Quantifying non-adherence to anti-tuberculosis treatment due to early discontinuation: a systematic literature review of timings to loss to follow-up.

BACKGROUND: The burden of non-adherence to anti-tuberculosis (TB) treatment is poorly understood. One type is early discontinuation, that is, stopping treatment early. Given the implications of early discontinuation for treatment outcomes, we undertook a systematic review to estimate its burden, using the timing of loss to follow-up (LFU) as a proxy measure. METHODS: Web of Science, Embase and Medline were searched up to 14 January 2021 using terms covering LFU, TB and treatment. Studies of adults (≥ 18 years) on the standard regimen for drug-sensitive TB reporting the timing of LFU (WHO definition) were included. A narrative synthesis was conducted and quality assessment undertaken using an adapted version of Downs and Black. Papers were grouped by the percentage of those who were ultimately LFU who were LFU by 2 months. Three groups were created: <28.3% LFU by 2 months, ≥28.3-<38.3%, ≥38.3%). The percentage of dose-months missed due to early discontinuation among (1) those LFU, and (2) all patients was calculated. RESULTS: We found 40 relevant studies from 21 countries. The timing of LFU was variable within and between countries. 36/40 papers (90.0%) reported the percentage of patients LFU by the end of 2 months. 31/36 studies (86.1%) reported a higher than or as expected percentage of patients becoming LFU by 2 months. The percentage of dose-months missed by patients who became LFU ranged between 37% and 77% (equivalent to 2.2-4.6 months). Among all patients, the percentage of dose-months missed ranged between 1% and 22% (equivalent to 0.1-1.3 months). CONCLUSIONS: A larger than expected percentage of patients became LFU within the first 2 months of treatment. These patients missed high percentages of dose months of treatment due to early discontinuation. Interventions to promote adherence and retain patients in care must not neglect the early months of treatment. PROSPERO REGISTRATION NUMBER: CRD42021218636.

No action is without its side effects: Adverse drug reactions and missed doses of antituberculosis therapy, a scoping review.

AIMS: A key reason for the failure of antituberculosis (anti-TB) treatment is missed doses (instances where medication is not taken). Adverse drug reactions (ADRs) are 1 cause of missed doses, but the global evidence, their relative contribution to missed doses vs. other causes, the patterns of missed doses due to ADRs and the specific ADRs associated with missed doses have not been appraised. We sought to address these questions through a scoping review. METHODS: MEDLINE, Embase and Web of Science were searched on 3 November 2021 using terms around active TB, missed doses and treatment challenges. Studies reporting both ADR and missed dose data were examined (PROSPERO: CRD42022295209). RESULTS: Searches identified 108 eligible studies: 88/108 (81%) studies associated ADRs with an increase in missed doses; 33/61 (54%) studies documenting the reasons for missed doses gave ADRs as a primary reason. No studies examined patterns of missed doses due to ADRs; 41/108 (38%) studies examined associations between 68 types of ADR (across 15 organ systems) and missed doses. Nuance around ADR-missed doses relations regarding drug susceptibility testing profile and whether the missed doses originated from the patient, healthcare professionals, or both were found. CONCLUSION: There is extensive evidence that ADRs are a key driver for missed doses of anti-TB treatment. Some papers examined specific ADRs and none evaluated the patterns of missed doses due to ADRs, demonstrating a knowledge deficit. Knowing why doses both are and are not missed is essential in providing targeted interventions to improve treatment outcomes.

Recent advances in the treatment of tuberculosis.

BACKGROUND: Tuberculosis (TB) is a global health challenge and one of the leading causes of death worldwide. In the last decade, the TB treatment landscape has dramatically changed. After long years of stagnation, new compounds entered the market (bedaquiline, delamanid, and pretomanid) and phase III clinical trials have shown promising results towards shortening duration of treatment for both drug-susceptible (Study 31/A5349, TRUNCATE-TB, and SHINE) and drug-resistant TB (STREAM, NiX-TB, ZeNix, and TB-PRACTECAL). Dose optimization of rifamycins and repurposed drugs has also brought hopes of further development of safe and effective regimens. Consequently, international and WHO clinical guidelines have been updated multiple times in the last years to keep pace with these advances. OBJECTIVES: This narrative review aims to summarize the state-of-the-art on treatment of drug-susceptible and drug-resistant TB, as well as recent trial results and an overview of ongoing clinical trials. SOURCES: A non-systematic literature review was conducted in PubMed and MEDLINE, focusing on the treatment of TB. Ongoing clinical trials were listed according to the authors' knowledge and completed consulting clinicaltrials.gov and other publicly available websites (www.resisttb.org/clinical-trials-progress-report, www.newtbdrugs.org/pipeline/trials). CONTENT: This review summarizes the recent, major changes in the landscape for drug-susceptible and drug-resistant treatment, with a specific focus on their potential impact on patient outcomes and programmatic TB management. Moreover, insights in host-directed therapies, and advances in pharmacokinetics and pharmacogenomics are discussed. A thorough outline of ongoing therapeutic clinical trials is presented, highlighting different approaches and goals in current TB clinical research. IMPLICATIONS: Future research should be directed to individualize regimens and protect these recent breakthroughs by preventing and identifying the selection of drug resistance and providing widespread, affordable, patient-centred access to new treatment options for all people affected by TB.

Students' and staffs' views and experiences of asymptomatic testing on a university campus during the COVID-19 pandemic in Scotland: a mixed methods study.

OBJECTIVES: To explore the acceptability of regular asymptomatic testing for SARS-CoV-2 on a university campus using saliva sampling for PCR analysis and the barriers and facilitators to participation. DESIGN: Cross-sectional surveys and qualitative semistructured interviews. SETTING: Edinburgh, Scotland. PARTICIPANTS: University staff and students who had registered for the testing programme (TestEd) and provided at least one sample. RESULTS: 522 participants completed a pilot survey in April 2021 and 1750 completed the main survey (November 2021). 48 staff and students who consented to be contacted for interview took part in the qualitative research. Participants were positive about their experience with TestEd with 94% describing it as 'excellent' or 'good'. Facilitators to participation included multiple testing sites on campus, ease of providing saliva samples compared with nasopharyngeal swabs, perceived accuracy compared with lateral flow devices (LFDs) and reassurance of test availability while working or studying on campus. Barriers included concerns about privacy while testing, time to and methods of receiving results compared with LFDs and concerns about insufficient uptake in the university community. There was little evidence that the availability of testing on campus changed the behaviour of participants during a period when COVID-19 restrictions were in place. CONCLUSIONS: The provision of free asymptomatic testing for COVID-19 on a university campus was welcomed by participants and the use of saliva-based PCR testing was regarded as more comfortable and accurate than LFDs. Convenience is a key facilitator of participation in regular asymptomatic testing programmes. Availability of testing did not appear to undermine engagement with public health guidelines.

Mendelian randomisation identifies priority groups for prophylactic EBV vaccination.

BACKGROUND: Epstein Barr virus (EBV) infects ~ 95% of the population worldwide and is known to cause adverse health outcomes such as Hodgkin's, non-Hodgkin's lymphomas, and multiple sclerosis. There is substantial interest and investment in developing infection-preventing vaccines for EBV. To effectively deploy such vaccines, it is vital that we understand the risk factors for infection. Why particular individuals do not become infected is currently unknown. The current literature, describes complex, often conflicting webs of intersecting factors-sociodemographic, clinical, genetic, environmental-, rendering causality difficult to decipher. We aimed to use Mendelian randomization (MR) to overcome the issues posed by confounding and reverse causality to determine the causal risk factors for the acquisition of EBV. METHODS: We mapped the complex evidence from the literature prior to this study factors associated with EBV serostatus (as a proxy for infection) into a causal diagram to determine putative risk factors for our study. Using data from the UK Biobank of 8422 individuals genomically deemed to be of white British ancestry between the ages of 40 and 69 at recruitment between the years 2006 and 2010, we performed a genome wide association study (GWAS) of EBV serostatus, followed by a Two Sample MR to determine which putative risk factors were causal. RESULTS: Our GWAS identified two novel loci associated with EBV serostatus. In MR analyses, we confirmed shorter time in education, an increase in number of sexual partners, and a lower age of smoking commencement, to be causal risk factors for EBV serostatus. CONCLUSIONS: Given the current interest and likelihood of a future EBV vaccine, these factors can inform vaccine development and deployment strategies by completing the puzzle of causality. Knowing these risk factors allows identification of those most likely to acquire EBV, giving insight into what age to vaccinate and who to prioritise when a vaccine is introduced.

Forgiveness Is the Attribute of the Strong: Nonadherence and Regimen Shortening in Drug-sensitive Tuberculosis.

Rationale: "Forgiveness" charts the ability of a drug or regimen to withstand nonadherence without negative clinical consequences. Objectives: We aimed to determine the influence of regimen length, regimen drugs, and dosing, and when during treatment nonadherence occurs on the forgiveness of antituberculosis regimens. Methods: Using data from three randomized controlled trials comparing experimental 4-month regimens for drug-sensitive tuberculosis with the standard 6-month regimen, we used generalized linear models to examine how the risk of a negative composite outcome changed as dose-taking decreased. The percentage of doses taken and the absolute number of doses missed were calculated during the intensive and continuation phases of treatment, and overall. A mediation analysis was undertaken to determine how much the association between intensive phase dose-taking and the negative composite outcome was mediated through continuation phase dose-taking. Measurements and Main Results: Forgiveness of the 4- and 6-month regimens did not differ for any treatment period. Importantly, 4-month regimens were no less forgiving of small numbers of absolute missed doses than the 6-month regimen (e.g., for 3-7 missed doses vs. no missed doses [baseline], 6-month regimen adjusted risk ratio 1.65 [95% confidence interval, 0.80-3.41] and 4-month regimens 1.80 [1.33-2.45]). No 4-month regimen was conclusively more forgiving than another. We found evidence of mediation by continuation phase dose-taking on the intensive phase dose-taking and negative composite outcome relationship. Conclusions: With the current appetite for, and progress toward, shorter drug-sensitive tuberculosis regimens worldwide, we offer reassurance that shorter regimens are not necessarily less forgiving of nonadherence. Given the importance of continuation phase adherence, patient support during this period should not be neglected.

The cascade of care for latent tuberculosis infection in congregate settings: A national cohort analysis, Korea, 2017-2018.

Background: In 2017, Korea implemented a nationwide project to screen and treat latent tuberculosis infection (LTBI) in high-risk for transmission public congregate settings. We aimed to assess programme success using a cascade of care framework. Materials and methods: We undertook a cohort study of people from three congregate settings screened between March 2017 and December 2018: (1) first-grade high school students, (2) employees of educational institutions, (3) employees of social welfare facilities. We report percentages of participants with LTBI completing each step in the cascade of care model. Poisson regression models were used to determine factors associated with not visiting clinics, not initiating treatment, and not completing treatment. Results: Among the 96,439 participants who had a positive interferon-gamma release assay result, the percentage visiting clinics for further assessment, to initiate treatment, and who then completed treatment were 50.7, 34.7, and 28.9%, respectively. Compared to those aged 20-34 years, individuals aged < 20 years and aged ≥ 65 years were less likely to visit clinics, though more likely to complete treatment once initiated. Using public health centres rather than private hospitals was associated with people "not initiating treatment" (adjusted risk ratio [aRR], 3.72; 95% confidence interval [CI], 3.95-3.86). Nine-month isoniazid monotherapy therapy was associated with "not completing treatment," compared to 3-month isoniazid and rifampin therapy (aRR, 1.28; 95% CI, 1.16-1.41). Conclusion: Among participants with LTBI from three congregate settings, less than one third completed treatment. Age, treatment centre, and initial regimen were important determinants of losses to care through the cascade.

Hidden loss to follow-up among tuberculosis patients managed by public-private mix institutions in South Korea.

In South Korea, public-private mix (PPM) was launched in 2011. This retrospective cohort study sought to determine the rate of loss to follow-up (LTFU) among drug-susceptible tuberculosis (DS-TB) patients in all nationwide PPM institutions, and the risk factors for LTFU. National notification data for DS-TB patients diagnosed between August 2011 and July 2014 in PPM institutions were analysed. Determination of LTFU included detection of instances where patients were transferred out, but when they did not attend at other TB centres in the following two months. Univariable and multivariable competing risk models were used to determine risk factors for LTFU. 73,046 patients with 78,485 records were enrolled. Nominally, 3426 (4.4%) of records were LTFU. However, after linking the multiple records in each patient, the percentage of LTFU was 12.3% (9004/73,046). Risk factors for LTFU were: being foreign-born (3.13 (95% CI 2.77-3.53)), prior LTFU (2.31 (2.06-2.59)) and greater distance between the patient's home and the TB centre (4.27 (4.03-4.53)). 'Transfer-out' was a risk factor in patients managed by treatment centres close to home (1.65 (1.49-1.83)), but protective for those attending centres further (0.77 (0.66-0.89)) or far-away (0.52 (0.46-0.59)) from home. By considering the complete picture of a patient's interactions with healthcare, we identified a much higher level of LTFU than previously documented. This has implications for how outcomes of treatment are reported and argues for a joined-up national approach for the management and surveillance of TB patients, in nations with similar healthcare systems.

Knowledge, Attitudes, and Behavior Related to COVID-19 Testing: A Rapid Scoping Review.

Testing programs for COVID-19 depend on the voluntary actions of members of the public for their success. Understanding people's knowledge, attitudes, and behavior related to COVID-19 testing is, therefore, key to the design of effective testing programs worldwide. This paper reports on the findings of a rapid scoping review to map the extent, characteristics, and scope of social science research on COVID-19 testing and identifies key themes from the literature. Main findings include the discoveries that people are largely accepting of testing technologies and guidelines and that a sense of social solidarity is a key motivator of testing uptake. The main barriers to accessing and undertaking testing include uncertainty about eligibility and how to access tests, difficulty interpreting symptoms, logistical issues including transport to and from test sites and the discomfort of sample extraction, and concerns about the consequences of a positive result. The review found that existing research was limited in depth and scope. More research employing longitudinal and qualitative methods based in under-resourced settings and examining intersections between testing and experiences of social, political, and economic vulnerability is needed. Last, the findings of this review suggest that testing should be understood as a social process that is inseparable from processes of contact tracing and isolation and is embedded in people's everyday routines, livelihoods and relationships.

Relational Dynamics of Treatment Behavior Among Individuals with Tuberculosis in High-Income Countries: A Scoping Review.

Although tuberculosis (TB) incidence has significantly declined in high-income, low-incidence (HILI) countries, challenges remain in managing TB in vulnerable populations who may struggle to stay on anti-TB treatment (ATT). Factors associated with non-adherence to ATT are well documented; however, adherence is often narrowly conceived as a fixed binary variable that places emphasis on individual agency and the act of taking medicines, rather than on the demands of being on treatment more broadly. Further, the mechanisms through which documented factors act upon the experience of being on treatment are poorly understood. Adopting a relational approach that emphasizes the embeddedness of individuals within dynamic social, structural, and health systems contexts, this scoping review aims to synthesize qualitative evidence on experiences of being on ATT and mechanisms through which socio-ecological factors influence adherence in HILI countries. Six electronic databases were searched for peer-reviewed literature published in English between January 1990 and May 2020. Additional studies were obtained by searching references of included studies. Narrative synthesis was used to analyze qualitative data extracted from included studies. Of 28 included studies, the majority (86%) reported on health systems factors, followed by personal characteristics (82%), structural influences (61%), social factors (57%), and treatment-related factors (50%). Included studies highlighted three points that underpin a relational approach to ATT behavior: 1) individual motivation and capacity to take ATT is dynamic and intertwined with, rather than separate from, social, health systems, and structural factors; 2) individuals' pre-existing experiences of health-seeking influence their views on treatment and their ability to commit to long-term regular medicine-taking; and 3) social, cultural, and political contexts play an important role in mediating how specific factors work to support or hinder ATT adherence behavior in different settings. Based on our analysis, we suggest that person-centered clinical management of tuberculosis should 1) acknowledge the ways in which ATT both disrupts and is managed within the everyday lives of individuals with TB; 2) appreciate that individuals' circumstances and the support and resources they can access may change over the course of treatment; and 3) display sensitivity towards context-specific social and cultural norms affecting individual and collective experiences of being on ATT.

Temporal trends and forecasting of COVID-19 hospitalisations and deaths in Scotland using a national real-time patient-level data platform: a statistical modelling study.

BACKGROUND: As the COVID-19 pandemic continues, national-level surveillance platforms with real-time individual person-level data are required to monitor and predict the epidemiological and clinical profile of COVID-19 and inform public health policy. We aimed to create a national dataset of patient-level data in Scotland to identify temporal trends and COVID-19 risk factors, and to develop a novel statistical prediction model to forecast COVID-19-related deaths and hospitalisations during the second wave. METHODS: We established a surveillance platform to monitor COVID-19 temporal trends using person-level primary care data (including age, sex, socioeconomic status, urban or rural residence, care home residence, and clinical risk factors) linked to data on SARS-CoV-2 RT-PCR tests, hospitalisations, and deaths for all individuals resident in Scotland who were registered with a general practice on Feb 23, 2020. A Cox proportional hazards model was used to estimate the association between clinical risk groups and time to hospitalisation and death. A survival prediction model derived from data from March 1 to June 23, 2020, was created to forecast hospital admissions and deaths from October to December, 2020. We fitted a generalised additive spline model to daily SARS-CoV-2 cases over the previous 10 weeks and used this to create a 28-day forecast of the number of daily cases. The age and risk group pattern of cases in the previous 3 weeks was then used to select a stratified sample of individuals from our cohort who had not previously tested positive, with future cases in each group sampled from a multinomial distribution. We then used their patient characteristics (including age, sex, comorbidities, and socioeconomic status) to predict their probability of hospitalisation or death. FINDINGS: Our cohort included 5 384 819 people, representing 98·6% of the entire estimated population residing in Scotland during 2020. Hospitalisation and death among those testing positive for SARS-CoV-2 between March 1 and June 23, 2020, were associated with several patient characteristics, including male sex (hospitalisation hazard ratio [HR] 1·47, 95% CI 1·38-1·57; death HR 1·62, 1·49-1·76) and various comorbidities, with the highest hospitalisation HR found for transplantation (4·53, 1·87-10·98) and the highest death HR for myoneural disease (2·33, 1·46-3·71). For those testing positive, there were decreasing temporal trends in hospitalisation and death rates. The proportion of positive tests among older age groups (>40 years) and those with at-risk comorbidities increased during October, 2020. On Nov 10, 2020, the projected number of hospitalisations for Dec 8, 2020 (28 days later) was 90 per day (95% prediction interval 55-125) and the projected number of deaths was 21 per day (12-29). INTERPRETATION: The estimated incidence of SARS-CoV-2 infection based on positive tests recorded in this unique data resource has provided forecasts of hospitalisation and death rates for the whole of Scotland. These findings were used by the Scottish Government to inform their response to reduce COVID-19-related morbidity and mortality. FUNDING: Medical Research Council, National Institute for Health Research Health Technology Assessment Programme, UK Research and Innovation Industrial Strategy Challenge Fund, Health Data Research UK, Scottish Government Director General Health and Social Care.

"You have to change your whole life": A qualitative study of the dynamics of treatment adherence among adults with tuberculosis in the United Kingdom.

Maintaining adherence to treatment for tuberculosis (TB) is essential if the disease is to be eliminated. As part of formative research to develop an intervention to improve adherence, we documented the lived experiences of adults receiving anti-TB treatment (ATT) in three UK cities and examined how personal, social, and structural circumstances interacted to impact on individuals' adherence to treatment. Using a topic guide that explored social circumstances and experiences of TB care, we conducted in-depth interviews with 18 adults (six women) who were being or had been treated for TB (patients) and four adults (all women) who were caring for a friend, relative, or partner being treated for TB (caregivers). We analysed transcripts using an adapted framework method that classified factors affecting adherence as personal, social, structural, health systems, or treatment-related. Eleven of 18 patients were born outside the UK (in South, Central, and East Asia, and Eastern and Southern Africa); among the seven who were UK-born, four were Black, Asian, or Minority Ethnic and three were White British. TB and its treatment were often disruptive: in addition to debilitating symptoms and side effects of ATT, participants faced job insecurity, unstable housing, stigma, social isolation, worsening mental health, and damaged relationships. Those who had a strong support network, stable employment, a routine that could easily be adapted, a trusting relationship with their TB team, and clear understanding of the need for treatment reported finding it easier to adhere to ATT. Changes in circumstances sometimes had dramatic effects on an individual's ability to take ATT; participants described how the impact of certain acute events (e.g., the onset of side effects or fatigue, episodes of stigmatisation, loss of income) were amplified by their timing or through their interaction with other elements of the individual's life. We suggest that the dynamic and fluctuating nature of these factors necessitates comprehensive and regular review of needs and potential problems, conducted before and during ATT; this, coupled with supportive measures that consider (and seek to mitigate) the influence of social and structural factors, may help improve adherence.

Real-time spatial health surveillance: Mapping the UK COVID-19 epidemic.

Introduction The COVID-19 pandemic has highlighted the need for robust data linkage systems and methods for identifying outbreaks of disease in near real-time. Objectives The primary objective of this study was to develop a real-time geospatial surveillance system to monitor the spread of COVID-19 across the UK. Methods Using self-reported app data and the Secure Anonymised Information Linkage (SAIL) Databank, we demonstrate the use of sophisticated spatial modelling for near-real-time prediction of COVID-19 prevalence at small-area resolution to inform strategic government policy areas. Results We demonstrate that using a combination of crowd-sourced app data and sophisticated geo-statistical techniques it is possible to predict hot spots of COVID-19 at fine geographic scales, nationally. We are also able to produce estimates of their precision, which is an important pre-requisite to an effective control strategy to guard against over-reaction to potentially spurious features of 'best guess' predictions. Conclusion In the UK, important emerging risk-factors such as social deprivation or ethnicity vary over small distances, hence risk needs to be modelled at fine spatial resolution to avoid aggregation bias. We demonstrate that existing geospatial statistical methods originally developed for global health applications are well-suited to this task and can be used in an anonymised databank environment, thus preserving the privacy of the individuals who contribute their data.

Measuring and reporting treatment adherence: What can we learn by comparing two respiratory conditions?

Medication non-adherence, defined as any deviation from the regimen recommended by their healthcare provider, can increase morbidity, mortality and side effects, while reducing effectiveness. Through studying two respiratory conditions, asthma and tuberculosis (TB), we thoroughly review the current understanding of the measurement and reporting of medication adherence. In this paper, we identify major methodological issues in the standard ways that adherence has been conceptualised, defined and studied in asthma and TB. Between and within the two diseases there are substantial variations in adherence reporting, linked to differences in dosing intervals and treatment duration. Critically, the communicable nature of TB has resulted in dose-by-dose monitoring becoming a recommended treatment standard. Through the lens of these similarities and contrasts, we highlight contemporary shortcomings in the generalised conceptualisation of medication adherence. Furthermore, we outline elements in which knowledge could be directly transferred from one condition to the other, such as the application of large-scale cost-effective monitoring methods in TB to resource-poor settings in asthma. To develop a more robust evidence-based approach, we recommend the use of standard taxonomies detailed in the ABC taxonomy when measuring and discussing adherence. Regimen and intervention development and use should be based on sufficient evidence of the commonality and type of adherence behaviours displayed by patients with the relevant condition. A systematic approach to the measurement and reporting of adherence could improve the value and generalisability of research across all health conditions.

All nonadherence is equal but is some more equal than others? Tuberculosis in the digital era.

Adherence to treatment for tuberculosis (TB) has been a concern for many decades, resulting in the World Health Organization's recommendation of the direct observation of treatment in the 1990s. Recent advances in digital adherence technologies (DATs) have renewed discussion on how to best address nonadherence, as well as offering important information on dose-by-dose adherence patterns and their variability between countries and settings. Previous studies have largely focussed on percentage thresholds to delineate sufficient adherence, but this is misleading and limited, given the complex and dynamic nature of adherence over the treatment course. Instead, we apply a standardised taxonomy - as adopted by the international adherence community - to dose-by-dose medication-taking data, which divides missed doses into 1) late/noninitiation (starting treatment later than expected/not starting), 2) discontinuation (ending treatment early), and 3) suboptimal implementation (intermittent missed doses). Using this taxonomy, we can consider the implications of different forms of nonadherence for intervention and regimen design. For example, can treatment regimens be adapted to increase the "forgiveness" of common patterns of suboptimal implementation to protect against treatment failure and the development of drug resistance? Is it reasonable to treat all missed doses of treatment as equally problematic and equally common when deploying DATs? Can DAT data be used to indicate the patients that need enhanced levels of support during their treatment course? Critically, we pinpoint key areas where knowledge regarding treatment adherence is sparse and impeding scientific progress.

Trade-offs between cost and accuracy in active case finding for tuberculosis: A dynamic modelling analysis.

BACKGROUND: Active case finding (ACF) may be valuable in tuberculosis (TB) control, but questions remain about its optimum implementation in different settings. For example, smear microscopy misses up to half of TB cases, yet is cheap and detects the most infectious TB cases. What, then, is the incremental value of using more sensitive and specific, yet more costly, tests such as Xpert MTB/RIF in ACF in a high-burden setting? METHODS AND FINDINGS: We constructed a dynamic transmission model of TB, calibrated to be consistent with an urban slum population in India. We applied this model to compare the potential cost and impact of 2 hypothetical approaches following initial symptom screening: (i) 'moderate accuracy' testing employing a microscopy-like test (i.e., lower cost but also lower accuracy) for bacteriological confirmation and (ii) 'high accuracy' testing employing an Xpert-like test (higher cost but also higher accuracy, while also detecting rifampicin resistance). Results suggest that ACF using a moderate-accuracy test could in fact cost more overall than using a high-accuracy test. Under an illustrative budget of US$20 million in a slum population of 2 million, high-accuracy testing would avert 1.14 (95% credible interval 0.75-1.99, with p = 0.28) cases relative to each case averted by moderate-accuracy testing. Test specificity is a key driver: High-accuracy testing would be significantly more impactful at the 5% significance level, as long as the high-accuracy test has specificity at least 3 percentage points greater than the moderate-accuracy test. Additional factors promoting the impact of high-accuracy testing are that (i) its ability to detect rifampicin resistance can lead to long-term cost savings in second-line treatment and (ii) its higher sensitivity contributes to the overall cases averted by ACF. Amongst the limitations of this study, our cost model has a narrow focus on the commodity costs of testing and treatment; our estimates should not be taken as indicative of the overall cost of ACF. There remains uncertainty about the true specificity of tests such as smear and Xpert-like tests in ACF, relating to the accuracy of the reference standard under such conditions. CONCLUSIONS: Our results suggest that cheaper diagnostics do not necessarily translate to less costly ACF, as any savings from the test cost can be strongly outweighed by factors including false-positive TB treatment, reduced sensitivity, and foregone savings in second-line treatment. In resource-limited settings, it is therefore important to take all of these factors into account when designing cost-effective strategies for ACF.

The impact of HIV infection on tuberculosis transmission in a country with low tuberculosis incidence: a national retrospective study using molecular epidemiology.

BACKGROUND: HIV is known to increase the likelihood of reactivation of latent tuberculosis to active TB disease; however, its impact on tuberculosis infectiousness and consequent transmission is unclear, particularly in low-incidence settings. METHODS: National surveillance data from England, Wales and Northern Ireland on tuberculosis cases in adults from 2010 to 2014, strain typed using 24-locus mycobacterial-interspersed-repetitive-units-variable-number-tandem-repeats was used retrospectively to identify clusters of tuberculosis cases, subdivided into 'first' and 'subsequent' cases. Firstly, we used zero-inflated Poisson regression models to examine the association between HIV status and the number of subsequent clustered cases (a surrogate for tuberculosis infectiousness) in a strain type cluster. Secondly, we used logistic regression to examine the association between HIV status and the likelihood of being a subsequent case in a cluster (a surrogate for recent acquisition of tuberculosis infection) compared to the first case or a non-clustered case (a surrogate for reactivation of latent infection). RESULTS: We included 18,864 strain-typed cases, 2238 were the first cases of clusters and 8471 were subsequent cases. Seven hundred and fifty-nine (4%) were HIV-positive. Outcome 1: HIV-positive pulmonary tuberculosis cases who were the first in a cluster had fewer subsequent cases associated with them (mean 0.6, multivariable incidence rate ratio [IRR] 0.75 [0.65-0.86]) than those HIV-negative (mean 1.1). Extra-pulmonary tuberculosis (EPTB) cases with HIV were less likely to be the first case in a cluster compared to HIV-negative EPTB cases. EPTB cases who were the first case had a higher mean number of subsequent cases (mean 2.5, IRR (3.62 [3.12-4.19]) than those HIV-negative (mean 0.6). Outcome 2: tuberculosis cases with HIV co-infection were less likely to be a subsequent case in a cluster (odds ratio 0.82 [0.69-0.98]), compared to being the first or a non-clustered case. CONCLUSIONS: Outcome 1: pulmonary tuberculosis-HIV patients were less infectious than those without HIV. EPTB patients with HIV who were the first case in a cluster had a higher number of subsequent cases and thus may be markers of other undetected cases, discoverable by contact investigations. Outcome 2: tuberculosis in HIV-positive individuals was more likely due to reactivation than recent infection, compared to those who were HIV-negative.

COVID-19 in Pregnancy in Scotland (COPS): protocol for an observational study using linked Scottish national data.

INTRODUCTION: The effects of SARS-CoV-2 in pregnancy are not fully delineated. We will describe the incidence of COVID-19 in pregnancy at population level in Scotland, in a prospective cohort study using linked data. We will determine associations between COVID-19 and adverse pregnancy, neonatal and maternal outcomes and the proportion of confirmed cases of SARS-CoV-2 infection in neonates associated with maternal COVID-19. METHODS AND ANALYSIS: Prospective cohort study using national linked data sets. We will include all women in Scotland, UK, who were pregnant on or became pregnant after, 1 March 2020 (the date of the first confirmed case of SARS-CoV-2 infection in Scotland) and all births in Scotland from 1 March 2020 onwards. Individual-level data will be extracted from data sets containing details of all livebirths, stillbirth, terminations of pregnancy and miscarriages and ectopic pregnancies treated in hospital or attending general practice. Records will be linked within the Early Pandemic Evaluation and Enhanced Surveillance of COVID-19 (EAVE II) platform, which includes primary care records, virology and serology results and details of COVID-19 Community Hubs and Assessment Centre contacts and deaths. We will perform analyses using definitions for confirmed, probable and possible COVID-19 and report serology results (where available). Outcomes will include congenital anomaly, miscarriage, stillbirth, termination of pregnancy, preterm birth, neonatal infection, severe maternal disease and maternal deaths. We will perform descriptive analyses and appropriate modelling, adjusting for demographic and pregnancy characteristics and the presence of comorbidities. The cohort will provide a platform for future studies of the effectiveness and safety of therapeutic interventions and immunisations for COVID-19 and their effects on childhood and developmental outcomes. ETHICS AND DISSEMINATION: COVID-19 in Pregnancy in Scotland is a substudy of EAVE II(, which has approval from the National Research Ethics Service Committee. Findings will be reported to Scottish Government, Public Health Scotland and published in peer-reviewed journals.