Enhanced SARS-CoV-2-Specific CD4+ T Cell Activation and Multifunctionality in Late Convalescent COVID-19 Individuals

Background: Examination of CD4(+) T cell responses during the natural course of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection offers useful information for the improvement of vaccination strategies against this virus and the protective effect of these T cells. Methods: We characterized the SARS-CoV-2-specific CD4(+) T cell activation marker, multifunctional cytokine and cytotoxic marker expression in recovered coronavirus disease 2019 (COVID-19) individuals. Results: CD4(+) T-cell responses in late convalescent (>6 months of diagnosis) individuals are characterized by elevated frequencies of activated as well as mono, dual- and multi-functional Th1 and Th17 CD4(+) T cells in comparison to early convalescent (<1 month of diagnosis) individuals following stimulation with SARS-CoV-2-specific antigens. Similarly, the frequencies of cytotoxic marker expressing CD4(+) T cells were also enhanced in late convalescent compared to early convalescent individuals. Conclusion: Our findings from a low-to middle-income country suggest protective adaptive immune responses following natural infection of SARS-CoV-2 are elevated even at six months following initial symptoms, indicating the CD4(+) T cell mediated immune protection lasts for six months or more in natural infection

Characterization of memory T cell subsets and common γ−chain cytokines in convalescent COVID-19 individuals

T cells are thought to be an important correlates of protection against SARS‐CoV2 infection. However, the composition of T cell subsets in convalescent individuals of SARS‐CoV2 infection has not been well studied. The authors determined the lymphocyte absolute counts, the frequency of memory T cell subsets, and the plasma levels of common γ−chain in 7 groups of COVID‐19 individuals, based on days since RT‐PCR confirmation of SARS‐CoV‐2 infection. The data show that both absolute counts and frequencies of lymphocytes as well as, the frequencies of CD4(+) central and effector memory cells increased, and the frequencies of CD4(+) naïve T cells, transitional memory, stem cell memory T cells, and regulatory cells decreased from Days 15–30 to Days 61–90 and plateaued thereafter. In addition, the frequencies of CD8(+) central memory, effector, and terminal effector memory T cells increased, and the frequencies of CD8(+) naïve cells, transitional memory, and stem cell memory T cells decreased from Days 15–30 to Days 61–90 and plateaued thereafter. The plasma levels of IL‐2, IL‐7, IL‐15, and IL‐21—common γc cytokines started decreasing from Days 15–30 till Days 151–180. Severe COVID‐19 patients exhibit decreased levels of lymphocyte counts and frequencies, higher frequencies of naïve cells, regulatory T cells, lower frequencies of central memory, effector memory, and stem cell memory, and elevated plasma levels of IL‐2, IL‐7, IL‐15, and IL‐21. Finally, there was a significant correlation between memory T cell subsets and common γc cytokines. Thus, the study provides evidence of alterations in lymphocyte counts, memory T cell subset frequencies, and common γ−chain cytokines in convalescent COVID‐19 individuals

A Quick, Deployable, Online Health Survey in Public Health Research: Emerging Horizons of mHealth during Disasters

Background: A nationwide lockdown in response to the ongoing coronavirus disease 2019 pandemic has disrupted various health surveys. Limited movements due to restricted public-transports, and the need to maintain social-distancing, make data collection at the field site through conventional methods such as face-to-face interviews challenging. Objectives: The objective of the study was to overcome such issues, we document a complete online survey, using mobile technologies, for public health research, and deployable during disasters. Methods: The survey form was uploaded online, and for the 1st time in India, the participant information page, consent, and assent forms were also deployed online. Informed consent forms from participants were captured electronically as hand-drawn signatures. A structured, electronic-questionnaire was shared to the participants’ smartphones, and the collected data were stored in a server using Research Electronic Data Capture, real-time. Results: Within a short span of 10 days, 1985 participants from 31 states and union territories took part in the survey. Among those, 79% had completed the survey, and the rest quit the survey mostly during the “consenting” phase, especially when they were asked to sign the consent/assent forms (16%). About 62.5% of the participant graded the online survey as “much better” followed by 19.5% suggesting “somewhat better,” indicating a positive public perception regarding the online survey. Conclusion: The real-time online survey in health research was perceived to be better than the conventional method. In the digital era, employing mHealth technologies in health research will be a cost-effective methodological approach to obtain the expected research outcome, in a resource and time-limited setting

Direct benefit transfer for nutritional support of patients with TB in India—analysis of national TB program data of 3.7 million patients, 2018–2022

Abstract Background Patients with TB have additional nutritional requirements and thus additional costs to the household. Ni-kshay Poshan Yojana(NPY) is a Direct Benefit Transfer (DBT) scheme under the National Tuberculosis Elimination Programme(NTEP) in India which offers INR 500 monthly to all notified patients with TB for nutritional support during the period of anti-TB treatment. Five years after its implementation, we conducted the first nationwide evaluation of NPY. Methods In our retrospective cohort study using programmatic data of patients notified with TB in nine randomly selected Indian states between 2018 and 2022, we estimated the proportion of patients who received at least one NPY instalment and the median time to receive the first instalment. We determined the factors associated (i) with non-receipt of NPY using a generalised linear model with Poisson family and log link and (ii) with time taken to receive first NPY benefit in 2022 using quantile regression at 50th percentile. Results Overall, 3,712,551 patients were notified between 2018 and 2022. During this period, the proportion who received at least one NPY instalment had increased from 56.9% to 76.1%. Non-receipt was significantly higher among patients notified by private sector (aRR 2.10;2.08,2.12), reactive for HIV (aRR 1.69;1.64,1.74) and with missing/undetermined diabetic status (aRR 2.02;1.98,2.05). The median(IQR) time to receive the first instalment had reduced from 200(109,331) days in 2018 to 91(51,149) days in 2022. Patients from private sector(106.9;106.3,107.4days), those with HIV-reactive (103.7;101.8,105.7days), DRTB(104.6;102.6,106.7days) and missing/undetermined diabetic status (115.3;114,116.6days) experienced longer delays. Conclusions The coverage of NPY among patients with TB had increased and the time to receipt of benefit had halved in the past five years. Three-fourths of the patients received at least one NPY instalment, more than half of whom had waited over three months to receive the first instalment. NTEP has to focus on timely transfer of benefits to enable patients to meet their additional nutritional demands, experience treatment success and avoid catastrophic expenditure

Estimation of tuberculosis incidence at subnational level using three methods to monitor progress towards ending TB in India, 2015–2020

Objectives We verified subnational (state/union territory (UT)/district) claims of achievements in reducing tuberculosis (TB) incidence in 2020 compared with 2015, in India.Design A community-based survey, analysis of programme data and anti-TB drug sales and utilisation data.Setting National TB Elimination Program and private TB treatment settings in 73 districts that had filed a claim to the Central TB Division of India for progress towards TB-free status.Participants Each district was divided into survey units (SU) and one village/ward was randomly selected from each SU. All household members in the selected village were interviewed. Sputum from participants with a history of anti-TB therapy (ATT), those currently experiencing chest symptoms or on ATT were tested using Xpert/Rif/TrueNat. The survey continued until 30 Mycobacterium tuberculosis cases were identified in a district.Outcome measures We calculated a direct estimate of TB incidence based on incident cases identified in the survey. We calculated an under-reporting factor by matching these cases within the TB notification system. The TB notification adjusted for this factor was the estimate by the indirect method. We also calculated TB incidence from drug sale data in the private sector and drug utilisation data in the public sector. We compared the three estimates of TB incidence in 2020 with TB incidence in 2015.Results The estimated direct incidence ranged from 19 (Purba Medinipur, West Bengal) to 1457 (Jaintia Hills, Meghalaya) per 100 000 population. Indirect estimates of incidence ranged between 19 (Diu, Dadra and Nagar Haveli) and 788 (Dumka, Jharkhand) per 100 000 population. The incidence using drug sale data ranged from 19 per 100 000 population in Diu, Dadra and Nagar Haveli to 651 per 100 000 population in Centenary, Maharashtra.Conclusion TB incidence in 1 state, 2 UTs and 35 districts had declined by at least 20% since 2015. Two districts in India were declared TB free in 2020