Evaluation of Tuberculosis Underreporting to National Tuberculosis Program (NTBP) based on data from laboratories in Tehran and NTBP.

Background: According to the Global tuberculosis (TB) Report 2014, released by World Health Organization (WHO), difference between estimated number of TB patients and the number of patients who are registered by the National Tuberculosis Programs (NTBP) is about 3 million annually in the world. In the current study, we investigated the level of under-reporting of TB cases between labs with poor collaboration background with NTBP in Tehran. Methods: In the context of TB, this is an inventory study that evaluating the level of under-reporting of TB cases. To do inventory study, first, after selecting laboratories based on poor collaboration background with NTBP and developing patient's list we matched the patient's list with the MoHME's database then, patients that were not recorded in NTBP's list were identified, and those with available telephone numbers were called. Results: Out of 23 selected labs, 10 (5 private, 5 public (other than PHC)) had individuals with positive results. 71.6% of all samples are tested in public labs. Out of 23633 performed tests, 1396 individuals were positive. The under-reporting was, 62.5% and 39% in public and private laboratories, respectively. Conclusion: Public and private sector laboratories will be able to significantly reduce their failure to report if they comply with the recommended requirements and standards of the NTBP in their Processes and software for registering patient information.

Bayesian estimation of the time-varying reproduction number for pulmonary tuberculosis in Iran: A registry-based study from 2018 to 2022 using new smear-positive cases.

Introduction: Tuberculosis (TB) is one of the most prevalent infectious diseases in the world, causing major public health problems in developing countries. The rate of TB incidence in Iran was estimated to be 13 per 100,000 in 2021. This study aimed to estimate the reproduction number and serial interval for pulmonary tuberculosis in Iran. Material and methods: The present national historical cohort study was conducted from March 2018 to March 2022 based on data from the National Tuberculosis and Leprosy Registration Center of Iran's Ministry of Health and Medical Education (MOHME). The study included 30,762 tuberculosis cases and 16,165 new smear-positive pulmonary tuberculosis patients in Iran. We estimated the reproduction number of pulmonary tuberculosis in a Bayesian framework, which can incorporate uncertainty in estimating it. Statistical analyses were accomplished in R software. Results: The mean age at diagnosis of patients was 52.3 ± 21.2 years, and most patients were in the 35-63 age group (37.1%). Among the data, 9121 (56.4%) cases were males, and 7044 (43.6%) were females. Among patients, 7459 (46.1%) had a delayed diagnosis between 1 and 3 months. Additionally, 3039 (18.8%) cases were non-Iranians, and 2978 (98%) were Afghans. The time-varying reproduction number for pulmonary tuberculosis disease was calculated at an average of 1.06 ± 0.05 (95% Crl 0.96-1.15). Conclusions: In this study, the incidence and the time-varying reproduction number of pulmonary tuberculosis showed the same pattern. The mean of the time-varying reproduction number indicated that each infected person is causing at least one new infection over time, and the chain of transmission is not being disrupted.

Spatial health risk assessments of nickel in the groundwater sources of a mining-impacted area.

Mining activities have increased the potential risks of metal pollution to the groundwater resources in arid areas across the globe. Therefore, this study aimed to examine the health risk associated with nickel (Ni) in the groundwater sources of a mining-impacted area, South Khorasan, Eastern Iran. A total of 110 stations were included in the study, comprising 62 wells, 40 qanats, and 8 springs in summer, 2020. Initially, the collected samples were tested for temperature, pH, and electrical conductivity (EC). Subsequently, the samples were filtered and treated with nitric acid (HNO3) to measure the concentration of Ni using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Hazard quotient (HQ) and non-carcinogenic risk assessments were employed to evaluate the potential risks of Ni to the inhabitants. The findings revealed that the concentration of Ni ranged from 0.02 to 132.39 µg l-1, and only two stations exhibited Ni concentrations above the WHO standards (20 µg l-1). The results demonstrated that 98.21% of the sampled locations had HQ values below one, indicating negligible risk, while 1.78% of the stations exhibited HQ values of one or higher, representing a high non-carcinogenic risk for water consumers. Overall, the concentration of nickel in the groundwater of South Khorasan exceeded the World Health Organization (WHO) limit solely in the Halvan station, posing a non-carcinogenic risk for the residents in that area, and therefore, additional efforts should be made to provide healthier groundwater to consumers in this region.

Comparison of predictions of daily evapotranspiration based on climate variables using different data mining and empirical methods in various climates of Iran.

To accurately manage water resources, a precise prediction of reference evapotranspiration (ETref) is necessary. The best empirical equations to determine ETref are usually the temperature-based Baier and Robertson (BARO), the radiation-based Jensen and Haise (JEHA), and the mass transfer-based Penman (PENM) ones. Two machine learning (ML) models were used: least squares support vector regression (LSSVR) and ANFIS optimized using the particle swarm optimization algorithm (ANFPSO). These models were applied to the daily ETref at 100 synoptic stations for different climates of Iran. Performance of studied models was evaluated by the correlation coefficient (R), coefficient of determination (R2), mean absolute error (MAE), root mean square error (RMSE), scatter index (SI) and the Nash-Sutcliffe efficiency (NSE). The combination-based ML models (LSSVR4 and ANFPSO4) had the lowest error (RMSE = 0.34-2.85 mm d-1) and the best correlation (R = 0.66-0.99). The temperature-based empirical relationships had more precision than the radiation- and mass transfer-based empirical equations.

The Pattern of Tuberculosis in Iran: A National Cross-Sectional Study.

Background: Despite of the remarkable achievement in control of tuberculosis, it is still a challenging health problem in Iran. Success in any health program depends on monitor the diseases epidemiology and finding the gaps. We aimed to describe the epidemiological profile of TB patients in Iran to find the gaps in the TB program and using the finding to set the program activities. Methods: This cross-sectional study was performed based on the data of tuberculosis patients registered in Iran in 2016-2017. The information of all TB patients is registered in the TB registry software. The patients were followed during the treatment phase. The data were analyzed by SPSS 23 software using Chi-Square test. Results: Overall 12% of cases were Afghans and 72.3% of patients had pulmonary tuberculosis. There was a significant difference in the success rate of treatment in smear-positive pulmonary patients by gender, HIV status, marital status, history of hospitalization and incarceration (P <0.01). The highest prevalence of antibiotic resistance was related to isoniazid (9.9%). In close contact persons who requiring prophylaxis, 65.3% of adults and 73.6% of children received full period of prophylaxis. Conclusion: Despite of the TB treatment success and low prevalence of MDR cases, TB incidence has not been decreased significantly in Iran. Delay in diagnosis, high TB burden in refugees and close contact investigation and prophylaxis are important issues in the TB control program in Iran to be considered in the control planning.

Prevalence of latent tuberculosis infection among tuberculosis laboratory workers in Iran.

OBJECTIVES: The risk of transmission of Mycobacterium tuberculosis from patients to health care workers (HCWs) is a neglected problem in many countries, including Iran. The aim of this study was to estimate the prevalence of latent tuberculosis (TB) infection (LTBI) among TB laboratory staff in Iran, and to elucidate the risk factors associated with LTBI. METHODS: All TB laboratory staff (689 individuals) employed in the TB laboratories of 50 Iranian universities of medical sciences and a random sample consisting of 317 low-risk HCWs were included in this cross-sectional study. Participants with tuberculin skin test indurations of 10 mm or more were considered to have an LTBI. RESULTS: The prevalence of LTBI among TB laboratory staff and low-risk HCWs was 24.83% (95% confidence interval [CI], 21.31 to 27.74%) and 14.82% (95% CI, 11.31 to 19.20%), respectively. No active TB cases were found in either group. After adjusting for potential confounders, TB laboratory staff were more likely to have an LTBI than low-risk HCWs (prevalence odds ratio, 2.06; 95% CI, 1.35 to 3.17). CONCLUSIONS: This study showed that LTBI are an occupational health problem among TB laboratory staff in Iran. This study reinforces the need to design and implement simple, effective, and affordable TB infection control programs in TB laboratories in Iran.

Comparison of the tuberculin skin test and the QuantiFERON-TB Gold test in detecting latent tuberculosis in health care workers in Iran.

OBJECTIVES: The tuberculin skin test (TST) and the QuantiFERON-TB Gold test (QFT) are used to identify latent tuberculosis infections (LTBIs). The aim of this study was to determine the agreement between these two tests among health care workers in Iran. METHODS: This cross-sectional study included 177 tuberculosis (TB) laboratory staff and 67 non-TB staff. TST indurations of 10 mm or more were considered positive. The Student's t-test and the chi-square test were used to compare the mean score and proportion of variables between the TB laboratory staff and the non-TB laboratory staff. Kappa statistics were used to evaluate the agreement between these tests, and logistic regression was used to assess the risk factors associated with positive results for each test. RESULTS: The prevalence of LTBIs according to both the QFT and the TST was 17% (95% confidence interval [CI], 12% to 21%) and 16% (95% CI, 11% to 21%), respectively. The agreement between the QFT and the TST was 77.46%, with a kappa of 0.19 (95% CI, 0.04 to 0.34). CONCLUSIONS: Although the prevalence of LTBI based on the QFT and the TST was not significantly different, the kappa statistic was low between these two tests for the detection of LTBIs.

Forecasting tuberculosis incidence in iran using box-jenkins models.

BACKGROUND: Predicting the incidence of tuberculosis (TB) plays an important role in planning health control strategies for the future, developing intervention programs and allocating resources. OBJECTIVES: The present longitudinal study estimated the incidence of tuberculosis in 2014 using Box-Jenkins methods. MATERIALS AND METHODS: Monthly data of tuberculosis cases recorded in the surveillance system of Iran tuberculosis control program from 2005 till 2011 was used. Data was reviewed regarding normality, variance equality and stationary conditions. The parameters p, d and q and P, D and Q were determined, and different models were examined. Based on the lowest levels of AIC and BIC, the most suitable model was selected among the models whose overall adequacy was confirmed. RESULTS: During 84 months, 63568 TB patients were recorded. The average was 756.8 (SD = 11.9) TB cases a month. SARIMA (0,1,1)(0,1,1)12 with the lowest level of AIC (12.78) was selected as the most adequate model for prediction. It was predicted that the total nationwide TB cases for 2014 will be about 16.75 per 100,000 people. CONCLUSIONS: Regarding the cyclic pattern of TB recorded cases, Box-Jenkins and SARIMA models are suitable for predicting its prevalence in future. Moreover, prediction results show an increasing trend of TB cases in Iran.