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Risk factors for infectiousness of patients with tuberculosis: a systematic review and meta-analysis

Published online by Cambridge University Press:  17 January 2018

Y.A. Melsew*
Affiliation:
School of Public Health and Preventive Medicine, Medicine, Nursing and Health Sciences, Monash University, Melbourne, Australia Department of Epidemiology and Biostatistics, Institute of Public Health, University of Gondar, Gondar, Ethiopia
T.N. Doan
Affiliation:
Australian Institute of Tropical Health and Medicine, James Cook University, Townsville, Australia Department of Medicine at the Royal Melbourne Hospital, University of Melbourne, Melbourne, Australia
M. Gambhir
Affiliation:
School of Public Health and Preventive Medicine, Medicine, Nursing and Health Sciences, Monash University, Melbourne, Australia
A.C. Cheng
Affiliation:
School of Public Health and Preventive Medicine, Medicine, Nursing and Health Sciences, Monash University, Melbourne, Australia Infection Prevention and Healthcare Epidemiology Unit, Alfred Health, Melbourne, Australia
E. McBryde
Affiliation:
Australian Institute of Tropical Health and Medicine, James Cook University, Townsville, Australia Department of Medicine at the Royal Melbourne Hospital, University of Melbourne, Melbourne, Australia
J.M. Trauer
Affiliation:
School of Public Health and Preventive Medicine, Medicine, Nursing and Health Sciences, Monash University, Melbourne, Australia
*
Author for correspondence: Y.A. Melsew, E-mail: [email protected] or [email protected]
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Abstract

We performed a systematic review and meta-analyses of studies assessing tuberculosis (TB) patient-related risk factors for transmission of Mycobacterium tuberculosis infection. Meta-analyses were conducted for sputum smear-positivity, lung cavitation and HIV seropositivity of index patients with both crude and adjusted odds ratios (AORs) pooled using random effect models. Thirty-seven studies were included in the review. We found that demographic characteristics such as age and sex were not significant risk factors, while behaviours such as smoking and alcohol intake were associated with infectiousness although inconsistently. Treatment delay of >28 days was a significant predictor of greater infectiousness. Contacts of sputum smear-positive index patients were found to be more likely to be infected than contacts of sputum smear-negative patients, with a pooled AOR of 2.15 (95% confidence interval (CI) 1.47–3.17, I2 = 38%). Similarly, contacts of patients with the cavitary disease were around twice as likely to be infected as contacts of patients without cavitation (pooled AOR 1.9, 95% CI 1.26–2.84, I2 = 63%). In contrast, HIV seropositive patients were associated with few contact infections than HIV seronegative patients (AOR 0.45, 95% CI 0.26–0.80, I2 = 52%). In conclusion, behavioural and clinical characteristics of TB patients can be used to identify highly infectious patients for targeted interventions.

Type
Original Papers
Copyright
Copyright © Cambridge University Press 2018 

Introduction

Despite recent improvements following the successful implementation of the Millennium Development Goals, tuberculosis (TB) is still the leading cause of mortality due to a single infectious pathogen [1].

The transmission of infectious diseases is affected by characteristics of the environment, infectious agent, and host, including both the infecting and infected hosts. For directly transmissible diseases, understanding the characteristics of the index patient that influence the capacity to transmit infection is essential to design the effective control strategies [Reference Woolhouse2, Reference Galvani and May3]. The spread of TB is strongly affected by the infectious individual's characteristics, with some individuals causing considerably greater numbers of new infections, while others produce very few or none [Reference Wang4].

A central goal of TB control strategies is the prevention of transmission. Hence, identifying highly contagious TB patients, by analysing risk factors from contact investigation studies, is critical for designing effective and efficient TB control interventions. We performed a systematic review of patient factors associated with the risk of transmission of TB to contacts.

Methods

The review protocol was prospectively registered with PROSPERO (International Prospective Register of Systematic Reviews, registration number: CRD42016053913) and we adhered to the guidelines of Meta-analyses and Systematic Review of Observational studies in Epidemiology (MOOSE) throughout [Reference Stroup5].

Search strategy

We searched the following electronic bibliographic databases from inception to 3 January 2017: MEDLINE, EMBASE, Web of Science, Global Health and Global Health Archive. All search terms were ‘exploded’ to include all resources and consisted of ‘Tuberculosis’, ‘Mycobacterium tuberculosis’, ‘TB’, ‘contact’, ‘contact investigation’, ‘transmission’, ‘index case’, ‘infectiousness’, ‘risk factors’, ‘secondary case’ and ‘latent infection’. The detailed search strategy is provided in Table S1.

Study selection

Search results were exported to EndNoteX8 (Clarivate Analytics, NY, USA) and duplicates were removed. Titles and abstracts were screened to identify potentially relevant articles. The outcome of interest was latent TB infection (LTBI) or TB disease among contacts of index TB patients. The full texts of the studies that were deemed relevant in this initial screening phase were then obtained and reviewed by two authors (Y. M. and T. D.). Studies were included if they diagnosed index patients according to the clinical, radiological or microbiological criteria, assessed LTBI or TB disease among contacts, reported the number of index patients and contacts, and quantified index patient-related risk factors for infection or disease in their contacts. Editorials, commentaries, case reports, outbreak reports, systematic reviews, mathematical modelling studies and studies in languages other than English were excluded, as were studies that did not assess index patient-related risk factors.

Data extraction

The following data were extracted: country, year, study design, index patient definition, contact definition, outcome status of contacts (LTBI or TB disease), number of index patients, number of contacts, study population, contact screening methods, results of screening and index risk factors investigated. Estimates of the effect of exposures on the outcomes of the proportion of contacts with active TB or with LTBI were also extracted, including adjusted risk ratio or odds ratio and their 95% confidence intervals (CIs). Y. M. and T. D. extracted the data independently using the same data extraction form with all discordant data resolved by consensus.

Assessment of study quality

Each article was evaluated using the Newcastle–Ottawa Scale [Reference Wells6] for its validity with respect to the selection of study participants, comparability between exposure groups and outcome measurements, by two authors (Y. M. and T. D.) (Table S2).

Meta-analyses

Exposure variables were selected based on the availability of sufficient data and were not specified a priori, three variables were chosen for meta-analysis based on importance and consistent availability: sputum smear-positivity, lung cavitation and HIV seropositivity. Meta-analyses were performed with MetaXL (Version 5.3, EpiGear International Pty Ltd, QLD, Australia) to estimate the pooled effects of each of these three exposures on the binary outcomes of contact LTBI or TB disease. Random effects models were used to estimate pooled effect measures. Heterogeneity among estimates was quantitatively evaluated with the I 2-statistic.

Results

Search results

The search strategy resulted in 4780 references, of which 1725 were duplicates, 321 were deemed eligible for full-text review and 37 studies were included in the systematic review. The detailed flow diagram of study selection is presented in Fig. S1. Of the included studies, 17 were cross-sectional, seven cohort studies, 12 follow-up studies without control groups and one case–control study. Twenty-four studies originated from one of the 30 high burden TB countries.

Contact and index definitions

Studies varied by the types of index patients and contacts included. Eight defined index patients as newly diagnosed smear-positive pulmonary TB patients, 12 studies considered confirmed pulmonary TB and six included all types of TB. With regard to contact definition, 20 studies considered only household contacts, six studies traced only children and adolescent contacts and three considered only close contacts who shared enclosed spaces (Table S3).

Outcome measures

The outcome of interest was LTBI or TB disease amongst contacts of different index patients, which was used as a marker of patients’ infectiousness; that is the capacity to transmit Mycobacterium tuberculosis (M. tb) to contacts. The included studies compared contacts who developed the outcome (LTBI or TB disease) to those who did not, based on the characteristics of index patients as the exposure variable. Thus, the measures of association (risk ratio or odds ratio) quantified the effect of exposure to an index patient with a given characteristic on the probability or odds of infection or disease in the exposed contact. The majority of included studies (29/37) considered LTBI as the main outcome, with 25 using tuberculin skin test (TST), one using interferon-gamma release assay (IGRA) and three using both TST and IGRA to determine infection. All studies using IGRAs to define infection used the manufacturer's recommended cut-off assessed at a single time point to define infection. Studies using TST mostly used a cut-off ⩾10 mm for HIV negative and ⩾5 mm for HIV positive contacts, although six studies used a cut-off of ⩾5 mm for all contacts and two other studies used 15 mm as the cut-off point for children having BCG vaccination. The remaining eight studies used the development of active TB in contacts as the measure of transmission (Table S4).

Index patient risk factors for M. tb transmission

The included studies considered a range of characteristics of index patients for their association with transmissibility. We categorised these index risk factors as demographic, behavioural, co-morbidities, TB-related clinical and household characteristics. We preferentially used the adjusted association reported from multivariate analyses. We also classified studies based on the type of association they had reported as: positive, negative or non-significant based on a P-value of <0.05 or a 95% CI not including unity.

Sociodemographic risk factors

Sex of index patients was a non-significant factor in most studies reporting its association with transmissibility [Reference Otero7Reference Snider17], although two studies found female sex to be associated with greater risk of infection [Reference Kifai and Bakari18, Reference Tornee19]. With one exception [Reference Lohmann13], included studies considered adult index patients exclusively. Of these, most studies that reported the effect of age found a non-significant association [Reference Otero7, Reference Grandjean9, Reference Godoy12, Reference Grandjean14, Reference Golub15, Reference Elliott20], although two studies reported that increasing age was positively associated with M. tb transmission [Reference Snider17, Reference Madhi21]. Of these two studies, one was conducted in France among contacts aged under 17 and found that contacts of patients aged 40 years old or above were more likely to be infected than contacts of younger patients [Reference Madhi21]. By contrast, a study from the USA reported that contacts of patients aged 64 years or above were less likely to be infected than contacts of younger patients [Reference Snider17].

One study from the Netherlands, which considered both close and casual contacts found that contacts of index patients who were employed or attending school were more likely to be infected [Reference Lohmann13], while two studies from Peru considering household contacts only found that employment status was not a significant risk factor for M. tb transmission [Reference Grandjean9, Reference Grandjean14]. Black race of the index patient was a positive risk factor in one study in the USA which considered all close contacts [Reference Golub15], while another study of contacts aged under 15 years in the USA found race was not associated with contact infection [Reference Snider17] (Table 1).

Table 1. Socio-demographic risk factors for infectiousness of index patients extracted from included studies

a Confidence interval not provided.

b Adjusted relative risk.

c Considered as a categorical variable.

AOR, adjusted odds ratio; CI, confidence interval.

Behavioural factors and co-morbidities

Index patients’ smoking status was a significant risk factor for LTBI among contacts in three studies [Reference Godoy12, Reference Singh22, Reference Huang23], but was non-significant in four [Reference Grandjean9, Reference Faksri10, Reference Huang23, Reference Nair24]. In one study from Peru, smoking more than one cigarette per day was associated with TB transmission to child contacts, but was not significant for transmission to adults. This study also reported that heavy alcohol consumption (compared with no alcohol intake) was associated with risk of contact infection [Reference Huang23], although other studies [Reference Jones-Lopez8Reference Faksri10, Reference Godoy12] found no significant association. Similarly, injection drug use was associated with higher TB transmission in a case–control study from Spain [Reference Cayla25], but this risk factor was non-significant in others [Reference Godoy12, Reference Golub15] (Table 2).

Table 2. Behavioural and co-morbidity risk factors for infectiousness of index patients extracted from included studies

a Adjusted relative risk.

b Indicates that these studies take contact active TB disease as an outcome.

AOR, adjusted odds ratio; CI, confidence interval.

TB-related clinical risk factors

Differences in the index patients’ clinical presentation were considered as potential risk factors for M. tb transmission to contacts by several studies (Table 3). Compared with contacts of index patients who did not cough, contacts of index patients with any cough were more likely to be infected in two studies [Reference Lohmann13, Reference Gessner, Weiss and Nolan26], while another two studies found no significant association [Reference Otero7, Reference Elmi27]. Of studies considering the duration of coughing, two studies found that contacts of patients coughing for 2 weeks or longer were more likely to be infected than contacts of patients who coughed for a shorter period of time or who did not cough [Reference Lohmann13, Reference Tornee19], while a study reported coughing for 5 weeks or longer to be a significant risk factor [Reference Lienhardt28]. In contrast, three studies found that duration of a cough, considered as a continuous variable was not statistically significant [Reference Grandjean9, Reference Nair24, Reference Mohammad29].

Table 3. Index tuberculosis disease-related clinical risk factors for infectiousness of index patients extracted from included studies

a Adjusted relative risk.

b Outcome considered was active TB disease in contacts.

AOR, adjusted odds ratio; CI, confidence interval.

Treatment delay was another risk factor considered for M. tb transmission, although studies considered different cut-off points for categorising a number of days of treatment delay. In three studies [Reference Otero7, Reference Tornee19, Reference Xu30] a treatment delay of 30 days or more (compared with <30 days) was associated with greater risk of infection and disease among contacts. Similarly, compared with no treatment delay, delay for more than 28 days [Reference Huang11] was a risk factor in one study, while in two other studies [Reference Golub15, Reference Xu30] delay of 90 days or more was significant. Another study reported the duration of illness considered as a continuous variable to be a significant factor for contact LTBI [Reference Mendes31].

Sputum smear-positivity was reported to be associated with M. tb transmission by ten studies [Reference Godoy12, Reference Lohmann13, Reference Golub15, Reference Singh22, Reference Gessner, Weiss and Nolan26, Reference Elmi27, Reference Loredo32]. Other studies compared patients based on the bacilli density per field, although categorisation was inconsistent. Sputum smear bacilli density of 2+ [Reference Huang11, Reference Huang23, Reference Espinal33] and 3+ [Reference Otero7, Reference Huang11, Reference Huang23, Reference Rathi34] compared with scanty were significant risk factors in all studies reporting this variable. Similarly, one study [Reference Madhi21] reported very high sputum smear densities ⩾100 bacilli/field as a significant risk factor. Sputum production and haemoptysis were found to be significant risk factors in one study [Reference Lohmann13].

Lung cavity lesion findings were associated with greater infectiousness in eight studies [Reference Godoy12, Reference Lohmann13, Reference Golub15, Reference Tornee19, Reference Madhi21, Reference Guwatudde35, Reference Lee36], but non-significant in another nine studies [Reference Jones-Lopez8, Reference Grandjean9, Reference Huang11, Reference Nunn16, Reference Elliott20, Reference Huang23, Reference Nair24, Reference Gessner, Weiss and Nolan26, Reference Mohammad29, Reference Mendes31]. The number of lung zones involved on CXR was also reported as a risk factor in one study, with the involvement of four or more zones associated with more contact infections than those with fewer zones involved [Reference Lienhardt28].

Of the four studies which compared transmission based on drug sensitivity, one [Reference Grandjean9] reported contacts of multidrug-resistant TB (MDR-TB) patients were less likely to be infected, while three [Reference Otero7, Reference Snider17, Reference Teixeira37] reported no significant difference.

Household risk factors

A history of TB among family members was found to be a risk factor for contact TB disease in two studies [Reference Nair24, Reference Lee36], although this was non-significant in one more recent study [Reference Otero7]. The type of residence of the index patient was also reported as a significant factor, with those living in slums or apartments associated with more infections among contacts [Reference Tornee19]. Household crowding with two or more persons per room was a significant risk factor for M. tb transmission in one study [Reference Tornee19] although two other studies found no significant effect [Reference Nair24, Reference Mohammad29].

Meta-analysis

Three factors were reported in a sufficient number of studies to permit meaningful meta-analysis. Twenty-six studies were included in one or more of these meta-analyses, with three factors of interest being sputum smear-positive disease, lung cavitation and HIV status of the index patient (Table S5).

Contacts of sputum smear-positive pulmonary TB patients were found to be more frequently infected than contacts of smear-negative patients, with a pooled adjusted odds ratio (AOR) of 2.15 (95% CI 1.47–3.17, I 2 = 38%) (Fig. 1). A similar association was observed from the pooled crude odds ratios (2.29, 95% CI 1.84–283, I 2 = 54%) (Fig. S2). Sensitivity analysis indicated that no single study, when excluded, affected the pooled estimates (Table S6), although funnel plots suggested possible publication bias (Fig. S5).

Fig. 1. Forest plot of adjusted odds ratios for the association between index patient sputum smear-positivity and infectiousness.

The odds of infection among contacts of patients with cavitation also appeared to be around two, although heterogeneity between study estimates was substantial. Our estimate of the pooled AOR is 1.90 (95% CI 1.26–2.84, I 2 = 63%) (Fig. 2) and 1.93 (95% CI 1.36–2.75, I 2 = 85%) for the pooled crude odds ratio (Fig. S3). In sensitivity analyses, excluding a cross-sectional study from Thailand [Reference Tornee19] lowered the pooled AOR to 1.64, while excluding other studies did not markedly change our point estimate. In the crude odds ratios analysis, exclusion of any individual study did not result in a marked change to our pooled estimate (Table S7) and publication bias was not revealed by funnel plots (Fig. S6).

Fig. 2. Forest plot of the association between index patient lung cavitation and infectiousness from adjusted odds ratio analysis.

HIV seropositivity of index patients was negatively associated with infectiousness in the AORs analysis (0.45, 95% CI 0.26–0.80, I 2 = 52%) (Fig. 3). However, this association was non-significant in the analysis of crude odds ratio (0.76, 95% CI 0.55–1.07, I 2 = 80%) (Fig. S4). Sensitivity analysis of the adjusted estimate found that excluding any one of the studies did not change the pooled estimate significantly (Table S8) and the funnel plot of studies revealed no evidence of publication bias (Fig. S7).

Fig. 3. Forest plot of the association between index patient HIV seropositivity and infectiousness from adjusted odds ratio analysis. *Indicates that these studies take contact active disease as an outcome. AOR, adjusted odds ratio; OR, odds ratio; CI, confidence interval.

Discussion

This systematic review and meta-analyses assessed the capacity of index TB patients to transmit the infection to their contacts based on their demographic, behavioural and clinical characteristics. Our meta-analysis showed that sputum smear-positivity, the presence of lung cavitation and HIV seronegativity were the factors most consistently associated with greater infectiousness of index cases. Our results were also broadly consistent with the premise that more severe lung parenchymal involvement being associated with greater infectiousness. We found no sociodemographic characteristics that were consistently associated with the infectiousness of patients. Clinical factors were studied and reported in a variety of ways, but generally consistent with the message that prolonged symptoms such as coughing and delay to diagnosis lead to increased infectiousness. Treatment delays of >28 days were found to be a predictor of a greater proportion of contact infections.

Although most studies found no significant association, smoking and alcohol intake were found to be risk factors for greater infectiousness in some studies. A possible explanation could be that these risk factors are associated with both biological changes in the host [Reference Davies38], as well as differences in social mixing behaviours such as sharing enclosed bars [Reference Lönnroth39], such the association is likely to be setting specific. In addition, exposure to second-hand smoke increases the susceptibility of contacts to infection, particularly among children [Reference Jubulis40, Reference Du Preez41].

Compared with smear-negative patients, smear-positive patients were found to be approximately twice as infectious. This association was not confounded by cavitation since all studies but one included in the pooled analysis had adjusted for this factor [Reference Elmi27]. The positive association between smear-positivity and infectiousness is likely to reflect smear-positive patients expelling a greater number of M. tb into the environment than smear-negative patients, as M. tb bacilli are only detectable with sputum microscopy when the concentration of the bacilli is sufficient [Reference Initiative42]. Similarly, index patients presenting cavitation were found to be twice as infectious as those without cavitation. This is consistent with the widely held belief that cavitary TB is the consequence of lung tissue damage and reflects the development of macroscopic openings between the site of infection and the airways, which facilitate expectoration of the bacteria [Reference Ernst43].

In contrast, we found that patients living with HIV were around half as likely to transmit to their contacts, after adjusting for other factors. Notably, all such studies involved patients with untreated HIV. A previous meta-analysis found no significant difference between HIV negative and positive index patients with regards to their infectiousness, although it should be noted that this study only pooled crude odds ratios or relative risks [Reference Cruciani44], in contrast to our study which considered estimates adjusted for potential confounders. The lower infectiousness of HIV-positive index patients may be due to their less frequent cavitation (due to suppression of the immune response) [Reference Ernst43, Reference Haramati, Jenny-Avital and Alterman45] or patterns of social mixing. Of the five studies included in this analysis, two [Reference Nunn16, Reference Mohammad29] adjusted for cavitation and one of which found HIV status non-significant [Reference Nunn16]. HIV-positive patients may also be diagnosed and treated for active TB more rapidly due to fast disease progress or their closer contact with health care services, which may decrease their infectious period. It has previously been found that HIV-positive TB patients are less likely to be smear positive than HIV-negative TB patients [Reference Elliott46, Reference Klein47]. However, four of the five studies included in our meta-analysis adjusted for sputum smear status, such that the association of HIV seropositivity with TB transmission does not appear to be mediated by sputum smear-positivity. Therefore, HIV-positive patients may have a modestly reduced level of infectiousness but should not be presumed to be non-infectious, which is consistent with extremely high disease burden in high HIV-burden countries. As such, an equal focus of contact investigation has been advised for both HIV-seropositive and negative index patients [Reference Martinez48].

The funnel plots suggest possible publication bias, particularly for studies that examined the association of infectivity and smear positivity. Other potential sources of bias result from the observational nature of studies included in this review, including selection bias and information bias. Non-differential misclassification bias could arise due to the inability of TST to differentiate recent LTBI attributable to the index exposure from distant past infection. This would dilute the effect, leading to an under-estimate and a bias towards the null. This may particularly be seen in studies with broader definitions of contacts, where distant latent infection might represent a greater proportion of all latent infection. By contrast, studies employing stricter definitions and focusing on those with greater exposure to the index case, such as close contacts only, would provide more accurate estimates, although this may be offset by lower precision due to smaller sample sizes. Studies using stricter definitions of infection (e.g. higher TST cut-offs) would also obtain more accurate effect size estimates, but at the expense of precision. Duration of follow-up differed between studies, with some assessing their study group at only a single point in time, which may affect the development of an infection response and its detection. Such insufficient duration of follow up could similarly lead to underestimation of the outcome measures, through greater dilution from distant infection. Studies considering less infectious index patients, such as those that included smear-negative patients, could also have a greater proportion of disease attributable to remote infection and a bias towards the null.

We have reviewed the outcomes of infection and subsequent disease together under the implicit assumption that both of these outcomes reflect index patient infectiousness. This is only correct if we consider that contacts have a similar risk of reactivation following infection regardless of the characteristics of the index patient. We believe this is reasonable because the risk of reactivation should be primarily attributable to contact characteristics (e.g. age, comorbidities) and because pooling of studies considering active disease with those considering LTBI did not increase statistical heterogeneity, although it could also be influenced by characteristics of the organism and extent of exposure. However, we have carefully indicated which outcome is being considered throughout and presented disaggregated meta-analysis results. Last, it should be noted that we are considering infectiousness as the proportion of contacts infected or diseased and have not considered the absolute number of infections generated, which may also reflect infectiousness to some extent.

Conclusions

We identified three clinical characteristics that can be used to identify TB patients with a greater capacity for transmission; smear positivity, the presence of cavitation on chest X-ray and HIV status. Thus, in an era of increasing use of molecular diagnostics, traditional diagnostic methods, such as sputum smear microscopy and chest radiography, still provide important information on patients’ infectiousness. HIV-positive TB patients not under treatment may be modestly less infectious, although such patients should not be presumed to be non-infectious. Sociodemographic and behavioural characteristics were less consistently associated with infectiousness and their importance may be setting-dependent. The public health implication of these findings is in the potential to provide close follow-up and targeted interventions for these highly infectious TB patients.

Supplementary Material

The supplementary material for this article can be found at https://doi.org/10.1017/S0950268817003041

Acknowledgements

The authors thank the Monash University for providing access to electronic databases. Y. A. Melsew is a recipient of a Monash Graduate Scholarship for his PhD study. No specific funding was received for this study.

Declaration of Interest

The authors declare that they have no competing interests.

References

1.World Health Organization (2015) A Global Action Framework for TB Research in Support of the Third Pillar of WHO's end TB Strategy. Geneva. WHO/HTM/TB/2015.26.Google Scholar
2.Woolhouse, ME, et al. (1997) Heterogeneities in the transmission of infectious agents: implications for the design of control programs. Proceedings of the National Academy of Sciences of the United States of America 94(1), 338342.Google Scholar
3.Galvani, AP and May, RM (2005) Epidemiology: dimensions of superspreading. Nature 438(7066), 293295.Google Scholar
4.Wang, C-S, et al. (2008) Predictors for identifying the most infectious pulmonary tuberculosis patient. Journal of the Formosan Medical Association 107(1), 1320.Google Scholar
5.Stroup, DF, et al. (2000) Meta-analysis of observational studies in epidemiology: a proposal for reporting. Jama 283(15), 20082012.Google Scholar
6.Wells, G, et al. (2000) The Newcastle–Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. Available from: http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp (accessed 4 January 2017).Google Scholar
7.Otero, L, et al. (2016) A prospective longitudinal study of tuberculosis among household contacts of smear-positive tuberculosis cases in Lima, Peru. BMC Infectious Diseases 16(259), 18.Google Scholar
8.Jones-Lopez, EC, et al. (2016) Cough Aerosols of Mycobacterium tuberculosis in the prediction of incident tuberculosis disease in household contacts. Clinical Infectious Diseases 63(1), 1020.Google Scholar
9.Grandjean, L, et al. (2015) Transmission of multidrug-resistant and drug-susceptible tuberculosis within households: a prospective cohort study. PLoS Medicine 12(6), e1001843.Google Scholar
10.Faksri, K, et al. (2015) Transmission and risk factors for latent tuberculosis infections among index case-matched household contacts. Southeast Asian Journal of Tropical Medicine & Public Health 46(3), 486495.Google Scholar
11.Huang, CC, et al. (2014) The effect of HIV-related immunosuppression on the risk of tuberculosis transmission to household contacts. Clinical Infectious Diseases 58(6), 765774.Google Scholar
12.Godoy, P, et al. (2013) Immigrants do not transmit tuberculosis more than indigenous patients in Catalonia (Spain). Tuberculosis 93(4), 456460.Google Scholar
13.Lohmann, EM, et al. (2012) Grading of a positive sputum smear and the risk of Mycobacterium tuberculosis transmission. International Journal of Tuberculosis and Lung Disease 16(11), 14771484.Google Scholar
14.Grandjean, L, et al. (2011) Tuberculosis in household contacts of multidrug-resistant tuberculosis patients. International Journal of Tuberculosis and Lung Disease 15(9), 11641169.Google Scholar
15.Golub, JE, et al. (2006) Delayed tuberculosis diagnosis and tuberculosis transmission. International Journal of Tuberculosis & Lung Disease 10(1), 2430.Google Scholar
16.Nunn, P, et al. (1994) The effect of human immunodeficiency virus type-1 on the infectiousness of tuberculosis. Tubercle & Lung Disease 75(1), 2532.Google Scholar
17.Snider, DE Jr, et al. (1985) Infection and disease among contacts of tuberculosis cases with drug-resistant and drug-susceptible bacilli. American Review of Respiratory Disease 132(1), 125132.Google Scholar
18.Kifai, EJ and Bakari, M (2009) Mantoux skin test reactivity among household contacts of HIV-infected and HIV un-infected patients with sputum smear positive TB in Dar es Salaam, Tanzania. East African Journal of Public Health 6(2), 211218.Google Scholar
19.Tornee, S, et al. (2004) Risk factors for tuberculosis infection among household contacts in Bangkok, Thailand. Southeast Asian Journal of Tropical Medicine & Public Health 35(2), 375383.Google Scholar
20.Elliott, AM, et al. (1993) The impact of HIV on infectiousness of pulmonary tuberculosis: a community study in Zambia. AIDS 7(7), 981987.Google Scholar
21.Madhi, F, et al. (2002) Transmission of tuberculosis from adults to children in a Paris suburb. Pediatric Pulmonology 34(3), 159163.Google Scholar
22.Singh, M, et al. (2005) Prevalence and risk factors for transmission of infection among children in household contact with adults having pulmonary tuberculosis. Archives of Disease in Childhood 90(6), 624628.Google Scholar
23.Huang, CC, et al. (2014) Cigarette smoking among tuberculosis patients increases risk of transmission to child contacts. International Journal of Tuberculosis & Lung Disease 18(11), 12851291.Google Scholar
24.Nair, D, et al. (2016) Household contact screening and yield of tuberculosis cases – a clinic based study in Chennai, South India. PLoS ONE 11(9), e0162090.Google Scholar
25.Cayla, JA, et al. (1996) The influence of intravenous drug use and HIV infection in the transmission of tuberculosis. AIDS 10(1), 95100.Google Scholar
26.Gessner, BD, Weiss, NS and Nolan, CM (1998) Risk factors for pediatric tuberculosis infection and disease after household exposure to adult index cases in Alaska. Journal of Pediatrics 132(3), 509513.Google Scholar
27.Elmi, OS, et al. (2014) Prevalence and associated factors with transmission of latent tuberculosis among household contacts of multi-drug resistant tuberculosis patients in Malaysia. World Journal of Medical Sciences 10(3), 285294.Google Scholar
28.Lienhardt, C, et al. (2003) Risk factors for tuberculosis infection in children in contact with infectious tuberculosis cases in the Gambia, West Africa. Pediatrics 111(5), e608e614.Google Scholar
29.Mohammad, Z, et al. (2002) A preliminary study of the influence of HIV infection in the transmission of tuberculosis. Southeast Asian Journal of Tropical Medicine & Public Health 33(1), 9298.Google Scholar
30.Xu, L, et al. (2008) Dose-response relationship between treatment delay of smear-positive tuberculosis patients and intra-household transmission: a cross-sectional study. Transactions of the Royal Society of Tropical Medicine and Hygiene 102(8), 797804.Google Scholar
31.Mendes, MA, et al. (2013) Ontact screening in tuberculosis: can we identify those with higher risk? European Respiratory Journal. 41(3), 758760.Google Scholar
32.Loredo, C, et al. (2014) Yield of close contact tracing using two different programmatic approaches from tuberculosis index cases: a retrospective quasi-experimental study. BMC Pulmonary Medicine 14(1), 133.Google Scholar
33.Espinal, MA, et al. (2000) Infectiousness of Mycobacterium tuberculosis in HIV-1-infected patients with tuberculosis: a prospective study. Lancet (British Edition) 355(9200), 275280.Google Scholar
34.Rathi, SK, et al. (2002) Prevalence and risk factors associated with tuberculin skin test positivity among household contacts of smear-positive pulmonary tuberculosis cases in Umerkot, Pakistan. International Journal of Tuberculosis and Lung Disease 6(10), 851857.Google Scholar
35.Guwatudde, D, et al. (2003) Tuberculosis in household contacts of infectious cases in Kampala, Uganda. American Journal of Epidemiology 158(9), 887898.Google Scholar
36.Lee, MS, et al. (2008) Early and late tuberculosis risks among close contacts in Hong Kong. International Journal of Tuberculosis & Lung Disease 12(3), 281287.Google Scholar
37.Teixeira, L, et al. (2001) Infection and disease among household contacts of patients with multidrug-resistant tuberculosis. International Journal of Tuberculosis & Lung Disease 5(4), 321328.Google Scholar
38.Davies, P, et al. (2006) Smoking and tuberculosis: the epidemiological association and immunopathogenesis. Transactions of the Royal Society of Tropical Medicine and Hygiene 100(4), 291298.Google Scholar
39.Lönnroth, K, et al. (2008) Alcohol use as a risk factor for tuberculosis–a systematic review. BMC Public Health 8(1), 289.Google Scholar
40.Jubulis, J, et al. (2014) Modifiable risk factors associated with tuberculosis disease in children in Pune, India. The International Journal of Tuberculosis and Lung Disease 18(2), 198204.Google Scholar
41.Du Preez, K, et al. (2011) Environmental tobacco smoke exposure increases Mycobacterium tuberculosis infection risk in children. The International Journal of Tuberculosis and Lung Disease 15(11), 14901497.Google Scholar
42.Initiative, GL (2014) Mycobacteriology Laboratory Manual. Geneva: WHO Stop TB Partnership.Google Scholar
43.Ernst, JD (2012) The immunological life cycle of tuberculosis. Nature Reviews Immunology 12(8), 581591.Google Scholar
44.Cruciani, M, et al. (2001) The impact of human immunodeficiency virus type 1 on infectiousness of tuberculosis: a meta-analysis. Clinical Infectious Diseases 33(11), 19221930.Google Scholar
45.Haramati, L, Jenny-Avital, E and Alterman, D (1997) Effect of HIV status on chest radiographic and CT findings in patients with tuberculosis. Clinical Radiology 52(1), 3135.Google Scholar
46.Elliott, A, et al. (1993) Negative sputum smear results in HIV-positive patients with pulmonary tuberculosis in Lusaka, Zambia. Tubercle and Lung Disease 74(3), 191194.Google Scholar
47.Klein, NC, et al. (1989) Use of mycobacterial smears in the diagnosis of pulmonary tuberculosis in AIDS/ARC patients. Chest 95(6), 11901192.Google Scholar
48.Martinez, L, et al. (2016) Infectiousness of HIV-seropositive patients with tuberculosis in a high-burden African setting. American Journal of Respiratory and Critical Care Medicine 194(9), 11521163.Google Scholar
49.Carvalho, ACC, et al. (2001) Transmission of Mycobacterium tuberculosis to Contacts of HIV-infected Tuberculosis Patients. American Journal of Respiratory and Critical Care Medicine 164(12), 21662171.Google Scholar
50.Baliashvili, D, et al. (2016) Contacts of retreatment tuberculosis cases with a prior poor treatment outcome are at increased risk of latent tuberculosis infection. International Journal of Infectious Diseases 43, 4950.Google Scholar
Figure 0

Table 1. Socio-demographic risk factors for infectiousness of index patients extracted from included studies

Figure 1

Table 2. Behavioural and co-morbidity risk factors for infectiousness of index patients extracted from included studies

Figure 2

Table 3. Index tuberculosis disease-related clinical risk factors for infectiousness of index patients extracted from included studies

Figure 3

Fig. 1. Forest plot of adjusted odds ratios for the association between index patient sputum smear-positivity and infectiousness.

Figure 4

Fig. 2. Forest plot of the association between index patient lung cavitation and infectiousness from adjusted odds ratio analysis.

Figure 5

Fig. 3. Forest plot of the association between index patient HIV seropositivity and infectiousness from adjusted odds ratio analysis. *Indicates that these studies take contact active disease as an outcome. AOR, adjusted odds ratio; OR, odds ratio; CI, confidence interval.

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