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\begin{document}

\title{Effectiveness and challenges associated with the symptoms-based
screening tool for active tuberculosis case finding in outpatient
departments in healthcare facilities in Ghana}



\author[1]{Diana Akila}%
\author[1]{Margaret Kweku}%
\author[1]{Enoch Aninagyei}%
\author[1]{Kwabena Duedu}%
\affil[1]{University of Health and Allied Sciences}%


\vspace{-1em}



  
  \date{June 14, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
Background: Successful active surveillance for infectious disease leads
to increased case detection and better management outcomes. Because of
that, the National Tuberculosis Programme (NTP), Ghana introduced
Symptoms-Based Screening (SBS) Tool for TB case finding. Despite these
efforts, Ghana has not achieved the 10\% target of TB screening in all
out-patient departments attendees as recommended by the NTP. Therefore,
this study determined the challenges and limitations of the SBS Tool
used for active tuberculosis case finding in Ghana. Methods: This study
targeted presumptive TB patients resident in Ho Municipality, Ghana.
Presumptive TB patients, recruited from Ho Teaching and Ho Municipal
Hospitals, were screened with the SBS tool and presumed TB patients
tested for M. tuberculosis using microscopy and positive samples
confirmed by geneXpert technique. Also health personnel were interviewed
to assess the user-friendliness, challenges and limitations associated
with the SBS tool. Chi square association of categorical data was done
by STATA version 14.1. P-values \textless{}0.05 was considered
statistically significant. Results: From both hospitals, 636 presumptive
patients and 24 health workers participated in this study. Of the total
patients screened, 1.73\% had active tuberculosis. Coughing for
\textgreater{} 2 weeks (x2=24.8; p\textless{}0.05); chest pains
(x2=28.3; p\textless{}0.01) and night sweat (x2=34.8; p\textless{}0.05)
associated significantly with M. tuberculosis infection status. The main
challenge associated with the SBS tool was its unfriendliness for
administration while lack of enough indicators to identify other
vulnerable individuals to TB (diabetics, cigarette smokers, alcoholics,
immunocompromised and malnourished individuals) limited the sensitivity
of the tool. Conclusion: The SBS tool was found not to be sensitive
enough to identify infected cases. Inclusion of signs and symptoms of
diabetes, immuno-suppression and malnutrition in the current tool and
subsequent training of all relevant health personnel on the use of the
tool could contribute to increase the sensitivity of the tool.%
\end{abstract}%



\sloppy


\section*{Background}

{\label{background}}

There are two outcomes of TB infection; latent and active. Many people
exposed to the TB bacilli are immuno-competent and remain
asymptomatic\textsuperscript{1,2}. Several factors make people more
susceptible to TB infections; people living with HIV/AIDS, chronic lung
disease, smoking cigarettes, excessive drinking of alcohol and
diabetics\textsuperscript{3,4}. Tuberculosis is also linked to
overcrowding and malnutrition and among group of people with limited
movement like prisoners \textsuperscript{5}. Students in hostels are
also at a higher risk of infection. Again, resource poor community
dwellers and children who are in close contact with infected patients
are also at risk\textsuperscript{6,7}.

In latent TB, the bacteria remain in the body in an inactive state.
There are no symptoms associated with this and the affected individuals
are not contagious. This can however transform to an active form of the
disease. Active TB is associated with various clinical symptoms and the
affected individuals can transmit the organisms to
others\textsuperscript{8}. About one-third of the world's population is
believed to have latent TB. In addition, there is a 10 percent chance of
latent TB becoming active, but this risk is much higher in people who
have compromised immune systems, i.e., people living with HIV or
malnutrition, or people who smoke\textsuperscript{8}.

TB remains a major public health problem in Ghana despite the progress
made in combating TB over the past years. In 2014, the estimated
national prevalence of TB in Ghana was 282 (95\% confidence interval:
111 - 530) per 100,000 population {[}9{]}. An estimated 14,668 new cases
of TB were reported in Ghana in 2014 and Ghana's case detection was 33\%
which was below the African regional average rate of 47\% and the WHO
target of 70\% \textsuperscript{9}. The quest to improve on case
detection using a Symptoms-Based Screening Tool (Chest Infection) for TB
active case finding in health facilities is key in Ghana Tuberculosis
control programme.

There have been some efforts to scale-up the systematic TB screening to
all districts in the Volta Region yet they still do not achieve the 10\%
target of TB screening in all OPD attendees as recommended in the
National Tuberculosis Programme (NTP). The overview of 2017 annual
performance review of tuberculosis in the Volta Region revealed that out
of General OPD attendance, 8.2\% were screened for TB out of which 1.2\%
were picked as presumptive TB cases. The Ghana National TB control
programme has taken several steps including the introduction of
Symptoms-Based Screening Tool (Chest Infection) for TB active case
finding in health facilities to increase case detection rates with the
aim of addressing the low case detection in the country.

Despite the progress made in combating TB over the past years, there is
still gap in TB case detection in the country and the region. This study
was designed to determine the effectiveness of the Symptoms-Based
Screening Tool (Chest Infection) for TB active case finding in two
health facilities in the Southern part of Volta Region, Ghana.
Specifically, this study determined the prevalence of TB among patients
presenting at the OPDs of these two hospitals following initial
screening with the Symptoms Based Screening Tool and also determined the
challenges faced by practitioners and factors limiting the sensitivity
of the screening tool.

\section*{Materials and methods}

{\label{materials-and-methods}}

\subsection*{Study Design}

{\label{study-design}}

This study was a health facility-based cross-sectional study that took
place from December, 2018 to January, 2019 in Ho Teaching and Ho
Municipal hospitals in the Volta Region, Ghana. Clinical nurses
administered the Symptoms-Based Screening Tool (SBS) for TB active case
finding at each consulting room in the hospitals. Two sputum samples
were collected from each presumptive patient for the determination of
tuberculosis bacilli in the Regional Hospital Laboratory, Ho.

\subsection*{Study site description}

{\label{study-site-description}}

The study was carried out in the Southern part of the Volta Region of
Ghana. The then Volta region was divided into 25 administrative
districts (now Oti region has been carved out of the then Volta region).
Ho is the capital of the Ho Municipality and also the Volta Regional
capital. Ho is a cosmopolitan city with brisk economic, social
activities as well as several tourist attraction sites. Again the
Municipality has several second cycle instructions, nursing training
colleges, colleges of education, technical university and health and
allied sciences university as well as several private universities. Also
there is a big market and other small markets in the Municipality. This
attract a lot of people into the Municipality and overcrowding is a
frequent occurrence. The two biggest hospitals in the Municipality were
Ho Teaching Hospital and Ho Municipal Hospital.

\subsection*{Training of data collection
team}

{\label{training-of-data-collection-team}}

The data collectors were trained nurses at the health facilities where
the study was done. They were trained for 2 days. The primary language
in the region is predominantly Ewe, hence role plays were done in Ewe
with minimal Twi (the most popular local language in Ghana) and English
(the official Ghanaian language). Ten (10) nurses were trained at each
facility for the data collection. Pre-testing of the survey tools was
done during the training period in the Ho Municipal hospital. This
afforded the team the opportunity to have practical experience with the
administration of the study tools.

\subsection*{Inclusion and exclusion
criteria}

{\label{inclusion-and-exclusion-criteria}}

Individuals aged 15 years and above who were residents of communities
that were selected for the study were eligible for inclusion. This age
range was selected because per NTP protocols, persons 15 years and over
are classified as adults and they can produce good sputum for
microbiological analysis. Additional inclusion criterion was cough for
two weeks or more. Written consent was obtained from all the study
participants. Persons excluded from the study were seriously ill
patients who could not provide informed consent as well as those that
could not produce sputum. All other presumptive tuberculosis patients
that did not fall within the study criteria were managed routinely by
existing tuberculosis management protocols in Ghana.

\subsection*{Sample size estimation}

{\label{sample-size-estimation}}

The sample size for this study was calculated using the formulae below:

N=\(\frac{\mathbf{Z}^{\mathbf{2}}\mathbf{P}\ (\mathbf{1}-\mathbf{P})}{e^{2}}\)

Where: N = calculated sample size, Z = Z score (reliability
co-efficient) of 1.96 at 95\% confidence interval, P = Prevalence of
0.282 which was the prevalence of TB per 100,000 population in the Volta
region for the year 2017 (Volta Regional Health Directorate, 2017) and e
= margin of error (0.05).

Using the above formula, the sample size was calculated to be 311.
Adjusting for 5\% non-response rate, the minimum sample size of 327 was
used for this study.

\subsection*{Sampling of participants}

{\label{sampling-of-participants}}

Patients who met the inclusion criteria were recruited into the study at
both the OPD and in the consulting rooms for each health facility. All
patients who visited the two hospitals during the study period and
consented to participate in the study were sampled. Those who consented
to participate were screened at a designated place at the OPD to ensure
privacy and confidentiality.

\subsection*{Administration of SBS
tool}

{\label{administration-of-sbs-tool}}

A Symptom-based screening (SBS) tool (adapted from an existing National
Tuberculosis Control Programme screening tool) was administered to
presumptive TB patients who satisfied the inclusion criteria. The SBS
tool was administered to individuals who complained of coughing for two
weeks or more. Other variables were collected: age, sex, cough of any
duration, chest pain, weight lost, night sweat, fever. Anyone who met
the aforementioned criteria was classified as patients with presumptive
TB and sputum was collected from them for examination for \emph{M.
tuberculosis} . Also, health workers who manage TB patients were also
interviewed on the challenges associated with the SBS tool.

\subsection*{Assessment of challenges and limitations of the SBS
tool}

{\label{assessment-of-challenges-and-limitations-of-the-sbs-tool}}

Twenty-four health personnel of different cadres, randomly selected from
each of the two health facilities, were interviewed to assess the
user-friendliness, efficiency, challenges and limitations associated
with the SBS tool. A semi-structured questionnaire was used to elicit
responses.

\subsection*{Sputum collection for TB
diagnosis}

{\label{sputum-collection-for-tb-diagnosis}}

As recommended by National Tuberculosis Control Programme, two sputum
samples were collected from each presumptive \emph{M.
tuberculosis}individuals; spot sample and second sample after one hour.
Presumptive\emph{M. tuberculosis} individuals were instructed on how to
induced sputum production. They were made to cough three times, after
taking a deep breath to produce sputum. Sputum collected were kept in
tight containers and transported to the laboratory within 24 hours for
microbiological examination.

\subsection*{\texorpdfstring{Microscopic detection of \emph{M.
tuberculosis} in sputum
samples}{Microscopic detection of M. tuberculosis in sputum samples}}

{\label{microscopic-detection-of-m.-tuberculosis-in-sputum-samples}}

Sputum examination was done in the Ho Teaching Hospital Laboratory by
two experienced Biomedical Laboratory Scientists. Standard size sputum
smears were prepared and labelled on a slide before heat fixing. Ziehl
Neelsen staining technique was used to examine the smear for presence of
acid-fast bacilli. Briefly, carbol fuchsin was flooded on the dried
smears, heated briefly till steam just appeared and left to stand for
not less than 5 minutes. The stain was tipped off and decolorized with
dilute sulphuric acid (20\% v/v strength) for exactly 5 minutes. The
decolorizer was tipped off and the smears counterstained with 0.3\%
(w/v) Methylene blue for 1 minute. Smears were air and examined using
x100 objective of the light microscope for presence of acid-fast
bacilli. A portion of the eleven microscopy samples were analyzed using
the GeneXpert machine for confirmation of the presence of tuberculosis.

\subsection*{Confirmation of M. tuberculosis by using geneXpert PCR
technique}

{\label{confirmation-of-m.-tuberculosis-by-using-genexpert-pcr-technique}}

MTB/RIF geneXpert analyzer operate on the principle of real-time
polymerase chain reaction. Detection of \emph{M. tuberculosis} was done
according to the manufacturer's recommendation without any modification.
Briefly, sample processing control (SPC) was added to sputum samples in
a ratio of 3:1. The specimen together with the SPC was vortexed
vigorously for a minute, incubated at 25 \selectlanguage{ngerman}°C for 10 minutes, vortexed
again for a minute and incubated again for 5 minutes. With the help of a
sterile Pasteur pipette, 2 mL of the homogenized sample was transferred
into Xpert MTB/RIF cartridge and run on the geneXpert analyzer using
recommended programme.

\subsection*{Procedure for HIV
screening}

{\label{procedure-for-hiv-screening}}

All eligible participants who agree to be tested for HIV were referred
to the HIV Counselling and Testing Unit of the hospital for counselling
before being tested for HIV using rapid diagnostic test (RDT) (First
response HIV1\&2 kits, Premier Medical Corporation Ltd., Kachigam,
India).

\subsection*{Data analysis}

{\label{data-analysis}}

Study data were recorded on Microsoft excel spreadsheet (2016) and were
subsequently verified for inconsistencies, completeness and accuracy.
Data were then exported to STATA version 14.1 for analysis. Simple
frequencies and percentages were used for categorical variables while
Chi-square was used to determine the association between the dependent
(prevalence of pulmonary TB) and independent variables p-value
\textless{}0.05 was considered statistically significant.

\section*{Results}

{\label{results}}

\subsection*{\texorpdfstring{Demographic characteristics of the
presumptive people with \emph{M.
tuberculosis}}{Demographic characteristics of the presumptive people with M. tuberculosis}}

{\label{demographic-characteristics-of-the-presumptive-people-with-m.-tuberculosis}}

A total of 636 presumptive people with \emph{M. tuberculosis} were
sampled from Ho Teaching Hospital (HTH) and Ho Municipal Hospital (HMH).
Majority of presumptive cases in each demographic indicator was females
and patients above 60 years. Christians were in the majority so as
married individuals. Frequencies of these and other parameters are
presented in Table 1. Table 2 represents the demographic profile of the
health workers who consented to answer the study questionnaires. In all
24 health care workers provided responses to the study questionnaire.
Most of the workers in both facilities were aged 23-33 years. Whereas
most of the staff were married in HMH, single staff dominated in VHR.
Almost all the staff have had tertiary education with majority of them
being Ewes. The dominant cadre of staff that were interviewed were
nurses.

\subsection*{\texorpdfstring{Prevalence of \emph{M. tuberculosis}and
Sensitivity of the TB symptoms-based
tool}{Prevalence of M. tuberculosisand Sensitivity of the TB symptoms-based tool}}

{\label{prevalence-of-m.-tuberculosis-and-sensitivity-of-the-tb-symptoms-based-tool}}

In all, 4 and 7 positive cases were recorded in HTH and HMH respectively
representing 1.24\% and 2.17\% HTH and HMH respectively. The overall
prevalence of tuberculosis found in the two health facilities was
1.73\%. The overall sensitivity of the SBS tool in detecting \emph{M.
tuberculosis} was 1.7\% while the hospital related sensitivities were
1.2 \% and 2.2\% in HTH and HMH respectively.

\subsection*{Preferred department of administration of TB symptoms-based
tool}

{\label{preferred-department-of-administration-of-tb-symptoms-based-tool}}

The preferred location of screening for \emph{M. tuberculosis} using SBS
was the OPD Front Desk. However, the difference in the cases recruited
from OPD and consulting rooms was not significant (\emph{x}
\textsuperscript{2}=1.007, p=0.316). Similar observation was made for
each of the 2 health facilities (Figure 1).

\subsection*{\texorpdfstring{Association between \emph{M. tuberculosis}
infection status and
symptoms}{Association between M. tuberculosis infection status and symptoms}}

{\label{association-between-m.-tuberculosis-infection-status-and-symptoms}}

There was a statistically significant association between TB infection
status and cough more than 2 weeks (x2=24.8; p\textless{}0.001); chest
pain and \emph{M. tuberculosis} status (\emph{x}
\textsuperscript{2}=28.3; p\textless{}0.001) and night sweat and
\emph{M. tuberculosis} infection status (\emph{x}
\textsuperscript{2}=34.8; p\textless{}0.001 (Table 3).

\textbf{Implementation challenges associated with the SBS tool}

Of the total staffs, 15 (62.5\%) did not have any challenges
administering the tool while 9 of them had some challenges with the
tool. The common challenges identified were inadequate health staff,
lack of patient's cooperation to provide responses, font sizes being too
small, too many questions and filling hard copies of several questions
is cumbersome and boring.

\subsection*{Limitations of the SBS
tool}

{\label{limitations-of-the-sbs-tool}}

Inability of the tool to capture other risk groups such as diabetics,
cigarette smokers, alcoholics, immunocompromised and malnourished
individuals was reported by the health care providers as the main
limitation of the tool.

\section*{Discussion}

{\label{discussion}}

In \emph{M. tuberculosis} infections, only one in 10 exposed humans will
be susceptible to the infection, hence develop active tuberculosis.
Again, in susceptible individuals, half (50\%) will develop TB within
1--2 years of exposure and the remaining 50\%, active infection can be
developed at any other time \textsuperscript{10}. Inactive tuberculosis
infections occurs when humans are infected with \emph{M.
tuberculosis}bacilli without any overt clinical symptoms, radiological
abnormality or microbiological evidence \textsuperscript{10}. The
estimated prevalence rate of inactive TB in low- or middle-income
countries is as high as 51.5\% while in high-income countries the
estimated prevalence rate is 28.1\% \textsuperscript{11}. It has also
been reported that most new clinical TB cases originate from progression
of inactive TB\textsuperscript{12,13}, therefore active case search to
detect both inactive and sub-clinical TB is a useful strategy for
reducing TB prevalence.

This current study screened 636 people with TB out of which 1.73\% (1730
per 100 000 population) infected with \emph{M. tuberculosis} . A similar
study in Ethiopia reported higher prevalence (4.4\%) of identified TB
cases \textsuperscript{14}. Similarly, in Tanzania, 4.1\% of TB were
detected in people with TB screened with the Symptoms-Based Screening
Tool \textsuperscript{15}. The differences in the prevalence reported in
these studies could be as a result of the differences in study
population in each study. In the study reported by
Menberu\textsuperscript{14} and Shayo et al. \textsuperscript{15} the
screening tool was administered to HIV-infected persons with TB. So it
was not surprising they had relatively high prevalence of TB among the
participants. HIV infections lead to host immunosuppression and thereby
rending the host susceptible to \emph{M. tuberculosis} infections.
Again, HIV is the most important risk factor for
tuberculosis\textsuperscript{16}. In contrast to this study, all the
presumptive people with TB were negative for HIV based on the rapid
testing kit. However, findings in this study underscore the fact that
the infected cases could have been missed but for the implementations of
the SBS tool. A lower prevalence was reported in our study could be due
to the fact that the study was carried out in an urban population.

Considering the socio-economic nature of Ghana, communal living and
communal activities are very common. If the infected individuals are not
treated promptly, they will remain continuous high risk source of
infection to their contacts. As soon as people with TB begin standard TB
medication, their infectiousness reduces. Previous studies found that
after anti-TB chemotherapy, \emph{M. tuberculosis} bacilli burden is
reduced to approximately 4\% of the initial bacilli load within 48 hours
start of treatment and to 1\% within 2--3 weeks of anti-TB chemotherapy
in drug-sensitive TB patients \textsuperscript{17,18}.

Detection of only 1.73\% of the presumptive TB cases reveals the lack of
sensitivity of the screening tool even though geneXpert is very
sensitive and specific for MTb. However, analysis of data obtained in
this study concluded that there were strong association between cough
more than 2 weeks, chest pain and night sweat, and TB infections status.
It is imperative that clinicians survey for these symptoms, irrespective
of the clinical complains and get them tested for tuberculosis using
geneXpert.

Few operational limitations to the use of SBS tool were identified in
this study. The health workers indicated that the screening tool is
laborious to administer. Likewise, Reid and Shah\textsuperscript{19}also
reported that similar screening tool available to them was not
user-friendly. Another major limitation identified by the health
providers was the inability of the tool to capture other risk groups
such as individuals with chronic lung disease, cigarette smokers,
chronic alcoholics, diabetics, pregnant women in their
2\textsuperscript{nd} trimester, prisoners, individuals with prolong
stay in overcrowded environments (market women, students in hostels etc)
as well as malnourished individuals. Also the tool did not allow for
screening of people who live in resource poor communities like slums.
These individuals have been found to be at higher risk of tuberculosis
disease \textsuperscript{3-7,20}.

\section*{Conclusion}

{\label{conclusion}}

This study was able to identify some patients infected with TB in the
study area. This underscores the fact that active Tb case search is very
important exercise in identifying cases that would have hitherto been
lost. Such individual pose threat to public health and disrupt national
program efforts. Even though the current SBS tool has some challenges,
it could be simplified to make it user-friendly and also redesigned to
capture other high-risk groups.

\section*{Declarations}

{\label{declarations}}

Ethics approval and consent to participate

Ethical approval was sought from the Research Ethics Committee (REC) of
the University of Health and Allied Sciences, Ho, Ghana. Each
participant signed an informed consent form prior to participation. The
informed consent form was approved by the ethics committee prior to use.

Consent for publication

Not applicable

Availability of data and materials

The data for this study is available at the respective hospitals (HTH
and HMH) and not accessible online. The data may be made available upon
written request to through the authors, provided the request complies
with the Ethical Review Committee guidelines.

Competing interests

The authors declare that they have no competing interests.

Funding

No direct funding was obtained for this study. The laboratory analysis
was conducted in the respective health facilities as part of routine
tests.

Authors' contributions

MK and KD conceived and designed the study, DAA contributed to
evaluation of the study design and data collection. EA drafted the
manuscript. All authors contributed to data analysis and interpretation
as well as read and approved the manuscript.

Acknowledgements

We acknowledge all the nurses, public health personnel and other health
care staff who assisted in the data collection. We also acknowledge the
laboratory managers of the health facilities for their support in the
analysis of the data.



\section*{References}

{\label{references}}

\begin{enumerate}
\tightlist
\item
  Centre for Disease Control. TB Treatment. CDC; 2014
\item
  Suzman R, Beard J. Global Health and Aging. NIH Publ 2011;
  1(4):273--27
\item
  Harries AD, Lawn SD, Getahun H, Zachariah R, Havlir DV. HIV and
  tuberculosis - Science and implementation to turn the tide and reduce
  deaths. Journal of the International AIDS Society 2012; 15(2):17396.
\item
  Van Zyl Smit RN, Pai M, Yew WW, Leung CC, Zumla A, Bateman ED, et al.
  Global lung health: The colliding epidemics of tuberculosis, tobacco
  smoking, HIV and COPD. Eur Respir J. 2010; 35(1):27--33.
\item
  Baussano I, Williams BG, Nunn P, Beggiato M, Fedeli U, Scano F.
  Tuberculosis incidence in prisons: a systematic review. PLoS Med.
  2010; 21;7(12):e1000381.
\item
  Ogbudebe CL, Chukwu JN, Nwafor CC, Meka AO, Ekeke N, Madichie NO, et
  al. Reaching the underserved: active tuberculosis case finding in
  urban slums in southeastern Nigeria. Int J Mycobacteriology 2015;
  4(1):18--24.
\item
  Oppong JR, Mayer J, Oren E. The global health threat of African urban
  slums: the example of urban tuberculosis. African Geogr Rev 2015;
  34(2):182--195
\item
  World Health Organization \textbar{} Tuberculosis. (2018). WHO.
  Internet{]}. 2018 Sep {[}cited 2019 Aug 3{]} Retrieved from
  http://www.who.int/immunization/diseases/tuberculosis/en/
\item
  World Health Organization \textbar{} Systematic screening for active
  tuberculosis: principles and recommendations. (2015).
\item
  Frieden TR, Sterling TR, Munsiff SS, Watt CJ, Dye C. Tuberculosis.
  Lancet 2003; 362:887-99.
\item
  Dheda K, Barry CE 3rd, Maartens G. Tuberculosis. Lancet 2016;
  387:1211-26.
\item
  Alland D, Kalkut GE, Moss AR, McAdam RA, Hahn JA, Bosworth W, et al.
  Transmission of tuberculosis in New York City: an analysis by DNA
  fingerprinting and conventional epidemiologic methods. N Engl J Med
  1994; 330:1710-6.
\item
  Small PM, Hopewell PC, Singh SP, Paz A, Parsonnet J, Ruston DC, et al.
  The epidemiology of tuberculosis in San Francisco: a population-based
  study using conventional and molecular methods. N Engl J Med 1994;
  330:1703-9.
\item
  Menberu, M. A. (2016). Performance of the WHO 2011 TB Symptom
  Screening Algorithm for Pulmonary TB Diagnosis among HIV-Infected
  Patients in Gondar University Referral Hospital, Ethiopia.
  International Journal of Microbiology, 2016; 1--5.
  https://doi.org/10.1155/2016/9058109
\item
  Shayo GA, Minja LT, Egwaga S, Bakari M, Mugusi FM. Symptom-based
  screening tool in ruling out active tuberculosis among HIV-infected
  patients eligible for isoniazid preventive therapy in Tanzania.
  Tropical Medicine \&International Health 2014; 19(6), 726--733.
  https://doi.org/10.1111/tmi.12307
\item
  García-Basteiro AL, López-Varela E, Respeito D, González R, Naniche D,
  Manhiça I, et al. High tuberculosis burden among people living with
  HIV in southern Mozambique. Eur Respir J. 2015; 45(2):547--549.
\item
  Jindani A, Dore CJ, Mitchison DA. Bactericidal and sterilizing
  activities of antituberculosis drugs during the first 14 days. Am J
  Respir Crit Care Med 2003; 167:1348-54.
\item
  National Tuberculosis Controllers Association; Centers for Disease
  Control and Prevention (CDC). Guidelines for the investigation of
  contacts of persons with infectious tuberculosis: recommendations
  from the National Tuberculosis Controllers Association and CDC. MMWR
  Recomm Rep 2005; 54:1-47.
\item
  Reid MJ, Shah NS. Approaches to tuberculosis screening and diagnosis
  in people with HIV in resource-limited settings. Lancet Infect Dis.
  2009; (3):173-- 84.
\item
  Loto OM, Awowole I. Tuberculosis in pregnancy: a review. J Pregnancy
  2012: 379271. doi:10.1155/2012/379271
\end{enumerate}



\textbf{FIGURES}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

\textbf{Figure 1: Departmental and health facility specific for the
administration of the SBS tool for \emph{MTB} screening by Health
Workers} .

\textbf{A.} Overall preferred site for the administration of the tool
and \textbf{B.} Distribution of the preferences within the respective
health facilities studied.

Key: HTH = Ho Teaching Hospital; HMH = Ho Municipal Hospital; CR =
Consulting Room; OPD = Out Patient Department Front Desk;
SBS-sympton-based screening

\textbf{Hosted file}

\verb`Table 1.docx`  available at \url{https://authorea.com/users/340200/articles/467318-effectiveness-and-challenges-associated-with-the-symptoms-based-screening-tool-for-active-tuberculosis-case-finding-in-outpatient-departments-in-healthcare-facilities-in-ghana}

\textbf{Hosted file}

\verb`Table 2.docx`  available at \url{https://authorea.com/users/340200/articles/467318-effectiveness-and-challenges-associated-with-the-symptoms-based-screening-tool-for-active-tuberculosis-case-finding-in-outpatient-departments-in-healthcare-facilities-in-ghana}

\textbf{Hosted file}

\verb`Table 3.docx`  available at \url{https://authorea.com/users/340200/articles/467318-effectiveness-and-challenges-associated-with-the-symptoms-based-screening-tool-for-active-tuberculosis-case-finding-in-outpatient-departments-in-healthcare-facilities-in-ghana}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-1/Figure-1}

\end{center}
\end{figure}

\selectlanguage{english}
\FloatBarrier
\end{document}

