The Conference theme: “STEP UP – Let’s embrace all to end TB!” provides a unique opportunity to reflect on what we have done across the entire spectrum of our programmes in response to TB, what has been effective and what not, what we need to do to find the missing cases and giving attention to the structural and social determinants which fuel this epidemic. What has worked, what lessons have we learned and how are we applying these to the new understanding we have gained over the years.
On behalf of the Program Committee, we cordially invite you to present your research, successful programmes, innovative interventions or best practices for consideration to be part of the programme and to contribute to this all important Conference.
The Conference will cover the following tracks: Track 1: Basic and Clinical Sciences Track 2: Public Health and Prevention Strategies Track 3: Health Systems, Monitoring and Evaluation Track 4: Human Rights, Stigma, Marginalised Populations
We will be covering the following themes over the three days of deliberation: Day 1: Finding the Missing Cases Day 2: Social and Biological Determinants Impacting the TB Cascade Day 3: Who has Access to new drugs? Managing DR TB
This Conference creates a platform wherein all scientists (basic and social), clinicians, activists and community workers can showcase their significant contribution towards curbing the TB epidemic.
We encourage you to contribute your experiences and knowledge to the discussions on the impact of TB infection on other related infectious diseases, social and ethical issues as well as provision of healthcare in general.
NB: If you missed the abstract deadline do not worry, as for the first time in this conference, we will have a late-breaker session. You can submit abstracts for this session from 1 – 30 April 2018
Models of HIV can be very simple (1) or very detailed (2,3). The simple models give a good overall understanding of the drivers of the epidemic while the detailed models allow one to explore the impact of different structures, transmission networks and interventions. The standard model of TB (4), even in its simplest form, can involve many different transition states for fast and slow progressors, latent TB and TB disease, those on treatment and those that fail treatment. Since all of these models are well established, it is tempting to model the combination of HIV and TB by repeating a suitable TB model a number of times corresponding to the various states of HIV: uninfected, early infection and various states corresponding to the progression of HIV through the various clinical stages of infection to death. This can, however, lead to a very complex model with tens, if not hundreds of parameters, requiring considerable computing power to run. Fortunately, the time scales over which the two infections progress are very different, allowing us to greatly simplify the problem.
Rising incidence of TB due to HIV has no impact on TB in HIV negatives
Very early in the epidemic of HIV it was clear that HIV was driving the incidence of TB rapidly upwards. Given the already very high rates of TB in countries like South Africa, and within South Africa in the gold-mines, people were concerned that the increase in TB resulting from the severe epidemic of HIV would spread TB throughout the population. Fortunately, this turned out not to be the case and the key study in this regard was carried out by Elizabeth Corbett studying the gold miners in the town of Welkom. Corbett carried out a retrospective analysis of the incidence and prevalence of TB in HIV-positive and HIV-negative miners (5) between the years 1990 and 2000. As expected, the incidence of TB in men with HIV increased, over this period, from 2.2% per annum (p.a.) in 1991–1997 to 5.9% p.a. in 1998–1999 to 9.4% p.a. in1999–2000. But, unexpectedly, the incidence of TB in men without HIV remained constant at 1.0% p.a., 1.1% p.a. and 1.1% p.a. Since this study covered the time when the epidemic of HIV was taking off it gave us a number of key insights. In 1990 most people with HIV must have been recently infected suggesting that soon after infection the risk of developing TB doubles. As time passes, more and more men have more advanced HIV-disease and, as their immune systems collapse, their risk of developing TB continues to increase. All of this was confirmed in subsequent studies that showed that a person’s CD4+ cell count drops by about 25% immediately after infection with HIV and then decreases almost linearly, on average reaching zero over about ten years – the untreated life expectancy. Further studies showed that the incidence of TB increases exponentially with declining CD4+ cell counts and this enables one to fit the observed epidemic trends quite well (6-8).
Just as important, however, was Corbett’s quite unexpected observation (5) that the dramatic rise in the incidence of TB, resulting from the rising epidemic of HIV, had no impact on TB in HIV negative people. The reason for this soon became clear: as people’s CD4+ cell counts decline their risk of developing TB rises, but the mortality of co-infected people increases so that they die that much more quickly. Since the prevalence of disease is roughly equal to the incidence times the duration of infectiousness, prevalence, and hence infectious pressure, would be the same even if the incidence increases by a factor of, say, ten, provided provide the mortality increases and the duration of infectiousness decreases, by the same factor.
Simple model to estimate impact of HIV on TB epidemic
This insight gives us a very simple way to model the impact of HIV on TB. First we note that TB is a very slow disease, with characteristic times of the order of decades, compared to HIV, with characteristic times of the order of years. Second, for the reasons given above, TB in HIV-positive people does not add to the incidence and therefore the risk of TB in other people We can therefore use whatever model we like for TB in HIV-negative people, ignoring the epidemic of HIV completely. For the HIV-positive people we assume: 1. That the incidence of TB disease doubles (7) immediately after the two week acute phase of HIV (9.10); 2. That the incidence of TB increases exponentially with time since infection using the stage of infection as a surrogate for the time since infection; 3. That the duration of TB disease in HIV positive people is less than in HIV-negative people; 4. ART reduces the incidence of TB in people with HIV (8). To model the epidemic of TB in HIV-positive people, given the epidemic of TB in HIV-negative people, we then have only two fixed and one variable parameter in model. The factor of 2 in the first assumption we take as fixed. The exponential rate of increase of TB with declining CD4+ cell counts in the second assumption is the only variable parameter. The increase in morality and the reduction in disease duration, the ‘Corbett factor’ appears to be the same over a number of different countries and can be taken as fixed (1). When we introduce ART the corresponding reduction in the incidence of TB appears also to be fixed at about 60%.
So given a model of what we expect to happen to TB without HIV and considering only the comparatively short time scale of HIV compared to TB, we can model the impact of HIV on TB with a model that requires three fixed but only one variable parameter and this has been shown to give very good fits to the TB epidemics in all of southern Africa (2) and indeed East Africa as well (Williams, unpublished).
The important lesson for modellers is that one is tempted to start with detailed models of TB and HIV and then combine them into one even more detailed TB-HIV model, giving a model with tens of parameters, and this is what the present author initially did (8). But clear thinking and a better understanding of the natural history of HIV and TB, drawing on the critical work of Corbett, makes it possible to model the epidemic of TB in the context of HIV with only a single variable parameter (1) which is not only much easier to do but gives greater insight into the way in which the two epidemics interact.
Tuberculosis (TB) notification rates in South Africa have been declining since 2009, mainly due to increased access to antiretroviral therapy for HIV positive people but also to increases in TB treatment success. However, TB remains the leading cause of death in South Africa which has the highest incidence of TB in the world (834 per 100,000 people). The newly released National Strategic Plan on HIV, STIs and TB proposes two ambitious goals for TB by 2022 (1). Goal 1 is to reduce overall TB incidence by 30%, which can only be achieved by a combination of interventions, for instance by ensuring that everyone infected with HIV is on anti-retroviral therapy, improving the uptake of TB preventive therapy, and successfully identifying and treating the estimated 150 thousand missing TB cases through a national campaign. Goal 2 sets a 90-90-90 target for TB: 1) Find 90% of all TB cases and place them on appropriate treatment, 2) Find at least 90% of the TB cases in key populations and place them on appropriate treatment, and 3) Successfully treat at least 90% of those diagnosed with drug sensitive TB and 75% of those with drug resistant TB. Key populations for TB are, for example: people living with HIV, people living with diabetes, household contacts of people with TB, people working in or living near mines, healthcare workers, and people living or working in prisons.
Current TB case finding strategy
The World Health Organisation recommends systematic symptom screening for active TB in individuals who are seeking health care or who are in health care and belong to selected high risk populations, which include areas where the prevalence in the general population is equal to or higher than 100/100,000 population (2). Although in the South African context this translates to symptom screening of everyone who walks into a public health care facility (so-called “universal” screening) independent of symptomatology, this is not currently part of any policies or guidelines. The South African National Tuberculosis management guidelines of 2009 stated that a “client who presents to a health facility with a cough for more than 2 weeks should be regarded as a tuberculosis suspect and investigated appropriately” (3). The 2014 version of the guidelines states that “every patient with a positive symptom screen must be investigated appropriately” where a positive symptom screen is defined as the presence of any TB related symptom (4) including a cough of more than 2 weeks, fever for more than 2 weeks, current night sweats and recent unexplained weight loss. Among HIV positive people, cough of any duration should be investigated. Investigations following a positive symptom screen currently consist of sputum GeneXpert® (for all presumptive cases) and sputum culture (for HIV positive cases with a negative GeneXpert®). However, symptom screening on its own presents many challenges, especially in a high burden, low resource setting like South Africa.
Diagnostic characteristics of systematic symptom screening
To investigate the effectiveness of screening rules in populations where the general prevalence is higher than 100/100,000 population, we revisited the results from the Zambia South Africa Tuberculosis and HIV/AIDS Reduction (ZAMSTAR) prevalence surveys to assess how well these screening rules perform in identifying TB cases. These communities were selected for the ZAMSTAR trial because of their high burden. In the 2010 survey, around 64,000 people from 8 communities in Cape Town and 16 communities in Zambia provided sputum samples for culture. The average prevalence of TB in the Cape Town communities was 2.4%, and in the Zambian communities 0.6% (5).
Among all participants, without reference to their HIV status, the sensitivity of using coughing for more than two weeks as entry into TB screening was only 20% in the South African group, so that 80% of TB cases would have been missed. The specificity was 95% so that 5 out of 100 TB negative people would be tested unnecessarily for TB. We also investigated the use of combinations of other symptoms in patients who did not have a prolonged cough to increase the sensitivity of screening, while setting a minimum specificity threshold of 85%. One option is to use at least two of the following symptoms: a short duration of cough (< 2 weeks), night sweats or sudden weight loss. This would increase the sensitivity to 35%, allowing an additional 15 out of 100 TB cases to be tested for TB. The specificity using this rule drops to 88% so that 12 out of 100 people would be unnecessarily tested for TB. In other words, in the general population, we would have to use two screening rules in order to increase sensitivity to 35%: (i) prolonged cough and, in those not having a prolonged cough, (ii) at least two of the following symptoms: short cough (<2weeks), night sweats or weight loss.
Exploring other ways to improve TB case finding
Systematic symptom screening in high risk populations, when this translates to screening everyone in the community, is neither sensitive nor cost-effective. To explore alternative methods of improving case finding, we carried out a study in the Buffalo district of the Eastern Cape in 2015 to estimate the proportion of symptomatic TB cases accessing health care that was missed by the health system. The study was designed to represent the population of the district. Adults who visited clinics, for whatever reason, were asked about respiratory symptoms upon exit, and were enrolled in the study if they reported any of the following: coughing, fever, night sweats or recent weight loss. Participants who did not provide sputum samples in the clinics were asked to provide samples to the study staff.
About half of the 1,255 study participants visited the clinics because of their TB symptoms. 80% of them reported that they were screened for TB in the clinic, but only 18% submitted a sputum sample to the clinic staff. Of the traceable results 12% were positive for TB. In the group that visited clinics for reasons other than their current TB symptoms, 20% were screened and 3.7% submitted sputum at the clinic. Of these, none of the traceable results were positive for TB. We managed to obtain approximately 800 evaluable sputum samples from the remaining approximately 1,100 of the participants who did not submit samples in the clinics and identified 39 more TB cases (5%), 3 of which were resistant to rifampicin. Due to the large fraction (50%) of samples submitted in the clinic that had no result recorded in the register, we cannot estimate precisely the fraction of TB cases missed by the health system since these cases might either be truly missed, or cases not recorded in the register but results may have been given to patients and/or patients initiated on treatment (so called “bottom-drawer cases”). Based on simple assumptions we estimate that between 63% and 79% of TB cases were missed among those who attended for their TB symptoms, and between 90% and 100% among those who attended for other reasons. Of the 515 symptomatic participants known to have been in one of the “key populations” (self-reported HIV positive, self-reported diabetes or household contact of TB case), only 48% were screened and only 12% were asked to provide a sputum sample (6).
Using two different approaches to improved case finding, namely (i) improving the sensitivity of symptom screening rules when applied to entire communities and (ii) screening symptomatic primary healthcare clinic attendees on exit, we have shown that symptom screening alone, if used in the community as an active case finding approach (“door-to-door”), would identify at most 35% of TB patients and this is not effective or cost-efficient. A more effective, cost-effective and efficient way would be to screen individuals already accessing healthcare. However, our study in primary healthcare clinics focused on symptomatic individuals only, and recent studies suggest that up to 55% of TB patients might be asymptomatic (7). It is therefore obvious that too many TB patients are asymptomatic for symptom-driven TB screening to be a sufficient case finding tool per se. Screening people who seek health care, for whatever reason, may be a feasible and helpful complementary strategy to symptom-driven testing, and this “universal screening” could have broader criteria for a positive screening test, including other key clinical and demographic characteristics in a screening tool, for instance body mass index, smoking history and previous history of TB.
The TB programme might therefore consider screening all individuals at primary healthcare facility level, irrespective of their reason for attending. The use of a screening tool with improved sensitivity in comparison to symptom screening alone would be preferable, followed by the current diagnostic algorithm. This approach could contribute to reaching the first of the 90-90-90 TB targets as mentioned above, although in what degree would have to be demonstrated by implementation research studies. In addition, it would contribute to Goal 1 of the National Strategic Plan, by identifying some of the missing cases. Ideally a comparison between a campaign, which probably means a “door-to-door” strategy, and universal screening among health care attendees on a national level should be compared to determine feasibility and cost-effectiveness. With the current situation in South Africa, showing only a modest decline in new TB cases since 2012, new avenues and strategies urgently need to be explored, tested and implemented in order to do everything in our power to curb this epidemic and reach the ultimate goal of a South Africa free of TB.
TB (Mycobacterium tuberculosis) disease has been known by various names for thousands of years including consumption, phthisis, scrofula, Pott’s disease, and the White Plague, and has of late been described in exquisite biological detail. Yet we still struggle to reliably answer the question: Does a particular person have ‘active’ TB?
In most of the world, until recently, TB has remained stubbornly persistent (‘endemic’). A combination of improved living conditions and (largely) effective treatment has pushed TB into the margins of developed countries, but in much of the world, including Africa and Asia in particular, it remains a major epidemic causing of loss of productive, healthy and happy life. In South Africa TB is the leading cause of death although only 1% of the population develop TB disease every year. Globally US$ 0.7 billion is spent annually on TB research. It is calculated that annually approximately UDS$ 2 billion is required to develop new tests and drugs needed to eliminate the if the TB epidemic. Many fine details of the lifecycle of the ‘infectious agent’ (the TB bacillus) are known from the extensive research conducted. In contrast, the available diagnostic tests have several limitations and perform poorly especially in developing countries where they are most needed. The unsatisfactory performance and availability of diagnostic tests has consequences for clinical management, costs, surveillance, and systems planning of any TB program.
The course of TB disease makes an early diagnosis difficult.
The course of TB in the human is complex due to the slow multiplication of the TB bacterium. TB is spread by inhaling micro-droplets which contain the TB bacterium. These micro-droplets are generated during coughing bouts, especially by adults who have active pulmonary (lung) TB. The microdroplets are inhaled and settle in the lung where they slowly multiply. At this stage the person is said to be infected with TB (TB infection) but has not yet developed TB disease. It is particularly difficult to diagnose TB infection due to the small number of TB bacteria the person is infected with, as well as the poor performance of the available tests (skin reaction and blood-based tests) used to diagnose TB infection. Only a small proportion (<10%) of people infected with TB will develop TB disease in their lifetime (active TB). TB of the lungs (pulmonary TB) is the most common form of TB occurring in approximately 80% of cases and those with a compromised immune systemt, wo mazy be HIV-infected, diabetics, receiving cancer drugs or infants, are especially prone to develop TB disease. As the TB disease progresses, the person will start developing symptoms. Initially the person will cough up only a small number of TB bacteria making early TB disease particularly difficult to diagnose. On average, the time the TB diseases flares up (reactivates) to the time a diagnosis of TB disease is made can be about 6 weeks even when modern diagnostic test are used.
Over time, as the TB disease progresses in the lungs, the number of TB bacteria coughed up in the sputum (lung phlegm) increases exponentially. In a person with advanced disease it is estimated that up to 1010 TB bacteria per ml of sputum are coughed up making such a person highly infectious. During this phase the diagnosis of TB is easier to confirm.
The TB bacteria can then spread from the lungs through the body and this ‘disseminated’ TB disease can develop in any organs. TB in organs outside the lung, extra-pulmmonary TB, is particularly difficult to diagnose as the sputum of the infected person may no longer contain TB bacteria.
The limitations of the old TB tests
Some of the most commonly used and familiar diagnostic tests using chest X-rays and or growing the bacterium in culture, are more than 100 years old. Although changes seen on a chest X-ray might suggest TB disease, these changes do not prove that the patient has TB disease or give an indication if the TB bacteria are resistant to the commonly used anti-TB antibiotics. Although the culture of TB bacteria from the sputum of a person with TB disease is an accurate diagnostic test, it also has a numerous weaknesses. TB culture is expensive and can take up to 6 weeks before it is known to be positive but once the bacteria have been grown in culture it can then be tested for resistance top various drugs. This is not acceptable as the disease will advance during the delay and the person will continue spreading TB in their household and community. In patients with severe suppression of their immunity, including people infected with HIV-infected persons the TB disease may spread so rapidly that the patient may die while waiting for their test result. The low sensitivity of chest X-rays and TB culture tests leads to the need to treat ‘presumptively’. Presumptive TB is diagnosed when on assessing the signs and symptoms of TB, night sweats, sudden weight loss, persistant coughing or blood in the sputum, the doctor feels that the diagnosis of TB disease is highly likely even though there is no definitive proof that the patient has TB disease. The diagnosis is based on a risk benefit analysis when the risks of harm from the unnecessary use of the TB drugs are outweighed by the risk of not treating actual TB disease. The problem with this approach is that a high proportion of patients are unnecessarily treated for TB; estimated to be between 20% to 40% and this is no small matter as the anti-TB drugs have to be taken for 6 months with have numerous unpleasant side effects.
Even with Xpert we are not there yet!
It is evident that new diagnostic tests are required that can rapidly, within minutes or hours, diagnose TB disease. The test should be widely available, preferably in the clinic, be accurate and able to determine the TB bacteria’s sensitivity to the available anti-TB antibiotics. The tests most likely to meet these requirements are based on the molecular analysis of the TB bacterium genes. The most promising of the new tests is geneXpert MTB/RIF often referred to as just Xpert. This is a molecular test, using modern DNA technology to detect the presence of TB bacterium in the sputum. The system is easy to use and can be performed in a basic laboratory. Xpert has a detection sensitivity that is similar to the six week TB culture methods but has one major advantage – namely that the results are available within 2 hours of starting the test. In addition the Xpert also gives the physician an indication whether the TB bacteria are sensitive or resistant to the commonly used anti-TB antibiotics preventing patients with resistant TB being started on incorrect treatment. The limitations of Xpert are that it is expensive, costing about US$ 100 per test, needs a small laboratory with a constant electrical supply and may not diagnose extra-pulmonary TB. For these reasons Xpertd is still not available in every clinic and ways need to be found to make this technology more widely available. Xpert is of limited value in children and patients with advanced HIV as they cough up a small number of TB bacteria below Xpert’s detection threshold but new machines, Xpert Ultra, with a lower detection threshold have been developed and are being field tested at present.
What would be the ideal TB diagnostic test?
Although Xpert has resulted in improved diagnosis of TB disease it is still far from the ideal diagnostic test. To make a difference we need diagnostic tests, available in all clinics, that are simple to perform on samples that are easy to collect from all patients including infants and children. Tests that depend on difficult to obtain samples will be of limited value. Babies and young children cannot cough up phlegm that is easily collected. At present stomach washings (gastric aspirates) or samples by sucking the phlegm from the back of the throat (induced sputum) are commonly collected to diagnose TB disease in children. However, these tests are invasive and unpleasant for both the child and the nurse performing the test. For this reason new tests must be able to analyse easy-to-collect samples sucxh as saliva, stools, urine or a drop of blood.
Tests to distinguish between TB infection and TB disease
A test that could differentiate between TB infection and TB disease would be of great value. If it were possible to accurately diagnose people infected with TB, we would be able to cure people more quickly and limit transmission to others. Recent studies have shown that TB infection can be successfully treated with 12 doses of antibiotics, taken weekly, with minimal side effects. This would be a major step forward in eliminating TB. Another approach would be a vaccine which could prevent a person from developing either TB infection and/or disease. Unluckily after numerous attempts it is estimated that an effective vaccine will not be freely available in the next 20 years.
Tests to predict the response to therapy
The flipside of diagnostics, using much the same biological and engineering ideas, is monitoring of ‘treatment response’ by quantitatively checking the progress of treatment. It is increasingly clear that not all patients being treated for TB require a 6 month course of treatment and tests that predict the patient’s response to therapy would be of great value. Patients with a favourable response could be treated with a shortened course while those with a poor response would require prolonged therapy. This would prevent patients not only from taking unnecessary therapy but also reduced the risk of developing unwanted side effects from the treatment.
The goal of the World Health Organization is to eliminate TB by 2050. To be able to achieve this goal we need new point of care diagnostic tests, to be able to accurately distinguish between TB infection and TB disease and have tests which accurately predict cure. We do not only need new diagnostics but also new and more powerful anti-TB antibiotics.
Insufficient tuberculosis (TB) case finding constitutes a major barrier to effective TB control. Despite considerable progress in improving healthcare service availability and accessibility, many people worldwide who fall ill with TB have no access to quality care, particularly in countries with a high disease burden. For example, in 2016, a total of 6.3 million TB cases were reported to national TB control programmes (NTPs) worldwide, leaving a case detection gap of nearly 40% (an estimated 10.4 million people had TB that year) (1). Increasing efforts to close this enormous gap will be crucial in the forthcoming years to effectively reduce TB incidence and mortality worldwide. This article describes opportunities, current challenges and open questions towards intensifying TB case finding.
Failure to find TB – consequences to individuals and populations
Failure to timely identify and treat TB has serious implications for affected individuals, their families, and entire populations. Progressive undiagnosed disease is likely to result in severe, chronic or recurring illness, disability and loss in quality of life. Chronic or recurring disease also leads to inability to work and loss of income, causing poverty and catastrophic costs to individuals and their families (2). Ultimately, not finding and treating TB leads to loss of lives. Historical studies from the pre-chemotherapy (and pre-HIV) era show that 50% of individuals with untreated TB died within five years; of those who survived, more than one-third continued to suffer from infectious TB (3). Ten-year case fatality rates of untreated TB between 53 and 86% have been reported among smear-positive, HIV-uninfected people, with an average duration between disease onset and either natural recovery or death of approximately three years (4). A high mortality of untreated TB is expected among people living with HIV infection, with an estimated average survival time of less than six months (4) compared to an average duration to either self-cure or death of 3 years among HIV-uninfected people (4)
Delayed and insufficient TB case finding increases potential for onward transmission (5). Prevalence studies from several high burden communities in Southern African have documented large burdens of undetected TB (6-8). Individuals who fall ill with TB may live in a community for a long time before being detected and treated: for example, durations of infectiousness before diagnosis of up to 2 years have been estimated in Zimbabwe (9). This prolonged and undetected infectious TB increases population-wide transmission, undermining the impact of treatment programs on local disease epidemiology.
Opportunities for intensifying TB case finding
TB control programs worldwide traditionally rely on passive case finding (PCF), i.e. the self-presentation of symptomatic individuals (“presumptive cases”) to health services to be diagnosed with TB. The World Health Organization (WHO) advocates the use of because actively searching for TB cases was deemed “prohibitively expensive” (10) while its impact on transmission was uncertain. An important limitation of PCF is that it relies on TB-specific symptoms (including cough for at least 2 weeks, fever, night sweats, weight loss) to be recognized (and reported) before individuals seek care and are evaluated for TB. Furthermore, low sensitivity and specificity of symptoms for active TB and under-recognition/under-reporting of symptoms poses a common barrier to timely diagnosis (11). Given the enormous case finding gap, there is consensus across the WHO and its partners that additional efforts are needed to promptly find, diagnose and treat TB to reduce morbidity, mortality and transmission.
Several promising opportunities exist that can help to intensify case finding in populations where PCF alone remains insufficient. The literature commonly distinguishes enhanced case finding (ECF), which aims at promoting self-presentation and diagnosis of presumptive TB cases, from active case finding (ACF), which describes efforts to actively reach out to seek and diagnose TB in the population. Often used synonymously with ACF is the term “systematic screening for TB” which the WHO defines as “the systematic identification of people with suspected active TB, in a predetermined target group, using tests, examinations or other procedures that can be applied rapidly” (12).
The target group of intensified TB case finding activities can be meaningfully distinguished by whether individuals are already seeking healthcare for any complaints, including those who had been in contact with TB-specific services, and those who have not yet (or may never) access healthcare services. We describe four principal categories (Figure 1) of interventions to intensify TB case finding in populations that address several shortcomings of PCF approaches.
Enhancing TB case finding in people who have not yet accessed (and may never access) healthcare. Improving access to TB care has always been a fundamental principle of the former and current global TB control strategies endorsed by the WHO. Besides making TB healthcare services more widely available, efforts are needed to promote healthcare seeking among presumptive TB cases who have not yet accessed healthcare.
Efforts to date have focussed on improving knowledge and awareness of TB and its characteristic symptoms (13) in populations and particularly in high-risk groups. However, an important challenge to these types of ECF activities is the fact that symptoms during TB may not always be specific or easily recognisable. Furthermore, several community-based case finding studies and TB prevalence surveys have documented considerable proportions of TB cases who did not report typical symptoms or no symptoms at all (12, 14), thus limiting the potential of raising symptom awareness to enhance case finding. This increases the need for diagnostics that can accurately rule-out TB in patients with few or minimal symptoms (see below). Closely related to improving knowledge and attitudes about TB, is the importance of reducing stigma through education and public health campaigns, which can also be used to offer individuals opportunities for diagnostic testing. Such campaigns aim at ensuring that case finding interventions gain community acceptance (15). Furthermore, to facilitate access to TB diagnosis and care, existing barriers for accessing TB services such as lengthy times (distances) and costs incurred by people need to be addressed (16). Combined interventions to raise awareness and facilitate access have been investigated. For example, a recent large community-randomised controlled trial in South Africa and Zambia combined community and school education and mobilization campaigns with enhancing access to sputum testing via mobile sputum collection points and open laboratory access to enhance TB case finding in high-burden communities, unfortunately without demonstrating an impact of ECF on local TB epidemiology (17).
Enhancing TB case finding and linkage to TB care in people who are seeking healthcare More recently, there is increasing recognition of the urgent need to find additional TB cases among people who are already seeking (or currently in) healthcare. Studies from high-incidence settings have documented high rates of (unsuspected) TB among individuals entering and exiting healthcare facilities (11) and poor adherence to screening algorithms by clinic staff (18). Interventions to enhance case finding include health education for people attending care and raising awareness among healthcare providers (practitioners) to encourage them to consider TB and refer presumptive cases to TB healthcare services. ECF strategies may focus on appropriate triages of symptomatic individuals in healthcare facilities to ensure timely diagnosis. Strengthening collaboration between (non-TB) public and private providers and the TB control program may help to shorten patients’ diagnostic journeys (20) and ensure timely TB diagnosis. Strengthening collaboration between disease-specific services and programs, for example between HIV- , diabetes- and TB healthcare services, whilst minimizing the additional health seeking burden on patients could help enhance TB case finding. Of particular importance are efforts to ensure timely linkage to TB care among patients who were diagnosed outside TB healthcare services. Towards this aim, strengthening TB recording and reporting among providers outside the NTPs as well as unified data systems can be useful. Although efforts to ensure timely treatment initiation among already diagnosed TB cases do not directly count towards case finding efforts, they may help prevent initial loss to follow-up (and hence transmission) and are thus able to reduce the gap between incident TB cases and those who are reported to NTPs and initiate treatment. For example, a recent study from South Africa estimated that people already seeking TB care contribute considerably to missing cases in the country due to loss to follow-up before treatment initiation, suggesting opportunities for interventions to reduce this initial loss (21).
Active TB case finding in high-risk groups (systematic screening for active TB)\ ACF is expected to shorten the time that people with TB remain undetected in communities and thereby pose a risk of infection to others (6). The development of effective and cost-effective ACF strategies is an important priority. The WHO promotes systematic screening for active TB and defines several risk groups that may be considered as target groups for screening (12), including groups in the community, in healthcare facilities, in residential institutions, immigration and refugee services, and workplaces (Table 1). Strong recommendations for systematic TB screening are currently limited to household contacts and close contacts of TB cases, people living with HIV (at each visit to a health facility), and current and former workers with silica dust exposure, whereas recommendations of screening in other risk groups remain conditional (12). The WHO advises that, before systematic screenings are considered, sufficient capacity for high-quality diagnosis, treatment and support must be available to match the anticipated increase in the number of cases detected. A rigorous assessment of the feasibility and acceptability of identifying, reaching and screening target group members must be made, as well as of the potential individual-level benefits, risks and costs associated with screenings. Furthermore, cost-effectiveness (cost benefits) at the population (health system) level must be considered (12).
Better TB diagnostic tests and algorithms. Intensifying case finding requires efforts to improve current diagnostic tests and algorithms. Individuals with undiagnosed TB often perceive few characteristic symptoms. These individuals may be less likely to go to clinics to be diagnosed and treated, presumably because they do not yet feel sufficiently unwell; they may harbour low concentrations of bacilli and be unable to expectorate sputum (the main material used for current TB diagnostic tests) (22). Community-based interventions to find TB cases pro-actively may address some of these challenges, however, the technology to accomplish this is only starting to emerge and is yet to mature. Rapid tests like Xpert MTB/RIF Ultra, which may potentially approach sensitivity rates of culture (23) and which can be combined with the portable GeneXpert OMNI platform are promising, but need evidence of their utility to justify their expense. Importantly, tests like Ultra may have advantages over previous generation tests like Xpert MTB/RIF, which misses most cases of TB in patients with few symptoms. The only true point-of-care test (urine LAM) unfortunately has very low sensitivity in detecting TB among individuals who did not yet seek care. Thus, while these tools may be useful for enhanced case finding among symptomatic individuals, few rapid tools are currently available for ACF. Culture, coupled with mechanisms to ensure positive patients start and complete treatment, probably remains the most useful test for ACF. Thus, whether high risk community members have symptoms or not, could be used to decide if they get Xpert Ultra or culture as the delayed time to diagnosis resulting from use of culture is likely easier to tolerate in people without or with few symptoms.
Challenges and open questions
TB control programs worldwide need to address and tackle gaps in case finding to make considerable progress in TB control. We have emphasised four categories of interventions that national and local TB control programs may consider to intensify case finding. The choice of suitable interventions is thus dependent on the prevailing local context. There is also interdependency of the effect of interventions in each of the four categories. For example, the necessity for (and the effect of) ACF will depend on the extent to which ECF activities are successful to reduce case finding delay in a setting. Furthermore, the effect of both ECF and ACF is dependent on the availability of sensitive and rapid diagnostic tests.
For any intervention to intensify case finding, in particular for systematic screening, choosing the right target group is challenging. For benefits to accrue from systematic screening, the target group must be at high risk of incident (and/or death from) TB. There should be at least suspicion that TB is underdiagnosed, or that there is considerable diagnostic delay. Target groups must be easily identifiable and reachable in populations, and screenings must be acceptable for target group members and their families. For benefits of systematic screening to extend to the population-level, the target group must be at high-risk but also contribute significantly to the overall prevalent TB burden and associated onward transmission. While the contribution of a specific high-risk group to overall TB can be estimated from TB prevalence surveys, knowledge about its contribution to transmission can be challenging to obtain.
The particular aim of a screening intervention should be considered. For example, a screening strategy may focus specifically on reducing mortality among severely ill (HIV co-infected) TB patients, whereas another screening strategy may aim at identifying as many TB cases as possible in order to impact transmission in a community.
The incremental benefits of intensifying TB case finding (relative to PCF alone) in settings may also change over time if the pool of undetected cases in a target group is eventually depleted, or if the rate of PCF changes over time. Temporary or periodic use of intensified case finding interventions might therefore be more reasonable than their indefinite use. Alternatively, dynamic case-finding policies may be considered, which allow decision makers to use easily observable indicators of TB surveillance, such as TB case notifications or screening yield over time, to determine when to make use of intensified case finding in addition to PCF in order to make more efficient use of existing resources (24). Mathematical modelling suggests that these dynamic case-finding policies dominate static policies that pre-specified the frequency and duration of case finding interventions irrespective of the current state and course of the TB epidemic (24).
Development and roll-out of better diagnostic tests is an important task for the international community to be able to intensify TB case finding worldwide. For screening, a rapid in-field test with high sensitivity for TB would be desirable to pre-select presumptive TB cases in the communities, so that the number of patients to be screened using more expensive tests (e.g., Xpert MTB/RIF Ultra) can be reduced. An advantage of such a triage test would be to identify patients with a high suspicion of TB at an earlier, asymptomatic stage and reduce our dependency of symptom-based diagnoses. Ideally, such a test should not depend on the use of sputa which is infectious and not always produced by patients, especially those with few symptoms, simple so that it does not require significant infrastructure or technical skills, potentially re-useable, and should ensure that people who test negative have a negligible probability of developing active disease. Promising candidates include blood-based host signatures (currently being refined into point-of-care tests) (25), breath volatile organic compound tests (26), and new approaches to detecting known biomarkers like LAM (27) but all. new tests need to satisfy the WHO’s target product profile for triage tests (28). Importantly, as tests get more analytically sensitive, they could detect remnants of prior TB disease as patients with a history of TB make up large proportions of communities in some settings and confirmatory testing should therefore be mandatory (29). Unfortunately, nothing in the diagnostic pipeline suggests that we are close to a test that, on its own, meets all these criteria for ACF purposes and can simultaneously rule-in and rule-out disease with high confidence. Thus, when new tools become available, we need to carefully select the specific patient contexts in which they are used and design setting-specific algorithms. The diagnostic yield of any ACF strategy will be the primary determinant of its effectiveness.
Although various studies of TB case finding have been conducted, there is a lack of research to evaluate the individual and community-level benefits of suitable interventions in different contexts (30) as well as the feasibility and acceptability of different case finding interventions in different populations or target groups. A particular challenge is the assessment of population-level effects of intensified case finding, which requires complex and large investigations. Suitable study designs include cluster-randomised controlled trials, which measure outcomes of case finding interventions in intervention clusters compared to control clusters. Stepped-wedge cluster-randomised designs involve a random cross over of clusters from control to intervention until all clusters are in the intervention. Other possible designs include quasi-experimental studies that compare outcome measures in a population before and after the case-finding intervention is implemented, and non-randomized comparisons. The latter two designs are vulnerable to confounding, including possible baseline trends of passive case finding over time. Cost-effectiveness (cost-benefit) analyses, in which epidemiological effects are related to costs are needed to identify most suitable case finding strategies. Transmission-dynamic mathematical models can help project population-level effects and cost-effectiveness of interventions to intensify case finding and thus guide their design and implementation in different populations (31, 32). Operational and qualitative research should accompany implemented interventions to enable lessons about their feasibility, acceptability, performance and scalability.
In conclusion, the need for intensifying TB case finding to strengthen the fight against TB has been widely recognized. Alternatives to the current passive case finding approach exist, including enhanced TB case finding strategies among people not (yet) seeking care and those already attending health services. Active TB case finding (systematic screening) should be considered for population subgroups that are identifiable, reachable, and at high risk of TB morbidity and mortality. In high-burden settings, TB case finding interventions in subgroups that contribute considerably to the overall (prevalent) TB burden and associated onward transmission are of particular interest. Innovation is needed to identify successful case-finding strategies in different local contexts and to develop novel diagnostic technologies for rapid triage in the field. Careful consideration of individual and community-level benefits (and harms) as well as costs and cost-benefits of different interventions is required to identify most feasible, (cost-) effective, and scalable strategies. More research, including trials of case-finding, cost-effectiveness analyses, mathematical models, operational and qualitative studies, and diagnostic research, will be required to inform intensified TB case finding in the future.
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