Ending the tuberculosis syndemic: is COVID-19 the (in)convenient scapegoat for poor progress?

Tuberculosis is a syndemic. Elimination requires a syndemic approach that addresses the individual and societal vulnerabilities that determine whether we become infected, get sick, die, or get better with disability and an impact on livelihoods.1 The WHO End TB Strategy, a global initiative launched in 2015, signifies that syndemic approach. End TB outlines fundamentals required to modify determinants of ill health, promote prevention of disease and early diagnosis with prompt treatment to save lives, prevent economic hardships, and reduce transmission. Yet, even before COVID-19 emerged, we were on track to miss all targets.2 The situation is unlikely to improve without a shift in our attitude to tuberculosis elimination

World TB Day 2018: The Challenge of Drug Resistant Tuberculosis.

On 24th March, the world commemorates the day in 1882 when Dr Robert Koch announced his discovery of Mycobacterium tuberculosis (MTB). Over 130 years later, tuberculosis (TB) continues to affect individuals, communities, and entire health systems and economies. Koch unsuccessfully tried to 'cure' TB, and despite major advances in other areas of medicine, control of TB remains elusive- in 2016 TB was the leading infectious cause of death. The STOP TB partnership and World Health Organization (WHO) have announced their theme for World TB Day 2018 "Wanted: Leaders for a TB-Free World. You can make history. End TB." This theme recognizes that TB is much larger than any one person, institute or discipline of research, and provides an opportunity for us to reflect on the major challenges and consider how we, as a scientific community, can work together and take the lead to address the global crisis of drug-resistant TB (DR-TB)

Development of a clinical prediction rule to diagnose Pneumocystis jirovecii pneumonia in the World Health Organization’s algorithm for seriously ill HIV-infected patients

Background: The World Health Organization (WHO) algorithm for the diagnosis of tuberculosis in seriously ill HIV-infected patients recommends that treatment for Pneumocystis jirovecii pneumonia (PJP) should be considered without giving clear guidance on selecting patients for empiric PJP therapy. PJP is a common cause of hospitalisation in HIV-infected patients in resource-poor settings where diagnostic facilities are limited.Methods: We developed clinical prediction rules for PJP in a prospective cohort of HIVinfected inpatients with WHO danger signs and cough of any duration. The reference standard for PJP was > 1000 copies/mL of P. jirovecii DNA on real-time sputum polymerase chain reaction (PCR). Four potentially predictive variables were selected for regression models: dyspnoea, chest X-ray, haemoglobin and oxygen saturation. Respiratory rate was explored as a replacement for oxygen saturation as pulse oximetry is not always available in resource-poor settings.Results: We enrolled 500 participants. After imputation for missing values, there were 56 PJP outcome events. Dyspnoea was not independently associated with PJP. Oxygen saturation and respiratory rate were inversely correlated. Two clinical prediction rules were developed: chest X-ray possible/likely PJP, haemoglobin ≥ 9 g/dL and either oxygen saturation < 94% or respiratory rate. The area under the receiver operating characteristic curve of the clinical prediction rule models was 0.761 (95% CI 0.683–0.840) for the respiratory rate model and 0.797 (95% CI 0.725–0.868) for the oxygen saturation model. Both models had zero probability for PJP for scores of zero, and positive likelihood ratios exceeded 10 for high scores.Conclusion: We developed simple clinical prediction rules for PJP, which, if externally validated, could assist decision-making in the WHO seriously ill algorithm

Altered ratio of IFN-γ/IL-10 in patients with drug resistant Mycobacterium tuberculosis and HIV-tuberculosis immune reconstitution inflammatory syndrome

We have described a clinical relationship between HIV-Tuberculosis Immune Reconstitution Inflammatory Syndrome (TB-IRIS) and anti-tubercular drug resistance. Here we studied the immune response of TB-IRIS patients from whom a drug-resistant (n = 11) or drug-susceptible (n = 25) Mycobacterium tuberculosis (MTB) strain was isolated after presenting with TB-IRIS. ELISpot analysis and multiplex cytokine analysis of the supernatant collected from peripheral blood mononuclear cells stimulated overnight with the heat-killed H37Rv MTB laboratory strain was used. Although there was no statistical difference in IFN-gamma ELISpot responses between the two groups, the results point towards higher bacterial load in the drug-resistant patients, possibly due to failed therapy. The ratio between secreted IFN-gamma/IL-10 and IL-2/IL-10 was significantly lower in TB-IRIS patients in whom the cause of TB was a drug-resistant strain compared to those with a fully sensitive strain (p = 0.02). Since host immune responses are dependent on the bacterial load, we hypothesise that the impaired cytokine balance is likely to be caused by the poorly controlled bacterial growth in these patients

Tracking COVID-19 using online search

Previous research has demonstrated that various properties of infectious diseases can be inferred from online search behaviour. In this work we use time series of online search query frequencies to gain insights about the prevalence of COVID-19 in multiple countries. We first develop unsupervised modelling techniques based on associated symptom categories identified by the United Kingdom's National Health Service and Public Health England. We then attempt to minimise an expected bias in these signals caused by public interest -- as opposed to infections -- using the proportion of news media coverage devoted to COVID-19 as a proxy indicator. Our analysis indicates that models based on online searches precede the reported confirmed cases and deaths by 16.7 (10.2 - 23.2) and 22.1 (17.4 - 26.9) days, respectively. We also investigate transfer learning techniques for mapping supervised models from countries where the spread of disease has progressed extensively to countries that are in earlier phases of their respective epidemic curves. Furthermore, we compare time series of online search activity against confirmed COVID-19 cases or deaths jointly across multiple countries, uncovering interesting querying patterns, including the finding that rarer symptoms are better predictors than common ones. Finally, we show that web searches improve the short-term forecasting accuracy of autoregressive models for COVID-19 deaths. Our work provides evidence that online search data can be used to develop complementary public health surveillance methods to help inform the COVID-19 response in conjunction with more established approaches.Comment: Published in Nature Digital Medicine. Please note that the published version differs from this preprin

Population tailored modification of tuberculosis specific interferon-gamma release assay

Objectives: Blood-based Interferon-Gamma Release Assays (IGRA) identify Mycobacterium tuberculosis (MTB) sensitisation with increased specificity, but sensitivity remains impaired in human immunodeficiency virus (HIV) infected persons. The QuantiFERON-TB Gold In-Tube test contains peptide 38e55 of Rv2654c, based on data indicating differential recognition between tuberculosis patients and BCG vaccinated controls in Europe. We aimed to fine map the T cell response to Rv2654c with the view of improving sensitivity. Methods: Interferon-gamma ELISpot assay was used in HIV uninfected persons with latent and active tuberculosis to map peptide epitopes of Rv2654c. A modified IGRA was tested in two further groups of 55 HIV uninfected and 44 HIV infected persons, recruited in South Africa. Results: The most prominently recognised peptide was between amino acids 51e65. Using p51-65 to boost the QuantiFERON-TB Gold In-Tube assay, the quantitative performance of the modified IGRA increased from 1.83 IU/ml (IQR 0.30e7.35) to 2.83 (IQR 0.28e12.2; p Z 0.002) in the HIV uninfected group. In the HIV infected cohort the percentage of positive responders increased from 57% to 64% but only after 3 months of ART (p Z ns)

A Systematic Review on the Safety of Mycobacterium tuberculosis-Specific Antigen-Based Skin Tests for Tuberculosis Infection Compared With Tuberculin Skin Tests

BACKGROUND: A systematic review showed that the accuracy of Mycobacterium tuberculosis antigen-based skin tests (TBSTs) for tuberculosis is similar to that of interferon γ release assay, but the safety of TBSTs has not been systematically reviewed. METHODS: We searched for studies reporting injection site reactions (ISRs) and systemic adverse events associated with TBSTs. We searched Medline, Embase, e-library, the Chinese Biomedical Literature Database, and the China National Knowledge Infrastructure database for studies through 30 July 2021, and the database search was updated until 22 November 2022. RESULTS: We identified 7 studies for Cy-Tb (Serum Institute of India), 7 (including 2 found through the updated search) for C-TST (Anhui Zhifei Longcom), and 11 for Diaskintest (Generium). The pooled risk of any injection site reactions (ISRs) due to Cy-Tb (n = 2931; 5 studies) did not differ significantly from that for tuberculin skin tests (TSTs; risk ratio, 1.05 [95% confidence interval, .70-1.58]). More than 95% of ISRs were reported as mild or moderate; common ISRs included pain, itching, and rash. In 1 randomized controlled study, 49 of 153 participants (37.6%) given Cy-Tb experience any systemic adverse event (eg, fever and headache), compared with 56 of 149 participants (37.6%) given TST (risk ratio, 0.85 [95% confidence interval, .6-1.2]). In a randomized controlled study in China (n = 14 579), the frequency of systemic adverse events in participants given C-TST was similar to that for TST, and the frequency of ISRs was similar to or lower than that for TST. Reporting of the safety data on Diaskintest was not standardized, precluding meta-analysis. CONCLUSION: The safety profile of TBSTs appears similar to that of TSTs and is associated with mostly mild ISRs

Community-based active-case finding for tuberculosis: navigating a complex minefield

Community-based active case finding (ACF) for tuberculosis (TB) involves an offer of screening to populations at risk of TB, oftentimes with additional health promotion, community engagement and health service strengthening. Recently updated World Health Organization TB screening guidelines conditionally recommend expanded offer of ACF for communities where the prevalence of undiagnosed pulmonary TB is greater than 0.5% among adults, or with other structural risk factors for TB. Subclinical TB is thought to be a major contributor to TB transmission, and ACF, particularly with chest X-ray screening, could lead to earlier diagnosis. However, the evidence base for the population-level impact of ACF is mixed, with effectiveness likely highly dependent on the screening approach used, the intensity with which ACF is delivered, and the success of community- and health-system participation. With recent changes in TB epidemiology due to the effective scale-up of treatment for HIV in Africa, the impacts of the COVID-19 pandemic, and the importance of subclinical TB, researchers and public health practitioners planning to implement ACF programmes must carefully and repeatedly consider the potential population and individual benefits and harms from these programmes. Here we synthesise evidence and experience from implementing ACF programmes to provide practical guidance, focusing on the selection of populations, screening algorithms, selecting outcomes, and monitoring and evaluation. With careful planning and substantial investment, community-based ACF for TB can be an impactful approach to accelerating progress towards elimination of TB in high-burden countries. However, ACF cannot and should not be a substitute for equitable access to responsive, affordable, accessible primary care services for all