Tuberculosis (TB) Aftermath: study protocol for a hybrid type I effectiveness-implementation non-inferiority randomized trial in India comparing two active case finding (ACF) strategies among individuals treated for TB and their household contacts.

BACKGROUND: Approximately 7% of all reported tuberculosis (TB) cases each year are recurrent, occurring among people who have had TB in the recent or distant past. TB recurrence is particularly common in India, which has the largest TB burden worldwide. Although patients recently treated for TB are at high risk of developing TB again, evidence around effective active case finding (ACF) strategies in this population is scarce. We will conduct a hybrid type I effectiveness-implementation non-inferiority randomized trial to compare the effectiveness, cost-effectiveness, and feasibility of two ACF strategies among individuals who have completed TB treatment and their household contacts (HHCs). METHODS: We will enroll 1076 adults (≥ 18 years) who have completed TB treatment at a public TB unit (TU) in Pune, India, along with their HHCs (averaging two per patient, n = 2152). Participants will undergo symptom-based ACF by existing healthcare workers (HCWs) at 6-month intervals and will be randomized to either home-based ACF (HACF) or telephonic ACF (TACF). Symptomatic participants will undergo microbiologic testing through the program. Asymptomatic HHCs will be referred for TB preventive treatment (TPT) per national guidelines. The primary outcome is rate per 100 person-years of people diagnosed with new or recurrent TB by study arm, within 12 months following treatment completion. The secondary outcome is proportion of HHCs < 6 years, by study arm, initiated on TPT after ruling out TB disease. Study staff will collect socio-demographic and clinical data to identify risk factors for TB recurrence and will measure post-TB lung impairment. In both arms, an 18-month "mop-up" visit will be conducted to ascertain outcomes. We will use the RE-AIM framework to characterize implementation processes and explore acceptability through in-depth interviews with index patients, HHCs and HCWs (n = 100). Cost-effectiveness will be assessed by calculating the incremental cost per TB case detected within 12 months and projected for disability-adjusted life years averted based on modeled estimates of morbidity, mortality, and time with infectious TB. DISCUSSION: This novel trial will guide India's scale-up of post-treatment ACF and provide an evidence base for designing strategies to detect recurrent and new TB in other high burden settings. TRIAL REGISTRATION: NCT04333485 , registered April 3, 2020. CTRI/2020/05/025059 [Clinical Trials Registry of India], registered May 6 2020.

Ending tuberculosis in a post-COVID-19 world: a person-centred, equity-oriented approach.

The COVID-19 pandemic has disrupted systems of care for infectious diseases-including tuberculosis-and has exposed pervasive inequities that have long marred efforts to combat these diseases. The resulting health disparities often intersect at the individual and community levels in ways that heighten vulnerability to tuberculosis. Effective responses to tuberculosis (and other infectious diseases) must respond to these realities. Unfortunately, current tuberculosis programmes are generally not designed from the perspectives of affected individuals and fail to address structural determinants of health disparities. We describe a person-centred, equity-oriented response that would identify and focus on communities affected by disparities, tailor interventions to the mechanisms by which disparities worsen tuberculosis, and address upstream determinants of those disparities. We detail four key elements of the approach (data collection, programme design, implementation, and sustainability). We then illustrate how organisations at multiple levels might partner and adapt current practices to incorporate these elements. Such an approach could generate more substantial, sustainable, and equitable reductions in tuberculosis burden at the community level, highlighting the urgency of restructuring post-COVID-19 health systems in a more person-centred, equity-oriented way.

Adaptive strategies for the deployment of rapid diagnostic tests for COVID-19: a modelling study

Background: Lateral flow assays (LFAs) for the rapid detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) provide an affordable, rapid and decentralised means for diagnosing coronavirus disease 2019 (COVID-19). Concentrating on urban areas in low- and middle-income countries, we examined whether ‘dynamic' screening algorithms, that adjust the use of confirmatory polymerase chain reaction (PCR) testing based on epidemiological conditions, could reduce cost without substantially reducing the impact of testing. Methods: : Concentrating on a hypothetical ‘second wave' of COVID-19 in India, we modelled the potential impact of testing 0.5% of the population per day at random with LFA, regardless of symptom status. We considered dynamic testing strategies where LFA positive cases are only confirmed with PCR when LFA positivity rates are below a given threshold (relative to the peak positive rate at the height of the epidemic wave), compared to confirming either all positive LFA results or confirming no results. Benefit was estimated based on cumulative incidence of infection, and resource requirements, based on the cumulative number of PCR tests used and the cumulative number of unnecessary isolations. Results: : A dynamic strategy of discontinuing PCR confirmation when LFA positivity exceeded 50% of the peak positivity rate in an unmitigated epidemic would achieve comparable impact to one employing PCR confirmation throughout (9.2% of cumulative cases averted vs 9.8%), while requiring 35% as many PCR tests. However, the dynamic testing strategy would increase the number of false-positive test results substantially, from 0.07% of the population to 1.1%. Conclusions: : Dynamic diagnostic strategies that adjust to epidemic conditions could help maximise the impact of testing at a given cost. Generally, dynamic strategies reduce the number of confirmatory PCR tests needed, but increase the number of unnecessary isolations. Optimal strategies will depend on whether greater priority is placed on limiting confirmatory testing or false-positive diagnoses.

Symptom-based vs asymptomatic testing for controlling SARS-CoV-2 transmission in low- and middle-income countries: A modelling analysis.

BACKGROUND: Diagnostic testing plays a critical role in the global COVID-19 response. Polymerase chain reaction (PCR) tests are highly accurate, but in resource-limited settings, limited capacity has led to testing delays; whereas lateral flow assays (LFAs) offer opportunities for rapid and affordable testing. We examined the potential epidemiological impact of different strategies for LFA deployment. METHODS: We developed a deterministic compartmental model of SARS-CoV-2 transmission, parameterised to resemble a large Indian city. We assumed that PCR would be used to test symptomatic individuals presenting to outpatient settings for care. We examined how the second epidemic wave in India could have been mitigated by LFA deployment in its early stages by comparing two strategies: (i) community-based screening, using LFAs to test a proportion of the population, irrespective of symptoms (in addition to symptom-driven PCR), and (ii) symptom-driven outpatient testing, using LFAs to replace PCR. RESULTS: Model projections suggest that a stock of 25 million LFAs, used over a 600-day period in a city of 20 million people, would reduce the cumulative symptomatic incidence of COVID-19 by 0.44% if used for community-based screening, and by 13% if used to test symptomatic outpatients, relative to a no-LFA, PCR-only scenario. Sensitivity analysis suggests that outpatient testing would be more efficient in reducing transmission than community-based screening, when at least 5% of people with symptomatic COVID-19 seek care, and at least 10% of SARS-CoV-2 infections develop symptoms. Under both strategies, however, 2% of the population would be unnecessarily isolated. INTERPRETATION: In this emblematic setting, LFAs would reduce transmission most efficiently when used to test symptomatic individuals in outpatient settings. To avoid large numbers of unnecessary isolations, mass testing with LFAs should be considered as a screening tool, with follow-up confirmation. Future work should address strategies for targeted community-based LFA testing, such as contact tracing.

Estimated Transmission Outcomes and Costs of SARS-CoV-2 Diagnostic Testing, Screening, and Surveillance Strategies Among a Simulated Population of Primary School Students.

Importance: In addition to illness, the COVID-19 pandemic has led to historic educational disruptions. In March 2021, the federal government allocated $10 billion for COVID-19 testing in US schools. Objective: Costs and benefits of COVID-19 testing strategies were evaluated in the context of full-time, in-person kindergarten through eighth grade (K-8) education at different community incidence levels. Design, Setting, and Participants: An updated version of a previously published agent-based network model was used to simulate transmission in elementary and middle school communities in the United States. Assuming dominance of the delta SARS-CoV-2 variant, the model simulated an elementary school (638 students in grades K-5, 60 staff) and middle school (460 students grades 6-8, 51 staff). Exposures: Multiple strategies for testing students and faculty/staff, including expanded diagnostic testing (test to stay) designed to avoid symptom-based isolation and contact quarantine, screening (routinely testing asymptomatic individuals to identify infections and contain transmission), and surveillance (testing a random sample of students to identify undetected transmission and trigger additional investigation or interventions). Main Outcomes and Measures: Projections included 30-day cumulative incidence of SARS-CoV-2 infection, proportion of cases detected, proportion of planned and unplanned days out of school, cost of testing programs, and childcare costs associated with different strategies. For screening policies, the cost per SARS-CoV-2 infection averted in students and staff was estimated, and for surveillance, the probability of correctly or falsely triggering an outbreak response was estimated at different incidence and attack rates. Results: Compared with quarantine policies, test-to-stay policies are associated with similar model-projected transmission, with a mean of less than 0.25 student days per month of quarantine or isolation. Weekly universal screening is associated with approximately 50% less in-school transmission at one-seventh to one-half the societal cost of hybrid or remote schooling. The cost per infection averted in students and staff by weekly screening is lowest for schools with less vaccination, fewer other mitigation measures, and higher levels of community transmission. In settings where local student incidence is unknown or rapidly changing, surveillance testing may detect moderate to large in-school outbreaks with fewer resources compared with schoolwide screening. Conclusions and Relevance: In this modeling study of a simulated population of primary school students and simulated transmission of COVID-19, test-to-stay policies and/or screening tests facilitated consistent in-person school attendance with low transmission risk across a range of community incidence. Surveillance was a useful reduced-cost option for detecting outbreaks and identifying school environments that would benefit from increased mitigation.

Antigen-based Rapid Diagnostic Testing or Alternatives for Diagnosis of Symptomatic COVID-19: A Simulation-based Net Benefit Analysis.

BACKGROUND: SARS-CoV-2 antigen-detection rapid diagnostic tests can diagnose COVID-19 rapidly and at low cost, but lower sensitivity compared with reverse-transcriptase polymerase chain reaction (PCR) has limited clinical adoption. METHODS: We compared antigen testing, PCR testing, and clinical judgment alone for diagnosing symptomatic COVID-19 in an outpatient setting (10% COVID-19 prevalence among the patients tested, 3-day PCR turnaround) and a hospital setting (40% prevalence, 24-hour PCR turnaround). We simulated transmission from cases and contacts, and relationships between time, viral burden, transmission, and case detection. We compared diagnostic approaches using a measure of net benefit that incorporated both clinical and public health benefits and harms of the intervention. RESULTS: In the outpatient setting, we estimated that using antigen testing instead of PCR to test 200 individuals could be equivalent to preventing all symptomatic transmission from one person with COVID-19 (one "transmission-equivalent"). In a hospital, net benefit analysis favored PCR and testing 25 patients with PCR instead of antigen testing achieved one transmission-equivalent of benefit. In both settings, antigen testing was preferable to PCR if PCR turnaround time exceeded 2 days. Both tests provided greater net benefit than management based on clinical judgment alone unless intervention carried minimal harm and was provided equally regardless of diagnostic approach. CONCLUSIONS: For diagnosis of symptomatic COVID-19, we estimated that the speed of diagnosis with antigen testing is likely to outweigh its lower accuracy compared with PCR, wherever PCR turnaround time is 2 days or longer. This advantage may be even greater if antigen tests are also less expensive.

Quantifying the potential value of antigen-detection rapid diagnostic tests for COVID-19: a modelling analysis.

BACKGROUND: Testing plays a critical role in treatment and prevention responses to the COVID-19 pandemic. Compared to nucleic acid tests (NATs), antigen-detection rapid diagnostic tests (Ag-RDTs) can be more accessible, but typically have lower sensitivity and specificity. By quantifying these trade-offs, we aimed to inform decisions about when an Ag-RDT would offer greater public health value than reliance on NAT. METHODS: Following an expert consultation, we selected two use cases for analysis: rapid identification of people with COVID-19 amongst patients admitted with respiratory symptoms in a 'hospital' setting and early identification and isolation of people with mildly symptomatic COVID-19 in a 'community' setting. Using decision analysis, we evaluated the health system cost and health impact (deaths averted and infectious days isolated) of an Ag-RDT-led strategy, compared to a strategy based on NAT and clinical judgement. We adopted a broad range of values for 'contextual' parameters relevant to a range of settings, including the availability of NAT and the performance of clinical judgement. We performed a multivariate sensitivity analysis to all of these parameters. RESULTS: In a hospital setting, an Ag-RDT-led strategy would avert more deaths than a NAT-based strategy, and at lower cost per death averted, when the sensitivity of clinical judgement is less than 90%, and when NAT results are available in time to inform clinical decision-making for less than 85% of patients. The use of an Ag-RDT is robustly supported in community settings, where it would avert more transmission at lower cost than relying on NAT alone, under a wide range of assumptions. CONCLUSIONS: Despite their imperfect sensitivity and specificity, Ag-RDTs have the potential to be simultaneously more impactful, and have a lower cost per death and infectious person-days averted, than current approaches to COVID-19 diagnostic testing.