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The Coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has prompted a massive global vaccination campaign, leading to the rapid development and deployment of several vaccines. Various COVID-19 vaccines are under different phases of clinical trials and include the whole virus or its parts like DNA, mRNA, or protein subunits administered directly or through vectors. Beginning in 2020, a few mRNA (Pfizer-BioNTech BNT162b2 and Moderna mRNA-1273) and adenovirus-based (AstraZeneca ChAdOx1-S and the Janssen Ad26.COV2.S) vaccines were recommended by WHO for emergency use before the completion of the phase 3 and 4 trials. These vaccines were mostly administered in two or three doses at a defined frequency between the two doses. While these vaccines, mainly based on viral nucleic acids or protein conferred protection against the progression of SARS-CoV-2 infection into severe COVID-19, and prevented death due to the disease, their use has also been accompanied by a plethora of side effects. Common side effects include localized reactions such as pain at the injection site, as well as systemic reactions like fever, fatigue, and headache. These symptoms are generally mild to moderate and resolve within a few days. However, rare but more serious side effects have been reported, including allergic reactions such as anaphylaxis and, in some cases, myocarditis or pericarditis, particularly in younger males. Ongoing surveillance and research efforts continue to refine the understanding of these adverse effects, providing critical insights into the risk-benefit profile of COVID-19 vaccines. Nonetheless, the overall safety profile supports the continued use of these vaccines in combating the pandemic, with regulatory agencies and health organizations emphasizing the importance of vaccination in preventing COVID-19’s severe outcomes. In this review, we describe different types of COVID-19 vaccines and summarize various adverse effects due to autoimmune and inflammatory response(s) manifesting predominantly as cardiac, hematological, neurological, and psychological dysfunctions. The incidence, clinical presentation, risk factors, diagnosis, and management of different adverse effects and possible mechanisms contributing to these effects are discussed. The review highlights the potential ambivalence of human response post-COVID-19 vaccination and necessitates the need to mitigate the adverse side effects.

Introduction: Early initiation of drug susceptibility testing (DST) guided anti-tuberculosis treatment benefits the patient in terms of better treatment outcomes and possibly reduces the transmission of tuberculosis (TB) disease in the community. To determine the status of universal DST (UDST) coverage in smear-positive pulmonary TB patients (PTB) initiated on treatment under the TB program in Greater Chennai Corporation. In addition, the barriers and facilitators for UDST were explored. Material and Methods: The data of PTB patients who were initiated on anti-TB treatment from July to December 2019 was abstracted from the NI-KSHAY database of TB Program. The barriers and facilitators for UDST were explored in 5 focus group discussions (FGDs) among the TB program healthcare workers (HCW). UDST coverage was based on the availability of Cartridge-based Nucleic Acid Amplification test (CBNAAT) results in the NI-KSHAY database. Results: The CBNAAT result was available for 1628 (82.6%) of the 1970 smear-positive PTB patients. Non-availability of CBNAAT results was significantly higher among the older age group (>50 years), in female PTB patients, and the Private Sector. Issues with sputum collection, transport of specimens, and receipt of results were highlighted by the HCWs for the non-availability of UDST results. Conclusion: Universal DST coverage in smear-positive PTB patients initiated on treatment in 2019 in Chennai was optimal as per National Strategic Plan for TB elimination UDST target of 80% for the year 2020 but with scope for improvement. The low UDST coverage in the private sector, among female patients and older age groups, needs to be addressed.

IntroductionTruenat MTB-RIF assay (Truenat), a nucleic acid amplification test (NAAT), is a real-time polymerase chain reaction (RT-PCR) chip-based assay that can detect Mycobacterium tuberculosis (Mtb) and rifampicin (RIF) drug resistance using portable, battery-operated devices. The National TB Elimination Program (NTEP) in India introduced this novel tool at the district and subdistrict level in 2020. This study aimed to assess the level and causes of inconclusive results (invalid results, errors, and indeterminate results) in MTB and RIF testing at NTEP sites and the root causes of these in the programmatic setting.MethodsTruenat testing data from 1,690 functional Truenat sites under the NTEP from April to June 2021 were analyzed to assess the rates of errors, invalid MTB results, and indeterminate RIF results. Following this analysis, 12 Truenat sites were selected based on site performance in Truenat testing, diversity of climatic conditions, and geographical terrain. These sites were visited to assess the root causes of their high and low rates of inconclusive results using a structured checklist.ResultsA total of 327,649 Truenat tests performed for MTB and RIF testing were analyzed. The rate of invalid MTB results was 5.2% [95% confidence interval (CI): 5.11–5.26; n = 16,998] and the rate of errors was 2.5% (95% CI: 2.46–2.57; n = 8,240) in Truenat MTB chip testing. For Mtb-positive samples tested using the Truenat RIF chip for detection of RIF resistance (n = 40,926), the rate of indeterminate results was 15.3% (95% CI: 14.97–15.67; n = 6,267) and the rate of errors was 1.6% (95% CI: 1.53–1.78; n = 675). There was a 40.1% retesting gap for Mtb testing and a 78.2% gap for inconclusive RR results. Among the inconclusive results retested, 27.9% (95% CI: 27.23–28.66; n = 4,222) were Mtb-positive, and 9.2% (95% CI: 7.84–10.76; n = 139) were detected as RR.ConclusionThe main causes affecting Truenat testing performance include suboptimal adherence to standard operating procedures (SOPs), inadequate training, improper storage of testing kits, inadequate sputum quality, lack of quality control, and delays in the rectification of machine issues. Root cause analysis identified that strengthening of training, external quality control, and supervision could improve the rate of inconclusive results. Ensuring hands-on training of technicians for Truenat testing and retesting of samples with inconclusive results are major recommendations while planning for Truenat scale-up. The recommendations from the study were consolidated into technical guidance documents and videos and disseminated to laboratory staff working at the tiered network of TB laboratories under the NTEP in order to improve Truenat MTB-RIF testing performance.

Background: Patients with first-line drug resistance (DR) to rifampicin (RIF) or isoniazid (INH) as a first-line (FL) line probe assay (LPA) were subjected to genotypic DST using second-line (SL) LPA to identify SL-DR (including pre-XDR) under the National TB Elimination Program (NTEP), India. SL-DR patients were initiated on different DR-TB treatment regimens and monitored for their outcomes. The objective of this retrospective analysis was to understand the mutation profile and treatment outcomes of SL-DR patients. Materials and Methods: A retrospective analysis of mutation profile, treatment regimen, and treatment outcome was performed for SL-DR patients who were tested at ICMR-NIRT, Supra-National Reference Laboratory, Chennai between the years 2018 and 2020. All information, including patient demographics and treatment outcomes, was extracted from the NTEP Ni-kshay database. Results: Between 2018 and 2020, 217 patients out of 2557 samples tested were identified with SL-DR by SL-LPA. Among them, 158/217 were FQ-resistant, 34/217 were SLID-resistant, and 25/217 were resistant to both. D94G (Mut3C) of gyrA and a1401g of rrs were the most predominant mutations in the FQ and SLID resistance types, respectively. Favorable (cured and treatment complete) and unfavorable outcomes (died, lost to follow up, treatment failed, and treatment regimen changed) were recorded in a total of 82/217 and 68/217 patients in the NTEP Ni-kshay database. Conclusions: As per the testing algorithm, SL- LPA is used for genotypic DST following identification of first-line resistance, for early detection of SL-DR in India. The fluoroquinolone resistance pattern seen in this study population corelates with the global trend. Early detection of fluoroquinolone resistance and monitoring of treatment outcome can help achieve better patient management.