound sources, workers were classified into three occupational groups including repairman, security, and official staff. Individual's health and sleep status were gathered using the 28-item General Health Questionnaire and Epworth Sleepiness Scales, respectively. Noise was measured based on ISO 9612. ANOVA, Chi-square, and linear and multiple regression tests were used for data analysis in the SPSS 20 software environment. Results: The mean values of 8-h equivalent continuous A-weighted sound pressure level (LAeq, 8 h) among whole workers was 71 ± 10 dB (A). The averages of somatic symptom, anxiety insomnia, social dysfunction, depression, and general health among the participants were 5 ± 2.44, 7 ± 2.35, 11 ± 2.65, 2 ± 1.54, 22 ± 6.53, and 7.3 ± 3.1, respectively. According to the results, SD and noise exposure had an adverse health effect on physical symptoms, depression, and overall general health of participants. Moreover, SD and work experience were effective factors on anxiety-insomnia. SD had greatest effect on general health when all variables are controlled, so that general health will increase by 2.42 units for each unit increase of SD. Conclusion: We found that in addition to the sound effect, noise-induced SD also affects worker's health and strengthen sound effects on human well-being