Establishment and application of triple PCR method for CPV, CCoV and CRV

Canine parvovirus (CPV), canine coronavirus (CCoV) and canine rotavirus (CRV) are the three main causative viruses of diarrhea in dogs with similar clinical symptoms;thereby it is necessary to establish a high effective molecular detection method for differentiating the above pathogens. By optimizing the primer concentration and annealing temperature, a triple PCR method was established for simultaneous detection of CPV, CCoV and CRV, and then the specificity, sensitivity and repeatability of the method were tested. The results showed that the target fragments of CPV VP2 gene (253 bp), CCoV ORF-1b gene (379 bp) and CRV VP6 gene (852 bp) could be accurately amplified by the triple PCR method with high specificity, the detection limits of CPV, CCOV and CRV were 6.44x10-1 pg/L, 8.72x10-1 pg/L and 8.35x10-1 pg/L respectively with high sensitivity, and the method had good stability. Using this triple PCR method, 135 canine diarrhea fecal samples collected in Chengdu region from 2019 to 2020 were detected, and compared with those of single PCR method. The detection rates of CPV, CCoV and CRV were 16.30%, 20.74% and 4.44%, respectively, and the total infection rate was 51.11% (65/135) with 20.00% (13/65) co-infection rate. The detection results were consistent with three single PCR methods. In conclusion, CPV/CCoV/CRV triple PCR method successfully established in this paper can be applied as an effective molecular method to detection of related pathogens and to the epidemiological investigation.

Molecular Epidemiology of SARS-CoV-2 during Five COVID-19 Waves and the Significance of Low-Frequency Lineages.

SARS-CoV-2 lineages and variants of concern (VOC) have gained more efficient transmission and immune evasion properties with time. We describe the circulation of VOCs in South Africa and the potential role of low-frequency lineages on the emergence of future lineages. Whole genome sequencing was performed on SARS-CoV-2 samples from South Africa. Sequences were analysed with Nextstrain pangolin tools and Stanford University Coronavirus Antiviral & Resistance Database. In 2020, 24 lineages were detected, with B.1 (3%; 8/278), B.1.1 (16%; 45/278), B.1.1.348 (3%; 8/278), B.1.1.52 (5%; 13/278), C.1 (13%; 37/278) and C.2 (2%; 6/278) circulating during the first wave. Beta emerged late in 2020, dominating the second wave of infection. B.1 and B.1.1 continued to circulate at low frequencies in 2021 and B.1.1 re-emerged in 2022. Beta was outcompeted by Delta in 2021, which was thereafter outcompeted by Omicron sub-lineages during the 4th and 5th waves in 2022. Several significant mutations identified in VOCs were also detected in low-frequency lineages, including S68F (E protein); I82T (M protein); P13L, R203K and G204R/K (N protein); R126S (ORF3a); P323L (RdRp); and N501Y, E484K, D614G, H655Y and N679K (S protein). Low-frequency variants, together with VOCs circulating, may lead to convergence and the emergence of future lineages that may increase transmissibility, infectivity and escape vaccine-induced or natural host immunity.

Molecular Epidemiology of SARS-CoV-2 Omicron Sub-Lineages Isolated from Turkish Patients Infected with COVID-19.

Early detection and characterization of new variants and their impacts enable improved genomic surveillance. This study aims to evaluate the subvariant distribution of Omicron strains isolated from Turkish cases to determine the rate of antiviral resistance of RdRp and 3CLpro inhibitors. The Stanford University Coronavirus Antiviral & Resistance Database online tool was used for variant analyses of the strains uploaded to GISAID as Omicron (n = 20.959) between January 2021 and February,2023. Out of 288 different Omicron subvariants, B.1, BA.1, BA.2, BA.4, BE.1, BF.1, BM.1, BN.1, BQ.1, CK.1, CL.1, and XBB.1 were the main determined subvariants, and BA.1 (34.7%), BA.2 (30.8%), and BA.5 (23.6%) were reported most frequently. RdRp and 3CLPro-related resistance mutations were determined in n = 150, 0.72% sequences, while the rates of resistance against RdRp and 3CLpro inhibitors were reported at 0.1% and 0.6%, respectively. Mutations that were previously associated with a reduced susceptibility to remdesivir, nirmatrelvir/r, and ensitrelvir were most frequently detected in BA.2 (51.3%). The mutations detected at the highest rate were A449A/D/G/V (10.5%), T21I (10%), and L50L/F/I/V (6%). Our findings suggest that continuous monitoring of variants, due to the diversity of Omicron lineages, is necessary for global risk assessment. Although drug-resistant mutations do not pose a threat, the tracking of drug mutations will be necessary due to variant heterogenicity.

Respiratory syncytial virus surge in 2022 caused by lineages already present before the COVID-19 pandemic.

In 2022, Austria experienced a severe respiratory syncytial virus (RSV) epidemic with an earlier-than-usual start (Weeks 35/2021-45/2022) and increased numbers of pediatric patients in emergency departments. This surge came 2 years after a season with no cases detected as a result of coronavirus disease 2019 nonpharmaceutical interventions. We analyzed epidemiologic patterns and the phylodynamics of RSV based on approximately 30 800 respiratory specimens collected year-round over 10 years from ambulatory and hospitalized patients from 248 locations in Austria. Genomic surveillance and phylogenetic analysis of 186 RSV-A and 187 RSV-B partial glycoprotein sequences collected from 2018 to 2022 revealed that the 2022/2023 surge was driven by RSV-B in contrast to the surge in the 2021/2022 season that was driven by RSV-A. Whole-genome sequencing and phylodynamic analysis indicated that the RSV-B strain GB5.0.6a was the predominant genotype in the 2022/2023 season and emerged in late 2019. The results provide insight into RSV evolution and epidemiology that will be applicable to future monitoring efforts with the advent of novel vaccines and therapeutics.

Metavirome in Sewage and Fecally-Tainted River Waters in the Philippines: Highlighting the Role of Environmental Surveillance in the Covid-19 Pandemic

Intro: The COVID-19 pandemic has triggered global collaborative efforts on response and research to detect SARS-CoV-2 particles not just in the human population but also in wastewater. While the examination of clinical samples from COVID-19 patients links SARS-CoV-2 to specific individuals, the analysis of an amalgam of human feces through environmental surveillance (ES) links SARSCoV-2 to populations and communities served by the wastewater system. Studies on SARS-CoV-2 in the environment were already done in high-resource countries. However, its epidemiology in wastewater bodies in the Philippines is limited. In this study, we used the National ES for Polio and Other Pathogens Network to investigate the molecular epidemiology and transmission dynamics of SARS-CoV-2 at the outset of the pandemic. Method(s): This is a retrospective study of 250 wastewater samples collected from May 2020 to July 2021. Samples were processed using the two-phase concentration technique. Pepper mild mottle virus RNAs were quantified as the internal control. Real-time PCR was used to detect the N-gene of the SARS-CoV-2. Whole genomes were sequenced using the COVID-19 ARTIC v4.0. Phylogenetic and mutation analysis were done and lineage assignments were established using the PANGOLIN software. Finding(s): Forty-two percent (107/250) of the environmental samples detected SARS-CoV-2 particles. Fifty-nine samples with Ct values <=38 were sequenced and the whole genome analysis revealed B.1.1 and B.6. lineages of SARS-CoV-2. When viral load were plotted with the weekly cases in the respective site, we observed that SARS-CoV2 can be detected in wastewater weeks before the spike of cases in the community. Conclusion(s): This is the first report on the detection of B.1.1 and B.6 SARS-CoV-2 particles in waste/surface waters in the Philippines. With the declining incidence of COVID-19 cases, this study provided data regarding the feasibility of establishing environmental surveillance for SARS-CoV-2 as a supplemental tool for human or case monitoring especially in resource-limited settings.Copyright © 2023

New Technological Developments in Identification and Monitoring of New and Emerging Infections

Human population growth, globalization, and climate change may pose a sustained risk of emerging infections of pandemic potential. Fortunately, technological development provides tools to identify and monitor emerging epidemics. The rapid full genome characterization of the SARS coronavirus-2 (SARS-CoV-2), responsible for coronavirus infectious disease 2019 (COVID-19), and free sharing of sequence information, enabled a rapid global response. This included diagnostics, epidemiological monitoring, nonmedical interventions, and vaccine development, limiting the pandemic impact. An early and efficient response to global health threats will continue to rely on the development, refinement, and utilization of novel technologies to detect and monitor emerging infectious diseases. © 2022 Elsevier Inc. All rights reserved.

Dynamic Epidemiological Networks: A Data Representation Framework for Modeling and Tracking of SARS-CoV-2 Variants.

The large-scale real-time sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes has allowed for rapid identification of concerning variants through phylogenetic analysis. However, the nature of phylogenetic reconstruction is typically static, in that the relationships between taxonomic units, once defined, are not subject to alterations. Furthermore, most phylogenetic methods are intrinsically batch mode in nature, requiring the presence of the entire data set. Finally, the emphasis of phylogenetics is on relating taxonomical units. These characteristics complicate the application of classical phylogenetics methods to represent relationships in molecular data collected from rapidly evolving strains of an etiological agent, such as SARS-CoV-2, since the molecular landscape is updated continuously as samples are collected. In such settings, variant definitions are subject to epistemological constraints and may change as data accumulate. Furthermore, representing within-variant molecular relationships may be as important as representing between variant relationships. This article describes a novel data representation framework called dynamic epidemiological networks (DENs) along with algorithms that underpin its construction to address these issues. The proposed representation is applied to study the molecular development underlying the spread of the COVID-19 (coronavirus disease 2019) pandemic in two countries: Israel and Portugal spanning a 2-year period from February 2020 to April 2022. The results demonstrate how this framework could be used to provide a multiscale representation of the data by capturing molecular relationships between samples as well as those between variants, automatically identifying the emergence of high frequency variants (lineages), including variants of concern such as Alpha and Delta, and tracking their growth. Additionally, we show how analyzing the evolution of the DEN can help identify changes in the viral population that could not be readily inferred from phylogenetic analysis.

Molecular In-Depth on the Epidemiological Expansion of SARS-CoV-2 XBB.1.5.

Since the beginning of the pandemic, the generation of new variants periodically recurs. The XBB.1.5 SARS-CoV-2 variant is one of the most recent. This research was aimed at verifying the potential hazard of this new subvariant. To achieve this objective, we performed a genome-based integrative approach, integrating results from genetic variability/phylodynamics with structural and immunoinformatic analyses to obtain as comprehensive a viewpoint as possible. The Bayesian Skyline Plot (BSP) shows that the viral population size reached the plateau phase on 24 November 2022, and the number of lineages peaked at the same time. The evolutionary rate is relatively low, amounting to 6.9 × 10-4 subs/sites/years. The NTD domain is identical for XBB.1 and XBB.1.5 whereas their RBDs only differ for the mutations at position 486, where the Phe (in the original Wuhan) is replaced by a Ser in XBB and XBB.1, and by a Pro in XBB.1.5. The variant XBB.1.5 seems to spread more slowly than sub-variants that have caused concerns in 2022. The multidisciplinary molecular in-depth analyses on XBB.1.5 performed here does not provide evidence for a particularly high risk of viral expansion. Results indicate that XBB.1.5 does not possess features to become a new, global, public health threat. As of now, in its current molecular make-up, XBB.1.5 does not represent the most dangerous variant.

Application of Phylodynamic Tools to Inform the Public Health Response to COVID-19: Qualitative Analysis of Expert Opinions.

BACKGROUND: In the wake of the SARS-CoV-2 pandemic, scientists have scrambled to collect and analyze SARS-CoV-2 genomic data to inform public health responses to COVID-19 in real time. Open source phylogenetic and data visualization platforms for monitoring SARS-CoV-2 genomic epidemiology have rapidly gained popularity for their ability to illuminate spatial-temporal transmission patterns worldwide. However, the utility of such tools to inform public health decision-making for COVID-19 in real time remains to be explored. OBJECTIVE: The aim of this study is to convene experts in public health, infectious diseases, virology, and bioinformatics-many of whom were actively engaged in the COVID-19 response-to discuss and report on the application of phylodynamic tools to inform pandemic responses. METHODS: In total, 4 focus groups (FGs) occurred between June 2020 and June 2021, covering both the pre- and postvariant strain emergence and vaccination eras of the ongoing COVID-19 crisis. Participants included national and international academic and government researchers, clinicians, public health practitioners, and other stakeholders recruited through purposive and convenience sampling by the study team. Open-ended questions were developed to prompt discussion. FGs I and II concentrated on phylodynamics for the public health practitioner, while FGs III and IV discussed the methodological nuances of phylodynamic inference. Two FGs per topic area to increase data saturation. An iterative, thematic qualitative framework was used for data analysis. RESULTS: We invited 41 experts to the FGs, and 23 (56%) agreed to participate. Across all the FG sessions, 15 (65%) of the participants were female, 17 (74%) were White, and 5 (22%) were Black. Participants were described as molecular epidemiologists (MEs; n=9, 39%), clinician-researchers (n=3, 13%), infectious disease experts (IDs; n=4, 17%), and public health professionals at the local (PHs; n=4, 17%), state (n=2, 9%), and federal (n=1, 4%) levels. They represented multiple countries in Europe, the United States, and the Caribbean. Nine major themes arose from the discussions: (1) translational/implementation science, (2) precision public health, (3) fundamental unknowns, (4) proper scientific communication, (5) methods of epidemiological investigation, (6) sampling bias, (7) interoperability standards, (8) academic/public health partnerships, and (9) resources. Collectively, participants felt that successful uptake of phylodynamic tools to inform the public health response relies on the strength of academic and public health partnerships. They called for interoperability standards in sequence data sharing, urged careful reporting to prevent misinterpretations, imagined that public health responses could be tailored to specific variants, and cited resource issues that would need to be addressed by policy makers in future outbreaks. CONCLUSIONS: This study is the first to detail the viewpoints of public health practitioners and molecular epidemiology experts on the use of viral genomic data to inform the response to the COVID-19 pandemic. The data gathered during this study provide important information from experts to help streamline the functionality and use of phylodynamic tools for pandemic responses.

In-Depth Analysis of the Re-Emergence of Respiratory Syncytial Virus at a Tertiary Care Hospital in Germany in the Summer of 2021 after the Alleviation of Non-Pharmaceutical Interventions Due to the SARS-CoV-2 Pandemic.

Following the extensive non-pharmaceutical interventions (NPIs) and behavioral changes in the wake of the SARS-CoV-2 pandemic, an interseasonal rise in respiratory syncytial virus (RSV) cases was observed in Germany in 2021. The aim of this study was to characterize the local molecular epidemiology of RSV infections in comparison to the three pre-pandemic seasons. Additionally, clinical data were retrieved from patient charts to determine the clinical significance of RSV infections. RSV detections peaked in calendar week 40 of 2021, 18 weeks earlier than the usual peak observed in the three pre-pandemic seasons. Sequence analysis revealed a close phylogenetic relatedness regardless of the season of origin. A significantly higher amount of pediatric cases (88.9% of all cases, p < 0.001) was observed for season 2021/2022. For the pediatric cases, significant differences were observed for an increased number of siblings in the household (p = 0.004), a lower rate of fever (p = 0.007), and a reduced amount of co-infections (p = 0.001). Although the mean age of the adult patients was significantly younger (47.1 vs. 64.7, p < 0.001), high rates of comorbidities, lower respiratory tract infections and intensive care unit admissions prevailed. The NPIs in the wake of the SARS-CoV-2 pandemic had a tremendous impact on the epidemiologic characteristics and seasonality of RSV and warrant further epidemiologic studies of this important pathogen.

Genomic characterization and phylogenetic analysis of sars-cov-2 in libya

The COVID-19 epidemic started in Libya in March 2020 and rapidly spread. To shed some light on the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) strains circulating in Libya, viruses isolated from 10 patients in this country were sequenced, characterized at the genomic level, and compared to genomes isolated in other parts of the world. As nine genomes out of 10 belonged to the SS1 cluster and one to SS4, three datasets were built. One included only African strains and the other two contained internationally representative SS1 and SS4 genomes. Genomic analysis showed that the Libyan strains have some peculiar features in addition to those reported in other world regions. Considering the countries in which the strains are genetically more similar to the Libyan strains, SARS-CoV-2 could have entered Libya from a North African country (possibly Egypt), sub-Saharan Africa (e.g., Ghana, Mali, Nigeria), the Middle East (e.g., Saudi Arabia), or Asia (India, Bangladesh).Copyright © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Complete genome sequencing and molecular genetic evolution analysis of Guangxi mutant of porcine epidemic diarrhea virus

In order to understand the genomic characteristics and molecular genetic diversity of porcine epidemic diarrhea virus(PEDV) in Guangxi in recent years, 11 pairs of specific primers were designed to detect the whole genome of PEDV GXNN isolated from porcine diarrhea in Nanning, Guangxi, China, and similarity comparison, genetic evolution, gene variation and S gene recombination were also analyzed. The results showed that full length of the GXNN strain was 28 035 bp, had similar genomic characteristics with other PEDV isolates, about 96.4%-98.7% nucleotide similarity with different reference strains, and the nucleotide similarity of S, ORF3, M and N genes was 93.7%-98.9%, 90.9%-99.4%, 97.4%-99.7% and 95.6%-99.2%;the amino acid similarity of them was 92.9%-99.5%, 91.3%-99.1%, 97.4%-99.1% and 96.4%-99.5%. GXNN is closely related to most domestic isolates in recent years. Phylogenetic tree showed that GXNN closely related to most strains isolated in China recent years, belonged to GII-b subtype. However, it was low relatedness to classic vaccine strains, domestic early epidemic strains, foreign epidemic strains and Guangxi CH-GX-2015-750 A, they belong to different subtypes. Compared with the 5 vaccine strains, the S gene of GXNN stain has a large variation, by inserting amino acid Q at positions 118 844 and 905 sizes, four unique amino acid mutations in the core neutralizing epitope(COE)region and the main epitope region, and 14 mutations in other regions. 126 T/A, 199 A/V and 103 T/A site mutations of ORF3, M and N genes were happened at position 126, 4 D4 region and PN-D4 region, respectively. Recombination analysis revealed that there was a potential recombination region in the hypervariable region of S gene at 826-3 142 nt. This study successfully obtained the complete genome sequence of a PEDV strain, and analyzed its genetic variation and provided a reference for PEDV molecular epidemiology research and new vaccine development.

Ending the HIV Epidemic: Identifying Barriers and Facilitators to Implement Molecular HIV Surveillance to Develop Real-Time Cluster Detection and Response Interventions for Local Communities.

The rapid implementation of molecular HIV surveillance (MHS) has resulted in significant challenges for local health departments to develop real-time cluster detection and response (CDR) interventions for priority populations impacted by HIV. This study is among the first to explore professionals' strategies to implement MHS and develop CDR interventions in real-world public health settings. Methods: Semi-structured qualitative interviews were completed by 21 public health stakeholders in the United States' southern and midwestern regions throughout 2020-2022 to identify themes related to the implementation and development of MHS and CDR. Results for the thematic analysis revealed (1) strengths and limitations in utilizing HIV surveillance data for real-time CDR; (2) limitations of MHS data due to medical provider and staff concerns related to CDR; (3) divergent perspectives on the effectiveness of partner services; (4) optimism, but reluctance about the social network strategy; and (5) enhanced partnerships with community stakeholders to address MHS-related concerns. Conclusions: Enhancing MHS and CDR efforts requires a centralized system for staff to access public health data from multiple databases to develop CDR interventions; designating staff dedicated to CDR interventions; and establishing equitable meaningful partnerships with local community stakeholders to address MHS concerns and develop culturally informed CDR interventions.

Molecular Epidemiology and Diversity of SARS-CoV-2 in Ethiopia, 2020-2022.

Ethiopia is the second most populous country in Africa and the sixth most affected by COVID-19 on the continent. Despite having experienced five infection waves, >499,000 cases, and ~7500 COVID-19-related deaths as of January 2023, there is still no detailed genomic epidemiological report on the introduction and spread of SARS-CoV-2 in Ethiopia. In this study, we reconstructed and elucidated the COVID-19 epidemic dynamics. Specifically, we investigated the introduction, local transmission, ongoing evolution, and spread of SARS-CoV-2 during the first four infection waves using 353 high-quality near-whole genomes sampled in Ethiopia. Our results show that whereas viral introductions seeded the first wave, subsequent waves were seeded by local transmission. The B.1.480 lineage emerged in the first wave and notably remained in circulation even after the emergence of the Alpha variant. The B.1.480 was outcompeted by the Delta variant. Notably, Ethiopia's lack of local sequencing capacity was further limited by sporadic, uneven, and insufficient sampling that limited the incorporation of genomic epidemiology in the epidemic public health response in Ethiopia. These results highlight Ethiopia's role in SARS-CoV-2 dissemination and the urgent need for balanced, near-real-time genomic sequencing.

Genome-based survey of the SARS-CoV-2 BF.7 variant from Asia.

The SARS-CoV-2 BF.7 variant represents one of the most recent subvariant under monitoring. At the beginning of the 2023 it caused several concerns especially in Asia because of a resurge in COVID-19 cases. Here we perform a genome-based integrative approach on SARS-CoV-2 BF.7 to shed light on this emerging lineage and produce some consideration on its real dangerousness. Both genetic and structural data suggest that this new variant currently does not show evidence of an high expansion capability. It is very common in Asia, but it appears less virulent than other Omicron variants as proved by its relatively low evolutionary rate (5.62 × 10-4 subs/sites/years). The last plateau has been reached around December 14, 2022 and then the genetic variability, and thus the viral population size, no longer increased. As already seen for several previous variants, the features that may be theoretically related to advantages are due to genetic drift that allows to the virus a constant adaptability to the host, but is not strictly connected to a fitness advantage. These results have further pointed that the genome-based monitoring must continue uninterruptedly to be prepared and well documented on the real situation.

Clinical characteristics and molecular epidemiology of human metapneumovirus in children with acute lower respiratory tract infections in China, 2017 to 2019: A multicentre prospective observational study.

Human metapneumovirus (HMPV) infection is one of the leading causes of hospitalization in young children with acute respiratory illness. In this study, we prospectively collected respiratory tract samples from children who were hospitalized with acute lower respiratory tract infection in six hospitals in China from 2017 to 2019. HMPV was detected in 145 out of 2733 samples (5.3%) from the hospitalized children. The majority of HMPV-positive children were under the age of two (67.6%), with a median age of one year. HMPV can independently cause acute lower respiratory tract infection in young children, while all patients showed mild clinical symptoms. Of all the co-infected patients, HMPV was most commonly detected with enterovirus (EV) or rhinovirus (RhV) (38.0%, followed by respiratory syncytial virus (RSV) (32.0%). The highest detection rate occurred from March to May in both northern and southern China. Out of 145 HMPV positive samples, 48 were successfully typed, of which 36 strains were subgrouped into subtypes A2c (75%), eight strains were included in subtype B1 (16.7%), and four strains were included in subtype B2 (8.3%). Moreover, 16 A2c strains contained 111-nucleotide duplications in the G gene. Twenty-seven complete HMPV genomes were successfully obtained, and 25 (92.6%) strains belonged to subtype A2c, whereas one strain was included in subgroup B1 and another was included in subgroup B2. A total of 277 mutations were observed in the complete genomes of 25 A2c strains. All results presented here improve our understanding of clinical characteristics and molecular epidemiology of HMPV infection in children.

Evaluating Data Sharing of SARS-CoV-2 Genomes for Molecular Epidemiology across the COVID-19 Pandemic.

Following the emergence of COVID-19 in December 2019, caused by the coronavirus SARS-CoV-2, the disease spread dramatically worldwide. The use of genomics to trace the dissemination of the virus and the identification of novel variants was essential in defining measures for containing the disease. We aim to evaluate the global effort to genomically characterize the circulating lineages of SARS-CoV-2, considering the data deposited in GISAID, the major platform for data sharing in a massive worldwide collaborative undertaking. We contextualize data for nearly three years (January 2020-October 2022) for the major contributing countries, percentage of characterized isolates and time for data processing in the context of the global pandemic. Within this collaborative effort, we also evaluated the early detection of seven major SARS-CoV-2 lineages, G, GR, GH, GK, GV, GRY and GRA. While Europe and the USA, following an initial period, showed positive results across time in terms of cases sequenced and time for data deposition, this effort is heterogeneous worldwide. Given the current immunization the major threat is the appearance of variants that evade the acquired immunity. In that scenario, the monitoring of those hypothetical variants will still play an essential role.

Genetic diversity of Mycobacterium tuberculosis isolates from northwest of Iran during COVID-19 era

Background: Tuberculosis (TB) is considered one of the most infectious diseases in the world. In this study, we intended to examine the epidemiology of tuberculosis by MIRU-VNTR to define the changes that occur in the transmission of tuberculosis in the region during the COVID-19 era. A total of 120 Mycobacterium tuberculosis isolates were collected from sputum samples of patients referred to East Azerbaijan Center TB from December 2020 to August 2021. Demographic information such as age, sex, place of birth, previous TB history, and relevant medical data was collected. The proportion method was performed for drug susceptibility testing, and the PCR-based MIRU-VNTR method was applied to identify molecular epidemiology relationships. Result(s): The isolates were collected from 78 male (65%) and 39 female (32.5%) Iranian patients and 3 (2.5%) Azerbaijani patients. Ninety-three distinct patterns were identified including 15 clustered patterns and 36 unique patterns. The largest cluster was composed of seven isolates. Furthermore, one cluster with 5 members, four clusters with 3 members, and nine clusters with 2 members. In MIRU-VNTR typing, 75 clusters belonged to the Tabriz region and just 3 to the Republic of Azerbaijan. All isolates were sensitive to rifampin, isoniazid, and ethambutol. Conclusion(s): Results of the current study showed COVID-19 pandemic had a direct effect on the transmission and diagnosis of tuberculosis. Less diagnosis and less clustering can indicate public controls and hygiene, and the use of masks had a direct effect on the transmission and diagnosis of tuberculosis. However, misidentification and less focus on other respiratory infections are expected during the pandemic. Studies on the co-infection of COVID-19 and tuberculosis and the role of mask and sanitization against TB are strongly recommended. Copyright © 2023, The Author(s).