Background: Estimation of the size of hidden and hard-to-reach sub-populations, such as drug-abusers, is a very important but difficult task. Network scale up (NSU) is one of the indirect size estimation techniques, which relies on the frequency of people belonging to a sub-population of interest among the social network of a random sample of the general population. In this study, we estimated the social network size of Kermanian males (C) as one of the main prerequisites for using NSU.Methods: A 500 random sample of Kermanian males between 18 and 45 years old were interviewed. We asked the size of their active networks using direct questions.In addition, we received the frequency of six names from the vital registry office among Kermanian males, and we estimated C indirectly using the received frequencies and the frequency of these names among the networks of our sample.Findings: Although different methods showed quite different Cs between 100 and 350, the best estimation for C was 303, which means that on average each Kermanian male knows around 303 males between the age range of 18 and 45 years.The estimated C did not have any strong association with the demographic variables of our subjects.Conclusion: Using the estimated C we may use the NSU technique to assess the frequency of many important hidden sub-populations such as drugabusers and those who have sexual contact with men and women.

Background: Network scale-up is an indirect method for estimating the size of hidden, hard-to-count or high risk populations. Social network size estimation is the first step in this method. The present study was conducted with the purpose of estimating the social network size of the Tehran Province residents and its determinants.Methods: Maximum Likelihood Estimation was applied to estimate people’s network sizes by using populations of known sizes and the scale-up method. Respondents were selected from Tehran province through convenience sampling in 2012. Out of thirteen selected subpopulations with known size, ten had minimum accuracy which used in our analysis.Results: Of the 1029 respondents in this study, 46.7% were male. The social network size of Tehran Province residents was estimated to be 259.1 (CI95%: 242.2, 276) based on the ten known populations remained in this study. This size was 291.8 in men and 230.4 in women. Younger people (18-25 years old) had larger network sizes compared to the other age groups (P<0.001).Conclusion: Our estimation for social network size of Tehran inhabitants was smaller than that previously estimated size for the whole country (c=380). In addition, we found that the social network of subpopulations was different.This difference means that we need local estimations for sub-populations to improve the accuracy of population size estimation using network scale up method.

Background: 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. Methods: 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 streetbased 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. Results: 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). Conclusion: The estimated social network size in Iranshahr was smaller than the value reported by a nationwide study (the ratiobased method).

Objective: To estimate (under reporting) UR of SDS (Suicide deaths) and SAS (suicide attempts) in Kermanshah Province which is among provinces with high suicide rate in Iran. Methods: For estimating the size of UR suicide death registers, all cases of SAS and suicide deaths were retrieved from forensic medicine and health centers. Then, using network scale up method, a sample of 500 cases, aged 18 to 65 years, were randomly selected from the general population on the basis of age-sex proportion. To find the 95% confidence interval, bootstrap technique was used. Results: The average coverage of SDS was 58. 4%, the lowest and highest coverage rate of SDS were attributed to self-immolation (34. 2%) and hanging (81. 2%), respectively. The coverage rate of SAS for self-immolation and deliberate self-poisoning were 82. 4% and 77. 2%, respectively. Size estimation of SAS by NSU method revealed that deliberate self-poisoning with medication (61. 7%), poisoning with toxins and chemicals (20. 6%), and selfimmolation (7. 7%) were the most frequent methods of SAS. Conclusion: Given the low coverage of suicide registers, all causes of death, especially deaths classified as accident or deaths with undetermined category, are required to be accurately registered. Investigations of causes of death, correction of wrong codes, as well as interviews with survivors to give them assurance can reduce the rate of suicide denial and result in increased accuracy of death register coverage.