DOI: 10.1111/tmi.13808
SYSTEMATIC REVIEW
Strategies to detect and manage latent tuberculosis infection
among household contacts of pulmonary TB patients in high TB
burden countries - a systematic review and meta-analysis
Karuna Devi Sagili1 | Malaisamy Muniyandi2 | Kalpita Shringarpure3 | Kavita Singh1 |
Richard Kirubakaran4 | Raghuram Rao5 | Jamhoih Tonsing6 |
Kuldeep Singh Sachdeva1 |
1
International Union Against Tuberculosis and
Lung Disease, South East Asia Office, New Delhi,
India
2
Indian Council of Medical Research (ICMR),
National Institution for Research in Tuberculosis,
Chennai, India
3
Department of Community Medicine, Medical
College Baroda, Baroda, India
4
Clinical Epidemiology Unit, Christian Medical
Centre, Vellore, India
5
National TB Elimination Program, Central TB
Division, Ministry of Health, New Delhi, India
6
Technical Advice and Partnerships Department,
The Global Fund, Geneva, Switzerland
Correspondence
Karuna Devi Sagili, Knowledge Management and
Research (ACSM-NTSU), International Union
Against Tuberculosis and Lung Disease, South
East Asia Office, New Delhi, India.
Email: drkarunas@gmail.com
Funding information
UK Government
Prathap Tharyan4
Abstract
Objective: To summarise latent tuberculosis infection (LTBI) management strategies
among household contacts of bacteriologically confirmed pulmonary tuberculosis
(TB) patients in high-TB burden countries.
Methods: PubMed/MEDLINE (NCBI) and Scopus were searched (January 2006 to
December 2021) for studies reporting primary data on LTBI management. Study
selection, data management and data synthesis were protocol-driven (PROSPEROCRD42021208715). Primary outcomes were the proportions of LTBI, initiating and
completing tuberculosis preventive treatment (TPT). Reported factors influencing the
LTBI care cascade were qualitatively synthesised.
Results: From 3694 unique records retrieved, 58 studies from 23 countries were
included. Most identified contacts were screened (median 99%, interquartile range
[IQR] 82%–100%; 46 studies). Random-effects meta-analysis yielded pooled proportions for: LTBI 41% (95% confidence interval [CI] 33%–49%; 21,566 tested contacts); TPT initiation 91% (95% CI 79%–97%; 129,573 eligible contacts, 34 studies);
TPT completion 65% (95% CI 54%–74%; 108,679 TPT-initiated contacts, 28 studies). Heterogeneity was significant (I2 ≥ 95%–100%) and could not be explained in
subgroup analyses. Median proportions (IQR) were: LTBI 44% (28%–59%); TPT
initiation 86% (60%–100%); TPT completion 68% (44%–82%). Nine broad themes
related to diagnostic testing, health system structure and functions, risk perception,
documentation and adherence were considered likely to influence the LTBI care
cascade.
Conclusion: The proportions of household contacts screened, detected with LTBI and
initiated on TPT, though variable was high, but the proportions completing TPT were
lower indicating current strategies used for LTBI management in high TB burden
countries are not sufficient.
KEYWORDS
diagnosis, high TB burden settings, household contacts, isoniazid preventive therapy, latent TB infection,
screening, TB preventive therapy, treatment, tuberculosis
Sustainable Development Goal: Good Health and Wellbeing.
This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium,
provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
© 2022 The Authors Tropical Medicine & International Health Published by John Wiley & Sons Ltd.
842
wileyonlinelibrary.com/journal/tmi
Trop Med Int Health. 2022;27:842–863.
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TROPICAL MEDICINE & INTERNATIONAL HEALTH
INTRODUCTION
Tuberculosis (TB) is a major public health problem and a
leading cause of death worldwide. Over 10 million people
are estimated to have developed TB in 2020; the majority
were from 30 high TB burden, resource-constrained, lowand middle-income countries (LMICs) [1]. In 2014, the
World Health Assembly adopted World Health Organisation’s (WHO) End TB Strategy which aims to eliminate the
global TB epidemic by the year 2035 [2].
Latent tuberculosis infection (LTBI) is a condition of
persistent immune response to infection by Mycobacterium
tuberculosis (M.tb) in people with no evidence of active TB
disease [3, 4]. It is estimated that approximately 1.7 billion
individuals (nearly a quarter of the global population) were
infected with LTBI in 2014, with a 5%–10% lifetime risk of
developing active TB; and that over 50% of the household
contacts of smear-positive index TB patients in LMICs
have LTBI [5, 6]. Hence, WHO recommends that those
with LTBI should be treated with tuberculosis preventive
therapy (TPT) to realise the goals of the End TB Strategy [7].
Contact investigation is an essential component of the
WHO’s TB management algorithms to detect those with
LTBI among high-risk groups, and to initiate TPT [4, 7, 8].
WHO guidelines recommend home visits as the preferred
mode of contact investigation; however, when home visits
are not possible, contact investigation at a health facility is
recommended. In either case, WHO advocates that trained
staff should elicit the required information from the index
TB patients [8] and counsel patients and their family members on the importance of LTBI testing, TPT initiation and
completion [4, 7, 8]. WHO recommends the tuberculin skin
test (TST) or interferon-gamma release assays (IGRA) to
detect LTBI [8]. TST is a reasonably low-cost tool; however,
its production is limited. IGRA results in fewer false-positive
results than with TST, but has higher cost and supply chain
issues that challenge its routine induction in national TB
programmes in LMICs [8].
The options for TPT currently recommended by WHO
for adults and children with LTBI, regardless of human
immunodeficiency virus (HIV) status, include: (1) isoniazid
monotherapy daily for 6 or 9 months, (2) rifampicin plus
isoniazid daily for 3 months, (3) rifapentine plus isoniazid
weekly for 3 months, (4) a 1-month daily regimen of rifapentine or isoniazid, or (5) 4 months of daily rifampicin [8].
As per the recommendations, child contacts under 5 years
of age can be provided with TPT irrespective of their LTBI
status after excluding TB [4, 7, 8].
The first-ever United Nations high-level meeting
(UNHLM) declaration in 2018 envisaged the rapid scale-up
of access to LTBI testing and provision of TPT, with a special focus on high TB burden countries, so that at least
30 million people receive TPT by 2022 [9]. In many lowburden, high-income countries, systematic LTBI management has contributed to lower rates of active TB. However,
in high TB burden LMICs, this is challenging as it requires
the diversion of resources from treating people with
active TB.
An ideal cascade of care for TPT starts with identifying
the eligible population, screening for and excluding active
TB, diagnosing LTBI, initiating TPT and ensuring TPT
completion. Multiple factors operating at every step of the
cascade affect the implementation of TPT. For instance, limited finance and manpower, low rates of contact screening
and treatment initiation, inadequate documentation of cascade components and so on are some of the factors that
adversely affect TPT implementation in LMICs with a high
TB burden [3, 10–13].
Synthesising evidence on implementation strategies and
factors that affect TPT in high TB burden settings is imperative to inform attempts to achieve the global targets for
managing LTBI. A recent systematic review and metaanalysis found that contact investigation was effective in
high-burden settings [14]. Another mixed-methods systematic review discussed the child contact losses that occur
through the care cascade, along with the variations in the
screening, initiation and completion of isoniazid preventive
therapy among child contacts [15]. However, strategies
used for child contact management were not described.
While these reviews provide information on the prevalence
of LTBI and the risk of incident TB, information on effective implementation strategies for the care cascade remains
unclear.
This systematic review aimed to summarise the strategies used in high TB burden countries for screening and
determining the eligibility for TPT among the household
contacts of bacteriologically confirmed pulmonary TB
patients, and to evaluate the outcomes of these strategies
with respect to TPT initiation and completion. We also
sought to ascertain the factors influencing these strategies
and outcomes.
METHODS
This review followed the methods described in the Preferred
Reporting Items for a Systematic Review and Meta-analysis
(PRISMA) 2020 statement [16] and was based on a protocol
registered on the International Prospective Register of Systematic Reviews (PROSPERO ID # CRD42021208715).
Search strategy and eligibility criteria
We searched PubMed/MEDLINE (NCBI) and SCOPUS
(Elsevier) for primary studies published between 1 January
2006 and 31 December 2021 describing the strategies for
implementing TPT among household contacts of pulmonary
TB patients in high-burden countries that reported data on
aspects of the TPT care cascade. The initial search did not
yield studies in child contacts; therefore, to ensure that all
age groups were covered, the search strategy was rerun with
additional keywords (child contacts) and the new output
844
was reviewed for inclusion (Table S1). We included studies
published in English that reported data on strategies used in
screening household contacts of bacteriologically confirmed
pulmonary TB patients for LTBI. The operational definitions we used are provided in Table S2. The permitted study
designs included randomised/non-randomised controlled
trials (RCTs/non-RCTs), prospective and retrospective
cohort studies, cross-sectional studies, longitudinal studies,
cost-effectiveness studies and studies with mixed designs.
Studies without usable numerical data for any component of
the TPT care cascade, as well as those conducted primarily
in clinically vulnerable and immunocompromised groups,
qualitative studies, and studies published in languages other
than English, were excluded.
Selection of studies and data management
process
The search results were exported to the web-application
Rayyan (https://www.rayyan.ai/). Three review authors (KS,
KDS and MM) independently screened titles and abstracts
for eligibility and selected studies. Full texts were evaluated,
or study authors were contacted, for additional information
to determine eligibility, and disagreements were resolved
through discussion. A fourth author (PT) independently
checked the appropriateness of study selection.
We used a data extraction form that had been pretested by two review authors (KS and KSS). Data were
extracted independently by three review authors (KS, MM
and KSS) and were checked by a fourth author (PT). From
each study, we extracted data regarding the target population, sample size, age of household contacts, setting, study
design, screening strategies, tests used, and the proportions
with positive test results, proportions initiating and completing TPT among those eligible, loss-to-follow-up,
adverse events and treatment failures (incident TB while
on TPT). We listed the factors that were reported by study
authors as influencing the TPT care cascade. We contacted
study authors for clarifications and for missing data. Since
different study designs that assessed different aspects of the
TPT care cascade were used, a formal risk of bias assessment was not possible, but deficiencies in reporting relevant data were recorded.
Data synthesis and statistical analysis
Extracted data regarding the characteristics of the included
studies were analysed using descriptive statistics with Microsoft Excel. The primary outcomes of interest were the proportions of household contacts who were screened and
tested for LTBI, and who initiated and completed TPT. We
conducted meta-analyses using the metafor package for the
statistical software environment R (https://www.metaforproject.org/doku.php) and generated forest plots of the
TROPICAL MEDICINE & INTERNATIONAL HEALTH
pooled estimates with 95% confidence intervals (CIs) for the
proportions with LTBI (positive either by TST or IGRA or
both as defined by study authors), and for the proportions
initiating TPT among those eligible, and completing TPT.
We anticipated that studies estimating LTBI positivity conducted in different regions of the world over several decades,
and using different screening and diagnostic tests, algorithms and treatment protocols would result in substantial
heterogeneity, and used the random-effects model in metaanalyses. We quantified heterogeneity using the I 2 statistic
with a value more than 50% to denote significant inconsistency in the estimates. This indicates that more than half of
the total heterogeneity stems from between-study variance
that could not be explained by sampling error. We also
reported Tau2 (τ 2) with a value more than zero denoting the
absolute value of the true variance (heterogeneity); higher
values of τ 2 indicate greater heterogeneity.
We explored potential causes for significant heterogeneity in LTBI estimates in the following subgroup analyses:
(1) the tests used to diagnose LTBI (TST, IGRA, combination); (2) the place of testing (hospital or health facility,
household, both); and (3) the study design used (prospective, cross-sectional or retrospective). We separately
analysed the LTBI positivity in studies done in Africa, Asia
and South America, sub-grouped by countries within geographical regions within these continents. We also explored
LTBI positivity in studies using TST alone sub-grouped by
the place of testing, and by the size of the skin induration
used to denote a positive TST result (≥5 mm; ≥10 mm).
Regarding the proportions initiating and completing TPT,
we explored heterogeneity in subgroup analysis of studies
including children aged <6 years; <18 years; all age groups.
We also reported the range and the median and interquartile
range (IQR) of these proportions for the overall pooled
results and in the subgroups. Factors reported in the studies
that were considered by study authors to have influenced
the TPT care cascade outcomes were extracted and grouped
under common categories.
RESULTS
Search results
The search yielded 3694 unique records after duplicates
were removed. Figure 1 depicts the flow of the search and
selection process.
After screening the title and abstracts, 3584 records not relevant to this review were excluded (Figure 1). The full texts of
110 potentially eligible studies were assessed, and 52 studies
were excluded because disaggregated data for household and
non-household contacts were not available (n = 29); or the
study designs were inappropriate (n = 9); or there were insufficient data regarding components of the TPT cascade
(n = 11). We included 58 studies that satisfied eligibility criteria in qualitative and quantitative synthesis (meta-analysis).
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FIGURE 1
Flow diagram for study selection. TPT, tuberculosis preventive treatment
Study characteristics
Table 1 summarises the characteristics of the 58 studies conducted in 23 LMICs that were included in this review.
Twenty-eight studies (48%) were conducted in Africa (12 from
countries in East Africa, 7 from West Africa and 9 in Southern
Africa). Twenty-five studies (43%) were conducted in Asia, of
which 17 were conducted in countries in South Asia (with
15 from India); 5 in South East Asia and 3 in East Asia. Three
studies were done in South America (all from Brazil). Two
were multi-country cost-effectiveness studies (one included
countries in Central and West Africa and the other included
centres in Asian and African countries). The majority of the
studies (45/58, 78%) were published between 2011 and 2020,
while six were published before 2010 (2006–2009), and seven
were published in 2021. The study designs included prospective cohorts [n = 28], prospectively ascertained programme
datasets [n = 6], RCTs [n = 2], cross-sectional studies [n =
19], retrospective cohorts [n = 1] and mixed designs [n = 2].
In 27 (46%) of the studies, the target population was
children, with only children <6 years of age included in
25 (43%). Children and adolescents were the target
population in 12 (21%), only adult contacts in 1 (2%), only
adolescents and adults in 1 (2%) and contacts of all ages in
17 (29%) of the studies. Household screening strategies were
used in 19 (33%), and facility-based screening was used in
35 (60%) of the studies. Three studies used both approaches,
and the approach was unclear in one.
Thirty-six (62%) of the studies reported data on screening and LTBI diagnosis, of which 14 also reported on TPT
initiation/completion. Thirty-four (59%) reported on components of TPT initiation/completion, of which 20 did not
report data for LTBI diagnosis. Twenty-eight studies (48%)
provided information on the factors that may have affected
the outcomes of the TPT cascade.
Components of the TPT care cascade
The implementation of the recommended sequence of
steps that formed the strategy used to implement TPT
among household contacts varied in the 58 studies from
the high TB burden, LMIC countries included in the
review.
Characteristics of the included studies
846
TABLE 1
No. Study ID
Geographic region
TB
incidence/100,000
peoplea
1.
Bonnet_Uganda_2017 [17]
East Africa
196
Children <5 years
2.
Chandrasekaran_India_2018
[18]
South Asia
188
Adults + children
3.
Machado_Brazil_2009 [19]
South America
45
Adults + children
4.
MacPherson_South
Africa_2020 [20]
Southern Africa
554
Adults + children
5.
Odera_Kenya_2020 [21]
East Africa
259
Adults ≥18 years
6.
Praveen_India_2020 [22]
South Asia
188
7.
Ronge South Africa_2021 [23]
Southern Africa
8.
Rutherford_Indonesia_2012
[24]
9.
Target population
Household contacts
screened among
those identified (%)
Diagnostic
Screening test(s)
TPT
initiated/
completed
Both
Place/setting
Study design
HC/urban
Prospective
cohort
V + CXR TST
HC/NR
Prospective
cohort
CXR
TST + IGRA NR
261/301 (86.7)
HC/NR
Prospective
cohort
NR
TST
2725/2985 (91.3)
HH/NR
RCT
V + CXR TST
NR
175/NR
HC/semi-urban
Crosssectional
NR
IGRA
NR
Adults + children
≥12 years
220/NR
HH/NR
Crosssectional
V
TST
NR
554
Children ≤15 years
669/669 (100)
HH/urban
Crosssectional
CXR
IGRA
NR
South East Asia
301
Children 6 months to
9 years
320/320 (100)
HC/urban
Prospective
cohort
V
TST + IGRA NR
Shah_South Africa_2011 [25]
Southern Africa
554
Children 6–16 years
270/270 (100)
HH + HC/NR
Prospective
cohort
NR
TST + IGRA NR
10.
Sharma_India_2017 [26]
South Asia
188
Adults + children 1–
65 years
1511/1511 (100)
HH/NR
Prospective
cohort
V + CXR TST + IGRA NR
11.
Stein_Uganda_2018 [27]
East Africa
196
Adults + children
2585/3102 (83.3)
HH/NR
Prospective
cohort
V
12.
Zhang_China_2019 [28]
East Asia
59
Adults + adolescents
>14 years
196/196 (100)
HC/NR
Prospective
cohort
V + CXR IGRA
NR
13.
Akhtar_Pakistan_2009 [29]
South Asia
259
Adults + ≥3 months
385/385 (100)
HH/rural
Crosssectional
V
NR
14.
Hu_China_2013 [30]
East Asia
59
Children + adolescents
9–18 years
School/urban
Crosssectional
V + CXR IGRA
NR
15.
Araujo_Brazil_2020 [31]
South America
554
Adults + children
394/NR
HC/urban
Retrospective
cohort
V
TST
Both
16.
Maraise_South Africa_2006
[32]
Southern Africa
554
Children <5 years
260/274 (94.9)
HC/urban
Prospective
cohort
CXR
TST
Both
17.
Nakaoka_Nigeria_2006 [33]
West Africa
219
Children <15 years
161/161 (100)
HH/urban
Crosssectional
V
TST + IGRA NR
18.
Oxlade_Multicentric_2021
[34]b
South East Asia
(Indonesia,
Vietnam), West
Africa (Ghana)
Indonesia = 301,
Viet
Nam = 176,
Ghana = 143
Children <5 years
1619/1619 (100)
281/339 (82.9)
1048/NR
HC/rural + urban RCT
TST
V + CXR TST
NR
Initiated
(Continues)
TROPICAL MEDICINE & INTERNATIONAL HEALTH
1120/1136 (98.6)
TST
Both
(Continued)
No. Study ID
Geographic region
TB
incidence/100,000
peoplea
19.
Sun_China_2021 [35]
East Asia
59
Children + adolescents
≤18 years
20.
Triasih_Indonesia_2016 [36]
South East Asia
301
Children ≤15 years
21.
Adjobimey_Benin_2016 [37]
West Africa
55
22.
Amisi_Kenya_2021 [38]
East Africa
23.
Silva_Brazil_2016 [39]
24.
Target population
Household contacts
screened among
those identified (%)
95/95 (100)
Place/setting
Study design
Diagnostic
Screening test(s)
TPT
initiated/
completed
HC/rural + urban Prospective
cohort
V
269/413 (65.1)
HC/NR
Prospective
cohort
V + CXR TST
Both
Children <5 years
497/499 (99.6)
HC/urban
Prospective
cohort
V
ND
Both
259
Children <5 years
553/NR
HC/rural + urban Programme
data
V + CXR ND
Both
South America
45
Children ≤15 years
1078/NR
HC/NR
CXR
TST
Both
Burmen_Kenya_2014 [40]
East Africa
259
Children <5 years
337/345 (97.7)
NR/rural + urban Programme
data
V
ND
Initiated
25.
Garie_Ethiopia_2011 [41]
East Africa
132
Children <15 years
184/184 (100)
HC/urban
Prospective
cohort
V
TST
Both
26.
Ginderdeuren_South
Africa_2021 [42]
Southern Africa
554
Children <15 years
77/170 (45.1)
HC/urban
Prospective
cohort
V
ND
Both
27.
Krishnamoorthy_India_2021
[43]
South Asia
188
Adults + children
HC/NR
Prospective
cohort
V + CXR TST
28.
Narasimhan_India_2017 [44]
South Asia
188
Adults + children
359/491 (73.1)
HH/NR
Prospective
cohort
V
TST + IGRA NR
29.
Paradkar_India_2020 [45]
South Asia
188
Adults + children
≥1 year
997/1009 (98.8)
HH + HC/NR
Prospective
cohort
V
TST + IGRA NR
30.
Okwara_Kenya_2017 [46]
East Africa
259
Children <5
428/428 (100)
HC/rural
Prospective
cohort
V
TST
Both
31.
Paul_Nigeria_2019 [47]
West Africa
219
Children ≤5 years
63/NR
HC/NR
Prospective
cohort
V + CXR TST
Both
32.
Rekha_India_2009 [13]
South Asia
188
Children ≤14 years
31/220 (14.1)
HC/rural + urban Crosssectional
V
NR
Both
33.
Rutherford _Indonesia_2012
[48]
South East Asia
301
Children <5 years
150/150 (100)
HC/NR
Prospective
cohort
V
TST + IGRA Both
34.
Sulis_Burkina Faso_2018 [49]
West Africa
46
Children <5 years
956/1166 (82.0)
HH/
Programme
rural + urban
data
V
ND
Initiated
35.
Pothukuchi _India_2011 [10]
South Asia
188
Children <6 years
116/172 (67.4)
HH/
Crossrural + urban
sectional
V
ND
Both
36.
Rekha_India_2013 [50]
South Asia
188
Children <6 years
53/87 (60.9)
HH/
Prospective
rural + urban
cohort
U
ND
Both
37.
Shivaramakrishna_India_2014
[51]
South Asia
188
Children <6 years
218/271 (80.4)
HH/rural
U
ND
Both
1523/NR
Crosssectional
NR
(Continues)
847
Crosssectional
TST + IGRA NR
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TABLE 1
(Continued)
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TABLE 1
No. Study ID
Geographic region
TB
incidence/100,000
peoplea
38.
Seid_Ethiopia_2020 [52]
East Africa
132
Children <5 years
39.
Singh_India_2017 [12]
South Asia
188
40.
Tadesse_Ethiopia_2016 [53]
East Africa
41.
Belgaumkar_India_2018 [11]
42.
Target population
Household contacts
screened among
those identified (%)
Diagnostic
Screening test(s)
TPT
initiated/
completed
Study design
125/129 (96.9)
HC/urban
Mixed
methods
U
ND
Both
Children <5 years
51/59 (86.4)
HH/rural
Mixed
methods
U
ND
Both
132
Children <5 years
237/282 (84.0)
HC/NR
Programme
data
U
ND
Both
South Asia
188
Children <6 years
53/178 (29.8)
HC/NR
Crosssectional
U
ND
Both
Birungi_Rwanda _2019 [54]
East Africa
58
Children <5 years
94/94 (100)
HC/NR
Prospective
cohort
V + CXR ND
Both
43.
Black_South Africa_2018 [55]
Southern Africa
554
Children <5 years
184/261 (70.5)
HC/NR
Crosssectional
V + CXR TST
Both
44.
Chauhan_India_2013 [56]
South Asia
188
Children <5 years
253/NR
HC/NR
Prospective
cohort
V + CXR TST
NR
45.
Datiko_Ethiopia_2017 [57]
East Africa
132
Adults + Children
24,267/24,267 (100)
HC/rural
Prospective
cohort
V + CXR ND
Both
46.
Egere_Gambia_2016 [58]
West Africa
157
Children <5 years
404/404 (100)
HH/
Prospective
rural + urban
cohort
V
TST
Both
47.
Wysocki_Brazil_2016 [59]
South America
554
Adults + children
267/326 (81.9)
HC/urban
Crosssectional
V
TST
Both
48.
Fentahun_Ethiopia_2020 [60]
East Africa
132
Children <5 years
149/230 (64.8)
HC/urban
Crosssectional
V
ND
Initiated
49.
Faksri_Thailand_2015 [61]
South East Asia
150
Adults + children
100/100 (100)
HC/NR
Crosssectional
V
TST + IGRA NR
50.
Sayedi_Afghanistan_2020 [62] South Asia
193
Adults + Children
Programme
data
V
ND
Both
51.
Schwoebel_Multicentric_2020
[63]
Central Africa (Bangui, 815
Cameroon), West
Africa (Benin,
Burkina Faso)
Children <5 years
HH/urban
Prospective
cohort
V + CXR TST
Both
52.
Sharma_India_2021 [64]
South Asia
188
Children <5 years
86/NR
HH/urban
Prospective
cohort
V
ND
Both
53.
Soelen_South Africa_2012 [65] Southern Africa
554
Children <5 years
39/NR
HC/urban
Programme
data
NR
ND
Initiated
54.
Gomes_Guinea-Bissau_2011
[66]
361
Children <15 years
HH/urban
Prospective
cohort
V
TST
Both
West Africa
586,292/856,782 (68.4) HH/urban
1965/1965 (100)
1895/1904 (99.5)
(Continues)
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Place/setting
849
Abbreviations: CXR, only chest x-ray; HC, health centre; HH, house-to-house; IGRA, interferon-gamma release assay; ND, not done; NR, not reported; RCT, randomised controlled trial; TB, tuberculosis; TST, tuberculin skin test; U, unclear;
V, only verbal screening; V + CXR, verbal screening + chest x-ray.
a
TB Incidence: The World Bank Data, 2020, https://data.worldbank.org/indicator/SH.TBS.INCD?locations=BJ.
b
Data only for children <5 years from the low- and middle-income countries evaluated.
NR
IGRA
Crosssectional
1809/NR
554
Southern Africa
Mzembe_South Africa_2020
[70]
58.
Children + adolescents
10–19 years
HH + HC/rural
NR
NR
TST
Crosssectional
148/148 (100)
149
South East Asia
Nguyen_Laos_2009 [69]
57.
Adults + children
HH/urban
NR
NR
IGRA
Crosssectional
112/112 (100)
West Africa
143
Mensah_Ghana_2017 [68]
56.
Adults + children
≥6 months
HC/urban
NR
NR
TST
V
Crosssectional
HC/urban
56/56 (100)
141
Southern Africa
Hector_Malawi_2017 [67]
55.
Children <15 years
Study design
Place/setting
Target population
Geographic region
No. Study ID
Household contacts
screened among
those identified (%)
TB
incidence/100,000
peoplea
TABLE 1
(Continued)
Diagnostic
Screening test(s)
TPT
initiated/
completed
TROPICAL MEDICINE & INTERNATIONAL HEALTH
Screening strategies
Twelve (21%) of the 58 included studies did not report the
proportion of household contacts screened among those
identified as contacts. In the 46 (79%) studies that provided
these data, the proportion of household contacts screened
among those identified ranged from 14% to 100%
(Table 1). Thirty-six studies (78%) screened >80% of identified contacts, 27 (59%) screened ≥95% and 20 (44%)
screened 100% of the identified contacts. Only three studies (7%) reported screening <50% of the identified contacts.
The median proportion of eligible contacts screened across
the studies was 99% (IQR 82%–100%). Of the 45 studies
that reported on the method used to screen out active TB,
only verbal screening for symptoms was used in 26 (58%)
studies and chest x-rays were used in 19 (42%) of the studies (Table 1).
Diagnosis of LTBI
Of the 58 studies, 22 (38%) did not test for TB; most of
them included children under 5–6 years of age where LTBI
testing was not required to initiate TPT (Table 2). Of the
36 studies that tested for LTBI, 21 (58%) used only TST,
with 17 requiring a skin induration size of ≥10 mm to
denote a positive TST result, while an induration size of
≥5 mm was used in the remainder. Four studies (11%) used
only IGRA, while 11 (31%) used both TST and IGRA to
aid diagnosis. In the studies where both tests were used, we
reported the proportions diagnosed as having LTBI based
on the study authors’ definitions. If this was not reported,
we used the IGRA results to denote LTBI positivity
(Table 2).
Estimates of LTBI positivity among household
contacts
Estimates of the proportions with LTBI among the 21,566
household contacts from 36 studies are presented in the forest plot in Figure 2, sub-grouped by studies that used TST
alone or IGRA alone or a combination of the two to
diagnose LTBI.
The pooled random-effects estimate for LTBI positivity
in the 36 studies was 41% (95% CI 33%–49%); however,
there was significant heterogeneity in these estimates that
far exceeded what could be accounted for by chance
(I 2 = 99%; τ 2 = 1.0; p = 0). The proportions diagnosed
with LTBI varied considerably among the studies and ranged from 5% to 81%. In 15/36 studies (42%; TST 9, IGRA
1, both 5), the upper and lower bounds of the 95% CI for
the LTBI positivity estimates did not overlap with the 95%
CI of the pooled estimates for the proportions with LTBI in
the sample (Figure 1). The median LTBI positivity estimate
across the studies was 44%, with an IQR of 28%–59%
(Table 3).
Diagnosis of LTBI among household contacts
No. Study_ID
Eligible household
contacts
850
TABLE 2
Number tested (%)
Test used
(TST/IGRA)
TST positive, IGRA
TST + IGRA
n (%)
positive, n (%) positive, n (%)
Testing
LTBI diagnosed (%, 95% CI) personnel
1.
Bonnet_Uganda_2017 [17]
281
278 (98.9)
TST
144 (51.8)a
NA
NA
2.
Chandrasekaran_India_2018
[18]
869
869 (100)
Both
478 (55)a
468(53.9)
300 (34.5)
3.
Machado_Brazil_2009 [19]
301
261 (86.4)
TST
145 (55.6)c
NA
NA
145 (49.5–61.5)
Trained nursing
and lab staff
4.
MacPherson_South
Africa_2020 [20]
2725
2725 (100)
TST
458 (16.8)a
ND
ND
458 (16.8, 15.5–18.3)
Nurse
111 (39.9, 34.4–45.8)
646b (74.3, 71.3–77.1)
Doctor
Trained lab staff
5.
Odera_Kenya_2020 [21]
175
174 (99.4)
IGRA
NA
97 (55.6)
NA
97 (55.6, 48.3–62.9)
NR
6.
Praveen_India_2020 [22]
220
220 (100)
TST
96 (43.6)c
NA
NA
96 (43.6, 37.3–50.2)
Trained staff
7.
Ronge_South Africa_2021
[23]
669
669 (100)
Both
302 (45.1)c
500 (74.7)
NA
500 (74.7, 71.3–77.9)
Nurse
8.
Rutherford_Indonesia_2012
[24]
304
302 (99.3)
Both
145 (48)c
152 (50.8)
180 (59.2)
180 (59.2, 54.6–64.6)
Project staff
9.
Shah_South Africa_2011 [25]
270
270 (IGRA) (100) Both
71/254 (28)a
79 (29) QFT
NR
71/254 (28.0, 23.0–34.0)
Project staff
263 (TST) (97.4)
10.
Sharma_India_2017 [26]
1511
1511 (100)
QFT 79/270 (29.3, 24.0–35.0)
Both
732 (48.4)c
c
917 (60.7)
540 (35.7)
917 (60.7, 58.2–63.1)
Trained staff
11.
Stein_Uganda_2018 [27]
2585
2562 (99.1)
TST
1683 (65.7)
NA
NA
1683 (65.7, 63.8–67.5)
12.
Zhang_China_2019 [28]
159
159 (100)
Both
72 (45.3)c
75 (47.2)
NR
75 (47.2, 39.6–55.0)
Trained staff
13.
Akhtar_Pakistan_2009 [29]
385
359 (93.3)
TST
179 (49.9)c
NA
NA
179 (49.9, 44.7–55.0)
Project staff
1120
1106 (98.8)
IGRA
NA
52 (4.7)
NA
475
435 (91.6)
TST
351 (80.7)a
NA
NA
351 (80.7, 76.7–84.1)
NR
c
NA
NA
122 (50.2, 44.0–56.4)
NR
61 (42.1)
NA
61 (42.1, 34.3–50.2)
14.
Hu_China_2013 [30]
15.
Araujo_Brazil_2020 [31]
Maraise_South Africa_2006
[32]
260
243 (93.5)
TST
122 (50.2)
17.
Nakaoka_Nigeria_2006 [33]
161
TST 161 (100)
Both
51 (31.9)c
18.
Sun_China_2021 [35]
Both
17 (17.9)c
Trained staff
Trained staff
IGRA 145 (90.1)
19.
Triasih_Indonesia_2016 [36]
20.
Silva_Brazil_2016 [39]
21.
Garie_Ethiopia_2011 [41]
95
413
1078
184
95 (100)
269 (65.1)
981d (91)
184 (100)
5 (5.3)
4 (4.2)
TST
119 (44.2)
c
5 (5.3, 2.3–11.7)
NR
NA
TST
322 (32.8)c
NA
NA
102 (37.9, 32.3–43.8)
NR
NA
321 (32.7, 29.9–35.7)
TST
106 (57.6)c
NR
NA
NA
106 (57.6, 50.4–64.5)
a
NR
NA
NA
801 (52.6, 50.1–55.1)
NR
Trained lab staff
22.
Krishnamoorthy_India_2021
[43]
1523
1523 (100)
TST
801 (52.6)
23.
Narasimhan_India_2017 [44]
359
TST 357 (99.4)
Both
193 (54.1)c
143 (44.1)
NR
143 (44.1, 38.8–49.6)
Both
524 (52.6)a
485 (48.5)
301 (30.2)
707 (70.9, 68.0–73.7)b Trained lab staff
IGRA 324 (90.1)
Both 323 (90)
24.
Paradkar_India_2020 [45]
997
997 (100)
(Continues)
TROPICAL MEDICINE & INTERNATIONAL HEALTH
16.
52 (4.7, 3.6–6.1)
NR
(Continued)
No. Study_ID
Eligible household
contacts
Number tested (%)
Test used
(TST/IGRA)
TST positive, IGRA
TST + IGRA
n (%)
positive, n (%) positive, n (%)
Testing
LTBI diagnosed (%, 95% CI) personnel
428
428 (100)
TST
96 (22.4)c
NA
NA
96 (22.4, 18.7–26.6)
NR
63
62 (98.4)
TST
6 (9.7)c
NA
NA
6 (9.7, 4.5–19.6)
NR
Chauhan_India_2013 [56]
240
200 (83.3)
TST
78 (39)c
NA
NA
78 (39.0, 32.5–45.9)
Project staff
28.
Egere_Gambia_2016 [58]
404
328 (81.2)
TST
63 (19.2)c
NA
NA
63 (19.2, 15.3–23.8)
NR
29.
Wysocki_Brazil_2016 [59]
336
267 (79.5)
TST
106/221
(48.0)a
NA
NA
106 (48.0, 41.5–54.5)
NR
30.
Faksri_Thailand_2015 [61]
70
70 (100)
Both
NR
25.
Okwara_Kenya_2017 [46]
26.
Paul_Nigeria_2019 [47]
27.
NR
15 (21.4)c
c
NA
NA
520 (27.9, 25.9–30.0)
Nurse
NA
NA
253 (21.8, 19.6–24.3)
NR
15 (21.4, 13.4–32.4)
Trained nurse
31.
Schwoebel_Multicentric_2020
[63]
1965
1866 (95.0)
TST
520 (27.9)
32.
Gomes_Guinea-Bissau_2011
[66]
1159
1159 (100)
TST
253 (21.8)c
33.
Hector_Malawi_2017 [67]
56
56 (100)
TST
37 (66.1)c
NA
NA
37 (66.1, 53.0–77.1)
NR
34.
Mensah_Ghana_2017 [68]
112
100 (89.3)
IGRA
NA
65 (65)
NA
65 (65.0, 55.1–73.6)
NR
35.
Nguyen_Laos_2009 [69]
148
148 (100)
TST
46 (31.1)c
NA
NA
46 (31.1, 24.2–39.0)
Project staff
36.
Mzembe_South Africa_2020
[70]
1809
266 (14.7)
IGRA
NA
78 (29.3)
NA
78 (29.3, 24.2–35.1)
NR
TROPICAL MEDICINE & INTERNATIONAL HEALTH
TABLE 2
Abbreviations: IGRA, interferon-gamma release assay; LTBI, latent tuberculosis infection; NA, not applicable; ND, not done; NR, not reported; TST, tuberculin skin test.
TST positive = induration ≥5 mm.
b
LTBI diagnosed if either TST or IGRA or both were positive (as defined by study authors); in other studies where both tests were done and authors had not defined LTBI diagnosis, IGRA positives were diagnosed to have LTBI.
c
TST positive = induration ≥10 mm.
d
Ninety-seven children did not return for TST reading.
a
851
852
TROPICAL MEDICINE & INTERNATIONAL HEALTH
F I G U R E 2 Forest plot of the latent tuberculosis infection positivity estimates in studies using tuberculin skin test or interferon-gamma release assay or a
combination of tests
Exploration of heterogeneity in the estimates
of LTBI
Table 3 summarises the results of subgroup analyses exploring heterogeneity in the LTBI positivity estimates. The
pooled estimates for the proportions with LTBI in the subgroup of studies using TST alone, IGRA alone or a combination of tests were similar to the pooled overall estimates,
with no significant differences between the subgroups, as
evident from the overlapping 95% CIs, and formal tests for
853
TROPICAL MEDICINE & INTERNATIONAL HEALTH
T A B L E 3 Summary of LTBI positivity using TST, IGRA or both and exploration of heterogeneity based on the tests used, the place of testing, the study
design and geographical location of the studies
LTBI diagnosis: all
(TST/IGRA/both)
Proportion with LTBI (%)
Pooled LTBI positivity (random
effects)
Range
Median (IQR)
% (95% CI)
I 2, τ 2; p
Forest plot
Studies
Household
contacts
LTBI
positive
36
21,566
9290
4.7–80.7
43.9 (28.3–58.8)
41.0 (33.0–49.0)
99%, 1.0; <0.01
Figure 2,
Figures S1
and S2
Subgroups analysis 1: diagnostic tests used
TST alone
21
14,509
5670
9.7–80.7
39.9 (25.2–51.4)
40.0 (32.0–49.0)
99%, 0.67; <0.01
Figure 2,
subgroup 1
4
1646
292
4.7–65.0
42.5 (10.9–62.7)
32.0 (10.0–65.0)
99%, 1.98; <0.01
Figure 2,
subgroup 2
11
5411
3328
5.3–74.7
47.2 (29.3–70.9)
47.0 (37.0–62.0)
98%, 1.2; <0.01
Figure 2,
subgroup 3
8236
4235
9.7–80.7
49.5 (35.3–62.1)
44.0 (35.0–55.0)
98%, 0.96; <0.01
Figure S1,
subgroup 1
4846
16.8–74.7
43.6 (27.9–60.7)
43.0 (32.0–54.0)
99%, 0.65; <0.01
Figure S1,
subgroup 2
1642
209
4.7–29.3
29.3 (4.7–29.3)
17.0 (6.0–39.0)
99%, 0.99; <0.01
Figure S1,
subgroup 3
IGRA alone
Both
Subgroup analysis 2: place of testing
Health facility
22
Household
11
Both/school
3
11.688
Subgroup analysis 3: study design
Prospective
22
16,616
7286
9.7–74.3
44.1 (25.2–58.4)
39.0 (30.0–49.0)
99%, 0.89; <0.01
Figure S2,
subgroup 1
Not prospective
14
4950
2004
4.7–80.7
45.8 (30.7–65.3)
44.0 (31.0–58.0)
99%, 1.14; <0.01
Figure S2,
subgroup 2
LTBI diagnosis (TST/IGRA/both): geographical regions
Africa
17
11,516
4325
9.7–74.7
39.9 (22.1–61.3)
39.0 (29.0–50.0)
99%, 0.81; <0.01
Figure S3
Subgroup analysis: regions
West and Central
Africa
6
3660
958
9.7–65.0
24.9 (16.8–47.8)
28.0 (16.0–44.0)
96%, 0.72; <0.01
Figure S3,
subgroup 1
East Africa
5
3627
2093
22.4–65.7
55.6 (31.2–61.7)
48.0 (34.0–62.0)
96%, 0.44; <0.01
Figure S3,
subgroup 2
Southern Africa
6
4229
1274
16.8–74.7
39.8 (26.2–68.3)
43.0 (26.0–62.0)
99%, 0.88; <0.01
Figure S3,
subgroup 3
15
8152
4042
4.7–74.3
44.1 (21.4–51.2)
40.0 (27.0–54.0)
99%, 1.24; <0.01
Figure S4
Asia
Subgroup analysis: regions
South Asia
8
6003
3567
39.0–74.3
51.3 (43.7–58.4)
55.0 (46.0–64.0)
97%, 0.26; <0.01
Figure S4,
subgroup 1
East Asia
3
1360
132
4.7–47.2
5.3 (4.7 to –)
12.0 (3.0–39.0)
99%, 1.82; <0.01
Figure S4,
subgroup 2
South East Asia
4
789
343
5.3–59.2
29.7 (9.3–53.9)
37.0 (25.0–52.0)
95%, 0.34; <0.01
Figure S4,
subgroup 3
4
1898
923
32.7–80.7
48.8 (36.5–72.9)
55.0 (36.0–73.0)
99%, 0.60: <0.01
Figure S5
South America
Brazil
Abbreviations: CI, confidence interval; IGRA, interferon-gamma release assay; IQR, interquartile range; LTBI, latent tuberculosis infection; TST, tuberculin skin test.
subgroup differences (Table 3; Figure 2). Significant heterogeneity was also present within the subgroups, indicating
that the inconsistency in LTBI estimates was not explained
by the tests used. Similarly, neither the place of testing
(Table 3; Figure S1), nor the study designs (Table 3;
Figure S2) explained the heterogeneity in LTBI estimates.
LTBI estimates did not also appear to be influenced by the
year of publication of the studies (Figure 2). The median
and IQR for the proportions with LTBI in these subgroups
also overlapped (Table 3).
Geographical variations in screening and testing protocols and in resources were also explored as potential causes
of heterogeneity in subgroup analyses. LTBI estimates from
studies among household contacts in Africa were
854
TROPICAL MEDICINE & INTERNATIONAL HEALTH
TABLE 4
Summary of LTBI positivity using TST only and exploration of heterogeneity based on place of testing and the size of skin induration
LTBI
diagnosis:
TST only
Proportion with LTBI (%)
Pooled LTBI positivity (random
effects)
Range
Median (IQR)
% (95% CI)
Studies
Household
contacts
LTBI
positive
22
14,811
5850
5.3–80.7
39.9 (25.2–51.4)
41.0 (33.0–49.0)
99%, 0.66; <0.01
Figures S6 and S7
I 2, τ 2; p
Forest plot
Subgroup analysis 1: place of testing
Health
facility
15
5772
2625
9.7–80.7
48.0 (32.7–57.6)
44.0 (34.0–54.0)
97%, 0.68; <0.01
Figure S6, subgroup 1
Household
7
9039
3225
5.3–65.7
27.9 (16.8–49.9)
36.0 (24.0–48.0)
100%, 0.53; <0.01
Figure S6, subgroup 2
Subgroup analysis 2: size of induration
Induration
≥5 mm
5
5182
1827
16.8–80.7
39.9 (28.4–66.7)
47.0 (28.0–68.0)
100%, 0.94; <0.01
Figure S7, subgroup 1
Induration
≥10 mm
17
9629
4023
5.3–66.1
39.0 (22.1–53.9)
39.0 (31.0–48.0)
99%, 0.55; <0.01
Figure S7, subgroup 2
Abbreviations: CI, confidence interval; IQR, interquartile range; LTBI, latent tuberculosis infection; TST, tuberculin skin test.
separately analysed, sub-grouped by countries in West and
Central Africa, East Africa and Southern Africa (Table 3;
Figure S3). Studies from Asia were sub-grouped by studies
from countries in South Asia, East Asia and South East
Asia (Table 3; Figure S4). Pooled estimates from studies
from South America were represented by three studies
from Brazil (Table 3; Figure S5). None of these sub-group
analyses adequately explained the heterogeneity in LTBI
estimates.
Additionally, we explored heterogeneity in LTBI estimates in studies using TST alone sub-grouped by the place
of testing (Table 4; Figure S6) and the size of skin induration
(Table 4; Figure S7). These sub-group analyses also did not
explain the heterogeneity in LTBI estimates.
Tuberculosis preventive treatment
Table 5 provides summary estimates of the proportion of
household contacts in whom TPT was initiated and the proportion completing TPT in the studies that reported these
outcomes. Of the 58 included studies, 34 (59%) reported
data regarding treatment initiation among the 129,573
household contacts considered eligible for TPT. Twenty-six
of these studies initiated TPT in children ≤6 years of age,
four studies included children and adolescents and four
included contacts of all ages (Table 5). Eighteen studies were
conducted in Africa. Ten studies were conducted in Asia
(seven in India). Four studies were from Brazil, and two
were multi-country studies (Table 5). Twenty-two studies
used a prospective design, while nine studies were cross-sectional, one was a retrospective cohort study, and two used
mixed methods.
Of the 34 studies reporting on TPT initiation, 28 (82%)
also reported the proportions completing TPT. Six of the
26 studies that initiated TPT in children ≤6 years of age did
not report treatment completion rates, with three reporting
that they had referred household contacts with LTBI elsewhere after treatment initiation. The methods used to facilitate treatment adherence were reported in only 13/34
studies (38%) and the proportions actually adherent was
infrequently reported. Adverse event monitoring and management were also poorly reported. Various TPT regimens
were used, though daily isoniazid for 6 months was the most
commonly used regimen.
In the 28 studies reporting treatment initiation and completion, 108,679 contacts were initiated on TPT. The numbers considered to be TPT treatment failures (incident TB
developed while on TPT) were reported in 12 (43%) of these
studies. Treatment failures were rare, affecting 25 of 74,991
(0.03%) contacts completing treatment in the 28 studies
(Tables 5 and 6).
As with the estimates of LTBI, the proportions that initiated and completed TPT varied considerably in the studies
reporting these estimates. The proportions initiated on TPT
in the 34 studies ranged from 15% to 100%; and in the
28 studies that also reported treatment completion, the proportions ranged from 5% to 94% (Tables 5 and 6).
Figure 3 displays the forest plot of the proportions initiating TPT, and Figure 4 displays the forest plot of the proportions completing TPT; sub-grouped by the age of the
household contacts included. Table 6 summarises the pooled
estimates for the proportions initiating and completing
treatment and the results of subgroup analyses exploring
heterogeneity, as well as the median proportions (with the
IQR) for treatment initiation and completion.
Figure 3 displays the estimates for treatment initiation
rates among 129,573 household contacts who were eligible
for treatment in the 34 studies. The pooled estimate for the
proportions initiating TPT was 91% (95% CI 79%–97%).
There was significant heterogeneity in the estimates
(I 2 = 99%; τ 2 = 7.79; p < 0.01), that was not explained by
subgroup analysis. The median proportion that was initiated
on TPT was 86% (IQR 60%–100%) (Table 6).
No.
Tuberculosis preventive therapy (TPT) initiation and completion among household contacts
Study_ID
Age
(years)
Eligible for
treatment (n)
Treatment initiated, n (%,
95% CI)
Adherence
monitoring
Treatment completion, n (%,
95% CI)
Treatment
regimen used
Treatment
failurea
1.
Bonnet_Uganda_2017 [17]
<5
234
234 (100, 98.0–100)
NR
188 (80.3, 74.8–84.9)
6HZ
1
2.
Machado_Brazil_2009 [19]
All
101
101 (100. 96.0–100)
NR
54 (53.5, 43.8–62.9)
6H
NR
233 (82.9, 78.1–86.9)
3.
Araujo_Brazil_2020 [31]
All
320
281 (87.8, 83.8–91.0)
NR
6HZ
1
4.
Maraise_South Africa_2006
[32]
<5
236
180 (76.3, 74.5–81.2)
Yes
36 (20.0, 14.8 to 26.4)
6H
4
5.
Oxlade_Multicentric_2021
[34]b
<5
347
250 (72.1, 67.1–76.5)
Yes
NR
6H
NR
6.
Triasih_Indonesia_2016 [36]
≤5
99
86 (86.9, 78.8–92.2)
NR
50 (58.1, 47.6–68.0)
6H
None
7.
Adjobimey_Benin_2016 [37]
<5
497
496 (99.8, 98.9–99.99)
Yes
427 (86.1, 82.8–88.9)
9H
3
8.
Amisi_Kenya_2021 [38]
<5
472
427 (90.5, 87.5–92.8)
NR
205 (48.0, 43.3–52.7)
6H
6
9.
Silva_Brazil_2016 [39]
≤15
322
109 (33.9, 28.9–39.2)
Yes
73 (67.0, 57.7–75.1)
9H, 6H
1
10.
Burmen_Kenya_2014 [40]
<5
337
51 (15.1, 11.7–19.4)
NR
NR
6H
NR
11.
Garie_Ethiopia_2011 [41]
<15
82
82 (100, 95.5–100)
Yes
10 (12.2, 6.8–21.0)
6H
1
12.
Ginderdeuren_South
Africa_2021 [42]
<15
56
56 (100, 93.5–100)
NR
24 (42.9, 30.8–52.9)
6H
1
13.
Paul_Nigeria_2019 [47]
≤5
55
55 (100, 93.5–100)
Yes
24 (43.6, 31.4–56.7)
6H
NR
14.
Rekha_India_2009 [13]
≤6
84
16 (19.1, 12.1–28.7)
NR
NR
6H
NR
15.
Rutherford _Indonesia_2012
[48]
<5
82
82 (100, 95.5–100)
Yes
21 (25.6, 17.4–36.0)
6H
NR
16.
Sulis_Burkina Faso_2018 [49]
<5
941
852 (90.5, 88.5–92.6)
NR
NR
6H
NR
17.
Pothukuchi _India_2011 [10]
<6
116
97 (83.6, 75.8–85.3)
NR
83 (85.6, 77.2–91.2)
6H
NR
18.
Rekha_India_2013 [50]
<6
53
53 (100, 93.2–100)
NR
39 (73.6, 60.4–83.6)
6H
NR
19.
Shivaramakrishna_India_2014
[51]
<6
209
70 (33.5, 27.4–40.1)
NR
16 (22.9, 14.6–40.0)
6H
NR
NR
20.
Seid_Ethiopia_2018 [52]
<5
125
94 (75.2, 67.0–81.9)
NR
74 (78.7, 69.4–85.8)
6H
21.
Singh_India_2017 [12]
<5
50
11 (22.0 1.8–35.2)
NR
10 (90.9, 62.3–98.4)
6H
NR
22.
Tadesse_Ethiopia_2016 [53]
<5
221
142 (64.3, 57.7–70.3)
NR
114 (80.3, 73.0–84.0)
6H
None
23.
Belgaumkar_India_2018 [11]
<6
33
28 (84.9, 69.1–93.1)
NR
21 (75.0, 56.6–87.3)
6H
NR
24.
Birungi_Rwanda_2019 [54]
<5
94
84 (89.4, 81.5–94.1)
Yes
74 (88.1, 79.5–93.4)
6H
1
74 (40.7, 33.8–48.0
NR
25.
Black_South Africa_2018 [55]
<5
182
NR
4 (5.4, 2.1–13.1)
6H
26.
Datiko_Ethiopia_2017 [57]
All
3027
1761 (58.2, 56.4–60.0)
Yes
1574 (89.4, 87.9–90.7)
6H
3
27.
Egere_Gambia_2016 [58]
<5
368
328 (89.1, 85.5–91.9)
Yes
255 (77.7, 72.9–81.9)
6H
NR
28.
Wysocki_Brazil_2016 [59]
All
106
64 (60.4, 50.9–69.2)
NR
36 (56.3, 44.1–67.7)
6H
NR
29.
Fentahun_Ethiopia_2020 [60]
<5
138
44 (31.9, 24.7–40.1)
NR
NR
6H
NR
30.
Sayedi_Afghanistan_2020 [62]
<5
117,593
101,084 (86.0, 85.8–86.2)
NR
6H
NR
69,273 (68.5, 68.2–68.8)
855
(Continues)
TROPICAL MEDICINE & INTERNATIONAL HEALTH
TABLE 5
856
NR
6H
9H
378 (46.1, 42.71–49.5)
Abbreviations: CI, confidence interval; H, isoniazid; NR, not reported; R, rifampicin; TPT, tuberculosis preventive treatment; Z, pyrazinamide; the numbers before the drug names denote the number of months of treatment.
Treatment failure: incident tuberculosis disease during the course of treatment.
b
Data only for children <5 years from the low- and middle-income countries evaluated.
a
989
Gomes_Guinea-Bissau_2011
[66]
34.
<15
820 (82.9, 80.4–85.1)
Yes
2
NR
6H
42 (67.7, 55.4–78.1)
20 (37.0, 25.4–50.4)
NR
Yes
62 (72.1, 61.8–80.5)
54 (100, 93.4–100)
54
86
<5
Sharma_India_2021 [64]
Soelen_South Africa_2012 [65]
32
33.
<5
1
3RH, 6H
<5
Schwoebel_Multicentric_2020
[63]
31.
1909
1746 (91.5, 90.1–92.6)
Yes
1642 (94.0, 92.8–95.1)
Treatment
failurea
Study_ID
No.
TABLE 5
(Continued)
Age
(years)
Eligible for
treatment (n)
Treatment initiated, n (%,
95% CI)
Adherence
monitoring
Treatment completion, n (%,
95% CI)
Treatment
regimen used
TROPICAL MEDICINE & INTERNATIONAL HEALTH
Compared to the more than 90% pooled estimates for
TPT initiation, the pooled estimate for the proportions
completing TPT (Figure 4) was considerably lower (65%,
95% CI 54%–74%), with significant heterogeneity in the
estimates (I 2 = 98%, τ 2 = 1.48, p < 0.01). The pooled
treatment completion proportions did not significantly
differ between the subgroups based on age; and did not
explain the heterogeneity in the estimates of the proportions completing treatment. The true estimates of treatment completion with TPT are uncertain, but the median
estimate for proportions completing treatment was 68%
(IQR 44%–82%) (Table 6).
Factors affecting the TPT care cascade
The factors reported in 28 studies which the authors considered to have affected one or more components of the TPT
care cascade are summarised in Table 7.
For the diagnosis of LTBI, short duration of the followup, and the type of tests used were reported as potentially
important (Table 7). The time of testing was reported as
another factor that might have affected the results since contacts incubating the infection might test negative if tested
early, thus leading to an underestimation of the infection
prevalence. In studies where data were collected retrospectively, inadequate documentation of the care cascade components was reported to have likely impacted the study
outcomes. In many settings, the information on the household contacts (especially for child contacts) was retrieved
from the index patient’s card, thus inadequate documentation could have led to selection bias for household contacts.
Furthermore, in studies that collected information from the
participants, recall bias, and the general tendency to provide
socially desirable responses were reported as factors that
could have resulted in over/underestimation of the findings
of the studies.
For preventive treatment, factors such as higher cost of
transportation, medication palatability, treatment duration,
social support and the knowledge and beliefs of healthcare
workers were thought to have influenced the reported treatment outcomes. Where described, treatment adherence was
defined based on pill count or the monthly prescription of
the medicines collected from the subjects. This might have
led to an overestimation of treatment adherence. Another factor that might have impacted the results was the risk perception of the participants; parents’ or caregivers’ own
experience concerning TB disease and its health consequences
that could have motivated them to initiate treatment among
their close contacts; whereas, in studies where adherence was
poor, absence of signs and symptoms among contacts could
have adversely impacted the treatment-related decisions. In
some studies, participants’ characteristics in terms of their
immune status were reported to have likely impacted the
findings. Health worker-related factors such as high patient to
health worker ratio and their working hours could compromise the quality of care. The timing of household visits by the
857
TROPICAL MEDICINE & INTERNATIONAL HEALTH
TABLE 6
Summary of the proportions initiating and completing TPT for LTBI and exploration of heterogeneity based on age of household contacts
TPT initiation
Proportion on TPT (%)
Pooled proportion on TPT (random
effects)
Range
Median (IQR)
% (95% CI)
I 2, τ 2; p
Forest plot
109,974
15.1–100.0
85.5 (59.9–100)
91.0 (79.0–97.0)
99%, 7.79; 0.00
Figure 3
Studies
Eligible
household
contacts
On
TPT
34
129,573
Subgroup analysis: age
<6 years
26
124,570
106,700
15.1–100.0
85.5 (58.4–98.9)
90.0 (75.0–97.0)
99%, 7.54; <0.01
Figure 3, subgroup 1
<18 years
4
1449
1067
33.9–100.0
91.5 (46.2–100.0)
98.0 (32.0–100.0)
99%, 14.88; <0.01
Figure 3, subgroup 2
All ages
4
3554
2207
58.2–100.0
74.1 (58.8–97.0)
89.0 (45.0–99.0)
97%, 4.63; <0.01
Figure 3, subgroup 3
28
108,679
74,991
5.4–94.0
68.1 (44.2–82.3)
65.0 (54.0–74.0)
98%, 1.48; <0.01
Figure 4
TPT completion
Subgroup analysis: age
<6 years
20
105,159
72,364
5.4–94.0
71.1 (38.7–84.3)
64.0 (49.0–76.0)
98%, 1.95; <0.01
Figure 4, subgroup 2
<18 years
4
1313
730
42.9–77.7
56.6 (43.7–75.2)
60.0 (44.0–73.0)
97%, 0.38; <0.01
Figure 4, subgroup 2
All ages
4
2207
1897
53.5–89.4
69.6 (54.2–87.8)
74.0 (55.0–87.0)
98%, 0.71; <0.01
Figure 4, subgroup 2
Abbreviations: CI, confidence interval; IQR, interquartile range; LTBI, latent tuberculosis infection; TPT, tuberculosis preventive treatment.
workers could lead to under-representation of certain age
groups (especially school-going children) as many might not
be available at that time (Table 7).
As reported in the studies, factors operating at multiple
levels can facilitate or hinder the execution of each component of the care cascade. Therefore, for a successful realisation of the care cascade, it is imperative to address these
factors in contextually appropriate ways.
DISCUSSION
This systematic review aimed to describe the strategies
used in studies from high TB burden countries for detecting LTBI in household contacts of people with bacteriologically confirmed pulmonary TB who were not
immunocompromised, and to ascertain the proportions
initiated on and completing TPT. The 58 included studies
provide updated estimates to supplement estimates from
existing systematic reviews in this area [3, 6, 14, 15]. The
pooled estimates for LTBI positivity of 41% (95% CI 33%–
49%), using a combination of TST or IGRA or both, in
21,566 household contacts of people with bacteriologically
confirmed pulmonary TB in the 36 studies provide a
timely reminder of the hidden burden of TB infection.
Even though there was significant heterogeneity in these
estimates, the median LTBI positivity estimates (44%, IQR
28%–59%) indicate that between a third to over half of the
household contacts of people with bacteriologically
proven TB are likely to have LTBI.
Over half of these studies used TST alone to detect LTBI.
Since most studies also used only verbal screening of symptoms to rule out active TB, concerns exist about the potential for false negative results with the use of TST alone. The
number of studies that used IGRA (alone or in combination
with TST) to diagnose LTBI was fewer. The relatively higher
LTBI yield in these studies (albeit with wide 95% CI that
overlapped with the TST-diagnosed LTBI estimates),
coupled with the likelihood of fewer false-positive results,
suggest that increasing the use of imaging modalities and
molecular tests could augment the utility of contact tracing
for LTBI management. However, this would need to be balanced against available resources and other programmatic
considerations.
WHO recommends that contact investigation be conducted through home visits but the data in this review did
not find the LTBI diagnostic yield to differ significantly
with health facility-based versus home-based contact
investigations.
The other notable finding in this review was the higher
proportions of contacts with LTBI initiating TPT compared
to the lower proportions completing treatment. The pooled
estimates for treatment initiation in 129,573 eligible household contacts in the 34 studies was an impressive 91% (95%
CI 79%–97%), compared to the pooled estimates of the proportions completing treatment (65%, 95% CI 54%–74%)
among 108,679 contacts who commenced TPT in 28 of
these studies. In spite of the significant heterogeneity in
these estimates, the nearly 20% difference in the median
proportion completing compared to initiating treatment,
reveals a flaw in the TPT care cascade that can adversely
impact the effectiveness of LTBI management among household contacts.
The qualitative synthesis of the factors reported by
study investigators provide complementary insights about
the factors related to the various components of the cascade of care that could have contributed to heterogeneity
in LTBI estimates and TPT outcomes. These factors can
also inform strategies to improve the effectiveness of LTBI
management. No single factor or intervention can be considered pre-eminent to improve the LTBI cascade, and
many incremental strategic adjustments will be needed to
reduce losses that can occur throughout the LTBI cascade
of care [71].
858
FIGURE 3
TROPICAL MEDICINE & INTERNATIONAL HEALTH
Forest plot of the proportions initiating tuberculosis preventive treatment sub-grouped by the age of household contacts
Limitations
A major limitation in this review was the lack of adequate
details provided in the included studies regarding the
processes used in screening, testing or treatment initiation due to which we were unable to adequately assess
the quality of implementation of LTBI management
strategies. The variety of included study designs precluded valid assessments of the risk of bias uniformly
applicable across these designs. The possibility of reporting biases is also high with systematic reviews using
observational data.
859
TROPICAL MEDICINE & INTERNATIONAL HEALTH
FIGURE 4
Forest plot of the proportions completing tuberculosis preventive treatment sub-grouped by the age of household contacts
Another major limitation was the significant heterogeneity in the pooled estimates from meta-analysis for the diagnostic yield. This was not explained in subgroup analyses
based on the diagnostic tests used and the place of testing.
Additional post hoc sub-group analyses based on the study
designs employed and geographical differences in the
countries where the studies were conducted also did not
explain the heterogeneity. Significant heterogeneity in the
estimates for TPT outcomes was also a serious limitation
that was not explained in pre-stated subgroup analyses
based on the age of the household contacts. The prevalence
of TB (and LTBI) varies across different populations within
860
TABLE 7
TROPICAL MEDICINE & INTERNATIONAL HEALTH
Factors reported to affect the TPT care cascade
Study
reference
Factors
Description
Duration of follow-up
Short duration of follow-up could have affected the assessment of TPT effectiveness and the magnitude of the
true burden of Mycobacterium tuberculosis infection.
[17, 26, 59]
Type of test used
Using TST could have resulted in low yield for M. tuberculosis infection, since IGRA correlates better with
recent M. tuberculosis exposure and has higher accuracy in diagnosing infection in children.
[18, 23]
Timing of tests
The timing of conducting tests could have affected the results in terms of LTBI positivity as the average time
for developing hypersensitivity reactions is 4–12 weeks, thus some household contacts who might have
been incubating the infection might have tested negative on the tests.
[24, 29]
Inadequate
documentation
Retrospective studies and studies on programmatic data reported that the lack of proper documentation on the
care cascade for TB management could have affected their assessment and findings. Collecting data from
the programme registers and from reports that lack rigour in documenting the information could lead to
selection bias for the number of household contacts.
[32, 38, 52,
53, 62]
Adherence to TPT
The common factors related to TPT adherence included: higher cost of transportation, medication palatability,
longer treatment duration, social support, and the knowledge and beliefs of HCWs and carers. Further,
treatment adherence reported in the studies could be an overestimation as it depended on pill count or on
the monthly collection of prescriptions.
[37, 39, 42,
48, 66]
Risk perception of the
participants
Parents’ or caregivers’ own experience concerning TB disease and its long-term health consequences was
reported as a motivating factor for TPT initiation and completion. Further, participants’ perception
regarding the risk related to LTBI influences the treatment initiation and adherence among HH contacts,
especially among child contacts. Parents were unable to comprehend the relevance of initiating TPT
among asymptomatic children.
[40, 41, 55,
60]
Recall bias
Studies that ascertained information on the care cascade from the participants reported that recall bias or the
tendency to provide socially desirable answers could have resulted in under- or over-estimation of the
results in the study.
[12, 43, 51,
60, 70]
Participants’
characteristics
One study reported that HIV positivity reduces the likelihood of completing testing, whereas in another, it was
reported that HIV-infected participants were more likely to get their contacts screened as they visit the
health facility regularly and are aware of the benefits of early contact screening. Another study mentioned
that subjects’ immunological status could also impact the testing outcomes as the T-SPOT.TB assay was
based on the individual activated T cell.
[20, 30, 60]
HCWs’ related
In one study, the high patient to health worker ratio was thought to have compromised the quality of care,
whereas another reported that the working hours of the HCWs could have resulted in underrepresentation of certain age group (especially school-going children).
[40, 57]
Abbreviations: HCWs, healthcare workers; HH, house-to-house; IGRA, interferon-gamma release assay; IPT, isoniazid preventive therapy; LTBI, latent tuberculosis infection; TB,
tuberculosis; TST, tuberculin skin test.
and between countries and between geographical regions,
as was also evident in other systematic reviews and metaanalysis of TB contact tracing [3, 6, 14, 15]; their results
were similar to the estimates in this review. This highlights
the inherent difficulty in accurately estimating, with the
available data, the effects of strategies like TB contact tracing among diverse populations.
Anticipating that meta-analysis of studies of disease
prevalence would result in significant heterogeneity, we
chose to use the random-effects model for meta-analysis.
The random-effects model adjusts the weights assigned to
each study to account for within-study and between-study
variability, and results in wider 95% CIs for the prevalence
estimates. With the magnitude of heterogeneity observed
(I 2 > 95%–100%), the weights assigned to each study in
random-effects meta-analysis are nearly equal, regardless of
the sample size and study variance. Therefore, the point estimates for LTBI and TPT outcomes in these studies generated through random-effects meta-analysis only represent
the mean of a wide range of possible estimates [72]. In spite
of the significant heterogeneity, we chose to retain the meta-
analysis estimates in order to explore heterogeneity, but caution against relying on these pooled estimates alone. The
median estimates (with the IQR) that accompany each analysis offer a more conservative interpretation of LTBI positivity and TPT outcomes in the included studies.
Recommendations for LTBI management
scale up
In spite of these limitations, the evidence synthesised in this
review provides important information that can inform the
national TB programmes in high TB burden countries while
scaling up LTBI management.
Firstly, a more systematic approach is needed for
screening TB symptoms (to exclude active TB). There are
already comprehensive guidelines on contact investigations
provided by WHO that most programmes have integrated
into their systems. However, the recording and reporting for
TPT eligibility need to be strengthened. Information regarding the personnel doing the screening and their training;
861
TROPICAL MEDICINE & INTERNATIONAL HEALTH
details on the timing and frequency of screening, particularly in relation to the timing since the index case was diagnosed, also need to be documented as these can impact
detection and implementation. Screening should not depend
only on verbal screening of symptoms to rule out active TB,
and imaging and molecular tools should be optimally
utilised.
Secondly, diagnostic testing for LTBI among the household contacts should be mandatory and TPT should not be
initiated without a positive result (except for those <5 years
and for those with HIV infection, or on the recommendation of a consulting physician), since, on an average, only a
third to a little more than half of household contacts may
have LTBI. Irrespective of the diagnostic test used or considered feasible, ensuring consistent protocols and adequately
trained staff in administrating the tests will result in better
outcomes.
Thirdly, mechanisms to ensure better integration of TPT
initiation with mechanisms to encourage and monitor
adherence, detect and manage adverse events, provide
counselling, to record treatment completion and follow-up
after TPT are required. Many of these problems already exist
in national TB programmes for active TB case finding, and
common solutions are needed for LTBI and TB case detection and management [73]. For optimum utilisation of
resources, adherence mechanisms integrated with active TB
management may work well, however real-world experience
indicates that this may overburden health workers who support TB treatment.
TPT scale-up, as recommended by WHO and the
commitments at UNHLM, is important. However, in
high-TB burden, resource-constrained countries, this
would require attending to approximately four-times
more people than the total number of TB patients diagnosed. Integrating TPT in the current active TB programmes, without providing additional human resources,
risks overburdening of existing staff, while leaving large
numbers without completing their treatment, and wasting
already limited resources in terms of free testing and
treatment provided under the programmes. While shorter
treatment regimens may aid in treatment completion, the
systems to support this need to be in place for this to
work. Follow-up mechanisms for those household contacts who complete TPT to document any further episodes
of TB also need to be in place.
proportions initiated on TPT were reassuringly high, treatment completion proportions were worryingly lower. The
qualitative data collected alongside the quantitative data
provide heuristic insights about factors that could reduce
losses in the LTBI cascade of care.
A C K N O W L E D G E M E N TS
We acknowledge Prof. Paul Garner, Director – Research,
Evidence and Development Initiative (READ-IT), Liverpool
School of Tropical Medicine, Liverpool for his support during the initial phase of prioritising the research question and
protocol development for systematic review. We thank the
authors who responded promptly and shared their full
papers for screening and inclusion in the review.
FUNDING INFORMATION
This publication is associated with the Research, Evidence
and Development Initiative (READ-It). READ-It (project
number 300342-104) is funded by UK aid from the UK
Government; however, the views expressed do not necessarily reflect the UK Government’s official policies.
REFERENC ES
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
CONCLUSION
The results of this systematic review and meta-analysis provide updated data on LTBI positivity, TPT initiation and
completion among household contacts in high TB burden
countries. The common strategies used to identify those eligible were contact investigation either at home or at health
facility, mostly using verbal screening. The proportions
detected with LTBI varied considerably in the studies, but
the median positivity for LTBI was 44%. While the
11.
12.
13.
Global tuberculosis report. Geneva: World Health Organization; 2021.
Licence:CC BY-NC-SA 3.0 IGO.
The end TB strategy. Geneva: World Health Organization; 2014.
Alsdurf H, Hill PC, Matteelli A, Getahun H, Menzies D. The cascade
of care in diagnosis and treatment of latent tuberculosis infection: a
systematic review and meta-analysis. Lancet Infect Dis. 2016;16(11):
1269–78.
Latent tuberculosis infection: updated and consolidated guidelines for
programmatic management. Geneva: World Health Organization;
2018.
Houben RM, Dodd PJ. The global burden of latent tuberculosis infection: a re-estimation using mathematical modelling. PLoS Med. 2016;
13(10):e1002152.
Fox GJ, Barry SE, Britton WJ, Marks GB. Contact investigation for
tuberculosis: a systematic review and meta-analysis. Eur Respir J.
2013;41(1):140–56.
WHO consolidated guidelines on tuberculosis. Module 1: prevention
– tuberculosis preventive treatment. Geneva: World Health Organization; 2020.
Recommendations for investigating contacts of persons with infectious tuberculosis in low- and middle-income countries. Geneva:
World Health Organization; 2012. p. 28–41.
Political declaration of the high-level meeting of the General Assembly
on the fight against tuberculosis. World Health Organization. The
General Assembly. 2018;2(2):101.
Pothukuchi M, Nagaraja SB, Kelamane S, Satyanarayana S,
Shashidhar BS, Dewan P, et al. Tuberculosis contact screening
and isoniazid preventive therapy in a South Indian district: operational issues for programmatic consideration. PLoS One. 2011;6(7):
e22500.
Belgaumkar V, Chandanwale A, Valvi C, Pardeshi G, Lokhande R,
Kadam D, et al. Barriers to screening and isoniazid preventive therapy
for child contacts of tuberculosis patients. Int J Tuberc Lung Dis.
2018;22(10):1179–87.
Singh AR, Kharate A, Bhat P, Kokane AM, Bali S, Sahu S, et al. Isoniazid preventive therapy among children living with tuberculosis
patients: is it working? A mixed-method study from Bhopal, India.
J Trop Pediatr. 2017;63(4):274–85.
Banu Rekha VV, Jagarajamma K, Wares F, Chandrasekaran V,
Swaminathan S. Contact screening and chemoprophylaxis in India’s
862
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
TROPICAL MEDICINE & INTERNATIONAL HEALTH
revised tuberculosis control programme: a situational analysis. Int J
Tuberc Lung Dis. 2009;13(12):1507–12.
Velen K, Shingde RV, Ho J, Fox GJ. The effectiveness of contact investigation among contacts of tuberculosis patients: a systematic review
and meta-analysis. Eur Respir J. 2021;58:2100266.
Szkwarko D, Hirsch-Moverman Y, Plessis LD, Preez KD, Carr C,
Mandalakas AM. Child contact management in high tuberculosis burden countries: a mixed-methods systematic review. PLoS One. 2017;
12(8):e0182185.
Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC,
Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline
for reporting systematic reviews. BMJ. 2021;372:n71.
Bonnet M, Kyakwera C, Kyomugasho N, Atwine D, Mugabe F,
Nansumba M, et al. Prospective cohort study of the feasibility and
yield of household child tuberculosis contact screening in Uganda. Int
J Tuberc Lung Dis. 2017;21(8):862–8.
Chandrasekaran P, Mave V, Thiruvengadam K, Gupte N,
Yogendra Shivakumar SVB, 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;13(8):
e0199360.
Machado A, Finkmoore B, Emodi K, Takenami I, Barbosa T,
Tavares M, et al. Risk factors for failure to complete a course of latent
tuberculosis infection treatment in Salvador, Brazil. Int J Tuberc Lung
Dis. 2009;13(6):719–25.
MacPherson P, Lebina L, Motsomi K, Bosch Z, Milovanovic M,
Ratsela A, et al. Prevalence and risk factors for latent tuberculosis
infection among household contacts of index cases in two
South African provinces: analysis of baseline data from a clusterrandomised trial. PLoS One. 2020;15(3):e0230376.
Odera S, Mureithi M, Aballa A, Onyango N, Anzala O, Oyugi J. Latent
tuberculosis among household contacts of pulmonary tuberculosis
cases in Nairobi, Kenya. Pan Afr Med J. 2020;37:87.
Praveen V. Prevalence of LTBI among household contacts of sputum
positive TB patients receiving DOTS chemotherapy. Indian J Tuberc.
2020;67(4):459–65.
Ronge L, Sloot R, Du Preez K, Kay AW, Kirchner HL, Grewal HMS,
et al. The magnitude of interferon gamma release assay responses in
children with household tuberculosis contact is associated with tuberculosis exposure and disease status. Pediatr Infect Dis J. 2021;40(8):
763–70.
Rutherford ME, Hill PC, Maharani W, Apriani L, Sampurno H, van
Crevel R, et al. Risk factors for Mycobacterium tuberculosis infection
in Indonesian children living with a sputum smear-positive case. Int J
Tuberc Lung Dis. 2012;16(12):1594–9.
Shah M, Kasambira TS, Adrian PV, Madhi SA, Martinson NA,
Dorman SE. Longitudinal analysis of QuantiFERON-TB Gold InTube in children with adult household tuberculosis contact in
South Africa: a prospective cohort study. PLoS One. 2011;6(10):
e26787.
Sharma SK, Vashishtha R, Chauhan LS, Sreenivas V, Seth D.
Comparison of TST and IGRA in diagnosis of latent tuberculosis
infection in a high TB-burden setting. PLoS One. 2017;12(1):
e0169539.
Stein CM, Zalwango S, Malone LL, Thiel B, Mupere E, Nsereko M,
et al. Resistance and susceptibility to mycobacterium tuberculosis
infection and disease in tuberculosis households in Kampala, Uganda.
Am J Epidemiol. 2018;187(7):1477–89.
Zhang HC, Ruan QL, Wu J, Zhang S, Yu SL, Wang S, et al. Serial TSPOT.TB in household contacts of tuberculosis patients: a 6-year
observational study in China. Int J Tuberc Lung Dis. 2019;23(9):
989–95.
Akhtar S, Rathi SK. Multilevel modeling of household contextual
determinants of tuberculin skin test positivity among contacts of
infectious tuberculosis patients, Umerkot, Pakistan. Am J Trop Med
Hyg. 2009;80(3):351–8.
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.
40.
41.
42.
43.
44.
45.
46.
47.
48.
Hu Y, Zhao Q, Wu L, Wang W, Yuan Z, Xu B. Prevalence of latent
tuberculosis infection and its risk factors in schoolchildren and adolescents in Shanghai, China. Eur J Public Health. 2013;23(6):1064–9.
Araújo NCN, Cruz CMS, Arriaga MB, Cubillos-Angulo JM,
Rocha MS, Silveira-Mattos PS, et al. Determinants of losses in the
latent tuberculosis cascade of care in Brazil: a retrospective cohort
study. Int J Infect Dis. 2020;93:277–83.
Marais BJ, Van Zyl S, Schaaf HS, Van Aardt M, Gie RP, Beyers N.
Adherence to isoniazid preventive chemotherapy: a prospective community based study. Arch Dis Child. 2006;91(9):762–5.
Nakaoka H, Lawson L, Squire SB, Coulter B, Ravn P, Brock I, et al.
Risk for tuberculosis among children. Emerg Infect Dis. 2006;12(9):
1383–8.
Oxlade O, Benedetti A, Adjobimey M, Alsdurf H, Anagonou S,
Cook VJ, et al. Effectiveness and cost-effectiveness of a health systems
intervention for latent tuberculosis infection management (ACT4): a
cluster-randomised trial. Lancet Public Health. 2021;6(5):e272–82.
Sun L, Qi X, Guo Y, Qi H, Li J, Wu X, et al. Tuberculosis infection
screening in children with close contact: a hospital-based study. BMC
Infect Dis. 2021;21(1):815.
Triasih R, Padmawati RS, Duke T, Robertson C, Sawyer SM,
Graham SM. A mixed-methods evaluation of adherence to preventive
treatment among child tuberculosis contacts in Indonesia. Int J
Tuberc Lung Dis. 2016;20(8):1078–83.
Adjobimey M, Masserey E, Adjonou C, Gbénagnon G, Schwoebel V,
Anagonou S, et al. Implementation of isoniazid preventive therapy in
children aged under 5 years exposed to tuberculosis in Benin. Int J
Tuberc Lung Dis. 2016;20(8):1055–9.
Amisi JA, Carter EJ, Masini E, Szkwarko D. Closing the loop in child
TB contact management: completion of TB preventive therapy outcomes in western Kenya. BMJ Open. 2021;11(2):e040993.
Barbosa Silva AP, Hill P, Belo MTCT, Rabelo SG, Menzies D,
Trajman A. Non-completion of latent tuberculous infection treatment
among children in Rio de Janeiro state, Brazil. Int J Tuberc Lung Dis.
2016;20(4):479–86.
Burmen B, Mutai K, Malika T. Isoniazid preventative therapy uptake
for child household contacts of tuberculosis index cases, Kisumu
County, Kenya, 2014-2015. J Public Health Afr. 2019;10(1):827.
Garie KT, Yassin MA, Cuevas LE. Lack of adherence to isoniazid chemoprophylaxis in children in contact with adults with tuberculosis in
Southern Ethiopia. PLoS One. 2011;6(11):e26452.
Van Ginderdeuren E, Bassett J, Hanrahan CF, Mutunga L, Van Rie A.
Gaps in the tuberculosis preventive therapy care cascade in children
in contact with TB. Paediatr Int Child Health. 2021;41(4):237–46.
Krishnamoorthy Y, Ezhumalai K, Murali S, Rajaa S, Jose M,
Sathishkumar A, et al. Prevalence and risk factors associated with
latent tuberculosis infection among household contacts of smear positive pulmonary tuberculosis patients in South India. Trop Med Int
Health. 2021;26(12):1645–51.
Narasimhan P, MacIntyre CR, Mathai D, Wood J. High rates of latent
TB infection in contacts and the wider community in South India.
Trans R Soc Trop Med Hyg. 2017;111(2):55–61.
Paradkar M, Padmapriyadarsini C, Jain D, Shivakumar SVBY,
Thiruvengadam K, Gupte AN, et al. Tuberculosis preventive treatment
should be considered for all household contacts of pulmonary tuberculosis patients in India. PLoS One. 2020;15(7):e0236743.
Okwara FN, Oyore JP, Were FN, Gwer S. Correlates of isoniazid preventive therapy failure in child household contacts with infectious
tuberculosis in high burden settings in Nairobi, Kenya – a cohort
study. BMC Infect Dis. 2017;17(1):623.
Paul NI, Gabriel-Job N. Adherence to isoniazid preventive therapy
(IPT) among children in close contact with adult pulmonary tuberculosis (PTB) patients. J Adv Med Med Res. 2019;30(11):1–8.
Rutherford ME, Ruslami R, Maharani W, Yulita I, Lovell S, Van
Crevel R, et al. Adherence to isoniazid preventive therapy in
Indonesian children: a quantitative and qualitative investigation. BMC
Res Notes. 2012;5(1):7.
863
TROPICAL MEDICINE & INTERNATIONAL HEALTH
49.
50.
51.
52.
53.
54.
55.
56.
57.
58.
59.
60.
61.
62.
63.
Sulis G, Combary A, Getahun H, Gnanou S, Giorgetti PF,
Konseimbo A, et al. Implementation of tuberculosis prevention for
exposed children, Burkina Faso. Bull World Health Organ. 2018;
96(6):386–92.
Rekha B, Jagarajamma K, Chandrasekaran V, Wares F,
Sivanandham R, Swaminathan S. Improving screening and chemoprophylaxis among child contacts in India’s RNTCP: a pilot study. Int J
Tuberc Lung Dis. 2013;17(2):163–8.
Shivaramakrishna HR, Frederick A, Shazia A, Murali L,
Satyanarayana S, Nair SA, et al. Isoniazid preventive treatment in children in two districts of South India: does practice follow policy? Int J
Tuberc Lung Dis. 2014;18(8):919–24.
Seid G, Tsedalu T, Ayele M. Adherence to isoniazid preventive therapy among under-five children in contact with adult bacteriologically
confirmed pulmonary tuberculosis patients: a mixed-method study.
Int J Microbiol. 2020;2020:8834806.
Tadesse Y, Gebre N, Daba S, Gashu Z, Habte D, Hiruy N, et al.
Uptake of isoniazid preventive therapy among under-five children: TB
contact investigation as an entry point. PLoS One. 2016;11(5):
e0155525.
Birungi FM, Graham SM, Uwimana J, Musabimana A, Van Wyk B.
Adherence to isoniazid preventive therapy among child contacts in
Rwanda: a mixed-methods study. PLoS One. 2019;14(2):e0211934.
Black F, Amien F, Shea J. An assessment of the isoniazid preventive
therapy programme for children in a busy primary healthcare clinic in
Nelson Mandela Bay Health District, Eastern Cape Province,
South Africa. S Afr Med J. 2018;108(3):217–23.
Chauhan S, Gahalaut P, Rathi AK. Tuberculin skin test, chest radiography and contact screening in children ≤5 y: relevance in Revised
National Tuberculosis Control Programme (RNTCP). Indian J
Pediatr. 2013;80(4):276–80.
Datiko DG, Yassin MA, Theobald SJ, Cuevas LE. A community-based
isoniazid preventive therapy for the prevention of childhood tuberculosis in Ethiopia. Int J Tuberc Lung Dis. 2017;21(9):1002–7.
Egere U, Sillah A, Togun T, Kandeh S, Cole F, Jallow A, et al. Isoniazid preventive treatment among child contacts of adults with smearpositive tuberculosis in The Gambia. Public Health Action. 2016;6(4):
226–31.
Wysocki AD, Villa TCS, Arakawa T, Brunello MEF, Vendramini SHF,
Monroe AA, et al. Latent tuberculosis infection diagnostic and treatment
cascade among contacts in primary health care in a city of Sao Paulo
state, Brazil: cross-sectional study. PLoS One. 2016;11(6):e0155348.
Fentahun N, Wasihun Y, Mamo A, Gebretsadik LA. Contact screening and isoniazid preventive therapy initiation for under-five children
among pulmonary tuberculosis-positive patients in Bahir Dar Special
Zone, Northwest Ethiopia: a cross-sectional study. Tuberc Res Treat.
2020;2020:6734675.
Faksri K, Reechaipichitkul W, Pimrin W, Bourpoern J, Prompinij S.
Transmission and risk factors for latent tuberculosis infections among
index case-matched household contacts. Southeast Asian J Trop Med
Public Health. 2015;46(3):486–95.
Sayedi SM, Seddiq MK, Rashidi MK, Qader G, Ikram N, Melese M,
et al. Active household contact screening for tuberculosis and provision of isoniazid preventive therapy to under-five children in
Afghanistan. PLoS One. 2020;15(10):e0240031.
Schwoebel V, Koura KG, Adjobimey M, Gnanou S, Wandji AG,
Gody JC, et al. Tuberculosis contact investigation and short-course
64.
65.
66.
67.
68.
69.
70.
71.
72.
73.
preventive therapy among young children in Africa. Int J Tuberc Lung
Dis. 2020;24(4):452–60.
Sharma N, Basu S, Khanna A, Sharma P, Chopra KK, Chandra S.
Adherence to isoniazid preventive therapy among children living with
tuberculosis patients in Delhi, India: an exploratory prospective study.
Indian J Tuberc. 2022;69(1):100–3.
Van Soelen N, Du Preez K, Van Wyk SS, Mandalakas AM,
Enarson DA, Reid AJ, et al. Does an isoniazid prophylaxis register
improve tuberculosis contact management in South African children?
PLoS One. 2013;8(12):e80803.
Gomes VF, Wejse C, Oliveira I, Andersen A, Vieira FJ, Carlos LJ,
et al. Adherence to isoniazid preventive therapy in children exposed
to tuberculosis: a prospective study from Guinea-Bissau. Int J Tuberc
Lung Dis. 2011;15(12):1637–43.
Hector J, Anderson ST, Banda G, Kamdolozi M, Jefferys LF, Shani D,
et al. TST positivity in household contacts of tuberculosis patients: a
case-contact study in Malawi. BMC Infect Dis. 2017;17:259.
Mensah G, Sowah S, Yeboah N, Addo K, Jackson-Sillah D. Utility of
QuantiFERON tuberculosis gold-in-tube test for detecting latent tuberculosis infection among close household contacts of confirmed tuberculosis patients in Accra, Ghana. Int J Mycobacteriol. 2017;6(1):27–33.
Nguyen TH, Odermatt P, Slesak G, Barennes H. Risk of latent tuberculosis infection in children living in households with tuberculosis
patients: a cross sectional survey in remote northern Lao People’s
Democratic Republic. BMC Infect Dis. 2009;9:96.
Mzembe T, Lessells R, Karat AS, Randera-Rees S, Edwards A, Khan P,
et al. Prevalence and risk factors for Mycobacterium tuberculosis infection among adolescents in rural South Africa. Open Forum Infect Dis.
2020;8(1):ofaa520.
Barss L, Moayedi-Nia S, Campbell JR, Oxlade O, Menzies D. Interventions to reduce losses in the cascade of care for latent tuberculosis: a
systematic review and meta-analysis. Int J Tuberc Lung Dis. 2020;
24(1):100–9.
Imrey PB. Limitations of meta-analyses of studies with high heterogeneity. JAMA Netw Open. 2020;3(1):e1919325.
Burugina Nagaraja S, Thekkur P, Satyanarayana S, Tharyan P,
Sagili KD, Tonsing J, et al. Active case finding for tuberculosis in
India: a syntheses of activities and outcomes reported by the National
Tuberculosis Elimination Programme. Trop Med Infect Dis. 2021;
6(4):206.
SU PP O RT I NG IN FO RM A T I ON
Additional supporting information can be found online in
the Supporting Information section at the end of this article.
How to cite this article: Sagili KD, Muniyandi M,
Shringarpure K, Singh K, Kirubakaran R, Rao R, et al.
Strategies to detect and manage latent tuberculosis
infection among household contacts of pulmonary TB
patients in high TB burden countries - a systematic
review and meta-analysis. Trop Med Int Health. 2022;
27(10):842–63. https://doi.org/10.1111/tmi.13808