mahshid nasehi

 Tuberculosis (TB) remains a major public health issue in Iran, especially smear-positive pulmonary tuberculosis (SPPTB), due to its high transmission rate. Examining the effective reproduction number(Rt ) of SPPTB and patient characteristics is crucial for crafting targeted TB control measures. This study aimed to assess the Rt of SPPTB in Iran from 2011 to 2021 and profile SPPTB patient demographics, initial smear bacilli density, diagnosis delays, and spatial distribution.

Study Design:

 This is a historical cohort study.

 A time-dependent method was used to estimate Rt , and monthly data from the national TB registry were scrutinized from 2011 to 2021.

 A decline was observed in SPPTB incidence rates of 50909 SPPTB cases in Iran from 2011 to 2021. Approximately 29.1% of the cases were diagnosed within a month, while 44.5% experienced a one to three-month delay in diagnosis. The analysis revealed substantial heterogeneity in TB transmission dynamics across various provinces of Iran. Provinces such as Sistan and Baluchestan, Golestan, Guilan, Khuzestan, Tehran, and Khorasan Razavi exhibited the highest effective reproduction numbers. Additionally, there was a decreasing trend in the effective reproduction numbers across all provinces from 2011 to 2020.

 Effective reproduction numbers declined in most provinces from 2011 to 2020 but increased moderately after the COVID-19 pandemic, highlighting the need for targeted public health interventions. Although SPPTB incidence rates are declining nationally, elevated incidence rates and effective reproduction numbers in regions such as Sistan and Baluchestan, Golestan, Guilan, Khuzestan, Tehran, and Khorasan Razavi signify the need for persistent TB management efforts in Iran.

Smear‑positive pulmonary tuberculosis (SPPTB) is a significant public health concern in Iran. This registry‑based study aimed to investigate the incidence rates of SPPTB in Iran from 2018 to 2022.

The study analyzed SPPTB cases using the Spatial Lag Model to investigate the spatial distribution of SPPTB incidence rates, income inequality, and delayed diagnosis across the provinces of Iran and mapped the results using GIS maps.

The study found that SPPTB is prevalent among older individuals and males. The analysis identified significant spatial variation in the distribution of SPPTB incidence rates, income inequality, and delayed diagnosis across the provinces. The highest incidence rate of SPPTB was found in Sistan and Baluchestan Province and Golestan provinces. The study found a positive association between income inequalities, measured by the Gini index, and SPPTB incidence rates, indicating that provinces with higher income inequality may have higher incidence rates of SPPTB. The negative correlation with delayed diagnosis implies that predominantly, SPPTB cases are identified in the early months.

The study highlights the need to address socioeconomic disparities in health outcomes and implement targeted interventions in areas with higher income inequality to reduce the burden of SPPTB in Iran. Despite decreased SPPTB incidence rates in Iran over the past decade, some regions, such as Sistan and Baluchestan, still have high incidence rates. The Iranian government has implemented policies and programs to reduce income inequality and delayed diagnosis within the country, which can contribute to reducing the burden of SPPTB.

Tuberculosis, caused by Mycobacterium tuberculosis, is one of the most common infectious diseases worldwide. Epidemiological studies of M. tuberculosis drug resistance are critical for improving patient treatment approaches and controlling the spread of tuberculosis. The present study aimed to determine antibiotic resistance among M. tuberculosis clinical isolates using the Microplate Alamar Blue Assay (MABA).

In this descriptive cross-sectional study, 25 M. tuberculosis isolates from clinical samples were identified and confirmed using standard microbiological and biochemical tests. Then, the MIC for the antibiotics Bedaquiline, isoniazid, rifampin, ethambutol, ofloxacin, moxifloxacin, capreomycin, and streptomycin was determined using the MABA method. The results were analyzed using SPSS version 16 software.

Among the 25 investigated isolates, the frequencies for MDR, Pre-XDR, and XDR isolates were 20%, 8%, and 32%, respectively. The highest rate of drug resistance was to isoniazid (80%), rifampicin, and ethambutol (76%), and the highest rate of sensitivity was to moxifloxacin (68%). The frequency of isoniazid mono-resistance and rifampicin mono-resistance was 5 cases (50%) and 4 cases (40%), respectively.

Our study revealed an alarming rate of MDR and XDR M. tuberculosis strains, indicating that current first-line treatments may be ineffective for a significant number of patients. The bedaquiline resistance among the isolates with no history of previous exposure to this drug suggests unexplored resistance mechanisms. Molecular techniques to accurately identify these mechanisms may contribute to developing more effective treatment strategies to combat drug-resistant tuberculosis.

Tuberculosis (TB) caused by the bacterium Mycobacterium tuberculosis remains a critical global public health concern due to the high morbidity and mortality rates. Mutation in atpE and Rv0678 genes contributes to drug resistance in M. tuberculosis. This study investigates the antibiotic resistance patterns and mutations in atpE and Rv0678 genes in 22 M. tuberculosis clinical isolates.

Drug susceptibility testing (DST) for rifampin, isoniazid, streptomycin, capreomycin, ofloxacin, kanamycin, and ethambutol was conducted using the proportional method. This was followed by determining the minimum inhibitory concentration (MIC) for bedaquiline (BDQ) via the microplate Alamar blue assay (MABA). Genomic regions encompassing atpE and Rv0678 genes were amplified and sequenced for mutation analysis. Data analysis was performed using SPSS software to interpret mutation patterns concerning drug susceptibility profiles.

Of 22 isolates, 5 (27.8%) were extensively drug-resistant tuberculosis (XDR-TB), and 13 (72.2%) were multi-drug resistant tuberculosis (MDR-TB). Resistance rates to kanamycin, ofloxacin, capreomycin, and streptomycin were 40.6%, 46.3%, 85%, and 74.6%, respectively. Additionally, phenotypic resistance to bedaquiline was observed in 12 (54.5%) isolates. Sequencing revealed no resistance-conferring mutations in the atpE or Rv0678 genes among the isolates.

Our findings showed substantial resistance to first- and second-line drugs in M. tuberculosis clinical isolates. This highlights the necessity for ongoing, comprehensive studies to elucidate the evolving drug resistance patterns and understand the underlying mechanisms in clinical isolates.

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.

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.

  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,

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.

Tuberculosis is the most common worldwide cause of death from microbial diseases. Extra-pulmonary tuberculosis accounts for 20% to 25% of all cases. In this study, we used generalized estimation equations to investigate the trend of changes in extra-pulmonary tuberculosis incidence.
The recorded data of all patients with extra-pulmonary tuberculosis from 2015 to 2019 in Iran’s National Tuberculosis Registration Center were included. The trend of standardized incidence changes in provinces of Iran was calculated and reported linearly. Also, we identified the risk factors related to the extra-pulmonary tuberculosis incidence in five consecutive years using generalized estimating equations.
We studied the data of 12,537 patients with extra-pulmonary tuberculosis, of whom 50.3% were female. The mean age of the subjects was 43.61±19.88 years. Around 15.4% of all patients had a history of contact with a tuberculosis patient, 43% had a history of hospital stay, and 2.6% had a human immunodeficiency virus infection. Regarding disease types, 25% were lymphatic, 22% were pleural, and 14% were bone. Golestan province had the highest (average of 28.50 ± 8.65 cases), and Fars province had the lowest (average of 3.06 ± 0.75 cases) standardized incidences in these five years. Also, time trend (P ˂ 0.001), employment rate (P = 0.037), and average annual rural income (P = 0.001) had a significant effect on reducing extra-pulmonary tuberculosis incidence.
Extra-pulmonary tuberculosis has a decreasing trend in Iran. Still, Golestan, Sistan and Baluchestan, Hormozgan, and Khuzestan provinces have a higher incidence rate compared to the other provinces.

 Tuberculosis is one of the oldest known diseases in humans, and early detection of tuberculosis is one of the main measures to decrease the spread of tuberculosis. In many parts of the world, including Iran, the diagnosis of tuberculosis is based on the detection of acid-fast bacillus in sputum smear microscopy and PCR. this study aimed to synthesize evidence on the diagnostic accuracy of sputum smear and PCR compared to sputum culture for the diagnosis of PT in Iranian patients.   

 This systematic review  and meta-analysis was conducted based on PRISMA guideline for systematic review and meta-analysis. Eligible studies were cross-sectional original diagnostic studies published in English and Persian in Iran which examined the sensitivity or specificity(study outcome) of sputum smear microscopy or PCR( as the test) relative to sputum culture (as the gold standard/comparator) among Iranian patients suspected of having tuberculosis( study population). Studies whose data were not complete or extractable were excluded.   

 A total of 3518 subjects were evaluated from 15 eligible studies. The pooled sensitivity of sputum smear and PCR was 75.12 (95% CI: 66.68-83.56) and 88.02 (95% CI: 82.87-93.27), respectively. The specificity for sputum smear and PCR was 93.94 (95% CI: 91.26-96.63) and 91.82 (95% CI: 87.29-96.35) respectively. The sensitivity of both sputum smears was higher in studies published after 2010, and had higher quality. The specificity of sputum smear was a bit lower in studies published after2010 but higher in studies with higher quality. The specificity of PCR was higher in studies published after 2010 but higher in studies with higher quality.   

 The increased sensitivity of sputum smear and PCR during recent years suggests the improvement of preparation and laboratory methods in recent years. However, the imperfect sensitivity of these tests highlights the need for a more accurate diagnostic method for the detection of pulmonary tuberculosis in Iran.

Given that tuberculosis infection is present in one-quarter of the world's population and is more likely to convert to tuberculosis, especially at a young age, its diagnosis and prevention is an important part of the World Health Organization's (WHO) program. The aim of this study is to evaluate the frequency of latent tuberculosis infection (LTBI) in different age groups of family members of pulmonary tuberculosis patients in two provinces of Iran with a high prevalence of tuberculosis during 18 months.

Family members of confirmed pulmonary tuberculosis patients were followed up as a retrospective and prospective study in the cities of Gorgan and Zabol at 0, 3, 12 and 18 months after the starting the study. LTBI was diagnosed by using the QuantiFERON test kit and the Tuberculin skin test (TST).

The number of LTBI cases based on QFT or TST was 354 (52.99%) in the whole study and 33.33% in children under 5 years old. Positive cases of TST, QFT and LTBI in the age group over 18 years were significantly different with 5 to 18 years and less than 5 years, while there was no significant difference between the age groups of less than 5 years and 5 to 18 years.

The results of this study showed that most cases of infection occur before the diagnosis of the index case or in the first phase of study, and there is no significant difference between the diagnosis with TST or QFT.

Tuberculosis (TB) is a major global health problem, so for better planning in the health sector, it is necessary to know the real burden of tuberculosis in our country. The main aim of this study was to calculate the burden of TB for the Iranian population in 2001-2012. 

The Disability Adjusted Life Years (DALYs) index was calculated using a computer model (DisMod version II) in Iran between the years 2001 and 2012. DALYs are age-weighted (β= 0.04) and are discounted for time preference (r= 0.03).

The trend was decreasing from 2001 till 2006, and after it, there is an increasing trend. The incidence was more in younger age groups and in female, and the YLL is higher in men (11744 in male vs 7897 in female in 2012); it showed that the life lost is higher in men. The YLD in men and women are very close. In comparison, the DALY of TB was higher in men than women.

In the present investigation, it has been found that the overall tendency to get TB was higher in the female population. It shows that the incidence was higher in the younger age groups but the mortality was higher in the elderly   groups. It that shows the significant success of the country in controlling the disease.

 The interferon-gamma release assays (IGRAs) are the most important diagnostic approach to Mycobacterium tuberculosis infection diagnosis. However, they cannot discriminate between latent tuberculosis infection (LTBI) and active tuberculosis (TB). Some recent studies suggested that interleukin-2 (IL-2) response to M. tuberculosis could be utilized as a potential biomarker to discriminate active disease from LTBI.

 The current study aimed at evaluating the potential role of IL-2 to detect both active TB and LTBI among household contacts of patients with pulmonary TB in two TB-endemic regions of Iran.

 A total of 650 household contacts of patients with TB were invited to participate in the current study. All subjects were diagnosed on extensive clinical evaluation of active TB and LTBI based on clinical manifestations and laboratory findings. The IGRA test was performed using QuantiFERON®-TB Gold Plus. The serum level of IL-2 was measured using the ELISA Development Kit.

 A total of 237 household contacts entered the final analysis, including 132 patients with LTBI and three with active TB. In addition, 14 subjects were included as TB controls and 102 as TB-uninfected controls. The serum level of IL-2 was significantly higher in active TB and LTBI patients than TB-uninfected controls. The ROC curve was plotted between active TB and LTBI, revealing that the cutoff point of 25.5 pg/mL identifies the active form with 88.24% sensitivity and 36.36% specificity.

 The current study indicated that the IL-2 assay could not discriminate between active TB and LTBI with acceptable sensitivity.

Since the beginning of the coronavirus disease 2019 (COVID-19) epidemic in Iran, the control and management of the epidemic were headed by the National Headquarter for the Control of COVID-19 Epidemic through setting up different scientific committees, including the COVID-19 National Epidemiology Committee. The present study reviews the missions, structures, achievements, and challenges of the Epidemiology Committee. Study design: A rapid review

All relevant reports, documents, guidelines, published literature, and surveillance data related to the establishment, visions, missions, roles, activities, and outputs of the COVID-19 Epidemiology Committee were critically reviewed in this study.

The efforts of the committee’s working groups may have impacted improvements in data registration/usage, provincial data quality at provincial levels, and perception of the epidemic situation in the provinces. The committees have also played role in informing the policies in different stages of the epidemic through routine or problem-based data/evidence analyses, epidemic investigations, and mathematical modeling.

The structure and experience gained by the committee can be used in similar situations within and outside the country. To further improve the impacts of our activities, it is essential to have effective interaction, collaboration, and data flow between the committee and a broad range of organizations within and outside the Ministry of Health and Medical Education.

Tuberculosis (TB) is the 10th</sup> most common infectious disease in the world, and it is one of the major health problems in Iran despite the implementation of the National Tuberculosis Control Program.

Tuberculosis data in Iran were used in 2016 by the Ministry of Health and Treatment. The data on mortality and incidence of disease were determined by age groups, sex, and the provinces of country. Data were analyzed using Excel (2010) and SPSS software.

The overall incidence rate of tuberculosis in the country was 9.7 per 100000 population (10.7 in men and 8.7 in women). The highest incidence rate of TB and mortality in both sexes were over 80 years. The death rate was 1 person per 100,000 populations, 57.7% of whom were men. Most of the deaths were from pulmonary tuberculosis. The highest incidence and mortality rates were reported in Golestan and Sistan and Baluchestan provinces.

The incidence and mortality rate of TB has decreased in recent decades in Iran. Nevertheless, considering the raising trend of human immunodeficiency virus (HIV) among the patients with TB, and the neighborhood with endemic countries, TB should be noticed as one of the most important health priorities in the health system of the country.

The network scale-up method is an indirect method of estimating the size of hidden and hard-to-reach populations. An important prerequisite in this method is to estimate the size of an active social network, as considered in the present study.

In 2015, the social network size was calculated using the known subpopulation approach and maximum likelihood estimation in the central, Bampur, and Bazman districts of Iranshahr province. Individuals older than 18 years took part in a street-based survey. The relationship between the demographic variables and social network size estimation was analyzed (p< 0.05). Linear regression was used to investigate the relationship of each known subpopulation with underlying variables. Data were analyzed in Excel 2010 and SPSS 19.

From among 1000 participants, 50.2% lived in rural areas. The social network size of the residents of Iranshahr was estimated to be 308.35 with 12 remaining subgroups. The Pearson’s correlation coefficient between the real and estimated values in known subpopulations was equal to 0.92 (p= 0.001). Men aged 25-39 years, those with high education levels, employees, and those residing in villages had a wider social network. The estimated social network size had a significant relationship with gender, education level, and place of residence (p< 0.001).

The estimated social network size in Iranshahr was smaller than the value reported by a nationwide study (the ratio-based method).

TB surveillance and preventing the further spread of the disease need the full knowledge of the biological characteristics influencing TB and detecting mathematical patterns to interpret the mechanism of TB spread. These models can provide explanations and knowledge of the dynamics of diseases and can be used for forecasting the ensuing values. To determine the possible
number of patients, the time ahead is vital for decision making in public health. However, it is essential to determine forecasts’ accuracy utilizing genuine forecasts. Thus, we obtained the TB cases from April 2007 until March 2018 in Razavi Khorasan province to develop a fit model and forecast the number of TB cases for the next 24 months.

We considered a time series of monthly incidence counts of TB in Razavi Khorasan province from April 2007 until March 2018. The data included total TB, pulmonary TB, new pulmonary TB, retreatment TB, and extrapulmonary TB cases. For choosing models and forecasting, we use about 20% of all data (24 data) for testing and the rest for training the model. The optimization of parameters was done automatically according to the smallest root mean squared error for these time-series analysis techniques with STATA. The models were EWMAs models (single exponential and double exponential smoothers) and totally, we compared the quality of forecasts provided by EWMAs models through the stand-alone measurement (RMSE).

The patterns of raw series of total TB, pulmonary TB, and new pulmonary TB were almost the same. They illustrated slowly downward trends with oscillation around the trend that was a property of cyclic trend. For retreatment TB and extrapulmonary TB cases, reductions occurred over time although with no pattern. The results of statistical models indicated that the values of smoothing
constants of all series were near zero that indicated a very smooth series with slowly changing counts. Total TB, pulmonary TB, and new pulmonary TB series had double exponential patterns with noisy and long-standing trend and they might be increasing in the 24 months ahead. Retreatment TB and extrapulmonary TB series had simple exponential patterns with noisy and without
secular trends; they might be with no changes in the 24 months ahead.

The end TB strategy, MDG 6, target 8 is to stop and start to inverse the incidence of TB by 2015 and we joined this strategy in January 2006. However, TB control remains one of the main public health concerns. In recent years, our country has experienced immigrants from neighboring countries, sanctions or/and attacks with category C of biological agents in moving toward tuberculosis elimination. Our implementation requires changes in strategies and activities that should evolve over time. The findings of this study are helpful in achieving this goal

Tuberculosis (TB) is an important infectious disease with high mortality in the world. None of the countries stay safe from TB. Nowadays, different factors such as Co-morbidities, increase TB incidence. World Health Organization (WHO) last report about Iran's TB status shows rising trend of multidrug-resistant tuberculosis (MDR-TB) and HIV/TB. More than 95% illness and death of TB cases are in developing countries. The most infections are in South East Asia and West Pacific that 56% of them are new cases in the world. The incidence is actually new cases of each year. Incidence prediction is affecting TB prevention, management and control. The purpose of this study is designing and creating a system to predict TB incidence by time series artificial neural networks (ANN) in Iran.

This study is a retrospective analytic. 10651 TB cases that registered on Iran’s Stop TB System from March 2014 to March 2016, Were analyzed. Most of reliable data used directly, some of them merged together and create new indicators and two columns used to compute a new indicator. At first, effective variables were evaluating with correlation coefficient tests then extracting by linear regression on SPSS statistical software, version 20 (IBM, Armonk, NY, USA). We used different algorithms and number of neurons in hidden layer and delay in time series neural network. R, MSE (mean squared error) and regression graph were used for compare and select the best network. Incidence prediction neural network were designed on MATLAB® software, version R2014a (Mathworks Inc., Natick, MA, USA).

At first, 23 independent variables entered to study. After correlation coefficient and regression, 12 variables with P≤0.01 in Spearman and P≤0.05 in Pearson were selected. We had the best value of R, MSE (mean squared error) and also regression graph in train, validation and tested by Bayesian regularization algorithm with 10 neuron in hidden layer and two delay.

This study showed that artificial neural network had acceptable function to extract knowledge from TB raw data; ANN is beneficial to TB incidence prediction.

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.

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.

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.

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.

The size estimation of key populations is a necessary part of surveillance systems to access global human immunodeficiency virus (HIV) infection. In this study, the NSU method was used to estimate injection drug users (IDUs).

NSU method was performed on 1000 individuals in Iranshahr province with street-based sampling from 2016 to 2017. A questionnaire comprising items on demographic information and items measuring the network size of participants about IDUs was administered. The estimated size was adjusted for transmission error and barrier effect with PF and VF factors. The relationship between knowing IDUs and demographic variables was assessed using logistic regression. All analyses were performed in SPSS 19 and Microsoft Excel.

In this study, 500 men and 500 women were included. The average age (standard deviation) of the participants was 29.6 (7.8) years. IDUs were estimated at 1263 per 100 000 population of Iranshahr in Sistan and Baluchestan province, Iran. The estimated size was 7.5 times more in men than in women (2766 vs 364). Moreover, the highest estimated size belonged to the population of 18-30-year-olds (1187). Sex and education level had significant relationships with knowing IDUs (p<0.001).

To improve preventive programs, the number of outreach teams must be increased to have access to IDUs, educate them, and upgrade the coverage of harm-reduction services. According to cultural considerations and the illegal nature of injection drug use, social mobilization is essential to reduce the stigma.

Leprosy is a chronic infectious disease with permanent complications that mainly affect the skin, peripheral nerves, mucosal surfaces of the upper respiratory tract, and eyes. The aim of this study was to investigate the epidemiology and trends of leprosy in Iran from 2005 to 2015.
This was a cross-sectional study analyzing leprosy records from the Center for Communicable Disease Control, Ministry of Health and Medical Education, during 2005-2015.
Of the 433 cases of leprosy diagnosed from 2005 to 2014, 87.1% were Iranian, and 56.2% of the Iranian cases were male. Furthermore, 82.5% of cases were multibacillary. The paucibacillary leprosy cases had a better remission rate in most years of the study. The annual prevalence and case detection rates of leprosy (per 100,000 population) significantly decreased in Iran between 2005 and 2015: from 0.2 to 0.02 and from 0.11 in 2005 to 0.02, respectively. The geographical distribution of leprosy cases in 2014 showed that leprosy is more common in the west, north, northwest, and south of Iran.
Although Iran is currently an area in which leprosy is not a serious problem, new cases of leprosy are still diagnosed in Iran. Considering that Iran is attempting to eradicate the disease, careful attention to all aspects of the disease is essential.

Social capital is an important interpersonal organizational resource that may affect health behaviors and seems to be an important factor in chronic diseases. Considering the lack of evidence on this topic, in the present study, we aimed at investigating the association between components of social capital, socioeconomic condition, and controlling Type 2 diabetes mellitus in Iran.
This study was conducted on 300 patients with Type 2 diabetes in Tehran, Iran. In this study, simple random sampling method was used for data collection. Path analysis model was used to examine the potential association between social capital components and to determine the factors that control Type 2 diabetes.
In the present study, most of the participants were female (70.7%) and married (78.7%). Path coefficients were calculated by a series of multiple regression analyses based on the conceptual model. The final model had a proper fit with Chi-square = 2.08 (DF = 1, P = 0.049), GFI = 0.542, AGFI = 0.915, NFI = 0.228, RFI = 0.284, IFI = 0.299, TLI = 0.292, CFI = 0.219, and RMSEA = 0.033. The Groups and networks (network) (β = 0.051, p = 0.036) and trust and solidarity (β = -0.018, p = 0.028) had a direct positive and negative effect on HbA1C, respectively. The results also revealed that education levels had a direct positive effect on groups and networks (network) (β = 0.118, p = 0.036), trust and solidarity (β = 0.082, p = 0.007), information and communication (β = 0.037, p = 0.027), and contribution in team works and public activities (β = 0.064, p = 0.003). In addition, education levels had an indirect positive effect on HbA1C through their effect on groups and networks (network), trust and solidarity, and information and communication.
Social capital has a significant relationship with diabetes. Although it was not specified clearly which components of social capital were associated with diabetes, trust and solidarity showed a negative direct effect on HbA1C, respectively. Therefore, developing and implementing local and collective programs to build trust and increase the standards of social trust in patients with diabetes can be effective in controlling HbA1C.

In order to achieve a dynamic surveillance system for the groups at risk of tuberculosis and to improve its quality, investigating its various aspects and benefiting from the opinions of the experts and experienced individuals in this field are very important. Hence, the objective of this study was to explore the status of the surveillance system for the groups at risk of tuberculosis in Iran.
Data collection was carried out via interviews with 17 experts in the tuberculosis control program of Iran. In order to evaluate the validity and reliability of data, four criteria of credibility, transferability, dependability and confirmability were used. Frame analysis was used for data analysis.
Based on the interviewee's opinions, twelve major groups at risk of tuberculosis and seven challenges in the surveillance system were identified. For the majority of these at risk groups, there is no structured program and the status of case finding and treatment is similar to the public population. For some others (HIV/ AIDS patients, prisoners and people at exposure), there is a program, but its effectiveness is uncertain.
Results indicate that groups at risk of tuberculosis are widespread and access to some of them is difficult; hence, these groups are the main challenges of the tuberculosis control program in Iran.

Poverty and low socioeconomic status are the most important reasons of increasing the global burden of tuberculosis, not only in developing countries but also in developed countries for particular groups. The purpose of this study was to assess the association between socioeconomic factors and the number of tuberculosis patients using quantile regression for count data.
This cross-sectional study was conducted on 11,320 tuberculosis patients from March 2010 to March 201 in Iran. Data was gathered from the 345 sections of Iran by Ministry of Health and Medical Education and Statistical Center of Iran. The jittering method was applied for smoothing, and then, the quantile regression for count data was fitted. The AIC was used to compare the fitness of quantile regression for count data model and Poisson log-linear model. The R (3.0.1) software and Quantreg and AER packages were used for all analysis and modeling of the data.
The results of fitting the quantile regression for count data showed that in all percentiles, the more increase in immigration rate, illiteracy rate, unemployment and urbanization rates, the more tuberculosis morbidity rate was increased. The maximum increase of tuberculosis due to immigration rate, urbanization rate, unemployment rate, and illiteracy rate was in 95th percentile (β ̂=0.315), 85'Th percentile (β ̂=0.162), 75'Th percentile (β ̂=0.114), and 95'Th percentile (β ̂=0.304), respectively. For 50th percentiles and higher percentiles, with increasing the sum of physicians to the number of population, the tuberculosis morbidity rate was decreased, and the maximum decrease was in 95'Th percentile (β ̂=-0.1). For all percentiles, the AIC showed that quantile regression for count data had been a better fit to data.
With respect to the relationship between socioeconomic factors and TB rate, health care observers should pay close attention to improving these factors in Iran to reduce the TB mortality and morbidity.

Determining the temporal variation and forecasting the incidence of smear positive tuberculosis (TB) can play an important role in promoting the TB control program. Its results may be used as a decision-supportive tool for planning and allocating resources. The present study forecasts the incidence of smear positive TB in Iran. This a longitudinal study using monthly tuberculosis incidence data recorded in the Iranian National Tuberculosis Control Program. The sum of registered cases in each month created 84 time points. Time series methods were used for analysis. Based on the residual chart of ACF, PACF, Ljung-Box tests and the lowest levels of AIC and BIC, the most suitable model was selected. From April 2005 until March 2012, 34012 smear positive TB cases were recorded. The mean of TB monthly incidence was 404.9 (SD=54.7). The highest number of cases was registered in May and the difference in monthly incidence of smear positive TB was significant (P<0.001). SARIMA (0,1,1)(0,1,1)12 was selected as the most adequate model for prediction. It was predicted that the incidence of smear positive TB for 2015 will be about 9.8 per 100,000 people. Based on the seasonal pattern of smear positive TB recorded cases, seasonal ARIMA model was suitable for predicting its incidence. Meanwhile, prediction results show an increasing trend of smear positive TB cases in Iran.

Objective (s): Study of observed changes in disease incidence provides valuable information for planning and reform programs. In this study we use Poisson piecewise regression model for modeling change points and their locations for TB trend in of Iran. The findings showed that there are two change points for TB trend in Iran. We find two change points in TB trend and consequently we could divide the TB trend into three segments with different rate of TB.

Tuberculosis is still a public health concern in Iran. The main challenge in monitoring epidemiological status of tuberculosis is to estimate its incidence accurately. We used a newly developed approach to estimate the incidence of tuberculosis in Sistan, an endemic area in southeast of Iran in 2012-13.Patients and This cross-sectional study was conducted on school children aged 6-9 years. We estimated a required sample size of 6350. Study participants were selected using stratified two-stage cluster sampling method and recruited in a tuberculin skin test survey. Indurations were assessed after 72 hours of the injection and their distributions were plotted. Prevalence and annual risk of tuberculosis infection (ARTI) were estimated using the Bayesian mixture model and some traditional methods. The incidence of active disease was calculated using the Markov Chain Monte Carlo technique. We assumed weibull, normal and normal as the best distributions for indurations due to atypical reactions, BCG (Bacillus Calmette–Guérin) reactions and Mycobacterium tuberculosis infection, respectively. The estimated infection prevalence and ARTI were 3.6% (95%CI: 3.1, 4.1) and 0.48%, respectively. These estimates were lower than those obtained from the traditional methods. The incidence of active tuberculosis was estimated as 107 (87-149) per 100000 population with a CDR of 54% (40%-68%). Although the mixture model showed slightly lower estimates than the traditional methods, it seems that this method might generate more accurate results for deep exploration of tuberculosis endemicity. Besides, we found that Sistan is a high endemic area for tuberculosis in Iran with a low case detection rate.