Tuberculosis Case Detection Research Articles

Analysis of care-seeking and diagnosis delay among pulmonary tuberculosis patients in Beijing, China.

Tuberculosis (TB) remains a significant public health challenge in China. Early detection and diagnosis of TB cases are crucial to interrupt disease transmission and prevent its progression. This study aims to describe the delay in seeking care and diagnosis among patients with pulmonary tuberculosis (PTB) and identify the influencing factors in two counties in Beijing. A retrospective analysis was carried out to investigate care-seeking and diagnosis delay in two counties in Beijing. Basic information of PTB patients from January 1 to December 31, 2021, was extracted from the Tuberculosis Information Management System of China (TBIMS), and all enrolled patients were interviewed via telephone using a standard questionnaire. Statistical description was performed using the median and interquartile range (IQR). Chi-square test and multivariate logistic regression model were used to analyze the influencing factors. 537 patients were enrolled. The median duration of care-seeking and diagnosis delay was 11 (IQR: 5-26) days and 8 (IQR: 0-18) days, with 41.71 and 35.20% of patients experiencing delays (>14 days). The study found that being asymptomatic (OR = 2.791, 95%CI: 1.710-4.555) before seeking medical care and not attending work during treatment (OR = 2.990, 95%CI: 1.419-6.298) were identified as risk factors for care-seeking delay. Patients who were tracked (OR = 2.632, 95%CI: 1.062-6.521) and diagnosed at tuberculosis control and prevention institutions (OR = 1.843, 95%CI: 1.061-3.202) had higher odds of diagnostic delays. 44.69% of patients presented a total delay (>28 days), with a median duration of 25 (IQR: 13-39) days. A multivariate logistic regression analysis showed that healthy examination (OR = 0.136, 95%CI: 0.043-0.425) was a protective factor for total delay. Public interventions are necessary to improve the efficiency of PTB patients detection and treatment in Beijing. Medical services should focus on the target population and improve access to medical care to further reduce delays for PTB patients.

Machine Learning for Prediction of Tuberculosis Detection: Case Study of Trained African Giant Pouched Rats.

Technological advancement has led to the growth and rapid increase of tuberculosis (TB) medical data generated from different health care areas, including diagnosis. Prioritizing better adoption and acceptance of innovative diagnostic technology to reduce the spread of TB significantly benefits developing countries. Trained TB-detection rats are used in Tanzania and Ethiopia for operational research to complement other TB diagnostic tools. This technology has increased new TB case detection owing to its speed, cost-effectiveness, and sensitivity. During the TB detection process, rats produce vast amounts of data, providing an opportunity to identify interesting patterns that influence TB detection performance. This study aimed to develop models that predict if the rat will hit (indicate the presence of TB within) the sample or not using machine learning (ML) techniques. The goal was to improve the diagnostic accuracy and performance of TB detection involving rats. APOPO (Anti-Persoonsmijnen Ontmijnende Product Ontwikkeling) Center in Morogoro provided data for this study from 2012 to 2019, and 366,441 observations were used to build predictive models using ML techniques, including decision tree, random forest, naïve Bayes, support vector machine, and k-nearest neighbor, by incorporating a variety of variables, such as the diagnostic results from partner health clinics using methods endorsed by the World Health Organization (WHO). The support vector machine technique yielded the highest accuracy of 83.39% for prediction compared to other ML techniques used. Furthermore, this study found that the inclusion of variables related to whether the sample contained TB or not increased the performance accuracy of the predictive model. The inclusion of variables related to the diagnostic results of TB samples may improve the detection performance of the trained rats. The study results may be of importance to TB-detection rat trainers and TB decision-makers as the results may prompt them to take action to maintain the usefulness of the technology and increase the TB detection performance of trained rats.

Increased tuberculosis case detection in Tanzanian children and adults using African giant pouched rats.

African giant pouched rats, trained by Anti-Persoonsmijnen Ontmijnende Product Ontwikkeling (APOPO), have demonstrated their ability to detect tuberculosis (TB) from sputum. We assessed rat-based case detection and compared the mycobacterium bacillary load (MTB-load) in children versus adults. From January-December 2022, samples were collected prospectively from 69 Directly Observed Therapy (DOT) facilities' presumed TB patients. Using an average of five rats, APOPO re-evaluated patients with bacteriologically negative (sputum-smear microscopy or Xpert MTB/RIF) results. Rat-positive samples were tested using concentrated smear light-emitting diode microscopy to confirm TB detection before treatment initiation. The rats' identification of pulmonary TB is based on smelling TB-specific volatile organic compounds (VOCs) in sputum. Using STATA, Chi-square for oddsratio and confidence interval was calculated and evaluated: (1) the yield of rat-based TB detection compared to that of the health facilities; (2) rat-based TB detection in children versus adults; and (3) rats' ability to detect TB across MTB-loads and between children and adults. From 35,766 patients, 5.3% (1900/35,766) were smear-positive and 94.7% (33,866/35,766) were smear or Xpert-negatives at DOTS facility. Of those with negative results, 2029 TB cases were detected using rats, contributing to 52% (2029/3929 of total TB identified), which otherwise would have been missed. Compared to DOT facilities, rats were six-fold more likely to detect TB among Acid Fast Bacilli (AFB) 1+/scanty [90% (1829/2029) versus 60% (1139/1900), odds ratio, OR = 6.11, 95% confidence interval, CI: 5.14-7.26]; twice more likely to identify TB cases among children [71% (91/129) versus 51% (1795/3542), OR = 2.3, 95% CI: 1.59-3.42]; and twice more likely to identify TB cases among children with AFB 1+/scanty than adults with the same MTB-load [5% (86/1703) versus 3% (28/1067), OR = 2.0, 95% CI: 1.28-3.03]. Rats contributed over half of the TB cases identified in program settings, and children, especially those with a lower MTB-load, were more likely to be diagnosed with TB by rats. The chemical signatures, VOCs, were only available for adults, and further research describing the characteristics of VOCs in children versus adults may pave the way to enhance TB diagnosis in children.

Chest X-ray evaluation using machine learning to support the early diagnosis of pulmonary TB.

<sec id="st1"><title>BACKGROUND</title>TB is a public health problem, and its diagnosis can be challenging. Among imaging methods, chest X-ray (CXR) is the leading choice for assessing pulmonary TB (PTB). Recent advancements in the field of artificial intelligence have stimulated studies evaluating the performance of machine learning (ML) for medical diagnosis. This study validated a new original Brazilian tool, the XmarTB, applied to CXR images to support the early diagnosis of PTB.</sec><sec id="st2"><title>METHODS</title>An ML model was trained on 3,800 normal images, 3,800 abnormal CXRs without PTB and 1,376 with PTB manifestations from the publicly available TBX11K database.</sec><sec id="st3"><title>RESULTS</title>The binary classification can distinguish between normal and abnormal CXR with a sensitivity of 99.4% and specificity of 99.4%. The XmarTB tool had a sensitivity of 98.1% and a specificity of 99.7% in detecting TB cases among CXRs with abnormal CXRs; sensitivity was 96.7% and specificity 98.7% in detecting TB cases among all samples.</sec><sec id="st4"><title>CONCLUSION</title>This diagnostic tool can accurately and automatically detect abnormal CXRs and satisfactorily differentiate PTB from other pulmonary diseases. This tool holds significant promise in aiding the proactive detection of TB cases, providing rapid and accurate support for early diagnosis.</sec>.

IJCM_256A: Trend in Tuberculosis Notification in Solapur district: Analysis from 2015 to 2022

Background: India contributes approximately 25% of the missing cases of tuberculosis (TB) globally. Even though ~50% of patients with TB are diagnosed and treated within India’s private sector, few are notified to the public healthcare system. India’s TB notification policy mandates that all patients with TB are notified through Nikshay (TB notification portal). We undertook this study to assess how mandatory notification has influenced the number of TB cases reported in the Nikshay portal from the private sector from Solapur district between 2015 and 2022. Objective: To evaluate the contribution of mandatory notification in enhancing TB notification in Solapur district between 2015 and 2022. Methodology: This study employed a quantitative observational approach, using record-based data extracted from the laboratory register and the Nikshay portal. The analysis period spanned from 2015 to 2022, allowing for an in- depth evaluation of TB notification trends before and after the implementation of the mandatory notification policy in 2018. Data was compiled and analysed using MS-Excel. Frequencies, means, and proportions used to effectively describe tuberculosis (TB) case notifications in both the private and public sectors were used. Results: Between 2015 and 2022, Solapur district experienced a variable but overall increasing trend in TB notification rates. In 2015, the TB notification rate was 58.15 per 100,000 population, which increased to 90.69 by 2022. The annual presumptive TB examination rates showed significant growth over the years. In 2015, the rate was 628 per 100,000 population, which escalated to 1965 by 2022. Conclusion: This rise is indicative of enhanced TB case detection, especially after the implementation of the mandatory notification policy and increase in presumptive TB examination rates is attributed to the rising use of advanced diagnostic methods such as CBNAAT and TrueNAT.

Effect of decentralising childhood tuberculosis diagnosis to primary health centre versus district hospital levels on disease detection in children from six high tuberculosis incidence countries: an operational research, pre-post intervention study

Childhood tuberculosis (TB) remains underdiagnosed largely because of limited awareness and poor access to all or any of specimen collection, molecular testing, clinical evaluation, and chest radiography at low levels of care. Decentralising childhood TB diagnostics to district hospitals (DH) and primary health centres (PHC) could improve case detection. We conducted an operational research study using a pre-post intervention cross-sectional study design in 12 DHs and 47PHCs of 12 districts across Cambodia, Cameroon, Côte d'Ivoire, Mozambique, Sierra Leone and Uganda. The intervention included 1) a comprehensive diagnosis package at patient-level with tuberculosis screening for all sick children and young adolescents <15 years, and clinical evaluation, Xpert Ultra-testing on respiratory and stool samples, and chest radiography for children with presumptive TB, and 2) two decentralisation approaches (PHC-focused or DH-focused) to which districts were randomly allocated at country level. We collected aggregated and individual data. We compared the proportion of tuberculosis detection in children and young adolescents <15 years pre-intervention (01 August 2018-30 November 2019) versus during intervention (07 March 2020-30 September 2021), overall and by decentralisation approach. This study is registered with ClinicalTrials.gov, NCT04038632. TB was diagnosed in 217/255,512 (0.08%) children and young adolescent <15 years attending care pre-intervention versus 411/179,581 (0.23%) during intervention, (OR: 3.59 [95% CI 1.99-6.46], p-value<0.0001; p-value=0.055 after correcting for over-dispersion). In DH-focused districts, TB diagnosis was 80/122,570 (0.07%) versus 302/86,186 (0.35%) (OR: 4.07 [1.86-8.90]; p-value=0.0005; p-value=0.12 after correcting for over-dispersion); and 137/132,942 (0.10%) versus 109/93,395 (0.11%) in PHC-focused districts, respectively (OR: 2.92 [1.25-6.81; p-value=0.013; p-value=0.26 after correcting for over-dispersion). Decentralising and strengthening childhood TB diagnosis at lower levels of care increases tuberculosis case detection but the difference was not statistically significant. Unitaid, Grant number 2017-15-UBx-TB-SPEED.

Antigen-specific chemokine profiles as biomarkers for detecting Mycobacterium tuberculosis infection.

Latent tuberculosis (TB) infection can progress to active TB, which perpetuates community transmission that undermines global TB control efforts. Clinically, interferon-γ release assays (IGRAs) are commonly used for active TB case detection. However, low IGRA sensitivity rates lead to false-negative results for a high proportion of active TB cases, thus highlighting IGRA ineffectiveness in differentiating MTB-infected individuals from healthy individuals. Participants enrolled at Beijing Chest Hospital from May 2020-April 2022 were assigned to healthy control (HC), LTBI, IGRA-positive TB, and IGRA-negative TB groups. Screening cohort MTB antigen-specific blood plasma chemokine concentrations were measured using Luminex xMAP assays then were verified via testing of validation cohort samples. A total of 302 individuals meeting study inclusion criteria were assigned to screening and validation cohorts. Testing revealed significant differences in blood plasma levels of CXCL9, CXCL10, CXCL16, CXCL21, CCL1, CCL19, CCL27, TNF-α, and IL-4 between IGRA-negative TB and HC groups. Levels of CXCL9, CXCL10, IL-2, and CCL8 biomarkers were predictive for active TB, as reflected by AUC values of ≥0.9. CXCL9-based enzyme-linked immunosorbent assay sensitivity and specificity rates were 95.9% (95%CI: 91.7-98.3) and 100.0% (92.7-100.0), respectively. Statistically similar AUC values were obtained for CXCL9 and CXCL9-CXCL10 assays, thus demonstrating that combined analysis of CXCL10 and CXCL9 levels did not improve active TB diagnostic performance. The MTB antigen stimulation-based CXCL9 assay may compensate for low IGRA diagnostic accuracy when used to diagnose IGRA-negative active TB cases and thus is an accurate and sensitive alternative to IGRAs for detecting MTB infection.

Analysis of Risk Factors on the Performance of Tuberculosis Control Program Officers in the Working Area of the Lubuk Kambing Health Center, Jambi, Indonesia

Indonesia is ranked 2nd in the country with the highest burden of tuberculosis (TB). In Jambi, the detection rate for pulmonary TB cases is still low (19%), and at the Lubuk Kambing Health Center, it only reaches 53%. This study aims to analyze the factors associated with the low rate of TB case detection in the Lubuk Kambing Health Center working area. Cross-sectional research design with 65 respondents. Data analysis uses logistic regression. There is a relationship between level of knowledge, motivation, workload, training, length of service, availability of TCM (molecular rapid test) facilities, active screening of pulmonary TB suspects, honorarium, family support, and evaluation of TB prevention and control officers and TB cadres with low detection capabilities d TB in the Lubuk Kambing Health Center working area. Availability of facilities is the dominant factor related to the low number of TB cases in the Lubuk Kambing Health Center working area. Efforts to increase knowledge, motivation, training, length of service, active screening, honorarium, and family support, as well as providing TCM facilities and regular evaluations, need to be carried out to increase the TB case detection rate.

Improving tuberculosis case detection through contact risk stratification by Xpert MTB/RIF Ultra and spatial parameters: Evaluation of an innovative active case finding strategy in Mozambique (Xpatial-TB)

Prompt diagnosis is critical for tuberculosis (TB) control, as it enables early treatment which in turn, reduces transmission and improves treatment outcomes. We investigated the impact on TB diagnosis of introducing Xpert Ultra as the frontline diagnostic test, combined with an innovative active-case finding (ACF) strategy (based on Xpert Ultra semi-quantitative results and spatial parameters), in a semi-rural district of Southern Mozambique. From January-December 2018 we recruited incident TB-cases (index cases, ICs) and their household contacts (HCs). Recruitment of close community contacts (CCs) depended on IC´s Xpert Ultra results, and the population density of their area. TB-contacts, either symptomatic or people living with HIV, were asked to provide a spot sputum for lab-testing. Trends on TB case notification were compared to the previous years and to those of two districts in the south of the Maputo province (control area), using an interrupted time series analysis with and without control (CITS/ITS). A total of 1010 TB ICs (37.1% laboratory-confirmed) were recruited; 3165 HCs and 4730 CCs were screened for TB. Eighty-nine additional TB cases were identified through the ACF intervention (52.8% laboratory-confirmed). The intervention increased by 8.2% all forms of TB cases detected in 2018. Xpert Ultra trace positive results accounted for a high proportion of laboratory confirmations in the ACF cohort (51.1% vs 13.7% of those passively diagnosed). The Number Needed to Screen to find a TB case differed widely among HCs (55) and CCs (153). During the intervention period, a reversal of the previous negative trend in lab-confirmed case notifications was observed in the district. However, the CITS model did not show any statistically significant difference compared to the control area. Paediatric population benefited the most from the ACF strategy and HCs screening seemed an effective intervention to find microbiological confirmed cases in early stages of the disease.

Improving TB detection among children in routine clinical care through intensified case finding in facility-based child health entry points and decentralized management: A before-and-after study in Nine Sub-Saharan African Countries.

In 2022, an estimated 1.25 million children <15 years of age developed tuberculosis (TB) worldwide, but >50% remained undiagnosed or unreported. WHO recently recommended integrated and decentralized models of care as an approach to improve access to TB services for children, but evidence remains limited. The Catalyzing Paediatric TB Innovation project (CaP-TB) implemented a multi-pronged intervention to improve TB case finding in children in nine sub-Saharan African countries. The intervention introduced systematic TB screening in different facility-based child-health entry-points, decentralisation of TB diagnosis and management, improved sample collection with access to Xpert® MTB/RIF or MTB/RIF Ultra testing, and implementation of contact investigation. Pre-intervention records were compared with those during intervention to assess effect on paediatric TB cascade of care. The intervention screened 1 991 401 children <15 years of age for TB across 144 health care facilities. The monthly paediatric TB case detection rate increased significantly during intervention versus pre-intervention (+46.0%, 95% CI 36.2-55.8%; p<0.0001), with variability across countries. The increase was greater in the <5 years old compared to the 5-14 years old (+53.4%, 95% CI 35.2-71.9%; p<0.0001 versus +39.9%, 95% CI 27.6-52.2%; p<0.0001). Relative contribution of lower-tier facilities to total case detection rate increased from 37% (71.8/191.8) pre-intervention to 50% (139.9/280.2) during intervention. The majority (89.5%) of children with TB were identified through facility-based intensified case-finding and primarily accessed care through outpatient and inpatient departments. In this multi-country study implemented under real-life conditions, the implementation of integrated and decentralized interventions increased paediatric TB case detection. The increase was driven by lower-tier facilities that serve as the primary point of healthcare contact for most patients. The effect was greater in children < 5 years compared to 5-14 years old, representing an important achievement as the TB detection gap is higher in this subpopulation. (Study number NCT03948698).

A social enterprise model for TB detection and treatment through the private sector in Pakistan.

Existing models to increase TB case notifications from the private sector in Pakistan are financially unsustainable and have achieved modest success due to limited coverage. To evaluate the impact of a social enterprise model (SEM) intervention on TB case detection in Karachi, Pakistan, and to assess its financial sustainability. Purpose-built centres were established within the private sector that integrated TB screening, diagnostics and treatment and operated 12 hours per day with convenient locations to improve access. TB services were offered free of cost, and revenue generation took place through user fees from other diagnostics. Private providers with a focus on the informal sector were engaged through community workers to generate screening referrals. Overall 171,488 people were screened and 18,683 cases were notified, including 197 individuals with drug-resistant TB. Annual TB notifications in Karachi increased from 18,105 in 2014 to a maximum of 25,840 (40% increase). The proportion of cases in Karachi notified by the centres grew to 27% in 2020. Commercial revenue reached USD288,065 and enabled operating cost recovery of 15%. Average cost per TB case notified was USD203. The SEM intervention contributed a large proportion of notifications in Karachi and achieved modest cost recovery.

Optimized Case Finding of tuberculosis among key populations in Ukraine. A follow up study.

In 2021, there were 4 million tuberculosis (TB) cases that were not detected by health systems, globally. Many of those cases are among hard-to-reach populations or key population groups. An Optimized Case Finding (OCF) strategy was introduced in Ukraine to enhance case detection and identify those "missing" cases. OCF included screening of up to eight referred household and social network contacts of an index TB case. Following the OCF project implementation, TB detection and characteristics of index cases and contacts were assessed. A cohort study using project data (July 2018 - April 2022) was conducted. In total 7,976 close contacts were engaged in the project from 1,028 index TB cases. Among the contacts, 507 were diagnosed with TB. The TB case detection was 6,356/100,000 and the number needed to investigate was 16. Multiple factors were identified as associated with TB detection including smoking, HIV, poverty, etc. About 90% of cases were identified at the initial screening of the contacts. OCF was proven to be 5.8 times more effective than the standard active case finding using household surveys and 106 times more effective than passive case finding in the general public. Our study demonstrated the effectiveness of OCF in detecting cases among key population groups and their social networks. We encourage adaptation and use of OCF by civil society organizations that already work with key vulnerable populations around the globe.

Improving TB Case Detection Through Active Case-Finding: Results of Multiple Intervention Strategies in Hard-to-Reach Riverine Areas of Southern Nigeria.

A major challenge to TB control globally is low case detection, largely due to routine health facility-based passive case-finding employed by national TB control programs. Active case-finding is a risk-population-based screening approach that has been established to be effective in TB control. This intervention aimed to increase TB case detection in hard-to-reach areas in southern Nigeria. Using a descriptive cross-sectional design, we conducted implementation research in 15 hard-to-reach riverine local government areas with historically recognized low TB case notification rates. Individuals with TB symptoms were screened using multiple strategies. Data were collected quarterly over a 4-year period using reporting tools and checklists. Descriptive analysis was done with Microsoft Excel spreadsheet 2019. A total of 1,089,129 individuals were screened: 16,576 in 2017; 108,102 in 2018; 697,165 in 2019; and 267,286 in 2020. Of those screened, 24,802 (2.3%) were identified as presumptive TB, of which 88.8% were tested and 10% were diagnosed with TB (0.23% of those screened). TB notifications more than doubled, increasing by 183.3% and 137.5% in the initial implementation and scale-up, respectively. On average, 441 individuals needed to be screened to diagnose 1 TB case. The cases, predominantly males (56.1%) and aged 15 years and older (77.4%), comprised 71.9% bacteriologically confirmed drug-sensitive TB, 25.8% clinically diagnosed drug-sensitive TB, and 2.3% drug-resistant cases. Detection sources included community outreach (1,786), health facilities (505), people living with HIV (57), and household contacts of bacteriologically confirmed TB cases (123). Remarkably, 98.1% of diagnosed TB cases commenced treatment. We found a significant yield in TB case notifications, more than doubling the baseline figures. Given these successful results, we recommend prioritizing resources to support active case-finding strategies in national programs, especially in hard-to-reach areas with high-risk populations, to address TB more comprehensively.

Knowledge and Practices toward Tuberculosis Case Identification among Accredited Drug Dispensing Outlets Dispensers in Magu District, Northwestern Tanzania.

Accredited Drug Dispensing Outlets dispensers (ADDO dispensers) have a crucial role in detecting and referring TB suspects. However, several studies highlight low knowledge of TB among ADDO dispensers. To facilitate this, the National TB and Leprosy Control Program trained ADDO dispensers on case identification and referral. Hence, this was a community-based cross-sectional study to determine the knowledge and practice of ADDO dispensers in the detection of active tuberculosis suspects in Magu Districts, Mwanza, Tanzania. This was a cross-sectional study that included 133 systematically selected ADDO dispensers. Out of 133 ADDO dispensers, 88 (66.9%) had attended TB training. About 108 (81%) participants had good knowledge of TB. The majority of ADDO dispensers 104 (78.4%) had poor practice toward the identification of TB cases. Attending training (AOR 4.49, CI 1.03-19.47), longer working experience (AOR 4.64, CI 1.99-10.81), and the presence of national TB guidelines (AOR 3.85, CI 1.11-13.34) was significantly associated with good self-reported TB case identification practices. Therefore, the study revealed adequate knowledge but with poor practice. Provisions to train ADDO dispensers in tuberculosis case detection and referral could yield great results.

Care pathways of individuals with tuberculosis before and during the COVID-19 pandemic in Bandung, Indonesia.

The COVID-19 pandemic is thought to have undone years' worth of progress in the fight against tuberculosis (TB). For instance, in Indonesia, a high TB burden country, TB case notifications decreased by 14% and treatment coverage decreased by 47% during COVID-19. We sought to better understand the impact of COVID-19 on TB case detection using two cross-sectional surveys conducted before (2018) and after the onset of the pandemic (2021). These surveys allowed us to quantify the delays that individuals with TB who eventually received treatment at private providers faced while trying to access care for their illness, their journey to obtain a diagnosis, the encounters individuals had with healthcare providers before a TB diagnosis, and the factors associated with patient delay and the total number of provider encounters. We found some worsening of care seeking pathways on multiple dimensions. Median patient delay increased from 28 days (IQR: 10, 31) to 32 days (IQR: 14, 90) and the median number of encounters increased from 5 (IQR: 4, 8) to 7 (IQR: 5, 10), but doctor and treatment delays remained relatively unchanged. Employed individuals experienced shorter delays compared to unemployed individuals (adjusted medians: -20.13, CI -39.14, -1.12) while individuals whose initial consult was in the private hospitals experienced less encounters compared to those visiting public providers, private primary care providers, and informal providers (-4.29 encounters, CI -6.76, -1.81). Patients who visited the healthcare providers >6 times experienced longer total delay compared to those with less than 6 visits (adjusted medians: 59.40, 95% CI: 35.04, 83.77). Our findings suggest the need to ramp up awareness programs to reduce patient delay and strengthen private provide engagement in the country, particularly in the primary care sector.

Assessing the impact of COVID-19 on tuberculosis detection and treatment in healthcare facilities across Addis Ababa, Ethiopia: A comprehensive mixed-method, multi-center study.

Ethiopia faces a significant burden of Tuberculosis (TB), being one of the high-burden countries, and the emergence of the Coronavirus Disease 2019 (COVID-19) has become a dominant health concern, particularly in resource-limited settings. The repercussions of COVID-19 on TB care are evident, leading to a surge in undiagnosed TB cases, challenges in medication adherence, and an escalation of drug resistance. Consequently, a thorough assessment of the impact of COVID-19 on TB care becomes imperative to devise a tailored program for managing TB amidst future pandemics, natural disasters, and conflict crises. A mixed-methods study design was utilized, encompassing a randomly selected 10 health centers (HCs) and 3 hospitals among government owned 98 HCs and 5 hospitals in Addis Ababa, Ethiopia. All TB patients who were on follow-up during the study period were included. The study period was from March 4, 2020, to December 4, 2020, with the corresponding period of March 4, 2019, to December 4, 2019, serving as the baseline for comparison. Quantitative data were gathered from TB patients' medical registries, laboratory registries, and treatment follow-up charts. Complementary qualitative data were acquired through in-depth interviews. Both qualitative and quantitative data were collected from January 17, 2022 to May 13, 2022. Following the onset of the pandemic, there was a notable and statistically significant decline in both the detection of TB cases and the number of positive results across all study sites. Bacteriological TB tests reduced from 5837 to 2126 patients, and TB-positive cases decreased from 500 to 218, representing declines of 63.6% and 56.4%, respectively. The overall number of TB patients undergoing treatment also experienced a decrease from 1431 to 1051, marking a 26.6% reduction. Additionally, there was a 10% increase in the proportion of extra-pulmonary TB cases. The impact of the pandemic extended to TB treatment outcomes, with adverse effects on cure rates, death rates, loss of follow-up, and medication adherence. The apprehension of contracting COVID-19 and the implementation of isolation measures contributed to a decline in healthcare-seeking behaviors among patients, fostering negative perceptions and practices among healthcare workers. The challenges further exacerbated due to a shortage of personal protective equipment, a lack of rapid diagnostic test tools, clinical presentations resembling COVID-19, and a shift in government policies. These factors collectively posed significant obstacles to effective TB care during the pandemic. The profound impact of COVID-19 on critical TB care service indicators, including TB detection, treatment initiation, and treatment outcomes, underscores the need for immediate and collaborative measures. It is imperative to implement strategies that ensure the resumption of all TB care services concurrently with efforts to control COVID-19. A comprehensive and coordinated approach is essential to mitigate the adverse effects of the pandemic on TB management and safeguard public health.

Analysis of factors affecting presumptive examination rate and understanding district wise issues from the last nine years (2015-2023) in the state of Telangana, India

Background: Tuberculosis caused by Mycobacterium Tuberculosis is detected by smear microscopy, molecular tests like CBNAAT (Cartridge based nucleic Acid Amplification test) or Truenat, Line Probe assays (LPA) and phenotypic tests like solid Culture and liquid Culture. Yet every year there are many cases which go undiagnosed due to lack of information, availability, and accessibility to these tests. Presumptive examination rate helps us to understand the scenario of existing individuals having any one of the symptoms of TB diagnosing TB and thus helping in detecting Tuberculosis cases much earlier. Interventions: A quality analysis and assessment were conducted to identify the reasons for the high and low Presumptive Examination Rates across all districts in Telangana, India. The availability of CBNAATs and truenats machines at the periphery level helped in increasing the number of tests in the year 2022. The state ensured the availability of logistics such as CBNAAT cartridges and Truenat chips. Extensive IEC efforts were carried out at both district and block levels to promote the availability of NAATs, aiming for optimal utilization of the machines for patients seeking care in both the public and private sectors. Results: The Presumptive examination rate, which was significantly lower in the year 2015 gradually, increased in the year 2023 with adequate availability of logistics in the NAAT facilities. This intervention not only increased the presumptive examination rate but also boosted TB detection rates and utilization of the public sector NAAT facilities by the private sector. Conclusion: Analyzing the presumptive examination rate provides insights into the availability and accessibility of facilities, the sufficiency of logistics, and the utilization of services across all sectors. This understanding aids in developing more effective strategies to make TB diagnostics more accessible.

Active case detection of rifampicin sensitive and resistant tuberculosis by systematic screening among household contacts of rifampicin-resistant tuberculosis patients in Dhaka, Bangladesh

Background/Aim: Patients with rifampicin resistant-tuberculosis (RRTB) may remain a source of infection longer than patients with rifampicin sensitive-tuberculosis (RS-TB). This study aimed to detect active cases of RS-TB and RR-TB through systematic screening among household contacts of RR-TB patients in Dhaka, Bangladesh. Methods: This cross-sectional study was conducted among the 355 household contacts (HHCs) of 93 RR-TB primary cases identified from various centres in Dhaka, diagnosed between November 2020 and October 2021. For the identification of active cases of tuberculosis (TB), systematic screening among HHCs was done, where verbal screening was performed to check the presence of symptoms of TB. Those who had at least one symptoms of TB were considered as symptomatic contacts. Later GeneXpert analysis of sputum was done among the screened symptomatic contacts. Data was collected using a pretested, semi-structured, interviewer-administered questionnaire. Results: An estimated 30.4 % of respondents were ≤ 15 years of age. TBlike symptoms were prevalent among 9.9 % of respondents. Loss of appetite (45.7 %), unexplained weight loss (40.0 %) and cough (37.1 %) were the most common symptoms. Among the contacts with TB-like symptoms, 6.7 % were diagnosed as a case of TB (3.35 % were RR-TB and 3.35 % were RS-TB). The number needed to be screened to find an active case of TB was established at 178 among the HHCs of RR-TB. Conclusions: About one in ten RR-TB HHCs showed TB-like symptoms. One in fifteen HHCs with TB-like symptoms was an active case of TB. Regular, effective screening of RR-TB contacts is needed to stop the transmission.

Contact screening of children exposed to active pulmonary tuberculosis: A hospital-based study in Navi Mumbai, India

Abstract Background: Contact investigation is a proactive method employed for active case-finding to improve the detection of active tuberculosis (TB) cases, constituting a crucial component of National TB Programs. Household contacts face a higher exposure risk than individuals in the general population. Although integrated into national policy, the execution of contact investigations is not regularly undertaken, and the outcomes of these investigations are inadequately characterized. Objective: To evaluate risk factors and determine the occurrence of TB disease among household contacts of individuals diagnosed with sputum smear-positive TB in Kamothe, Navi Mumbai, India. Materials and Methods: From December 2018 to November 2020, active screening was carried out for 120 household contact children aged up to 18 years, linked to 52 index cases receiving care at MGM Medical College and Hospital in Navi Mumbai, India. Results: Out of the 120 screened children, 10 (8.3%) showed symptoms, whereas 110 (91.6%) were asymptomatic. Among those exhibiting symptoms, 5 (50%) had abnormal chest X-ray findings. The diagnosis of TB was established in eight cases, including five with pulmonary TB, two with lymph node TB, and one with central nervous system TB. All confirmed TB-positive cases underwent antitubercular treatment, with children under 5 years receiving Isoniazid Preventive Therapy. Conclusion: The study resulted in a 6.67% incidence rate, offering an opportunity to initiate chemoprophylaxis among children. This research identified risk factors associated with the development of TB disease, encompassing female gender, underweight status, residing in crowded conditions, prolonged contact, and extended duration of exposure.

Facilitators and barriers to implementing chest radiography in tuberculosis systematic screening of clinically high-risk groups in Ethiopia: A qualitative study.

Chest X-ray has been included in national tuberculosis screening algorithms as a sensitive tuberculosis screening tool among high-risk groups. However, the implementation was influenced by multiple factors. We aimed to explore facilitators and barriers to implementing chest X-ray in systematic tuberculosis screening of clinically high-risk groups in Addis Ababa, Ethiopia. We conducted face-to-face, in-depth interviews with purposively selected participants at tertiary-level hospitals and a tuberculosis program coordinator at the Ethiopian Ministry of Health, who coordinates chest X-ray-guided systematic tuberculosis screening. A framework analysis was conducted using the consolidated framework for implementation research. We identified 11 constructs that influenced the implementation of the chest X-ray intervention. Facilitators included the relative sensitivity of chest X-ray over symptom-based screening, its potential integration into existing systems, technological advancements in the area, policies and laws supporting the screening intervention, and the quality of the evidence of the screening intervention. Barriers included implementation complexity, high costs of the intervention, knowledge gaps among healthcare providers, training gaps, low priority for chest X-ray screening at the healthcare facility level, and a lack of external support from the Ministry of Health and stakeholders. This study identified contextual factors that influence the implementation of chest X-ray guided systematic tuberculosis screening among clinically high-risk groups that healthcare facilities and health ministries may use for decision-making. Addressing the barriers identified by the study would help to improve the implementation of chest X-rays for improved tuberculosis case detection and prompt treatment in clinically high-risk groups.