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Cough-aerosol cultures of Mycobacterium tuberculosis in the prediction of outcomes after exposure. A household contact study in Brazil

  • Carlos Acuña-Villaorduña ,

    Roles Formal analysis, Writing – original draft, Writing – review & editing

    Affiliation Section of Infectious Diseases, Department of Medicine, Boston University School of Medicine and Boston Medical Center, Boston, Massachusetts, United States of America

  • Luiz Guilherme Schmidt-Castellani,

    Roles Data curation, Project administration, Writing – review & editing

    Affiliation Mycobacteriology Laboratory, Núcleo de Doenças Infecciosas, Universidade Federal do Espírito Santo, Vitória, Brazil

  • Patricia Marques-Rodrigues,

    Roles Data curation, Writing – review & editing

    Affiliation Núcleo de Doenças Infecciosas, Universidade Federal do Espírito Santo, Vitória, Brazil

  • Laura F. White,

    Roles Formal analysis

    Affiliation Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America

  • David Jamil Hadad,

    Roles Data curation

    Affiliation Núcleo de Doenças Infecciosas, Universidade Federal do Espírito Santo, Vitória, Brazil

  • Mary Gaeddert,

    Roles Data curation, Project administration, Writing – review & editing

    Affiliation Section of Infectious Diseases, Department of Medicine, Boston University School of Medicine and Boston Medical Center, Boston, Massachusetts, United States of America

  • Jerrold J. Ellner,

    Roles Funding acquisition, Investigation, Supervision, Writing – review & editing

    Affiliation Section of Infectious Diseases, Department of Medicine, Boston University School of Medicine and Boston Medical Center, Boston, Massachusetts, United States of America

  • Kevin P. Fennelly,

    Roles Conceptualization, Methodology, Writing – review & editing

    Affiliation Pulmonary Clinical Medicine Section, Cardiovascular and Pulmonary Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, United States of America

  • Moises Palaci,

    Roles Data curation, Resources, Supervision, Writing – review & editing

    Affiliation Mycobacteriology Laboratory, Núcleo de Doenças Infecciosas, Universidade Federal do Espírito Santo, Vitória, Brazil

  • Reynaldo Dietze,

    Roles Conceptualization, Project administration, Supervision, Writing – review & editing

    Affiliations Núcleo de Doenças Infecciosas, Universidade Federal do Espírito Santo, Vitória, Brazil, Global Health & Tropical Medicine - Instituto de Higiene e Medicina Tropical - Universidade Nova de Lisboa, Lisbon, Portugal

  • Edward C. Jones-López

    Roles Conceptualization, Funding acquisition, Methodology, Writing – review & editing

    Affiliation Section of Infectious Diseases, Department of Medicine, Boston University School of Medicine and Boston Medical Center, Boston, Massachusetts, United States of America



Mycobacterium tuberculosis cultures of cough-generated aerosols from patients with pulmonary tuberculosis (TB) are a quantitative method to measure infectiousness and to predict secondary outcomes in exposed contacts. However, their reproducibility has not been established.


To evaluate the predictive value of colony-forming units (CFU) of M. tuberculosis in cough aerosols on secondary infection and disease in household contacts in Brazil.


Adult sputum smear+ and culture+ pulmonary TB cases underwent a standard evaluation and were categorized according to aerosol CFU. We evaluated household contacts for infection at baseline and at 8 weeks with TST and IGRA, and secondary disease.


We enrolled 48 index TB cases; 40% had negative aerosols, 27% low aerosols (<10 CFU) and 33% high aerosols (≥10 CFU). Of their 230 contacts, the proportion with a TST ≥10 mm at 8 weeks was 59%, 65% and 75%, respectively (p = 0.34). Contacts of high aerosol cases had greater IGRA readouts (median 4.6 IU/mL, IQR 0.02–10) when compared to those with low (0.8, 0.2–10) or no aerosol (0.1, 0–3.7; p = 0.08). IGRA readouts in TST converters of high aerosol cases (median 20 IU/mL, IQR 10–24) were larger than those from aerosol-negative (0.13, 0.04–3; p = o.o2). 8/9 (89%) culture+ secondary TB cases occurred in contacts of aerosol+ cases.


Aerosol CFU predicts quantitatively IGRA readouts among household contacts of smear positive TB cases. Our results strengthen the argument of using cough aerosols to guide targeted preventive treatment strategies, a necessary component of current TB elimination projections.


Successful transmission of Mycobacterium tuberculosis results from a complex web of interactions between the source case, the exposed contact and the infecting pathogen within a variety of environments [1,2]. Together, these factors determine the number and viability of M. tuberculosis bacilli contained in cough-generated aerosols, the infectious moiety in tuberculosis (TB) [3,4]. Yet, despite long standing evidence for the latter, most of the evidence on TB transmission outcomes is based on the visualization of acid-fast bacilli (AFB) in sputum, which is still regarded as the definitive marker for infectiousness. However, in addition to poorly predicting transmission, sputa specimens fail to consider the complexities and stresses required for M. tuberculosis aerosolization, a necessary first step for successful transmission [1,5]

Over the last decade, our group has shown that the number of colony forming units (CFU) of M. tuberculosis cultured in cough-generated aerosols is a quantitative and more precise method for measuring source infectiousness and risk of infection in exposed contacts than sputum AFB smear microscopy. We have observed wide variability in aerosol CFU even among sputum AFB+ and culture-positive TB patients, [6] and found both qualitative and quantitative differences in tuberculin skin test (TST) and interferon gamma release assay (IGRA) readouts between contacts of aerosol-positive and aerosol-negative TB cases [7]. Significantly, in a follow-up study, household contacts of high aerosol (≥10 CFU) TB patients were at increased risk of incident TB disease [8]. Taken together, these data suggest aerosol CFU represent a promising marker of the infecting inoculum (e.g. inhaled dose), and that the inoculum size is a critical determinant modulating TB outcomes in humans, as observed in experimental TB models [5,9].

Whereas the aerosol collection method we use is validated [10, 11], the generalizability of our findings in exposed contacts is unknown. In our initial studies, the predictive value of aerosols was most evident in household contacts undergoing TST conversion, but less so in those that were TST-positive at baseline [67]. The utility of aerosols in settings with a lower TB prevalence, different environmental conditions (i.e. ambient humidity and temperature), and different M. tuberculosis strains is unknown. We conducted this household contact study to determine the reproducibility of cough aerosols to predict exposure outcomes in contacts of pulmonary TB patients.


Study population

This study was conducted at the Núcleo de Doenças Infecciosas (NDI) located in Vitória, the capital city of the State of Espírito Santo, Brazil. The NDI has organized a network of five laboratories in the metropolitan region of Vitória that serve a network of 16 TB clinics. The prevalence of HIV in the general population is <1%, and 7% in TB cases. The annual TB incidence in Espírito Santo is 38/100,000 inhabitants [12].


TB cases.

Pulmonary TB patients identified through the NDI clinic network were eligible to participate, provided they fulfilled the following: 1) age ≥18 years with cough ≥3 weeks and 2) new TB episode with ≥1 sputum specimen with AFB ≥2+ with subsequent M. tuberculosis growth in culture. We excluded index cases who were HIV-infected, had a history of TB treatment, or who were too ill to consent, unable to understand, or to comply with the study protocol. To minimize differences in exposure time between study households, participating families were screened and enrolled within the first 2 weeks after the index case first presented to the municipal TB clinic. We collected clinical information and measured cough severity using a self-reported visual analog cough scale (VACS) [13], and the Leicester Cough Questionnaire (LCQ) [14], as reported [15]. We obtained three sputa specimens for AFB smear (auramine O fluorescent stain) [16], solid media (Ogawa-Kudoh) [17], and liquid (MGIT 960) cultures. The radiological extent of disease was graded on a four-category ordinal scale (normal, minimal, moderate and far-advanced) by an experienced radiologist [18]. We cultured M. tuberculosis from cough aerosols using the cough aerosol sampling system (CASS), as described [19]. Briefly, patients were instructed to cough into the CASS apparatus for two 5-minute periods separated by a 5-minute rest. CASS agar plates were read weekly for up to 6 weeks to count CFU of M. tuberculosis, the primary CASS outcome. All patients were offered TB treatment according to Brazilian guidelines [20].

Household contacts.

We followed recommendations of the Brazilian National TB Program for household contact investigations [20]. Study staff visited dwellings to verify the identity of contacts, record clinical information, measure individual contact time with the index case, and to perform an environmental evaluation (crowding and ventilation). We recorded demographic and clinical characteristics of contacts and evaluated them for M. tuberculosis infection with both TST and IGRA, according to a predefined testing algorithm (S1 File) [15].

Secondary TB cases.

In November 2017, we searched the Vitória TB Control Program records and the Brazilian National Notifiable Disease Information System (SINAN) database for the name, address, and date of birth of household contacts enrolled in the study to ascertain those that had developed subsequent TB; for those identified as TB cases, we registered date of diagnosis, AFB smear and culture results. We defined microbiologically confirmed TB as secondary TB cases among contacts with a positive culture for M. tuberculosis.

Statistical methods

Our primary exposure variable was the cough aerosol status of the index TB patient living in the household. We categorized households into: aerosol negative (0 CFU), low aerosol (1–9 CFU), and high aerosol (≥10 CFU). We chose a 10 CFU cut-off because at this point we noted an increase risk in TST conversion in previous studies [6]. Our primary outcome was TST ≥10mm in contacts, using the maximum TST for each individual (e.g. 1st or 2nd TST), and completed an age-stratified analysis of TST results. We also performed a quantitative analysis of IGRA readouts using standard box plots to represent normalized IGRA values for each contact at 8–12 weeks. Our secondary outcome was microbiologically confirmed TB disease in contacts; given the small number of secondary TB cases, we categorized the exposure for this analysis as aerosol negative vs. aerosol positive. We calculated descriptive statistics to identify clinical and demographic differences between contact groups. To account for clustering within households, we calculated P values using generalized estimating equations or non-parametric tests if appropriate (SAS 9.1, SAS Institute, Inc., Cary, NC). Dataset is available in S1 Dataset.

Ethical approvals

The study was approved by the Comitê de Ética em Pesquisa do Centro de Ciências da Saúde—Universidade Federal do Espírito Santo and the Comissão Nacional de Ética em Pesquisa (CONEP), and the Institutional Review Boards of Boston University Medical Center and New Jersey Medical School—Rutgers University (formerly UMDNJ). We obtained written informed consent and assent in Portuguese in accordance with age-specific ethical guidelines.


From April 2013 to June 2015, we screened 53 TB cases, but excluded 5 (10%) of them (Figure A in S1 File). Also, of the 253 eligible household contacts, 23 (9%) were excluded because of missing TST results. Therefore, the study population comprised 48 index TB cases and their 230 household contacts. Excluded contacts were similar to those included in terms of age (p = 0.35), gender (p = 0.57) and BCG vaccination scar (p = 0.78).

Index TB cases and M. tuberculosis in cough aerosols

Index TB cases were mostly male (75%), with a median [interquartile range, IQR] age of 31 years [22–44], had a median duration of cough of 12 [7–24] weeks, 75% were sputum AFB 3+, and 69% had advanced disease on chest radiograph Table 1 and Table A in S1 File. Nineteen (40%) were aerosol-negative, 13 (27%) had low aerosols (1–9 CFU) and 16 (33%) had high aerosols (≥10 CFU); there was significant variability in CFU among aerosol-positive patients (median 31, range 1–333). Unlike sputum AFB, aerosol CFU was not associated with markers of pulmonary disease severity or bacterial load in sputum (Table 1).

Table 1. Characteristics of 48 index tuberculosis cases and their 230 household contacts according to the number of colony-forming units of M. tuberculosis in cough-generated aerosols and sputum acid-fast bacilli smear microscopy results.

Household contacts and baseline TST results

Household contacts were young (median age 23 [15–42]), majority female (58%) and 84% had a BCG scar (Table 1). The number of contacts exposed to aerosol-negative, low, and high aerosol cases was 82 (36%), 64 (28%) and 84 (37%), respectively (Figure A in S1 File). At baseline (Table 2 and Fig 1, Panel A), the frequency of TST ≥10mm in contacts increased following a dose-response pattern as aerosol CFU increased: aerosol negative (59%), low aerosol (67%), and high aerosol (75%), respectively (p = 0.46); these results were unchanged when using a TST cut-off of 5mm or 15 mm. Similarly, in a quantitative analysis, the median TST diameter increased in parallel to aerosol CFU. In contrast, when using sputum AFB to risk-stratify the exposure, neither the proportion of contacts with TST ≥10 mm nor the TST diameter followed a dose-response pattern.

Fig 1. TST and IGRA results in 230 household contacts of TB patient according to the number of CFU of M. tuberculosis in cough-generated aerosols or AFB smear microscopy in the index TB case.

(A) Histograms represent the proportion of contacts with a TST ≥10mm at baseline (black) and those with TST conversion (grey). The solid line represents the median TST diameter (mm) for contacts with TST ≥10mm at baseline (circles) and maximum TST for those with TST conversion (triangles) for each exposure group. (B) Standard box plots of maximum IGRA readouts in contacts of smear + culture + TB cases. P = 0.08 for aerosol CFU, p = 0.26 for AFB sputum smear (C) Standard box plots of IGRA readouts in contacts with TST conversion. P = 0.02 for aerosol CFU, p = 0.33 for AFB sputum smear.

Table 2. Tuberculin skin test (TST) and interferon gamma release assay (IGRA) in household contacts according to the number of colony-forming units of M. tuberculosis in cough-generated aerosols and sputum acid-fast bacilli smear microscopy results.

TST conversion in contacts

Seventy-six (33%) contacts had TST <10mm at baseline and were therefore at risk of TST conversion (Fig 1, Panel A). Of these, 34/82 (41%), 21/64 (33%) and 21/84 (25%) were contacts of aerosol-negative, low and high aerosol TB patients, respectively (p = 0.46). By 8–12 weeks after enrollment, 16 (21%) contacts had undergone TST conversion. Of these, 7 (21%) were contacts of aerosol-negative, 3 (14%) of low and 6 (29%) of high aerosol cases (p = 0.52). The median diameter in TST converters of high aerosol (21 mm [IQR 20–24]) patients was larger than in those of aerosol-negative (14 mm [IQR 14–16], P = 0.02) patients.

IGRA readouts in household contacts

To examine the possibility of TST confounding by BCG and boosting, we analyzed infection outcomes according to IGRA. Qualitatively, the proportion of individuals with IGRA+ at study conclusion (8–12 weeks) followed a similar aerosol dependent dose-response pattern to that observed with TST results (Table 2). Similarly, quantitative IGRA readouts showed a strong dose-response pattern according to aerosol CFU, both when measured as mean maximum IGRA values per contact (Fig 1, Panel B; P = 0.08) or, in TST converters only (Fig 1, Panel C; P = 0.02). As observed with TST results, these quantitative IGRA differences were not apparent when using sputum AFB to risk-stratify the exposure (Table 2 and Fig 1).

Age stratified analysis of TST results

To further elucidate the potential effect of BCG on TST and indirectly estimate community-based transmission, we performed an age-stratified analysis of TST results. The proportion of contacts with TST ≥ 10 mm was similar across all ages, 0–10 years 26/37 (70%), 11–20 years 42/56 (75%), 21–40 years 54/70 (77%) and > 40 years 46/61 (75%). However, except for young children (0–10 years) where BCG could be influencing TST results, the prevalence of infection across contact age groups was consistently lower in contacts of aerosol-negative patients when compared to contacts of aerosol-positive patients, suggesting TST-positive results in the former likely reflect cumulative community exposures. Further, TST induration sizes and IGRA readouts were consistently larger for aerosol-positive HHCs in each age group (Fig 2).

Fig 2. Proportion of household contacts with a positive (≥10mm) tTST and IGRA at study completion (8–12 weeks) by contact age group and CFU of M. tuberculosis in cough-generated aerosols in the index case: Negative (CFU = 0) or positive (CFU ≥1).

The “N” under each histogram indicates the number of contacts within each age-exposure category. The stars (*) represent the median TST or mean IGRA readout associated with each group.

Secondary TB disease in household contacts

After a median follow-up of 3.6 years, 13 of 230 (5.6%) contacts developed secondary TB disease, of which 9 (4%) were culture-positive cases. Of the latter, 1/82 (1.2%) was in contacts of aerosol-negative cases and 8/148 (5.4%) in contacts of aerosol-positive cases (p = 0.176). The corresponding incidence of culture-proven secondary TB disease was 356 cases per 100,000 (95% CI 50–2,331) and 1,439 (95% CI 719–2,878), respectively. When all 13 secondary TB cases were included (4/82 [5%] vs. 9/148 [6%]), the association between positive aerosols and risk of secondary TB disease was weaker (p = 0.73).


In this household contact study in a setting with moderate TB incidence, we found that contacts of high aerosol TB patients were more likely to become infected and had larger TST and IGRA readouts compared to contacts of low and negative aerosol TB cases. Moreover, albeit limited by a small sample size, most cases of culture-proven secondary TB in contacts clustered around aerosol–positive index TB cases. Data from this study are consistent with our initial study in Uganda where contacts of high aerosol cases were also more frequently infected, displayed larger TST and IGRA readouts [7], and were at increased risk of incident TB disease (8). Taken together, these findings confirm that aerosol CFU is a promising marker of transmission risk and strengthens our hypothesis that the inoculum size is important in modulating TB outcomes after exposure in humans [5].

Close contacts of pulmonary TB cases are known to have increased risk of TB infection and disease when compared to the general population [2]. However, there is abundant both experimental and epidemiological evidence of marked variability in risk, as most secondary infections and disease cases cluster around a minority of TB cases [24]. Our findings that only a minority of sputum AFB+ (and culture+) TB cases naturally produce viable aerosolized M. tuberculosis during cough- is consistent with the existence of disease superspreaders [21]. As such, measuring cough aerosols allows identification of a subset of individuals at a particularly high risk of infection and disease, presumably as a result of a larger infectious dose. It follows that these contacts would benefit most of preventive therapy, while also increasing the efficiency of household contact investigations by redefining the population at highest risk. As we observed previously, these findings were not apparent through the prism of two standard indicators of infectiousness such as sputum AFB and lung cavitation on chest radiograph suggesting that risk stratification is limited without aerosols, the infectious moiety in TB [3].

In this study, we observed a dose response pattern in prevalent TB infection per aerosol group, an association that was not observed in Uganda. This suggests the aerosol phenotype is stable over time, as the 1st TST results reflect the index cases’ infectiousness prior to study initiation. Interestingly, the proportion of aerosol-negative contacts with TST ≥10 mm at baseline was 59%, which is above the expected level of community transmission in Brazil [22]–indicating TST positivity does occur after exposure to aerosol-negative TB disease. However, whereas there was variability in individual results, the median IGRA in contacts of aerosol-negative TB patients was close to zero, suggesting that a TST+/IGRA- result in these contacts may be measuring a qualitatively different infection when compared to a comparatively positive TST result that is also accompanied by a robust IGRA response in contacts of aerosol-positive patients.

Some differences from our initial Ugandan studies [68] are noteworthy. First, we found a higher rate of aerosol production (60% vs 36%) in TB cases from Brazil. We suspect this is because in this study most patients were sampled prior to initiating antituberculous treatment. The rapid decrease of culturable organisms in aerosols is consistent with both experimental and clinical studies showing a marked reduction in infectiousness promptly after chemotherapy is started, even when sputum AFB smear and culture remain positive [3, 23,24]. Second, we did not find a significant difference in TST conversion per aerosol groups, but rather observed the effect of aerosols on TST positivity at baseline. Given the small number of TST converters in this study (n = 16), our study was likely underpowered to detect differences in TST conversion. Nevertheless, as observed in Uganda, IGRA readouts among Brazilian TST converters of high aerosol cases were significantly higher than those of aerosol-negative cases–suggesting that some conversions in aerosol-negative contacts could be due to TST boosting or low dose infection, and hence, presumably carry a lesser risk of progression to TB disease. An alternative explanation is that a delayed IGRA response is due to a less intense infectious exposure [25]. Finally, Ugandan contacts had a higher frequency of TST ≥10 mm and larger TST induration sizes, likely reflecting increased community transmission and more advanced disease in TB cases in the former setting.

We used TST as our primary outcome because it is the most widely used test to diagnose M. tuberculosis infection in resource constrained settings and to be consistent with our prior Ugandan study. Although BCG is known to produce false positive TST results, the effect is minimal after 10 years of age [26]. Further, 75% of HHCs had TST ≥ 10 mm compared with 53% of IGRA ≥ 0.35 UI/ml which is consistent with other household contact studies in developing countries whereas TST often yields more positive results compared with IGRA [2728].

We have now accumulated enough evidence to demonstrate that our findings are neither spurious nor related to the aerosol collector device used [10]. To date, our group has collected aerosols in more than 25o patients from The United States, Uganda, and Brazil, and others have validated the CASS apparatus in South Africa [11]. Taken together, our data confirm the marked variability in TB transmission described in seminal studies [3] and in multiple epidemiological studies in both low and high burden settings [29,30]. Future studies should evaluate the use of exposure-based interventions where targeted preventive therapy is provided based on the ability of the TB index case to aerosolize M. tuberculosis rather than in the TST/IGRA status of the contacts and compare the efficacy and cost-effectiveness of such a strategy against universal preventive therapy, gene signatures blood biomarkers [31] and predictive scores [3234].

Our study has limitations. In its current form, the CASS device is designed as a research tool rather than a point of care test, which limits its ability to be used at peripheral health care centers in developing countries where most TB cases are concentrated. Future designs should try to improve its applicability in resources constrained settings and to incorporate polymerase chain reaction (PCR) technologies to more rapidly identify aerosolized M. tuberculosis, although this improvement in time-to-result may not adequately reflect bacterial viability in aerosols [35]. Importantly, in the present study, the number of CFU in aerosols after two weeks of growth in cultures did not alter the final categorization (e.g. negative, low or high), suggesting that exposure-based interventions may be implementable in a timely manner. We had an important number of missing IGRA results in contacts; selection bias may have been introduced if differential IGRA levels were seen on contacts of high aerosol TB cases. We did not have access to genotypic testing of M. tuberculosis isolates to confirm that secondary TB cases originated from the index TB case in the household; however, Vitória is a setting with moderate TB incidence and thus we expect that most of the secondary TB cases originated from the household TB index case. Finally, our study was underpowered.

In conclusion, cultures of M. tuberculosis from cough-generated aerosols predict risk of infection, as measured by both qualitative and quantitative TST and IGRA readouts. Our results further strengthens the argument of using cough aerosols to implement targeted preventive therapy, a necessary component for current TB elimination targets.

Supporting information

S1 File.

Table A: Additional Characteristics of 48 Index Tuberculosis Cases and their 230 Household Contacts Figure A: Study profile. IC = Index tuberculosis (TB) cases; HHC = Household contacts; TST = Tuberculin skin test; IGRA = Interferon gamma release assay (Quantiferon Gold In-Tube).


S1 Dataset. Database of 48 index tuberculosis cases and their 230 household contacts.



The authors would like to acknowledge the invaluable contribution made by Geisa Fregona, PhD (study coordinator), Lucilia Pereira Dutra Molina, MD (medical officer), Roberto Rabello de Souza, Thamy Carvalho Lacerda and Andressa da Silva Borges (study nurses), Ethel Leonor Noia Maciel (support and supervision of field team), Ana Carolina Oliveira Cheibub (NDI data manager), Antônio Lourenço Canal and Eliseu Soares Rangel (NDI drivers), Leduc Mageski (NDI logistician), João Batista Pereira da Silva and Mário César Gomes (NDI TB laboratory technicians), and Tatiana Resende Co (NDI TB laboratory supervision). We also wish to thank all the personnel affiliated with the TB programs in Vitória, Serra, Maruípe and Vila Velha for their interest and dedication to this study.


  1. 1. Roy CJ, Milton DK. Airborne transmission of communicable infection—the elusive pathway. N Engl J Med. 2004 Apr 22;350(17):1710–2. pmid:15102996.
  2. 2. Yates TA, Khan PY, Knight GM, Taylor JG, McHugh TD, Lipman M. The transmission of Mycobacterium tuberculosis in high burden settings. Lancet Infect Dis. 2016 Feb;16(2):227–38. Epub 2016 Jan 26. pmid:26867464
  3. 3. Riley RL, Mills CC, O'Grady F, Sultan LU, Wittstadt F, Shipvuri DN. Infectiousness of air from a tuberculosis ward. Ultraviolet irradiation of infected air: comparative infectiousness of different patients. Am Rev Respir Dis. 1962 Apr;85:511–25. pmid:14492300.
  4. 4. Escombe AR, Oeser C, Gilman RH, Navincopa M, Ticona E, Martínez C, et al. The detection of airborne transmission of tuberculosis from HIV-infected patients, using an in vivo air sampling model. Clin Infect Dis. 2007 May 15;44(10):1349–57. Epub 2007 Apr 9. pmid:17443474.
  5. 5. Fennelly KP, Jones-López EC. Quantity and Quality of Inhaled Dose Predicts Immunopathology in Tuberculosis. Front Immunol. 2015 Jun 29;6:313. pmid:26175730
  6. 6. Fennelly KP, Jones-López EC, Ayakaka I, Kim S, Menyha H, Kirenga B, et al. Variability of infectious aerosols produced during coughing by patients with pulmonary tuberculosis. Am J Respir Crit Care Med. 2012 Sep 1;186(5):450–7. pmid:22798319
  7. 7. Jones-López EC, Namugga O, Mumbowa F, Ssebidandi M, Mbabazi O, Moine S, et al. Cough aerosols of Mycobacterium tuberculosis predict new infection: a household contact study. Am J Respir Crit Care Med. 2013 May 1;187(9):1007–15 pmid:23306539
  8. 8. Jones-López EC, Acuña-Villaorduña C, Ssebidandi M, Gaeddert M, Kubiak RW, Ayakaka I, et al. Cough Aerosols of Mycobacterium tuberculosis in the Prediction of Incident Tuberculosis Disease in Household Contacts. Clin Infect Dis. 2016 Jul 1;63(1):10–20. pmid:27025837
  9. 9. Saini D, Hopkins GW, Seay SA, Chen CJ, Perley CC, Click EM, et al. Ultra-low dose of Mycobacterium tuberculosis aerosol creates partial infection in mice. Tuberculosis (Edinb). 2012 Mar;92(2):160–5
  10. 10. Acuña-Villaorduña C, White LF, Fennelly KP, Jones-López EC. Tuberculosis transmission: sputum vs aerosols. Lancet Infect Dis. 2016 Jul;16(7):770–771.
  11. 11. Dheda K, Limberis JD, Pietersen E, Phelan J, Esmail A, Lesosky M, et al. Outcomes, infectiousness, and transmission dynamics of patients with extensively drug-resistant tuberculosis and home-discharged patients with programmatically incurable tuberculosis: a prospective cohort study. Lancet Respir Med. 2017 Apr;5(4):269–281. pmid:28109869
  12. 12. Prado TN, Caus AL, Marques M, Maciel EL, Golub JE, Miranda AE. Epidemiological profile of adult patients with tuberculosis and AIDS in the state of Espírito Santo, Brazil: cross-referencing tuberculosis and AIDS databases. J Bras Pneumol. 2011 Jan-Feb;37(1):93–9 pmid:21390437
  13. 13. Raj AA, Birring SS. Clinical assessment of chronic cough severity. Pulm Pharmacol Ther. 2007;20(4):334–7 pmid:17113330
  14. 14. Birring SS, Fleming T, Matos S, Raj AA, Evans DH, Pavord ID. The Leicester Cough Monitor: preliminary validation of an automated cough detection system in chronic cough. Eur Respir J. 2008 May;31(5):1013–8 pmid:18184683
  15. 15. Jones-López EC, Kim S, Fregona G, Marques-Rodrigues P, Hadad DJ, Molina LP, et al. Importance of cough and M. tuberculosis strain type as risks for increased transmission within households. PLoS One. 2014 Jul 2;9(7):e100984 pmid:24988000
  16. 16. Organization. WH. Laboratory Services in Tuberculosis Control: Part II Microscopy; 1998 No. WHO/TB/98.258.
  17. 17. Palaci M, Peres RL, Maia R, Cunha EA, Ribeiro MO, Lecco R, et al. Contribution of the Ogawa-Kudoh swab culture method to the diagnosis of pulmonary tuberculosis in Brazil. Int J Tuberc Lung Dis. 2013 Jun;17(6):782–6 pmid:23676162
  18. 18. Falk AOCJ, Pratt C. Classification of pulmonary tuberculosis. In: Diagnostic standards and classification of tuberculosis. New York, NY: National Tuberculosis and Respiratory Disease Association; 1969.
  19. 19. Fennelly KP, Martyny JW, Fulton KE, Orme IM, Cave DM, Heifets LB. Cough-generated aerosols of Mycobacterium tuberculosis: a new method to study infectiousness. Am J Respir Crit Care Med. 2004 Mar 1;169(5):604–9 pmid:14656754
  20. 20. Ministério da Saúde. Secretaria de Vigilância em Saúde. Programa Nacional de Controle da Tuberculose. Manual de Recomendações para o Controle da Tuberculose. Brasília: Ministério da Saúde; 2010.
  21. 21. Lloyd-Smith JO, Schreiber SJ, Kopp PE, Getz WM. Superspreading and the effect of individual variation on disease emergence. Nature. 2005 Nov 17;438(7066):355–9 pmid:16292310
  22. 22. Dye C, Scheele S, Dolin P, Pathania V, Raviglione MC. Consensus statement. Global burden of tuberculosis: estimated incidence, prevalence, and mortality by country. WHO Global Surveillance and Monitoring Project. JAMA. 1999 Aug 18;282(7):677–86. pmid:10517722
  23. 23. Dharmadhikari AS, Mphahlele M, Venter K, Stoltz A, Mathebula R, Masotla T, et al. Rapid impact of effective treatment on transmission of multidrug-resistant tuberculosis. Int J Tuberc Lung Dis. 2014 Sep;18(9):1019–25. pmid:25189547
  24. 24. Yuen CM, Amanullah F, Dharmadhikari A, Nardell EA, Seddon JA, Vasilyeva I, et al. Turning off the tap: stopping tuberculosis transmission through active case-finding and prompt effective treatment. Lancet. 2015 Dec 5;386(10010):2334–43. pmid:26515675
  25. 25. Collins LF, Geadas C, Ellner JJ. Diagnosis of Latent Tuberculosis Infection: Too Soon to Pull the Plug on the Tuberculin Skin Test. Ann Intern Med. 2016 Jan 19;164(2):122–4. pmid:26642354
  26. 26. Farhat M, Greenaway C, Pai M, Menzies D. False-positive tuberculin skin tests: what is the absolute effect of BCG and non-tuberculous mycobacteria? Int J Tuberc Lung Dis. 2006 Nov;10(11):1192–204 pmid:17131776
  27. 27. Castellanos ME, Kirimunda S, Martinez L, Quach T, Woldu H, Kakaire R, et al. Performance of the QuantiFERON -TB Gold In-Tube assay in tuberculin skin test converters: a prospective cohort study. IntJ Tuberc Lung Dis. 2018 Sep 1;22(9):1000–1006
  28. 28. Chandrasekaran P, Mave V, Thiruvengadam K, Gupte N, Shivakumar SVBY, Hanna LE, et al. Tuberculin skin test and QuantiFERON-Gold In Tube assay for diagnosis of latent TB infection among household contacts of pulmonary TB patients in high TB burden setting. PLoS One. 2018 Aug 1;13(8):e0199360 pmid:30067752
  29. 29. Van Geuns HA, Meijer J, Styblo K. Results of contact examination in Rotterdam, 1967–1969. Bull Int Union Tuberc. 1975;50(1):107–21. pmid:1218286
  30. 30. Fennelly KP. Variability of airborne transmission of Mycobacterium tuberculosis: implications for control of tuberculosis in the HIV era. Clin Infect Dis. 2007 May 15;44(10):1358–60. pmid:17443475
  31. 31. Zak DE, Penn-Nicholson A, Scriba TJ, Thompson E, Suliman S, Amon LM, et al. A blood RNA signature for tuberculosis disease risk: a prospective cohort study. Lancet. 2016 Jun 4;387(10035):2312–22 pmid:27017310
  32. 32. Saunders MJ, Wingfield T, Tovar MA, Baldwin MR, Datta S, Zevallos K,et al. A score to predict and stratify risk of tuberculosis in adult contacts of tuberculosis index cases: a prospective derivation and external validation cohort study. Lancet Infect Dis. 2017 Nov;17(11):1190–1199 pmid:28827142
  33. 33. Acuña-Villaorduña C, Jones-Lopez E, Fregona G, Marques-Rodrigues P, Gaeddert M, Geadas C,et al. Intensity of exposure to pulmonary tuberculosis determines risk of tuberculosis infection and disease. European Resp Journal 2017 (in press)
  34. 34. Mandalakas AM, Kirchner HL, Lombard C, Walzl G, Grewal HM, Gie RP, et al. Well-quantified tuberculosis exposure is a reliable surrogate measure of tuberculosis infection. Int J Tuberc Lung Dis. 2012 Aug;16(8):1033–9 pmid:22692027
  35. 35. Patterson B, Morrow C, Singh V, Moosa A, Gqada M, Woodward J, et al. Detection of Mycobacterium tuberculosis bacilli in bio-aerosols from untreated TB patients. Gates Open Res. 2017 Nov 7;1:11. pmid:29355225