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We have entered a new phase of the ongoing COVID-19 pandemic, as the strategy of relying solely on the current SARS-CoV-2 vaccines to bring the pandemic to an end has become infeasible. In response, public-health authorities in many countries have advocated for a strategy of using the vaccines to limit morbidity and mortality while permitting unchecked SARS-CoV-2 spread (“learning to live with the disease”). The feasibility of this strategy is critically dependent on the infection fatality rate (IFR) of COVID-19. An expectation exists, both in the lay public and in the scientific community, that future waves of the virus will exhibit decreased IFR, either due to viral attenuation or the progressive buildup of immunity. In this work, we examine the basis for that expectation, assessing the impact of virulence on transmission. Our findings suggest that large increases in virulence for SARS-CoV-2 would result in minimal loss of transmission, implying that the IFR may be free to increase or decrease under neutral evolutionary drift. We further examine the effect of changes in the IFR on the steady-state death toll under conditions of endemic COVID-19. Our modeling suggests that endemic SARS-CoV-2 implies vast transmission resulting in yearly US COVID-19 death tolls numbering in the hundreds of thousands under many plausible scenarios, with even modest increases in the IFR leading to an unsustainable mortality burden. Our findings thus highlight the critical importance of enacting a concerted strategy (involving for example global access to vaccines, therapeutics, prophylactics and nonpharmaceutical interventions) to suppress SARS-CoV-2 transmission, thereby reducing the risk of catastrophic outcomes. Our findings also highlight the importance of continued investment in novel biomedical interventions to prevent viral transmission.

Background Timika scoring system is a radiographic grading tool, widely employed for grading the severity of tuberculosis (TB). We evaluated the predictive accuracy of this tool for adverse treatment outcomes among TB patients in Indian setting. Methods We undertook a longitudinal analysis of cohort data under the RePORT-India consortium. Cohort having participants with active pulmonary TB were included. CXRs were independently scored by chest physicians. Timika scoring system had a total score of 140. The predictive nature of the tool was assessed using the ROC analysis. Results Around 364 laboratory confirmed TB patients were enrolled. The mean (SD) of overall Timika score was 62.3 (24.9). Sputum conversion was achieved among 218/260 (83.8%) patients available at end of intensive phase. AUC for Timika score was 0.53 (95% CI: 0.43–0.63) and for percent lung affected, was 0.56 (95% CI: 0.46–0.65). Unfavorable treatment outcome was observed among 67/287 (23.3%) at the end of continuation phase. AUC for percent lung affected was 0.62 (95% CI: 0.54–0.70) and for Timika score was 0.59 (95% CI: 0.51–0.67). Conclusion Both Timika scoring system and percent lung affected had poor predictive accuracy, highlighting the inability of a single CXR scoring system to predict the treatment outcome in Indian setting.

Mycobacterium tuberculosis (Mtb) is a complex pathogen causing multiple possible disease states in its host including latency, active disease, and elimination. While there is reasonable indirect evidence of elimination of tuberculosis (TB) in the absence of treatment, direct reports of autoregression are rare. We report a case of smear-negative, polymerase chain reaction (PCR)-positive TB disease regression in the absence of therapy due to severe adverse effects from antimycobacterial drugs. Indirect reports of TB autoregression, or self-cure, in the literature are reviewed, and an updated framework for conceptualizing Mtb infection is discussed.

The Infectious Diseases Society of America (IDSA) has set clear priorities in recent years to promote inclusion, diversity, access, and equity (IDA&E) in infectious disease (ID) clinical practice, medical education, and research. The IDSA IDA&E Task Force was launched in 2018 to ensure implementation of these principles. The IDSA Training Program Directors Committee met in 2021 and discussed IDA&E best practices as they pertain to the education of ID fellows. Committee members sought to develop specific goals and strategies related to recruitment, clinical training, didactics, and faculty development. This paper represents a presentation of ideas brought forth at the meeting in those spheres and is meant to serve as a reference document for ID training program directors seeking guidance in this area.

Background Blood-based biomarkers for diagnosing active tuberculosis (TB), monitoring treatment response, and predicting risk of progression to TB disease have been reported. However, validation of the biomarkers across multiple independent cohorts is scarce. A robust platform to validate TB biomarkers in different populations with clinical end points is essential to the development of a point-of-care clinical test. NanoString nCounter technology is an amplification-free digital detection platform that directly measures mRNA transcripts with high specificity. Here, we determined whether NanoString could serve as a platform for extensive validation of candidate TB biomarkers. Methods The NanoString platform was used for performance evaluation of existing TB gene signatures in a cohort in which signatures were previously evaluated on an RNA-seq dataset. A NanoString codeset that probes 107 genes comprising 12 TB signatures and 6 housekeeping genes (NS-TB107) was developed and applied to total RNA derived from whole blood samples of TB patients and individuals with latent TB infection (LTBI) from South India. The TBSignatureProfiler tool was used to score samples for each signature. An ensemble of machine learning algorithms was used to derive a parsimonious biomarker. Results Gene signatures present in NS-TB107 had statistically significant discriminative power for segregating TB from LTBI. Further analysis of the data yielded a NanoString 6-gene set (NANO6) that when tested on 10 published datasets was highly diagnostic for active TB. Conclusions The NanoString nCounter system provides a robust platform for validating existing TB biomarkers and deriving a parsimonious gene signature with enhanced diagnostic performance.

Background Undernutrition is the leading cause of tuberculosis (TB) in India and is associated with increased TB mortality. Undernutrition also decreases quality of life and economic productivity. Methods We assessed the cost-effectiveness of providing augmented rations to undernourished Indians through the government’s Targeted Public Distribution System (TPDS). We used Markov state transition models to simulate disease progression and mortality among undernourished individuals in 3 groups: general population, household contacts (HHCs) of people living with TB, and persons living with human immunodeficiency virus (HIV). The models calculate costs and outcomes (TB cases, TB deaths, and disability-adjusted life years [DALYs]) associated with a 2600 kcal/day diet for adults with body mass index (BMI) of 16–18.4 kg/m2 until they attain a BMI of 20 kg/m2 compared to a status quo scenario wherein TPDS rations are unchanged. We employed deterministic and probabilistic sensitivity analyses to test result robustness. Results Over 5 years, augmented rations could avert 81% of TB cases and 88% of TB deaths among currently undernourished Indians. Correspondingly, this intervention could forestall 78% and 48% of TB cases and prevent 88% and 70% of deaths among undernourished HHCs and persons with HIV, respectively. Augmented rations resulted in 10-fold higher resolution of undernutrition and were highly cost-effective with (incremental cost-effectiveness ratio [ICER] of $470/DALY averted). ICER was lower for HHCs ($360/DALY averted) and the HIV population ($250/DALY averted). Conclusions A robust nutritional intervention would be highly cost-effective in reducing TB incidence and mortality while reducing chronic undernutrition in India.

RationaleMany blood-based transcriptional gene signatures for tuberculosis (TB) have been developed with potential use to diagnose disease, predict risk of progression from infection to disease, and monitor TB treatment outcomes. However, an unresolved issue is whether gene set enrichment analysis (GSEA) of the signature transcripts alone is sufficient for prediction and differentiation, or whether it is necessary to use the original statistical model created when the signature was derived. Intra-method comparison is complicated by the unavailability of original training data, missing details about the original trained model, and inadequate publicly-available software tools or source code implementing models. To facilitate these signatures’ replicability and appropriate utilization in TB research, comprehensive comparisons between gene set scoring methods with cross-data validation of original model implementations are needed.ObjectivesWe compared the performance of 19 TB gene signatures across 24 transcriptomic datasets using both re-rebuilt original models and gene set scoring methods to evaluate whether gene set scoring is a reasonable proxy to the performance of the original trained model. We have provided an open-access software implementation of the original models for all 19 signatures for future use.MethodsWe considered existing gene set scoring and machine learning methods, including ssGSEA, GSVA, PLAGE, Singscore, and Zscore, as alternative approaches to profile gene signature performance. The sample-size-weighted mean area under the curve (AUC) value was computed to measure each signature’s performance across datasets. Correlation analysis and Wilcoxon paired tests were used to analyze the performance of enrichment methods with the original models.Measurement and Main ResultsFor many signatures, the predictions from gene set scoring methods were highly correlated and statistically equivalent to the results given by the original diagnostic models. PLAGE outperformed all other gene scoring methods. In some cases, PLAGE outperformed the original models when considering signatures’ weighted mean AUC values and the AUC results within individual studies.ConclusionGene set enrichment scoring of existing blood-based biomarker gene sets can distinguish patients with active TB disease from latent TB infection and other clinical conditions with equivalent or improved accuracy compared to the original methods and models. These data justify using gene set scoring methods of published TB gene signatures for predicting TB risk and treatment outcomes, especially when original models are difficult to apply or implement.

OBJECTIVE We aimed to determine the prevalence and find the risk factors associated with latent tuberculosis infection (LTBI) among the household contacts (HHC) of pulmonary TB patients. METHODS This cohort study was conducted from 2014 to 2019. Pretested standardised questionnaires and tools were used for data collection. The prevalence of LTBI among HHCs of TB patients was summarised as proportion with 95% confidence interval (CI). Mixed-effects generalised linear modelling function (meglm) in STATA with family Poisson and log link was performed to find the factors associated with LTBI. RESULTS In total, 1523 HHC of pulmonary TB patients were included in the study. Almost all HHC shared their residence with the index case (IC) for more than a year; 25% shared the same bed with the IC. The prevalence of LTBI among the HHC of TB patients was 52.6% (95% CI: 50.1-55.1%). In an adjusted model, we found that among HHC belonging to the age group of 19-64 years (aIRR = 1.2; 95% CI: 1.1-1.3; p-value: 0.02), to the age group >65 years (aIRR = 1.4, 95% CI: 1.1-1.9, p-value: 0.02) and sharing the same bed with the IC (aIRR = 1.2, 95% CI: 1.1-1.3, p value: 0.04) were independent determinants of LTBI among the HHC. CONCLUSION One in two household contacts of TB patients have latent tuberculosis infection. This underscores the need of targeted contact screening strategies, effective contact tracing and testing using standardised methods in high TB burden settings.

India has made substantial advancements in reducing the burden of tuberculosis (TB), but persons living with active TB (PLWATB) still face myriad challenges in seeking and receiving care, including TB-related stigma. To meet the END TB targets, it is critical that PLWATB engage in care and are able to adhere to treatment. This qualitative study aimed to understand TB-related stigma (perceived, enacted, and internalised) and possible interventions to reduce stigma in Puducherry and Tamil Nadu, India. We conducted 47 in-depth interviews with PLWATB and household members and eight focus group discussions: two each with PLWATB, their household members, healthcare workers, and key informants. We found varying TB-related knowledge: the vast majority of interview participants reported incorrect modes of transmission, although most were also aware that TB is curable. Participants reported high levels of perceived stigma, with nearly two-thirds of PLWATB choosing to hide their disease to avoid being stigmatised in their community. Participants supported interventions including celebrity advocacy and school-based programming to increase community knowledge and reduce enacted stigma as well as support groups and counselling to reduce internalised stigma in PLWATB. This study has the potential to inform future interventions to reduce TB-related stigma in India.

Background Chagas disease affects an estimated 326 000–347 000 people in the United States and is severely underdiagnosed. Lack of awareness and clarity regarding screening and diagnosis is a key barrier. This article provides straightforward recommendations, with the goal of simplifying identification and testing of people at risk for US healthcare providers. Methods A multidisciplinary working group of clinicians and researchers with expertise in Chagas disease agreed on 6 main questions, and developed recommendations based on the Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology, after reviewing the relevant literature on Chagas disease in the United States. Results Individuals who were born or resided for prolonged time periods in endemic countries of Mexico and Central and South America should be tested for Trypanosoma cruzi infection, and family members of people who test positive should be screened. Women of childbearing age with risk factors and infants born to seropositive mothers deserve special consideration due to the risk of vertical transmission. Diagnostic testing for chronic T. cruzi infection should be conducted using 2 distinct assays. Conclusions Increasing provider-directed screening for T. cruzi infection is key to addressing this neglected public health challenge in the United States.

Tuberculosis is the leading cause of deaths from an infectious disease worldwide. WHO's End TB Strategy is falling short of several 2020 targets. Undernutrition is the leading population-level risk factor for tuberculosis. Studies have consistently found that undernutrition is associated with increased tuberculosis incidence, increased severity, worse treatment outcomes, and increased mortality. Modelling studies support implementing nutritional interventions for people living with tuberculosis and those at risk of tuberculosis disease to ensure the success of the End TB Strategy. In this Personal View, we highlight nutrition-related immunocompromisation, implications of undernutrition for tuberculosis treatment and prevention, the role of nutritional supplementation, pharmacokinetics and pharmacodynamics of antimycobacterial medications in undernourished people with tuberculosis, and the role of social protection interventions in addressing undernutrition as a tuberculosis risk factor. To catalyse action on this insufficiently addressed accelerant of the global tuberculosis epidemic, research should be prioritised to understand the immunological pathways that are impaired by nutrient deficiencies, develop tools to diagnose clinical and subclinical tuberculosis in people who are undernourished, and understand how nutritional status affects the efficacy of tuberculosis vaccine and therapy. Through primary research, modelling, and implementation research, policy change should also be accelerated, particularly in countries with a high burden of tuberculosis.

The rapid emergence of immune-evading viral variants of SARS-CoV-2 calls into question the practicality of a vaccine-only public health strategy for managing the ongoing COVID-19 pandemic. It has been suggested that widespread vaccination is necessary to prevent the emergence of future immune-evading mutants. Here we examine that proposition using stochastic computational models of viral transmission and mutation. Specifically, we look at the likelihood of emergence of immune escape variants requiring multiple mutations, and the impact of vaccination on this process. Our results suggest that the transmission rate of intermediate SARS-CoV-2 mutants will impact the rate at which novel immune-evading variants will appear. While vaccination can lower the rate at which new variants appear, other interventions that reduce transmission can also have the same effect. Crucially, relying solely on widespread and repeated vaccination (vaccinating the entire population multiple times a year) is not sufficient to prevent the emergence of novel immune-evading strains if transmission rates remain high within the population. Thus, vaccines alone are incapable of slowing the pace of evolution of immune evasion, and vaccinal protection against severe and fatal outcomes for COVID-19 patients is therefore not assured.

Identifying predictors of loss to follow-up (LTFU; treatment lapse ≥ 2 months) among people with tuberculosis (TB) may assist programmatic efforts in controlling the spread of TB. Newly diagnosed smear-positive TB patients were enrolled in the Regional Prospective Observational Research for TB study in Puducherry and Tamil Nadu, India. Treatment records were used to identify LTFU of those who were enrolled from May 2014 through December 2017. This nested case–control study evaluated male TB patients. Predictors were assessed using multivariable logistic regression. Of 425 men with TB, 82 (19%) were LTFU. In the adjusted analyses of males, divorced/separated marital status (adjusted odds ratio [aOR] 3.80; 95% CI: 1.39–10.38) and at-risk alcohol use (aOR 1.92; 95% CI: 1.12–3.27) were significant predictors for increased risk of LTFU, and diabetes was a significant predictor for decreased risk of LTFU (aOR 0.52; 95% CI: 0.29–0.92). Of 53 men with recorded date of last treatment visit, 23 (43%) and 43 (81%) had LTFU within the first 2 and first 4 months of treatment, respectively. Addressing at-risk alcohol use and providing more intensive follow-up could lead to improved treatment completion.

Background Non-immune international travellers are at risk of acquiring hepatitis A. Although hepatitis A vaccination is recommended for unvaccinated travellers to high or intermediate hepatitis A virus endemicity, compliance with this recommendation is not universal. The main objective was to describe the demographic and travel characteristics of international travellers infected with hepatitis A during travel. Methods Available data on travellers with confirmed (positive molecular test) or probable (symptomatic individuals with a single positive IgM test) hepatitis A diagnosed during and after travel from January 2008 to December 2020 were obtained from the GeoSentinel Surveillance Network database. We analysed demographic and travel characteristics of infected travellers. Results Among 254 travellers with hepatitis A (185 confirmed and 69 probable), the median age was 28 years (interquartile range: 19–40), 150 (59%) were male, and among 54 travellers with information available, 53 (98%) were unvaccinated. The most common reasons for travel included tourism (n = 120; 47%) and visiting friends or relatives (VFR; n = 72; 28%). About two-thirds of VFR travellers with hepatitis A (n = 50; 69%) were younger than 20 years old. Hepatitis A was acquired most frequently in South-Central Asia (n = 63; 25%) and sub-Saharan Africa (n = 61; 24%), but 16 travellers (6%) acquired hepatitis A in regions with low endemicity including Western Europe (n = 7; 3%), the Caribbean (n = 6; 2%) and North America (n = 3; 1%). Median duration from illness onset to GeoSentinel site presentation was ~7 days (interquartile range : 4–14 days). Among 88 travellers with information available, 59% were hospitalized. Conclusions Despite availability of highly effective vaccines, travellers still acquire hepatitis A, even when traveling to low-endemicity destinations. Providing pre-departure hepatitis A vaccine to susceptible travellers is crucial to reducing travel-associated hepatitis A and should be offered to all travellers as part of the pre-travel consultation, regardless of destination.

Background Undernutrition is the leading risk factor for tuberculosis (TB) globally. Its impact on treatment outcomes is poorly defined. Methods We conducted a prospective cohort analysis of adults with drug-sensitive pulmonary TB at 5 sites from 2015–2019. Using multivariable Poisson regression, we assessed associations between unfavorable outcomes and nutritional status based on body mass index (BMI) nutritional status at treatment initiation, BMI prior to TB disease, stunting, and stagnant or declining BMI after 2 months of TB treatment. Unfavorable outcome was defined as a composite of treatment failure, death, or relapse within 6 months of treatment completion. Results Severe undernutrition (BMI Conclusions Premorbid undernutrition, undernutrition at treatment initiation, lack of BMI increase after intensive therapy, and severe stunting are associated with unfavorable TB treatment outcomes. These data highlight the need to address this widely prevalent TB comorbidity. Nutritional assessment should be integrated into standard TB care.

BackgroundCOVID-19 symptoms vary widely. This retrospective study assessed which of three clinical screening tools—a nursing triage screen (NTS), an ED review of systems (ROS) performed by physicians and physician assistants and a standardised ED attending (ie, consultant) physician COVID-19 probability assessment (PA)—best identified patients with COVID-19 on a subsequent reverse transcription PCR (RT-PCR) confirmation.MethodsAll patients admitted to Boston Medical Center from the ED between 27 April 2020 and 17 May 2020 were included. Sensitivity, specificity and positive predictive value (PPV) and negative predictive value (NPV) were calculated for each method. Logistic regression assessed each tool’s performance.ResultsThe attending physician PA had higher sensitivity (0.62, 95% CI 0.53 to 0.71) than the NTS (0.46, 95% CI 0.37 to 0.56) and higher specificity (0.76, 95% CI 0.72 to 0.80) than the NTS (0.71, 95% CI 0.66 to 0.75) and ED ROS (0.62, 95% CI 0.58 to 0.67). Categorisation as moderate or high probability on the ED physician PA was associated with the highest odds of having COVID-19 in regression analyses (adjusted OR=4.61, 95% CI 3.01 to 7.06). All methods had a low PPV (ranging from 0.26 for the ED ROS to 0.40 for the attending physician PA) and a similar NPV (0.84 for both the NTS and the ED ROS, and 0.89 for the attending physician PA).ConclusionThe ED attending PA had higher sensitivity and specificity than the other two methods, but none was accurate enough to replace a COVID-19 RT-PCR test in a clinical setting where transmission control is crucial. Therefore, we recommend universal COVID-19 testing prior to all admissions.

ObjectiveTo determine the prevalence and determinants of diabetes mellitus (DM) among tuberculosis (TB) patients and to assess the additional yield and number needed to screen (NNS) to obtain a newly diagnosed DM among TB patients.DesignWe undertook a cross-sectional analysis of the cohort data under Regional Prospective Observational Research for Tuberculosis-India consortium. Newly diagnosed TB patients recruited into the cohort between 2014 and 2018 were included. Pretested standardised questionnaires and tools were used for data collection. Prevalence of DM among TB patients was summarised as proportion with 95% CI. Type II DM was diagnosed if random blood sugar level was >200 mg/dL or if the participant had a documented history of DM. NNS by blood glucose testing to diagnose one new DM case among TB patients was also calculated.SettingThree districts of South India: Puducherry, Cuddalore and VillupuramSubjectsNewly diagnosed sputum smear positive pulmonary TB patients aged ≥16 yearsResultsIn total, 1188 TB patients were included. Prevalence of DM among TB patients was 39% (95% CI: 36.2% to 41.8%). In unadjusted analysis, elderly TB, marital status, caste, gender, higher education level, household income and obesity had a significant association with DM. However, in adjusted analysis, only marital status (currently married aPR; 3.77 (95 CI: 2.20 to 6.49), widowed/separated/divorced aPR; 3.66 (95 CI: 1.96 to 6.83)) and body mass index category (normal weight aPR; 3.26 (95 CI: 2.55 to 4.16), overweight aPR; 3.86 (95 CI: 2.69 to 5.52), obesity aPR; 4.08 (95 CI: 2.81 to 5.94)) were found to be significant determinants. The number of TB patients needed to be screened to find a new DM case was 12.ConclusionWe found that one in three TB patients had coexisting DM. The number of TB patients needed to be screened to obtain a newly diagnosed DM patients was also determined. The study supports and highlights the need of RNTCP’s effort in bidirectional screening of TB and DM.

SETTING Accurate testing and treatment for latent tuberculous infection is necessary for tuberculosis elimination. Certain parasite infections are associated with increased tuberculin skin test positivity; species-specific effects on QuantiFERON®-TB Gold In-Tube (QGIT) have not been described. OBJECTIVE To determine whether infection with helminths or protozoa affects QGIT results. DESIGN We retrospectively analyzed QGIT and parasite testing results for immigrants screened in Boston, MA, USA, from 2012 to 2017. We also prospectively measured cytokines in QGIT supernatants for a subset (n = 68) with 1) helminths, 2) Blastocystis hominis, 3) other protozoa, and 4) no parasites. RESULTS Of 527 immigrants screened, 141 (26.8%) were QGIT-positive and 229 (43.4%) had parasites detected: 27/527 (5.1%) had helminths and 202/527 (38.3%) protozoa. Cytokine analysis revealed increased interleukin-10 concentrations with protozoa (P = 0.04), and non-significantly higher T-helper 2 concentrations with helminths compared with no parasites. No significant differences emerged in QGIT positivity or interferon-gamma concentrations in any group. CONCLUSION Study results support the use of QGIT in parasite-endemic settings. .

Background Early detection of imported multidrug-resistant tuberculosis (MDR-TB) is crucial, but knowledge gaps remain about migration- and travel-associated MDR-TB epidemiology. The aim was to describe epidemiologic characteristics among international travellers and migrants with MDR-TB. Methods Clinician-determined and microbiologically confirmed MDR-TB diagnoses deemed to be related to travel or migration were extracted from GeoSentinel, a global surveillance network of travel and tropical medicine clinics, from January 2008 through December 2020. MDR-TB was defined as resistance to both isoniazid and rifampicin. Additional resistance to either a fluoroquinolone or a second-line injectable drug was categorized as pre-extensively drug-resistant (pre-XDR) TB, and as extensively drug-resistant (XDR) TB when resistance was detected for both. Sub-analyses were performed based on degree of resistance and country of origin. Results Of 201 patients, 136 had MDR-TB (67.7%), 25 had XDR-TB (12.4%), 23 had pre-XDR TB (11.4%) and 17 had unspecified MDR- or XDR-TB (8.5%); 196 (97.5%) were immigrants, of which 92 (45.8%) originated from the former Soviet Union. The median interval from arrival to presentation was 154 days (interquartile range [IQR]: 10–751 days); 34.3% of patients presented within 1 month after immigration, 30.9% between 1 and 12 months and 34.9% after ≥1 year. Pre-XDR- and XDR-TB patients from the former Soviet Union other than Georgia presented earlier than those with MDR-TB (26 days [IQR: 8–522] vs. 369 days [IQR: 84–827]), while patients from Georgia presented very early, irrespective of the level of resistance (8 days [IQR: 2–18] vs. 2 days [IQR: 1–17]). Conclusions MDR-TB is uncommon in traditional travellers. Purposeful medical migration may partly explain differences in time to presentation among different groups. Public health resources are needed to better understand factors contributing to cross-border MDR-TB spread and to develop strategies to optimize care of TB-infected patients in their home countries before migration.

Objective Limited evidence suggests that higher levels of serum vitamin D (25(OH)D) protect against SARS-CoV-2 virus (COVID-19) infection. Black women commonly experience 25(OH)D insufficiency and are overrepresented among COVID-19 cases. We conducted a prospective analysis of serum 25(OH)D levels in relation to COVID-19 infection among participants in the Black Women’s Health Study. Methods Since 1995, the Black Women’s Health Study has followed 59,000 U.S. Black women through biennial mailed or online questionnaires. Over 13,000 study participants provided a blood sample in 2013–2017. 25(OH)D assays were performed in a certified national laboratory shortly after collection of the samples. In 2020, participants who had completed the online version of the 2019 biennial health questionnaire were invited to complete a supplemental online questionnaire assessing their experiences related to the COVID-19 pandemic, including whether they had been tested for COVID-19 infection and the result of the test. We used logistic regression analysis to estimate odds ratios (OR) and 95% confidence intervals (CI) for the association of 25(OH)D level with COVID-19 positivity, adjusting for age, number of people living in the household, neighborhood socioeconomic status, and other potential confounders. Results Among 5,081 eligible participants whose blood sample had been assayed for 25(OH)D, 1,974 reported having had a COVID-19 test in 2020. Relative to women with 25(OH)D levels of 30 ng/mL (75 nmol/l) or more, multivariable-adjusted ORs for COVID-19 infection in women with levels of 20–29 ng/mL (50–72.5 nmol/l) and Conclusion The present results suggest that U.S. Black women with lower levels of 25(OH)D are at increased risk of infection with COVID-19. Further work is needed to confirm these findings and determine the optimal level of 25(OH)D for a beneficial effect.

This cross-sectional study evaluated epidemiologic characteristics of persons living with HIV (PWH) coinfected with Trypanosoma cruzi in Cochabamba, Bolivia, and estimated T. cruzi parasitemia by real-time quantitative polymerase chain reaction (qPCR) in patients with and without evidence of reactivation by direct microscopy. Thirty-two of the 116 HIV patients evaluated had positive serology for T. cruzi indicative of chronic Chagas disease (27.6%). Sixteen of the 32 (50%) patients with positive serology were positive by quantitative polymerase chain reaction (qPCR), and four of the 32 (12.5%) were positive by direct microscopy. The median parasite load by qPCR in those with CD4+

Background Black individuals have been disproportionately affected by the coronavirus disease 2019 (COVID-19). However, it remains unclear whether there are any biological factors that predispose Black patients to COVID-19-related morbidity and mortality. Objective To compare in-hospital morbidity, mortality, and inflammatory marker levels between Black and White hospitalized COVID-19 patients. Design and Participants This single-center retrospective cohort study analyzed data for Black and White patients aged ≥18 years hospitalized with a positive SARS-CoV-2 PCR test between March 1, 2020, and August 4, 2020. Main Measures The exposure was self-identified race documented in the medical record. The primary outcome of was in-hospital death. Secondary outcomes included intensive care unit admission, hospital morbidities, and inflammatory marker levels. Key Results A total of 1,424 Black and White patients were identified. The mean ± SD age was 56.1 ± 17.4 years, and 663 (44.5%) were female. There were 683 (48.0%) Black and 741 (52.0%) White patients. In the univariate analysis, Black patients had longer hospital stays (8.1 ± 10.2 vs. 6.7 ± 8.3 days, p = 0.011) and tended to have higher rates of in-hospital death (11.0% vs. 7.3%), myocardial infarction (6.9% vs. 4.5%), pulmonary embolism (PE; 5.0% vs. 2.3%), and acute kidney injury (AKI; 39.4% vs. 23.1%) than White patients (p

As the COVID-19 pandemic drags into its second year, there is hope on the horizon, in the form of SARS-CoV-2 vaccines which promise disease elimination and a return to pre-pandemic normalcy. In this study we critically examine the basis for that hope, using an epidemiological modeling framework to establish the link between vaccine characteristics and effectiveness in bringing an end to this unprecedented public health crisis. Our findings suggest that vaccines that do not prevent infection will allow extensive endemic SARS-CoV-2 spread upon a return to pre-pandemic social and economic conditions. Vaccines that only reduce symptomatic COVID-19 or mortality will fail to mitigate serious COVID-19 mortality risks, particularly in the over-65 population, likely resulting in hundreds of thousands of US deaths on a yearly basis. Our modeling points to the possibility of complete SARS-CoV-2 elimination with high population-level compliance and a vaccine that is highly effective at reducing SARS-CoV-2 infection. Notably, vaccine-mediated reduction of transmission is critical for elimination, and in order for partially-effective vaccines to play a positive role in SARS-CoV-2 elimination, other stackable (complementary) interventions must be deployed simultaneously.

Background The word ‘pandemic’ conjures dystopian images of bodies stacked in the streets and societies on the brink of collapse. Despite this frightening picture, denialism and noncompliance with public health measures are common in the historical record, for example during the 1918 Influenza pandemic or the 2015 Ebola epidemic. The unique characteristics of SARS-CoV-2—its high basic reproduction number (R0), time-limited natural immunity and considerable potential for asymptomatic spread—exacerbate the public health repercussions of noncompliance with interventions (such as vaccines and masks) to limit disease transmission. Our work explores the rationality and impact of noncompliance with measures aimed at limiting the spread of SARS-CoV-2. Methods In this work, we used game theory to explore when noncompliance confers a perceived benefit to individuals. We then used epidemiological modeling to predict the impact of noncompliance on control of SARS-CoV-2, demonstrating that the presence of a noncompliant subpopulation prevents suppression of disease spread. Results Our modeling demonstrates that noncompliance is a Nash equilibrium under a broad set of conditions and that the existence of a noncompliant population can result in extensive endemic disease in the long-term after a return to pre-pandemic social and economic activity. Endemic disease poses a threat for both compliant and noncompliant individuals; all community members are protected if complete suppression is achieved, which is only possible with a high degree of compliance. For interventions that are highly effective at preventing disease spread, however, the consequences of noncompliance are borne disproportionately by noncompliant individuals. Conclusions In sum, our work demonstrates the limits of free-market approaches to compliance with disease control measures during a pandemic. The act of noncompliance with disease intervention measures creates a negative externality, rendering suppression of SARS-CoV-2 spread ineffective. Our work underscores the importance of developing effective strategies for prophylaxis through public health measures aimed at complete suppression and the need to focus on compliance at a population level.

As the COVID-19 pandemic drags into its second year, there is hope on the horizon, in the form of SARS-CoV-2 vaccines which promise disease suppression and a return to pre-pandemic normalcy. In this study we critically examine the basis for that hope, using an epidemiological modeling framework to establish the link between vaccine characteristics and effectiveness in bringing an end to this unprecedented public health crisis. Our findings suggest that a return to pre-pandemic social and economic conditions without fully suppressing SARS-CoV-2 will lead to extensive viral spread, resulting in a high disease burden even in the presence of vaccines that reduce risk of infection and mortality. Our modeling points to the feasibility of complete SARS-CoV-2 suppression with high population-level compliance and vaccines that are highly effective at reducing SARS-CoV-2 infection. Notably, vaccine-mediated reduction of transmission is critical for viral suppression, and in order for partially-effective vaccines to play a positive role in SARS-CoV-2 suppression, complementary biomedical interventions and public health measures must be deployed simultaneously.

Background: Undernutrition is the leading cause of tuberculosis (TB) in India and is associated with increased TB mortality. Independent of TB, undernutrition decreases quality of life and economic productivity. Material and Methods: We assessed the cost-effectiveness of providing augmented rations to undernourished Indians through the government’s Targeted Public Distribution System (TPDS) using Markov state transition models which simulated disease progression and mortality among undernourished individuals in three groups: general population, household contacts (HHCs) of people living with TB, and persons with HIV. The models calculate costs and outcomes (TB cases, TB deaths, and quality-adjusted life years, QALYs) associated with a 2600 KCal/day diet for adults with body mass index [BMI] of 16-18.4 kg/m2 until they attain a BMI of 20kg/m2 compared to a “do nothing” scenario wherein TPDS rations are unchanged. We employed deterministic and probabilistic sensitivity analyses to test result robustness. Results: Over 5 years, augmented rations could avert 78% of TB cases and 88% of TB deaths among currently undernourished Indians. Correspondingly, this intervention could forestall 78% and 43% of TB cases among undernourished HHCs and HIV positive persons and prevent 88% and 68% of deaths, respectively. Augmented rations resulted in ten-fold higher resolution of undernutrition. Augmented rations were highly cost-effective (incremental cost effectiveness ratio (ICER): $460/QALY). ICER was lower for HHCs ($437/QALY) and the HIV population ($407/QALY). QALYs gained from improving nutritional status eclipsed those from preventing TB. Conclusions: A robust nutritional intervention would be highly cost-effective in reducing TB incidence and mortality while reducing chronic undernutrition. Funding Information: This work was supported by the National Institutes of Health (grant 5T32AI052074-13) to PS; US Civilian Research and Development Foundation (CRDF; award USB-31150-XX-13 to N. S. H. and C. R. H.); the National Science Foundation (cooperative agreement OISE-9531011 to N. S. H. and C. R. H.), with federal funds from the Government of India’s Department of Biotechnology, the Indian Council of Medical Research, the National Institutes of Health, the National Institute of Allergy and Infectious Diseases, and the Office of AIDS Research and distributed in part by CRDF Global; grant from the Warren Alpert Foundation and Boston University School of Medicine (N.S.H); the Clinical and Translational Sciences Institute (grant 1UL1TR001430 to N.S. H.); the Providence/Boston Center for AIDS Research (grant P30AI042853 to C. R. H.); funding from Boston University Foundation India (to N.S.H.); and the Boston University/Rutgers Tuberculosis Research Unit (grant U19AI111276 to C. R. H.). Declaration of Interests: We do not report any conflicts of interest.

As the United States grapples with the ongoing COVID-19 pandemic, a particularly thorny set of questions surrounds the reopening of K-12 schools and universities. The benefits of in-person learning are numerous, in terms of education quality, mental health, emotional well-being, equity and access to food and shelter. Early reports suggested that children might have reduced susceptibility to COVID-19, and children have been shown to experience fewer complications than older adults. Over the past few months, our understanding of COVID-19 has been further shaped by emerging data, and it looks increasingly likely that children are as susceptible to infection as adults and have a similar viral load during infection. While the higher prevalence of asymptomatic disease among children makes symptom-based isolation strategies ineffective, asymptomatic patients do not in fact carry a reduced viral load. Using assumptions consistent with the emerging understanding of the disease, we conducted epidemiological modeling to explore the feasibility and consequences of school reopening in the face of differing rates of COVID-19 prevalence and transmission. Our findings indicate that, regardless of the initial prevalence of the disease, and in the absence of systematic surveillance testing, most schools in the United States can expect 20-60 days without a major cluster emerging. Without testing or contact tracing, the true extent of these disease clusters may not be apparent, and our research suggests that the case count will underestimate the true size of the clusters by a large margin. These disease clusters, in turn, can be expected to propagate silently through the community, with potentially hundreds to thousands of additional cases resulting from each individual school cluster. Thus, our findings suggest that the debate between the risks to student safety and benefits of in-person learning frames a false dual choice. Given the current circumstances in the United States, the most likely outcome in the late fall is that students will be deprived of the benefits of in-person learning while having incurred a significant risk to themselves and their communities.

The word ‘pandemic’ conjures dystopian images of bodies stacked in the streets and societies on the brink of collapse. Despite this frightening picture, denialism and noncompliance with public health measures are common in the historical record, for example during the 1918 Influenza pandemic or the 2015 Ebola epidemic. The unique characteristics of SARS-CoV-2—its high reproductive number (R0), time-limited natural immunity and considerable potential for asymptomatic spread—exacerbate the public health repercussions of noncompliance with biomedical and nonpharmaceutical interventions designed to limit disease transmission. In this work, we used game theory to explore when noncompliance confers a perceived benefit to individuals, demonstrating that noncompliance is a Nash equilibrium under a broad set of conditions. We then used epidemiological modeling to explore the impact of noncompliance on short-term disease control, demonstrating that the presence of a noncompliant subpopulation prevents suppression of disease spread. Our modeling shows that the existence of a noncompliant population can also prevent any return to normalcy over the long run. For interventions that are highly effective at preventing disease spread, however, the consequences of noncompliance are borne disproportionately by noncompliant individuals. In sum, our work demonstrates the limits of free-market approaches to compliance with disease control measures during a pandemic. The act of noncompliance with disease intervention measures creates a negative externality, rendering COVID-19 disease control ineffective in the short term and making complete suppression impossible in the long term. Our work underscores the importance of developing effective strategies for prophylaxis through public health measures aimed at complete suppression and the need to focus on compliance at a population level.

The control of shipborne disease outbreaks represents a vexing but entirely predictable challenge at the start of any pandemic. Passenger ships, with large numbers of people confined in close quarters, can serve as incubators of disease, seeding the pandemic across the globe as infected passengers return home. Short-term steps taken by local authorities can exacerbate this problem, creating humanitarian crises and worsening the scale of the outbreak. In this work, we have undertaken a model-based examination of the USS Theodore Roosevelt outbreak to understand the dynamics of COVID-19 spread aboard the aircraft carrier. We have used a series of counterfactual “what-if” analyses to better understand the options available to public health authorities in such situations. The models suggest that rapid mass evacuation and widespread surveillance testing can be effective in these settings. Our results lead to a set of generalizable recommendations for disease control that are broadly applicable to the current COVID-19 crisis as well as to future pandemics.

We regret that this article is behind a paywall., Objective Identifying the risk factors for deaths during tuberculosis (TB) treatment is important for achieving the vision of India's National Strategic Plan of ‘Zero Deaths’ by 2025. We aimed to determine the proportion of deaths during TB treatment and its risk factors among smear positive pulmonary TB patients aged more than 15 years. Study design We performed a cohort study using data collected for RePORT India Consortium (Regional Prospective Observational Research in Tuberculosis). Setting Revised TB Control Program (RNTCP) in three districts of South India. Participants The cohort consisted of newly diagnosed drug sensitive patients enrolled under the Revised National TB Control Program during 2014–2018 in three districts of southern India. Information on death was collected at homes by trained project staff. Primary outcome measures We calculated ‘all-cause mortality’ during TB treatment and expressed this as a proportion with 95% confidence interval (CI). Risk factors for death were assessed by calculating unadjusted and adjusted relative risks with 95% CI. Results The mean (SD) age was of the 1167 participants was 45 (14.5) years and 79% of them were males. Five participants (0.4%) were HIV infected. Among the males, 560 (61%) were tobacco users and 688 (75%) reported consuming alcohol. There were 47 deaths (4%; 95% CI 3.0–5.3) of which 28 deaths (60%) occurred during first two months of treatment. In a bi-variable analysis, age of more than 60 years (RR 2.27; 95%CI: 1.24–4.15), male gender (RR 3.98; 95% CI: 1.25–12.70), alcohol use in last 12 months (RR 2.03; 95%CI: 1.07–3.87), tobacco use (RR 1.87; 95%CI: 1.05–3.36) and severe anaemia (RR 3.53: 95%CI: 1.34–9.30) were associated with a higher risk of death. In adjusted analysis, participants with severe anaemia (