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Original Article
Social Contact Patterns Associated With Tuberculosis: A Case-control Study in Southwest Iran
Neda Amoori1orcid, Bahman Cheraghian2orcid, Payam Amini3orcid, Seyed Mohammad Alavi1orcid
Journal of Preventive Medicine and Public Health 2022;55(5):485-491.
Published online: September 30, 2022
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1Infectious and Tropical Diseases Research Center, Health Research Institute, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran

2Hearing Research Center, Department of Biostatistics and Epidemiology, School of Public Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran

3Department of Biostatistics and Epidemiology, School of Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran

Corresponding author: Seyed Mohammad Alavi, Infectious and Tropical Diseases Research Center, Health Research Institute, Ahvaz Jundishapur University of Medical Sciences, West 11th Street, Ahvaz 6155734511, Iran, E-mail:
• Received: August 2, 2022   • Accepted: September 21, 2022

Copyright © 2022 The Korean Society for Preventive Medicine

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

  • Objectives
    Tuberculosis (TB) is a major public health concern worldwide. Social contact patterns can affect the epidemiology and risk of airborne diseases such as TB. This study was designed to investigate the social contact patterns associated with TB.
  • Methods
    In this case-control study, groups of participants with and without TB were matched by age and sex. Participants reported the nature, location, frequency, and average duration of social contacts over 1 month. The duration and number of social and spatial contacts were compared between groups using the chi-square test and the t-test. Odds ratios (ORs) with 95% confidence intervals (CIs) were used to quantify the relationship between social contact time and TB status. Data were analyzed using Stata version 11 statistical software. A p-value of <0.05 was considered to indicate statistical significance.
  • Results
    In this study, 80 patients with TB and 172 control participants were included, and a total of 3545 social contacts were registered. Social contact with family members (OR, 1.72; 95% CI, 1.10 to 2.40), contact with a person with TB (OR, 1.53; 95% CI, 1.16 to 2.01), and contact at the participant’s home (OR, 1.42; 95% CI, 1.19 to 1.82) were significantly associated with TB status.
  • Conclusions
    The duration of long-term social contact, rather than the number of contacts, may be the main contact-related factor associated with TB transmission in this population. The focus of contact-tracing efforts should be on finding and treating both family members and long-term contacts in non-household settings.
Tuberculosis (TB), which is caused by Mycobacterium tuberculosis, is the most common cause of death due to infectious disease in the world. Among all causes of death, the disease ranks 10th globally and first in developing countries [1]. The incidence rates in the world, the Eastern Mediterranean region, Iran, and the Khuzestan province of Iran are 132, 114, 16, and 14.5 cases per 100 000 people, respectively, representing a decrease relative to previous years [2,3]. World Health Organization reports indicate distinct geographical distributions of TB in different parts of the world [4]. Epidemiological studies have shown that several factors can increase the risk of TB. These include injection drug use, smoking, malnutrition, a body mass index of less than 18.5 kg/m2, and vitamin D deficiency [5,6]. Diseases such as silicosis, diabetes, kidney failure, various cancers, and bone marrow or organ transplants are also associated with an increased risk of TB [7,8].
TB is considered a social disease, and its infection and progression are strongly associated with socioeconomic factors as well as social and environmental interactions, including financial insecurity and congestion in living spaces [911]. Studies have shown that social contact patterns, including the frequency, duration, situation, and location of daily social interactions, are closely associated with the risk of heterogeneous infection in the community [12], which may indicate discrepancies in the risk of TB across communities [13,14]. In previous studies, researchers have largely identified patterns of social contact related to general populations without describing or comparing patterns of contact in high-risk populations or with persons with TB [15,16]. Identifying notable social contact patterns associated with TB may lead to new control interventions. Additionally, it can aid in contact tracing and case detection to prevent transmission by focusing attention on high-risk, high-priority contacts [17]. The identification of TB-associated contact patterns may also be useful for the development of mathematical transfer models used to identify high-risk groups (such as age or sex groups) in communities [11,18].
Contact with a person with TB is a key factor in the transmission of the disease; if a patient with active TB is placed in a closed environment, those in close contact may be infected within 12 hours [10]. In recent studies, a high rate of TB spread in different environments has been observed due to exposure to infected individuals in the community [14]. By identifying areas of the community at high-risk of TB, we can improve diagnosis and public health monitoring, and by performing environmental interventions, we may reduce the risk of exposure and transmission of the disease [17,19].
In the present study, we examined the patterns of social contact associated with TB with the primary goal of assessing the relationship between this disease and the duration of social contact. We hypothesized that longer social contact times were more likely to be reported by participants with TB. Our secondary goal was to identify specific types and locations of social contact associated with TB.
Study Population
A case-control study was conducted to assess the social contact patterns associated with TB. The selected cases were newly registered, bacteriologically confirmed pulmonary TB patients who were over 18 years old and were referred to 36 health centers in Ahvaz, southwest Iran. The controls were attendees who were matched with the cases regarding age and sex and were referred to the same health centers for non-TB health problems.
Sampling Procedure

Selection of cases

The cases were newly identified patients who presented for treatment at the selected health centers in Ahvaz. The basic tests for pulmonary TB included a sputum smear test as well as a complete medical evaluation for TB including chest radiology (X-rays), culture, medical history, a physical examination, and a tuberculin skin test. In the data collection process, all newly registered TB patients were included until the required sample size was reached. For each case, 2 control participants were selected.

Selection of health facility controls

Attendees at the same facility who were age-matched (within 5-year age bands) and sex-matched with an individual case were selected as controls. Those who met the age and sex criteria were evaluated on a day when the clinic was operating. If a selected patient refused to participate in the study, the next eligible clinic attendee was evaluated. To manage the control patients’ medical conditions and to exclude pulmonary TB, they were visited by a doctor associated with the study. If the individual showed any sign of TB, the necessary laboratory tests for TB were performed according to the national diagnostic algorithm. Acid-fast bacilli microscopy tests are provided free of charge at the institutions, so participants were not charged for those exams. However, the costs of any necessary additional investigations, such as X-ray imaging, were covered by the study.
Data Collection
After selecting the research sample based on the inclusion criteria, explaining the study objectives, and assuring the participants of the confidentiality of the information collected, informed consent was obtained from all participants. Then, information was collected through face-to-face interviews using checklists and standard forms. The data collected included basic demographic data (age, sex, education level, monthly income, and employment status), as well as type and place of contact. In this study, all social contacts with the case and control participants during the month prior to entering the study were examined. All participants reported contacts according to the type of social relationship (family, friend, co-worker, or neighbor) and main places where the social contacts took place (private home, relatives’ home, school, workplace, mosque, market or store, restaurant, park, hairdresser, or health center). For each reported social contact, we asked the participant to indicate the average number of times per week they were in contact during the past month (e.g., daily, twice, or 3 times) and the average duration (in hours) of each contact.
Statistical Analysis
The contact time was calculated for every reported location and social contact. The estimation was performed by multiplying the average weekly frequency of each contact by the average duration of that contact. For example, if a participant reported meeting a social contact twice a week for 2.5 hours per meeting, the contact time would be 5 hours per week. To obtain an overall exposure time, the estimated contact time for each social contact was found for each participant. Reported social contacts and contact times were summarized in tables.
To analyze and compare the demographic variables in both groups, the t-test and chi-square test were used for continuous and categorical data, respectively. Logistic regression was used to estimate odds ratios (ORs) for the association between total social contact time and TB infection. The ORs for TB disease and total social contact time for each category of contact and location were also estimated.
Age and sex were included in the model to adjust for frequency matching. Income and education levels were included in the regression models to control for potential confounding due to their association with TB status and duration of social contact. Data were analyzed using Stata version 11 (StataCorp., College Station, TX, USA). A p-value of <0.05 was considered to indicate statistical significance.
Ethics Statement
This study was part of a PhD thesis that was approved by the Ethics Committee of Ahvaz Jundishapur University of Medical Sciences (IR.AJUMS.REC.1400.240). All methods were performed in accordance with the relevant guidelines and regulations of the Helsinki Declaration. Informed written consent/assent was obtained from all participants, who were assured of the confidential nature of the information gathered. All data collected were anonymized using unique study identifiers.
A total of 80 cases and 172 controls were included in the study. The mean ages of participants in the case and control groups were 34.1 years and 32.5 years, and more than half of the participants were male (59.9%). The control participants were more educated (p<0.001) and had higher employment levels (p<0.001) and monthly income (p=0.04) than the case group.
Overall, over the 1-month period, cases (n=1545) reported fewer social contacts than controls (n=2000). Family members represented the highest proportion of reported contacts for both case (n=880, 57.0%) and control (n=990, 49.5%) groups. The second most frequent type of social contact was with friends (n=380, 24.6%) in the case group and with colleagues (n=480, 24.0%) in the control group. Social contacts reported by cases most frequently occurred in the participants’ homes (n=480, 31.7%), while the most common location reported by the control participants was the workplace (n=529, 23.3%). The differences between groups regarding place of contact were statistically significant (Table 1).
Among the cases, the longest reported contact time was with family members (81.0%), followed by friends (10.0%) and co-workers (8.0%). In the control group, most of the contact time was with family members (70.0%), but the second contact time was with a colleague (22.0%) and then friends (5.0%) (Figure 1). In general, the highest reported contact time ratio for both case and control occurred at home and work (Figure 2).
The total contact duration with persons with TB was 947 hours (9% of overall contact time) in the case group but only 129 hours (1%) in the control group (Supplemental Material 1). The average numbers of social contacts reported by cases and controls are shown in Table 2. On average, the control group reported significantly more social contacts (mean±standard deviation, 23.92±13.45) than the case group (23.41±14.52) (p<0.001), and social contacts outside the home were similarly more frequent in the control group (7.68±5.44) than in the case group (7.21±5.35) (p=0.02). Regarding social contacts with people with TB, the case group reported significantly more contacts (1.15±3.23) than the control group (0.15±0.48, p<0.001) (Table 2). While controls reported more social contacts than did cases, the overall contact time was shorter among control participants (11.67±12.43 hr/wk) than cases (13.71±10.22 hr/wk). This difference was statistically significant (p=0.03) (Table 2). While the average numbers of family and home contacts did not differ significantly between cases and controls (p=0.08), the case group reported significantly more social contact time with family members than the control group (p<0.001) as well as more social contact time at home (p=0.02). Both groups reported more social contact time in the workplace, markets, stores and health centers (Table 2).
Contact times per individual contact are reported in Supplemental Material 2. Generally, cases reported significantly longer social contact times per individual contact than the control participants (p<0.001). Cases reported significantly longer social contact times for each family member (p<0.001), co-worker (p=0.01), friend (p=0.04), and non-household contact (p=0.01). Cases reported longer social contacts in their homes (p=0.02), markets and stores, workplaces, and health centers than the control group (p<0.001).
After adjusting for age, sex, income, and education level, both duration of social contact with family members (OR, 1.72; 95% CI, 1.10 to 2.40; p=0.01) and history of contact with a patient with TB (OR, 1.53; 95% CI, 1.16 to 2.01; p<0.001) were significantly associated with TB status. Duration of social contact in the participant’s home (OR, 1.42; 95% CI, 1.19 to 1.82; p=0.03) was also associated with TB (Table 3).
In this case-control study, we compared patterns of social contact between TB patients and healthy individuals to identify patterns that may be associated with disease transmission. Control participants reported more social contact than the case group, but cases had longer overall contact times than the control group, especially with family members and people with TB. These results demonstrate the possible types of exposure to TB cases that may confer higher risk of transmitting the TB disease due to longer contact times. These findings may be used by health organizations to strengthen and improve disease detection and infection control programs in environments with a high-risk of TB exposure. Although we found no association between overall contact time and TB, we noted that in almost all subgroups, cases reported longer contact periods than controls.
TB status was significantly associated with only duration of contact with family members and history of contact with people with TB. While most TB transmission and infection are thought to occur in non-household settings, we found that most social contact occurs in homes and with other families. Studies from Peru Town and Lima have demonstrated that a minority of tuberculosis transmission occurs within households [20].
Previous studies have demonstrated that participants with TB had a higher proportion of social contact with others with TB than did control participants, which was consistent with the results of our study [21]. Perhaps most importantly, most contacts with other known cases of TB occurred in non-home environments, indicating a risk of transmission to the community [22].
Contact time at home was significantly associated with TB status. Contact times at others’ homes, schools, markets or stores, workplaces, and hairdressers were associated with TB, but not to a statistically significant degree. The durations of social contact in health centers, parks, and restaurants were not associated with TB status. These results are somewhat consistent with the findings of a study conducted by Bui et al. [20].
Our study had several limitations. We used face-to-face interviews to collect long-term social contact data, and recall bias may have resulted in underestimation of social contacts or differential recall of contacts among cases. For example, the numbers of social contacts in parks, hairdressers, and restaurants were much lower than the figures reported in other studies in which diaries were used to collect social contact information [22,23]. Previous studies have shown that the use of prospective paper diaries, which require participants to record contacts during the day, yields more contacts than the retrospective questionnaire format used in the present study [22,24]. These results suggest that disease detection may be enhanced by focusing on long-term efforts in non-household environments.
In this study, the social contact patterns of participants with TB were compared with those of healthy individuals. We found that contact duration in the household and with individuals with TB are risk factors for TB, although most contacts with known TB cases occurred outside the home. Finally, participants with TB had fewer contacts but had longer durations of contact than control participants, and this pattern of contact may reflect TB transmission in the target population.
Supplemental materials are available at


The authors have no conflicts of interest associated with the material presented in this paper.


Financial support was provided by the Vice-Chancellor for Research at Ahvaz Jundishapur University of Medical Sciences.

We appreciate all the observers who helped us to conduct this project.


Conceptualization: Alavi SM, Amoori N. Data curation: Alavi SM, Amoori N. Formal analysis: Amini P, Amoori N. Funding acquisition: Alavi SM. Methodology: Cheraghian B, Amoori N, Alavi SM. Project administration: Alavi SM, Amoori N. Visualization: Amoori N, Amini P, Cheraghian B, Alavi SM. Writing – original draft: Amoori N, Alavi SM, Amini P, Cheraghian B. Writing – review & editing: Amoori N, AlaviSM, Cheraghian B, Amini P.

Figure 1
Total contact time reported by case and control participants based on social contact type.
Figure 2
Total contact time reported by case and controls based on the location of social contact.
Table 1
Demographic factors and social contacts reported by case and control participants
Variables Case (n=80) Control (n=172) p-value
Age (y) 34.1±15.3 32.5±12.0 0.080

Sex <0.001
 Male 62 (77.5) 89 (51.7)
 Female 18 (22.5) 83 (48.3)

Education level <0.001
 Illiterate 16 (20.0) 2 (1.2)
 Can read and write 13 (16.3) 3 (1.7)
 Up to elementary school 22 (27.5) 31 (18.0)
 Secondary school 15 (18.8) 47 (27.3)
 College or more 13 (17.6) 89 (51.7)

Monthly income (US$) 0.040
 <100 24 (30.0) 21 (12.2)
 100–200 26 (32.5) 59 (34.4)
 200–300 18 (22.5) 32 (18.6)
 >300 12 (15.0) 60 (34.9)

Employment status <0.001
 Unemployed 38 (47.5) 74 (43.0)
 Employed 42 (52.5) 98 (57.0)

Contact type 0.010
 Family 880 (57.0) 990 (49.5)
 Friend 380 (24.6) 410 (20.5)
 Co-worker 215 (13.9) 480 (24.0)
 Neighbor 70 (4.5) 120 (6.0)

Total non-household contacts 495 (50.2) 1332 (66.0) <0.001

Total contacts with tuberculosis 55 (32.0) 9 (3.6) <0.001

Place of contact <0.001
 Home 480 (31.7) 500 (22.0)
 Contact’s home 160 (10.5) 185 (8.2)
 School 13 (0.9) 54 (2.3)
 Workplace 201 (13.3) 529 (23.3)
 Market/store 282 (18.6) 320 (14.1)
 Health center 201 (13.3) 344 (15.1)
 Park 26 (1.7) 33 (1.5)
 Mosque 55 (3.6) 96 (4.2)
 Hairdresser 62 (4.1) 140 (6.1)
 Restaurant 30 (1.9) 67 (2.9)

Values are presented as mean±standard deviation or number (%).

Table 2
Social contacts in the prior month by type and location for case and control participants
Variable No. of contacts Contact duration (hr/wk)

Case Control p-value1 Case Control p-value1
Contact type
 All contact 23.41±14.52 23.92±13.45 <0.001 13.71±10.22 11.67±12.43 0.03
 Family member 15.84±12.62 14.3±11.57 0.08 7.73±4.31 5.78±4.22 <0.001
 Friend 2.21±3.43 2.65±3.32 0.39 2.73±1.87 2.12±2.86 0.23
 Co-worker 4.00±5.00 4.00±5.11 <0.001 2.76±3.54 2.84±3.61 0.92
 Neighbor 0.88±1.65 1.24±2.26 0.06 0.62±1.31 1.02±1.95 0.11

Household and TB status
 Household contacts 15.23±6.58 13.92±6.41 0.07 5.82±4.36 4.58±3.97 0.02
 Non-household contacts 7.21±5.35 7.68±5.44 0.02 11.92±12.78 9.53±11.82 0.75
 Contacts with TB 1.15±3.23 0.15±0.48 <0.001 5.32±4.16 1.58±2.22 <0.001

Place of contact
 Home 15.23±6.51 13.92±6.43 0.07 5.83±4.38 2.00±1.40 0.02
 Contact’s home 7.27±6.12 6.83±5.96 0.64 1.86±1.69 1.42±1.81 0.29
 School 0.16±0.73 0.31±0.93 0.15 2.10±1.65 2.27±2.41 0.82
 Workplace 4.42±6.35 4.61±6.23 <0.001 1.42±1.86 1.32±2.26 <0.001
 Market/store 5.00±3.56 3.00±3.32 0.01 3.31±2.31 0.33±1.00 <0.001
 Health center 2.48±3.46 1.92±2.73 0.02 2.03±2.53 0.24±0.65 0.04
 Park 0.07±0.38 0.07±0.48 0.99 0.23±0.82 0.59±0.72 0.09
 Mosque 0.68±1.54 0.55±1.42 0.52 0.36±0.74 0.25±0.56 0.85
 Hairdresser 0.77±0.98 0.81±0.98 0.77 0.50±0.80 0.59±0.72 0.45
 Restaurant 0.37±0.78 0.38±1.00 0.91 0.24±0.56 0.25±0.56 0.63

Values are presented as mean±standard deviation.

TB, tuberculosis.

1 t-test.

Table 3
Adjusted logistic regression results by contact type and location
Variables OR (95% CI) p-value
Contact type
 All contact 0.80 (0.61, 1.06) 0.280
 Family member 1.72 (1.10, 2.40) 0.010
 Friend 0.18 (0.01, 2.64) 0.180
 Co-worker 0.97 (0.56, 1.67) 0.370
 Neighbor 1.21 (0.25, 5.83) 0.810

Household and TB status
 Household contact 1.25 (1.02, 1.53) 0.030
 Non-household contact 0.18 (0.01, 2.64) 0.460
 Contacts with TB 1.53 (1.16, 2.01) <0.001

Place of contact
 Home 1.42 (1.19, 1.82) 0.030
 Contact’s home 1.53 (0.40, 5.85) 0.530
 School 1.66 (0.60, 4.57) 0.760
 Workplace 2.25 (0.79, 6.24) 0.120
 Market/store 0.72 (0.46, 1.26) 0.120
 Health center 0.41 (0.17, 1.62) 0.400
 Park 0.71 (0.44, 1.18) 0.400
 Mosque 0.79 (0.26, 2.43) 0.690
 Hairdresser 2.14 (0.81, 5.66) 0.120
 Restaurant 0.77 (0.08, 6.98) 0.690

OR, odds ratio; CI, confidence interval; TB, tuberculosis.

  • 1. MacNeil A, Glaziou P, Sismanidis C, Date A, Maloney S, Floyd K. Global epidemiology of tuberculosis and progress toward meeting global targets - worldwide, 2018. MMWR Morb Mortal Wkly Rep 2020;69(11):281-285ArticlePubMedPMC
  • 2. Tavakoli A. Incidence and prevalence of tuberculosis in Iran and neighboring countries. Zahedan J Res Med Sci 2017;19(7):e9238Article
  • 3. World Health Organization. Global tuberculosis report; 2018 [cited 2022 Aug 1]. Available from:
  • 4. Khan A, Marks S, Katz D, Morris SB, Lambert L, Magee E, et al. Changes in tuberculosis disparities at a time of decreasing tuberculosis incidence in the United States, 1994–2016. Am J Public Health 2018;108(S4):S321-S326ArticlePubMedPMC
  • 5. Goldhaber-Fiebert JD, Jeon CY, Cohen T, Murray MB. Diabetes mellitus and tuberculosis in countries with high tuberculosis burdens: individual risks and social determinants. Int J Epidemiol 2011;40(2):417-428ArticlePubMedPMC
  • 6. Johnstone-Robertson SP, Mark D, Morrow C, Middelkoop K, Chiswell M, Aquino LD, et al. Social mixing patterns within a South African township community: implications for respiratory disease transmission and control. Am J Epidemiol 2011;174(11):1246-1255ArticlePubMedPMC
  • 7. Zelner JL, Murray MB, Becerra MC, Galea J, Lecca L, Calderon R, et al. Identifying hotspots of multidrug-resistant tuberculosis transmission using spatial and molecular genetic data. J Infect Dis 2016;213(2):287-294ArticlePubMedPMC
  • 8. Zelner JL, Murray MB, Becerra MC, Galea J, Lecca L, Calderon R, et al. Age-specific risks of tuberculosis infection from household and community exposures and opportunities for interventions in a high-burden setting. Am J Epidemiol 2014;180(8):853-861ArticlePubMedPMC
  • 9. Bhargava A, Pai M, Bhargava M, Marais BJ, Menzies D. Can social interventions prevent tuberculosis? The Papworth experiment (1918–1943) revisited. Am J Respir Crit Care Med 2012;186(5):442-449ArticlePubMed
  • 10. Oren E, Koepsell T, Leroux BG, Mayer J. Area-based socio-economic disadvantage and tuberculosis incidence. Int J Tuberc Lung Dis 2012;16(7):880-885ArticlePubMed
  • 11. Hargreaves JR, Boccia D, Evans CA, Adato M, Petticrew M, Porter JD. The social determinants of tuberculosis: from evidence to action. Am J Public Health 2011;101(4):654-662ArticlePubMedPMC
  • 12. Ferraro CF, Trotter CL, Nascimento MC, Jusot JF, Omotara BA, Hodgson A, et al. Household crowding, social mixing patterns and respiratory symptoms in seven countries of the African meningitis belt. PLoS One 2014;9(7):e101129ArticlePubMedPMC
  • 13. Worrell MC, Kramer M, Yamin A, Ray SM, Goswami ND. Use of activity space in a tuberculosis outbreak: bringing homeless persons into spatial analyses. Open Forum Infect Dis. 2017. 4(1):ofw280.ArticlePubMedPMCPDF
  • 14. Yates TA, Khan PY, Knight GM, Taylor JG, McHugh TD, Lipman M, et al. The transmission of Mycobacterium tuberculosis in high burden settings. Lancet Infect Dis 2016;16(2):227-238ArticlePubMed
  • 15. Horby P, Pham QT, Hens N, Nguyen TT, Le QM, Dang DT, et al. Social contact patterns in Vietnam and implications for the control of infectious diseases. PLoS One 2011;6(2):e16965ArticlePubMedPMC
  • 16. Grijalva CG, Goeyvaerts N, Verastegui H, Edwards KM, Gil AI, Lanata CF, et al. A household-based study of contact networks relevant for the spread of infectious diseases in the highlands of Peru. PLoS One 2015;10(3):e0118457ArticlePubMedPMC
  • 17. Ahajjam S, Badir H. Identification of influential spreaders in complex networks using HybridRank algorithm. Sci Rep 2018;8(1):11932ArticlePubMedPMCPDF
  • 18. Ali M. Treating tuberculosis as a social disease. Lancet 2014;383(9936):2195ArticlePubMed
  • 19. Kitsak M, Gallos LK, Havlin S, Liljeros F, Muchnik L, Stanley HE, et al. Identification of influential spreaders in complex networks. Nature Phys 2010;6: 888-893ArticlePDF
  • 20. Bui DP, Oren E, Roe DJ, Brown HE, Harris RB, Knight GM, et al. A case-control study to identify community venues associated with genetically-clustered, multidrug-resistant tuberculosis disease in Lima, Peru. Clin Infect Dis 2019;68(9):1547-1555ArticlePubMedPMCPDF
  • 21. Otero L, Krapp F, Tomatis C, Zamudio C, Matthys F, Gotuzzo E, et al. High prevalence of primary multidrug resistant tuberculosis in persons with no known risk factors. PLoS One 2011;6(10):e26276ArticlePubMedPMC
  • 22. Bui DP. Social contact patterns associated with multidrug-resistant tuberculosis [dissertation]. Tucson: University of Arizona; 2018
  • 23. Wood R, Racow K, Bekker LG, Morrow C, Middelkoop K, Mark D, et al. Indoor social networks in a South African township: potential contribution of location to tuberculosis transmission. PLoS One 2012;7(6):e39246ArticlePubMedPMC
  • 24. McCaw JM, Forbes K, Nathan PM, Pattison PE, Robins GL, Nolan TM, et al. Comparison of three methods for ascertainment of contact information relevant to respiratory pathogen transmission in encounter networks. BMC Infect Dis 2010;10: 166ArticlePubMedPMCPDF

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