Quantifying Mycobacterium tuberculosis transmission dynamics across global settings: a systematic analysis.

The degree to which individual heterogeneity in the production of secondary cases ("superspreading") affects tuberculosis (TB) transmission has not been systematically studied. We searched for population-based or surveillance studies in which whole genome sequencing was used to estimate TB transmission and the size distributions of putative TB transmission clusters were enumerated. We fit cluster size distribution data to a negative binomial branching process model to jointly infer the transmission parameters $R$ (the reproductive number) and dispersion parameter, $k$, which quantifies the propensity of superspreading in a population (generally, lower values of $k$ ($<1.0$) suggest increased heterogeneity). Of 4,796 citations identified in our initial search, nine studies met inclusion criteria ($n=5$ all TB; $n=4$ drug resistant TB) from eight global settings. Estimated $R$ values (range: 0.10, 0.73) were below 1.0, consistent with declining epidemics in the included settings; estimated $k$ values were well below 1.0 (range: 0.02, 0.48), indicating the presence of substantial individual-level heterogeneity in transmission across all settings. We estimated that a minority of cases (range 2-31%) drive the majority (80%) of ongoing transmission at the population level. Identifying sources of heterogeneity and accounting for them in TB control may have a considerable impact on mitigating TB transmission.

An assessment of the laboratory network in Ghana: A national-level ATLAS survey (2019-2020).

Background: Integrated health systems with strong laboratory networks are critical in improving public health. The current study assessed the laboratory network in Ghana and its functionality using the Assessment Tool for Laboratory Services (ATLAS). Intervention: A national-level laboratory network survey was conducted among stakeholders of the Ghanaian laboratory network in Accra. Face-to-face interviews were conducted from December 2019 to January 2020, with follow-up phone interviews between June and July 2020. Also, we reviewed supporting documents provided by stakeholders for supplementary information and transcribed these to identify themes. Where possible, we completed the Laboratory Network scorecard using data obtained from the ATLAS. Lessons learnt: The Laboratory Network (LABNET) scorecard assessment was a valuable addition to the ATLAS survey as it quantified the functionality of the laboratory network and its overall advancement toward achieving International Health Regulations (2005) and Global Health Security Agenda targets. Two significant challenges indicated by respondents were laboratory financing and delayed implementation of the Ghana National Health Laboratory Policy. Recommendations: Stakeholders recommended a review of the country's funding landscape, such as funding laboratory services from the country's internally generated funds. Also, they recommended laboratory policy implementation to ensure adequate laboratory workforce and standards.

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.

Comparative assessment of the cost-effectiveness of Tuberculosis (TB) active case-finding interventions: A systematic analysis of TB REACH wave 5 projects.

PURPOSE: Interventions that can help streamline and reduce gaps in the tuberculosis (TB) care cascade can play crucial roles in TB prevention and care, but are often operationally complex and resource intensive, given the heterogenous settings in which they are implemented. In this study, we present a comparative analysis on cost-effectiveness of TB REACH Wave 5 projects with diverse programmatic objectives to inform future decisions regarding funding, strategic adoption, and scale-up. METHODS: We comprehensively reviewed project reports and financial statements from TB REACH Wave 5, a funding mechanism for interventions that aimed to strengthen the TB care cascade in diverse settings. Two independent reviewers abstracted cost (in 2017 US dollars) and key programmatic data, including project type (case-finding only; case-finding and linkage-to-care; or case-finding, linkage-to-care and patient support), operational setting (urban or rural), and project outputs (numbers of people with TB diagnosed, started on treatment, and successfully completing treatment). Cost-effectiveness ratios for each project were calculated as ratios of apportioned programmatic expenditures to corresponding project outputs. RESULTS: Of 32 case finding and patient support projects funded through TB REACH Wave 5, 29 were included for analysis (11 case-finding only; 9 case-finding and linkage-to-care; and 9 case-finding, linkage-to-care and patient support). 21 projects (72%) were implemented in either Africa or Southeast Asia, and 19 (66%) focused on serving urban areas. Average cost-effectiveness was $184 per case diagnosed (range: $30-$10,497), $332 per diagnosis and treatment initiation ($123-$10,608), and $40 per patient treatment supported ($8-$160). Cost per case diagnosed was lower for case-finding-only projects ($132) than projects including linkage-to-care ($342) or linkage-to-care and patient support ($254), and generally increased with the corresponding country's per-capita GDP ($543 per $1000 increase, 95% confidence interval: -$53, $1138). CONCLUSION: The costs and cost-effectiveness of interventions to strengthen the TB care cascade were heterogenous, reflecting differences in context and programmatic objective. Nevertheless, many such interventions are likely to offer good value for money. Systematic collection and analysis of cost-effectiveness data can help improve comparability, monitoring, and evaluation.

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.

Potential Effects of the Coronavirus Disease 2019 (COVID-19) Pandemic on Human Immunodeficiency Virus (HIV) Transmission: A Modeling Study in 32 US Cities.

BACKGROUND: The degree to which the 2019 novel coronavirus disease (COVID-19) pandemic will affect the US human immunodeficiency virus (HIV) epidemic is unclear. METHODS: We used the Johns Hopkins Epidemiologic and Economic Model to project HIV infections from 2020 to 2025 in 32 US metropolitan statistical areas (MSAs). We sampled a range of effects of the pandemic on sexual transmission (0-50% reduction), viral suppression among people with HIV (0-40% reduction), HIV testing (0-50% reduction), and pre-exposure prophylaxis use (0-30% reduction), and indexed reductions over time to Google Community Mobility Reports. RESULTS: Simulations projected reported diagnoses would drop in 2020 and rebound in 2021 or 2022, regardless of underlying incidence. If sexual transmission normalized by July 2021 and HIV care normalized by January 2022, we projected 1161 (1%) more infections from 2020 to 2025 across all 32 cities than if COVID-19 had not occurred. Among "optimistic" simulations in which sexual transmission was sharply reduced and viral suppression was maintained we projected 8% lower incidence (95% credible interval: 14% lower to no change). Among "pessimistic" simulations where sexual transmission was largely unchanged but viral suppression fell, we projected 11% higher incidence (1-21% higher). MSA-specific projections are available at www.jheem.org?covid. CONCLUSIONS: The effects of COVID-19 on HIV transmission remain uncertain and differ between cities. Reported diagnoses of HIV in 2020-2021 are likely to correlate poorly with underlying incidence. Minimizing disruptions to HIV care is critical to mitigating negative effects of the COVID-19 pandemic on HIV transmission.

What Will It Take to End HIV in the United States? : A Comprehensive, Local-Level Modeling Study.

BACKGROUND: The Ending the HIV Epidemic (EHE) initiative aims to reduce incident HIV infections by 90% over a span of 10 years. The intensity of interventions needed to achieve this for local epidemics is unclear. OBJECTIVE: To estimate the effect of HIV interventions at the city level. DESIGN: A compartmental model of city-level HIV transmission stratified by age, race, sex, and HIV risk factor was developed and calibrated. SETTING: 32 priority metropolitan statistical areas (MSAs). PATIENTS: Simulated populations in each MSA. INTERVENTION: Combinations of HIV testing and preexposure prophylaxis (PrEP) coverage among those at risk for HIV, plus viral suppression in persons with diagnosed HIV infection. MEASUREMENTS: The primary outcome was the projected reduction in incident cases from 2020 to 2030. RESULTS: Absent intervention, HIV incidence was projected to decrease by 19% across all 32 MSAs. Modest increases in testing (1.25-fold per year), PrEP coverage (5 percentage points), and viral suppression (10 percentage points) across the population could achieve reductions of 34% to 67% by 2030. Twenty-five percent PrEP coverage, testing twice a year on average, and 90% viral suppression among young Black and Hispanic men who have sex with men (MSM) achieved similar reductions (13% to 68%). Including all MSM and persons who inject drugs could reduce incidence by 48% to 90%. Thirteen of 32 MSAs could achieve greater than 90% reductions in HIV incidence with large-scale interventions that include heterosexuals. A web application with location-specific results is publicly available (www.jheem.org). LIMITATION: The COVID-19 pandemic was not represented. CONCLUSION: Large reductions in HIV incidence are achievable with substantial investment, but the EHE goals will be difficult to achieve in most locations. An interactive model that can help policymakers maximize the effect in their local environments is presented. PRIMARY FUNDING SOURCE: National Institutes of Health.

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.

The potential impact of the COVID-19 pandemic on the tuberculosis epidemic a modelling analysis.

BACKGROUND: Routine services for tuberculosis (TB) are being disrupted by stringent lockdowns against the novel SARS-CoV-2 virus. We sought to estimate the potential long-term epidemiological impact of such disruptions on TB burden in high-burden countries, and how this negative impact could be mitigated. METHODS: We adapted mathematical models of TB transmission in three high-burden countries (India, Kenya and Ukraine) to incorporate lockdown-associated disruptions in the TB care cascade. The anticipated level of disruption reflected consensus from a rapid expert consultation. We modelled the impact of these disruptions on TB incidence and mortality over the next five years, and also considered potential interventions to curtail this impact. FINDINGS: Even temporary disruptions can cause long-term increases in TB incidence and mortality. If lockdown-related disruptions cause a temporary 50% reduction in TB transmission, we estimated that a 3-month suspension of TB services, followed by 10 months to restore to normal, would cause, over the next 5 years, an additional 1⋅19 million TB cases (Crl 1⋅06-1⋅33) and 361,000 TB deaths (CrI 333-394 thousand) in India, 24,700 (16,100-44,700) TB cases and 12,500 deaths (8.8-17.8 thousand) in Kenya, and 4,350 (826-6,540) cases and 1,340 deaths (815-1,980) in Ukraine. The principal driver of these adverse impacts is the accumulation of undetected TB during a lockdown. We demonstrate how long term increases in TB burden could be averted in the short term through supplementary "catch-up" TB case detection and treatment, once restrictions are eased. INTERPRETATION: Lockdown-related disruptions can cause long-lasting increases in TB burden, but these negative effects can be mitigated with rapid restoration of TB services, and targeted interventions that are implemented as soon as restrictions are lifted. FUNDING: USAID and Stop TB Partnership.

The Relationship of COVID-19 Severity with Cardiovascular Disease and Its Traditional Risk Factors: A Systematic Review and Meta-Analysis.

BACKGROUND: Whether cardiovascular disease (CVD) and its traditional risk factors predict severe coronavirus disease 2019 (COVID-19) is uncertain, in part, because of potential confounding by age and sex. METHODS: We performed a systematic review of studies that explored pre-existing CVD and its traditional risk factors as risk factors of severe COVID-19 (defined as death, acute respiratory distress syndrome, mechanical ventilation, or intensive care unit admission). We searched PubMed and Embase for papers in English with original data (≥10 cases of severe COVID-19). Using random-effects models, we pooled relative risk (RR) estimates and conducted meta-regression analyses. RESULTS: Of the 661 publications identified in our search, 25 papers met our inclusion criteria, with 76,638 COVID-19 patients including 11,766 severe cases. Older age was consistently associated with severe COVID-19 in all eight eligible studies, with RR >~5 in >60-65 versus <50 years. Three studies showed no change in the RR of age after adjusting for covariate(s). In univariate analyses, factors robustly associated with severe COVID-19 were male sex (10 studies; pooled RR = 1.73, [95% CI 1.50-2.01]), hypertension (8 studies; 2.87 [2.09-3.93]), diabetes (9 studies; 3.20 [2.26-4.53]), and CVD (10 studies; 4.97 [3.76-6.58]). RR for male sex was likely to be independent of age. For the other three factors, meta-regression analyses suggested confounding by age. Only four studies reported multivariable analysis, but most of them showed adjusted RR ~2 for hypertension, diabetes, and CVD. No study explored renin-angiotensin system inhibitors as a risk factor for severe COVID-19. CONCLUSIONS: Despite the potential for confounding, these results suggest that hypertension, diabetes, and CVD are independently associated with severe COVID-19 and, together with age and male sex, can be informative for predicting the risk of severe COVID-19.