Challenges in setting up a diagnostic microbiology laboratory during coronavirus disease 2019 crisis and impact on the diagnosis of communicable diseases.

The coronavirus disease 2019 (COVID-19) pandemic has left the health-care workers exhausted and the system dwindling. The challenges have been immense everywhere and even worse in developing countries. Despite the Indian Government's forethought and active investment in various national programs, the pandemic has brought unconceivable repercussions on the management and notification of several other lethal infectious diseases including human immunodeficiency virus (HIV) and tuberculosis. Although the phenomenal capacity building for COVID-19 testing and diagnosis over a short time is admirable, the journey has been arduous. From convincing the hospital managements to create the recommended infrastructure, to the procurement of necessary equipment and consumables on an urgent basis, and providing services round the clock with limited workforce, the laboratory personnel throughout the country have done a remarkable job in their quest to combat the pandemic. However, the work needs to be pursued further in apprehension and preparedness for any emerging agents.

COVID-19: Analytic results for a modified SEIR model and comparison of different intervention strategies.

The Susceptible-Exposed-Infected-Recovered (SEIR) epidemiological model is one of the standard models of disease spreading. Here we analyse an extended SEIR model that accounts for asymptomatic carriers, believed to play an important role in COVID-19 transmission. For this model we derive a number of analytic results for important quantities such as the peak number of infections, the time taken to reach the peak and the size of the final affected population. We also propose an accurate way of specifying initial conditions for the numerics (from insufficient data) using the fact that the early time exponential growth is well-described by the dominant eigenvector of the linearized equations. Secondly we explore the effect of different intervention strategies such as social distancing (SD) and testing-quarantining (TQ). The two intervention strategies (SD and TQ) try to reduce the disease reproductive number, R 0 , to a target value R 0 target < 1 , but in distinct ways, which we implement in our model equations. We find that for the same R 0 target < 1 , TQ is more efficient in controlling the pandemic than SD. However, for TQ to be effective, it has to be based on contact tracing and our study quantifies the required ratio of tests-per-day to the number of new cases-per-day. Our analysis shows that the largest eigenvalue of the linearised dynamics provides a simple understanding of the disease progression, both pre- and post- intervention, and explains observed data for many countries. We apply our results to the COVID data for India to obtain heuristic projections for the course of the pandemic, and note that the predictions strongly depend on the assumed fraction of asymptomatic carriers.

Universal scaling in active single-file dynamics.

We study the single-file dynamics of three classes of active particles: run-and-tumble particles, active Brownian particles and active Ornstein-Uhlenbeck particles. At high activity values, the particles, interacting via purely repulsive and short-ranged forces, aggregate into several motile and dynamical clusters of comparable size, and do not display bulk phase-segregation. In this dynamical steady-state, we find that the cluster size distribution of these aggregates is a scaled function of the density and activity parameters across the three models of active particles with the same scaling function. The velocity distribution of these motile clusters is non-Gaussian. We show that the effective dynamics of these clusters can explain the observed emergent scaling of the mean-squared displacement of tagged particles for all the three models with identical scaling exponents and functions. Concomitant with the clustering seen at high activities, we observe that the static density correlation function displays rich structures, including multiple peaks that are reminiscent of particle clustering induced by effective attractive interactions, while the dynamical variant shows non-diffusive scaling. Our study reveals a universal scaling behavior in the single-file dynamics of interacting active particles.

A hybrid and scalable error correction algorithm for indel and substitution errors of long reads.

BACKGROUND: Long-read sequencing has shown the promises to overcome the short length limitations of second-generation sequencing by providing more complete assembly. However, the computation of the long sequencing reads is challenged by their higher error rates (e.g., 13% vs. 1%) and higher cost ($0.3 vs. $0.03 per Mbp) compared to the short reads. METHODS: In this paper, we present a new hybrid error correction tool, called ParLECH (Parallel Long-read Error Correction using Hybrid methodology). The error correction algorithm of ParLECH is distributed in nature and efficiently utilizes the k-mer coverage information of high throughput Illumina short-read sequences to rectify the PacBio long-read sequences.ParLECH first constructs a de Bruijn graph from the short reads, and then replaces the indel error regions of the long reads with their corresponding widest path (or maximum min-coverage path) in the short read-based de Bruijn graph. ParLECH then utilizes the k-mer coverage information of the short reads to divide each long read into a sequence of low and high coverage regions, followed by a majority voting to rectify each substituted error base. RESULTS: ParLECH outperforms latest state-of-the-art hybrid error correction methods on real PacBio datasets. Our experimental evaluation results demonstrate that ParLECH can correct large-scale real-world datasets in an accurate and scalable manner. ParLECH can correct the indel errors of human genome PacBio long reads (312 GB) with Illumina short reads (452 GB) in less than 29 h using 128 compute nodes. ParLECH can align more than 92% bases of an E. coli PacBio dataset with the reference genome, proving its accuracy. CONCLUSION: ParLECH can scale to over terabytes of sequencing data using hundreds of computing nodes. The proposed hybrid error correction methodology is novel and rectifies both indel and substitution errors present in the original long reads or newly introduced by the short reads.

Evaluation of Xpert MTB/RIF Assay for Diagnosis of Tuberculosis in Children.

Introduction: Childhood tuberculosis (TB) is now a global priority. With the advent of Xpert MTB/RIF, more TB cases in children are being reported. This study was undertaken to evaluate the performance of Xpert in diagnosis of pulmonary and extra-pulmonary TB in children. Methods: Specimens from 171 suspected TB cases in children aged <15 years were tested with Xpert, culture and smear microscopy in the Department of Microbiology, Institute of Medical Sciences, India. Results: The specimens included 106 gastric aspirates, 51 cerebrospinal fluids, 8 induced sputum and 6 lymph node aspirates. Xpert detected Mycobacterium tuberculosis in 19 cases (14 pulmonary and 5 extra-pulmonary), 7 of which were rifampicin-resistant. Sensitivity, specificity, positive predictive value and negative predictive value of Xpert compared with culture were 88.89, 98.04, 84.21 and 98.68%, respectively. The sensitivity was 100% in children aged 1-5 years and 6-10 years and in gastric aspirates. Conclusion: Xpert is an efficient diagnostic tool in childhood tuberculosis.

Immunoregulatory functions and expression patterns of PE/PPE family members: Roles in pathogenicity and impact on anti-tuberculosis vaccine and drug design.

The Mycobacterium tuberculosis genome was sequenced more than 15 years ago. It revealed a lot of interesting information, one of which was that 10% of the total coding capacity of the M. tuberculosis genome is dedicated to the PE/PPE family. There is a gradual expansion of these proteins from nonpathogenic to pathogenic mycobacteria, and there is increasing evidence that PE/PPE proteins play important roles in mycobacterial pathogenesis. In this review, we discuss PE/PPE proteins, their close functional association with the ESX clusters, their immunomodulatory functions, and their important roles in mycobacterial virulence. In addition, we have attempted to review and compile information available in the literature detailing the expression patterns of PE/PPE family members in different mycobacterial species and also during infection. Our attempt has been to provide a succinct overview of this interesting family.

Fermented Polyherbal Formulation Ameliorates the Severity of Acute Multiple Antibiotics-Resistant Pseudomonas aeruginosa-Infected Burn Wound in a Rat Burn Model.

Pseudomonas aeruginosa, a Gram-negative opportunistic bacterium, has emerged as a cause of life-threatening infections in burn wounds. Current therapeutic approaches through wound dressings and systemic medicines are far from satisfactory; resistance to more than two antibiotics shown by pathogens contributes to failures of therapy causing mortality. This animal study was conducted to check the efficacy of one Ayurveda-based fermented polyherbal preparation (AP 01) against multiple antibiotics-resistant (MAR) P. aeruginosa HW01-infected rat burn wounds. AP-01 was applied on artificially infected burn wound on a rat model infected with MAR P. aeruginosa to register the healing effects in terms of reduction in residual wound area percentage, the presence of C-reactive protein in blood, and the presence of viable bacteria colony. Topical application with conventional antibiotics served as a positive control. The polyherbal preparation had reduced the infected residual burn wound area at 40.63% ± 0.69 from the initial burn wound area within two weeks after a single intervention, whereas residual burn wound area remained much higher in the case of animals left untreated and in the case of the animals treated with control drug. Restoration to the normalcy of serum C-reactive protein level was also achieved earlier in the case of polyherbal AP-01-treated groups than in other groups. Fermented formulations using components of AP-01 singly or in different combinations had never been tested earlier for topical application in infected burn wound. The formulation of AP-01 was found superior in terms of the rate of healing and control of infection by MAR P. aeruginosa strains in burn wounds in rat models.

Nitazoxanide refractory cryptosporidiosis complicating Burkitt lymphoma in a child.

Cryptosporidium species cause watery diarrhea in several vertebrate hosts, including humans. Most apparently, immunocompetent-infected individuals remain asymptomatic, whereas immunocompromised may develop severe or chronic cryptosporidiosis. We report here the case of a 6-year-old girl undergoing chemotherapy for Burkitt lymphoma who experienced multiple episodes of watery diarrhea during her hospital stay. Microscopic examination of her stool sample revealed oocysts of Cryptosporidium species. The rapid immunochromatographic test was also positive for Cryptosporidium species. She was treated with nitazoxanide for 3 weeks, which failed to provide both clinical improvement and parasitological clearance. This case highlights the importance of treatment failure in human cryptosporidiosis.

A super SDM (species distribution model) 'in the cloud' for better habitat-association inference with a 'big data' application of the Great Gray Owl for Alaska.

The currently available distribution and range maps for the Great Grey Owl (GGOW; Strix nebulosa) are ambiguous, contradictory, imprecise, outdated, often hand-drawn and thus not quantified, not based on data or scientific. In this study, we present a proof of concept with a biological application for technical and biological workflow progress on latest global open access 'Big Data' sharing, Open-source methods of R and geographic information systems (OGIS and QGIS) assessed with six recent multi-evidence citizen-science sightings of the GGOW. This proposed workflow can be applied for quantified inference for any species-habitat model such as typically applied with species distribution models (SDMs). Using Random Forest-an ensemble-type model of Machine Learning following Leo Breiman's approach of inference from predictions-we present a Super SDM for GGOWs in Alaska running on Oracle Cloud Infrastructure (OCI). These Super SDMs were based on best publicly available data (410 occurrences + 1% new assessment sightings) and over 100 environmental GIS habitat predictors ('Big Data'). The compiled global open access data and the associated workflow overcome for the first time the limitations of traditionally used PC and laptops. It breaks new ground and has real-world implications for conservation and land management for GGOW, for Alaska, and for other species worldwide as a 'new' baseline. As this research field remains dynamic, Super SDMs can have limits, are not the ultimate and final statement on species-habitat associations yet, but they summarize all publicly available data and information on a topic in a quantified and testable fashion allowing fine-tuning and improvements as needed. At minimum, they allow for low-cost rapid assessment and a great leap forward to be more ecological and inclusive of all information at-hand. Using GGOWs, here we aim to correct the perception of this species towards a more inclusive, holistic, and scientifically correct assessment of this urban-adapted owl in the Anthropocene, rather than a mysterious wilderness-inhabiting species (aka 'Phantom of the North'). Such a Super SDM was never created for any bird species before and opens new perspectives for impact assessment policy and global sustainability.

Evaluation of a rapid immunochromatographic test for the diagnosis of intestinal protozoan infections among patients attending a rural outreach outpatient department in Northern India.

Despite great efforts, intestinal protozoan infections remain a significant healthcare concern worldwide. Although many point-of-care (POC) tests are increasingly being used, microscopic examination of stool specimens remains the mainstay for their diagnosis, especially in resource-limited settings. We assessed the utility of rapid POC tests based on immunochromatography among patients from rural Northern India. A total of 78 patients were enrolled in the study. Out of nine specimens that tested positive for Giardia duodenalis on microscopy, an immunochromatographic test (ICT) could detect only five (55.55%). Entamoeba histolytica/dispar was demonstrated in two specimens on microscopy, both of which were missed by ICT. Its overall sensitivity, specificity, and positive and negative predictive value were 50%, 98.5%, 83.3%, and 93%, respectively. Its performance was considered unsatisfactory. Although ICT-based tests provide a relatively rapid and less labor-intensive alternative, they should be used to supplement and not replace stool microscopy.

Evaluation of three protocols for direct susceptibility testing for Gram-negative rods from flagged positive blood culture bottles.

Bloodstream infections are associated with high mortality, which can be reduced by targeted antibiotic therapy in the early stages of infection. Direct antibiotic susceptibility testing (AST) from flagged positive blood cultures may facilitate the administration of early effective antimicrobials much before the routine AST. This study aimed to evaluate three different direct AST protocols for Gram-negative rods from flagged positive blood culture broths. Blood culture broths showing Gram-negative rods only were subjected to direct AST by Clinical and Laboratory Standards Institute-recommended direct disk diffusion (protocol A). Additionally, automated AST (protocol B) and Kirby-Bauer disk diffusion (protocol C) were performed with standard inoculum prepared from bacterial pellets obtained by centrifuging blood culture broths in serum separator vials. For comparison, conventional AST of isolates from solid media subculture was also performed with Kirby-Bauer disk diffusion (reference standard) and the automated method. Overall, categorical agreements of protocols A, B, and C were 97.6%, 95.7%, and 95.9%, respectively. Among Enterobacterales, minor error, major error, and very major error rates of protocol B were 3.5%, 0.36%, and 0.43%, respectively, whereas minor error, major error, and very major error rates of protocol C were 3.4%, 0.72%, and 0.21%, respectively, and among non-fermenters, protocol B had a minor error rate of 6.5%, and protocol C had a minor error rate of 4.1% and major error rate of 1.9%. All three direct AST protocols demonstrated excellent categorical agreements with the reference method. Performance of protocols B and C between Enterobacterales and non-fermenters was not statistically different. IMPORTANCE: Bloodstream infections are associated with high mortality that can be reduced by targeted antibiotic therapy in the early stages of infection. Direct antibiotic susceptibility testing (AST) from flagged positive blood cultures may facilitate the administration of early effective antimicrobials much before the routine AST. Clinical and Laboratory Standards Institute-recommended direct AST can be performed with a limited number of antibiotic disks only. On the other hand, using an automated system for direct AST will not only allow effective laboratory workflow with reduced turnaround time but also provide the minimum inhibitory concentration values of tested antibiotics. However, using expensive automated systems for direct AST may not be feasible for resource-limited laboratories. Therefore, in this study, we aimed to evaluate the CLSI-recommended method and two other direct AST protocols (one with an automated system and the other with disk diffusion) for Gram-negative rods from flagged positive blood cultures.

Evaluation of a simple method for testing aztreonam and ceftazidime-avibactam synergy in New Delhi metallo-beta-lactamase producing Enterobacterales.

NDM-producing carbapenem-resistant bacterial infections became a challenge for clinicians. Combination therapy of aztreonam and ceftazidime-avibactam is a prudent choice for these infections. However, there is still no recommendation of a practically feasible method for testing aztreonam and ceftazidime-avibactam synergy. We proposed a simple method for testing aztreonam and ceftazidime-avibactam synergy and compared it with reference broth micro-dilution and other methods. Carbapenem-resistant Enterobacterales clinical isolates were screened for the presence of the NDM gene by the Carba R test. NDM harbouring isolates were tested for aztreonam and ceftazidime-avibactam synergy by broth microdilution (reference method), E strip-disc diffusion, double disc diffusion, and disc replacement methods. In the newly proposed method, the MHA medium was supplemented with ceftazidime-avibactam (corresponding to an aztreonam concentration of 4µg/ml). The MHA medium was then inoculated with the standard inoculum (0.5 McFarland) of the test organism. An AZT disc (30 µg) was placed on the supplemented MHA medium, and the medium was incubated overnight at 37°C. Aztreonam zone diameter on the supplemented MHA medium (in the presence of ceftazidime-avibactam) was compared with that from a standard disc diffusion plate (without ceftazidime-avibactam), performed in parallel. Interpretation of synergy was based on the restoration of aztreonam zone diameter (in the presence of ceftazidime-avibactam) crossing the CLSI susceptibility breakpoint, i.e., ≥ 21 mm. Of 37 carbapenem-resistant NDM-producing isolates, 35 (94.6%) were resistant to aztreonam and tested synergy positive by the proposed method. Its sensitivity and specificity were 97.14% and 100%, respectively. Cohen's kappa value showed substantial agreement of the reference method with the proposed method (κ = 0.78) but no other methods. The proposed method is simple, easily interpretable, and showed excellent sensitivity, specificity, and agreement with the reference method. Therefore, the new method is feasible and reliable for testing aztreonam synergy with avibactam in NDM-producing Enterobacterales.

Coarsening, condensates, and extremes in aggregation-fragmentation models.

We use extreme value statistics to study the dynamics of coarsening in aggregation-fragmentation models which form condensates in the steady state. The dynamics is dominated by the formation of local condensates on a coarsening length scale which grows in time in both the zero range process and conserved mass aggregation model. The local condensate mass distribution exhibits scaling, which implies anomalously large fluctuations, with mean and standard deviation both proportional to the coarsening length. Remarkably, the state of the system during coarsening is governed not by the steady state, but rather a preasymptotic state in which the condensate mass fluctuates strongly.

Designing New Magic Bullets to Penetrate the Mycobacterial Shield: An Arduous Quest for Promising Therapeutic Candidates.

Mycobacterium spp. intimidated mankind since time immemorial. The triumph over this organism was anticipated with the introduction of potent antimicrobials in the mid-20th century. However, the emergence of drug resistance in mycobacteria, Mycobacterium tuberculosis, in particular, caused great concern for the treatment. With the enemy growing stronger, there is an immediate need to equip the therapeutic arsenal with novel and potent chemotherapeutic agents. The task seems intricating as our understanding of the dynamic nature of the mycobacteria requires intense experimentation and research. Targeting the mycobacterial cell envelope appears promising, but its versatility allows it to escape the lethal effect of the molecules acting on it. The unique ability of hiding (inactivity during latency) also assists the bacterium to survive in a drug-rich environment. The drug delivery systems also require upgradation to allow better bioavailability and tolerance in patients. Although the resistance to the novel drugs is inevitable, our commitment to the research in this area will ensure the discovery of effective weapons against this formidable opponent.

Evolution of Diagnostic and Forensic Microbiology in the Era of Artificial Intelligence.

Diagnostic microbiology plays a vital role in managing infectious diseases, combating antimicrobial resistance, and containment of outbreaks. During the fourth industrial revolution, when artificial intelligence (AI) became an essential part of our day-to-day lives, its integration into healthcare would further revolutionize our knowledge and potential. Although in the budding stage, AI with machine learning is being increasingly utilized in various aspects of diagnostic microbiology. It can handle large datasets that are difficult to analyze manually. Researchers have developed and demonstrated several machine-learning algorithms for interpreting bacterial cultures, conducting image analysis for microbial detection, and predicting antimicrobial susceptibility patterns. Thus, AI may most likely be the ultimate solution to the ever-increasing demand for improved results with shorter turnaround times. AI can also assist forensic microbiologists in crime scene investigations, as it can guide individual identification, cause and time since death, and manner of death. This review summarizes the application of AI in diagnostic microbiology for performing diverse sets of microbial investigations and is an essential aid in forensic microbiology.

Artificial Intelligence Revolutionizing the Field of Medical Education.

Medical education has ventured into a new arena of computer-assisted teaching powered by artificial intelligence (AI). In medical institutions, AI can serve as an intelligent tool facilitating the decision-making process effectively. AI can enhance teaching by assisting in developing new strategies for educators. Similarly, students also benefit from intelligent systems playing the role of competent teachers. Thus, AI-integrated medical education paves new opportunities for advanced teaching and learning experiences and improved outcomes. On the other hand, optical mark recognition and automated scoring are ways AI can also transform into a real-time assessor and evaluator in medical education. This review summarizes the AI tools and their application in medical teaching or learning, assessment, and administrative support. This article can aid medical institutes in planning and implementing AI according to the needs of the educators.

The Outbreak of SARS-CoV-2 in a Medical Ward and Its Containment: An Experience From a Tertiary Care Centre in North India.

Background Periodic outbreaks of SARS-CoV-2 in hospital settings amidst the recent pandemic are well known. However, the timely control of such outbreaks was key to preventing morbidity among vulnerable patients as well as reducing sickness absenteeism among healthcare workers. This is the first study of its kind in India. Methods An outbreak investigation was conducted between June 12 and July 18, 2020, at the All India Institute of Medical Sciences, New Delhi, India, during the first wave of COVID-19. Results A total of 27 individuals were infected during this time, including people visiting the hospital and healthcare workers. A thorough investigation led us to the epidemiological link between cases and allowed us to bring reforms to the existing hospital policy of screening and admission of COVID-19 patients and those suspected to have the infection. This experience helped us avoid future outbreaks during the second wave of COVID-19 in our hospital. Conclusion The SARS-CoV-2 virus is highly transmissible, especially in hospital settings due to the high burden of patients and close proximity between patients. Timely intervention is the key to effective control of hospital outbreaks, as it can avoid morbidity in patients and reduce sickness absenteeism among healthcare workers.

Breakthrough infection among healthcare personnel following exposure to COVID-19: Experience after one year of the world's largest vaccination drive.

Context: The COVID-19 vaccination drive globally was supposedly a game-changing event. However, the emerging variants of the virus and waning immunity over time posed new challenges for breakthrough infections. Standing at the frontline of defense against COVID-19, healthcare personnel (HCP) were vulnerable to such infections. Aims: This study estimates i) the vaccine breakthrough infections (VBI) among HCP following exposure to COVID-19 cases, and ii) the mean interval between the second dose of vaccine and laboratory-confirmed SARS-CoV-2 infection. Materials and Methods: A cross-sectional study was conducted including 385 HCP with a history of exposure to COVID-19 cases during January and February 2022. Demographic details and clinical and vaccination history were collected from the test forms and the Web-based hospital management system. Laboratory testing of COVID-19 was carried out by real-time RT-PCR test. Results: The majority of the HCP were males (262; 68.05%) and nurses (180; 46.75%) by occupation. Two doses of vaccines were received by 278 (87.7%) HCP. VBI was confirmed in 185 (66.55%) HCP. No significant difference in VBI between the COVAXIN and COVISHIELD recipients (P = 0.69) was observed. The interval between the second dose and confirmed SARS-CoV-2 infection was significantly higher (P < 0.00001) in COVAXIN recipients (median 228 days) than in COVISHIELD recipients (median 95 days). Conclusions: The incidence of VBI was very high among the HCP, but not statistically different among the COVAXIN and COVISHIELD-recipients. Waning immunity over time suggests boosting immunity with a third dose because of emerging variants.

Relevance of Conventional Microscopy in the Diagnosis of Mucormycosis during COVID-19 Pandemic.

Introduction: Mucormycosis is a lethal disease which bewildered the health-care community of India during the ongoing second wave of the COVID-19 pandemic. The diagnosis is challenging considering the poor isolation in culture. Aims: The aim of the study was to emphasize the utility of potassium hydroxide (KOH) mount examination using conventional light microscopy for early diagnosis of mucormycosis in resource-limited settings. Materials and Methods: A retrospective analysis of results for all the samples including tissue biopsies, swabs, and pus received in the laboratory for KOH microscopy was done, and results were recorded. The clinical and demographic details of the patients were collected from the hospital information system. Results: A total of 75 samples from 50 patients were received in the laboratory. Out of these, 43 samples from 35 patients showed fungal hyphae (38 patients with only nonseptate hyaline hyphae, 2 with septate hyaline hyphae, and 3 samples with mixed infections). All patients except one were positive for severe acute respiratory syndrome coronavirus 2 infection. The most common age group was 45-59 years (40%), followed by 30-44 years (34.28%) with a male predominance. There was a significant difference in hemoglobin A1C (P = 0.005) and ferritin (P = 0.017) levels between laboratory-confirmed mucormycosis patients and clinically suspected mucormycosis patients without confirmation. Conclusion: Early diagnosis and initiation of targeted therapy is the cornerstone for treating mucormycosis patients. Hence, a rapid and reliable mode of diagnosis is the need of the hour. Conventional microscopy is such a tool that may be used, especially in resource-limited settings.

A case of Klebsiella pneumoniae hypervirulent phenotype causing necrotizing fasciitis of chest wall: A mono-microbial entity emerging in the Indian subcontinent.

Necrotizing fasciitis of the chest wall or upper torso is a rare clinical entity. Monomicrobial Klebsiella pneumoniae as a causative agent of necrotizing fasciitis is far less common than the polymicrobial etiology. Here, we report a case of community-onset pyogenic necrotizing fasciitis caused by Klebsiella pneumoniae in an immunocompetent male of tribal background from the rural area of Jharkhand, India. The hypermucoviscous phenotype of the bacterium causing necrotizing fasciitis has been infrequently reported from the Indian subcontinent to date. The existence of multidrug resistant trait in the hypervirulent pathotype poses a unique challenge in treatment in such a case and emerges as a critical community health problem requiring prompt attention of the public health stakeholders. Thus, there is a need for widespread awareness for proper protocols in antimicrobial usage, infection control, early diagnosis, and prompt treatment.