SARS-CoV-2 infection is characterized by a highly variable clinical course with patients experiencing asymptomatic infection all the way to requiring critical care support. This variation in clinical course has led physicians and scientists to study factors that may predispose certain individuals to more severe clinical presentations in hopes of either identifying these individuals early in their illness or improving their medical management. We sought to understand immunogenomic differences that may result in varied clinical outcomes through analysis of T-cell receptor sequencing (TCR-Seq) data in the open access ImmuneCODE database. We identified two cohorts within the database that had clinical outcomes data reflecting severity of illness and utilized DeepTCR, a multiple-instance deep learning repertoire classifier, to predict patients with severe SARS-CoV-2 infection from their repertoire sequencing. We demonstrate that patients with severe infection have repertoires with higher T-cell responses associated with SARS-CoV-2 epitopes and identify the epitopes that result in these responses. Our results provide evidence that the highly variable clinical course seen in SARS-CoV-2 infection is associated to certain antigen-specific responses. One of the defining features of SARS-CoV-2 infection that predisposes patients to requiring critical care support is acute respiratory distress syndrome (ARDS) that often complicates the clinical course of many patients; thought to be secondary to an overactive and dysfunctional/dysregulated immune response8.In December 2019, SARS-CoV-2, a novel coronavirus was first reported in Wuhan, China, and was later named a pandemic by the WHO in March 2020. Notably, the clinical course of SARS-CoV-2 infection is highly variable with individuals exhibiting asymptomatic infection all the way through to requiring critical care support in the intensive care unit (ICU)18. In this effort, Adaptive Biotechnologies and Microsoft have partnered together to release ImmuneCODE20, a database of T-cell receptor (TCR) repertoires from individuals who were either sampled while acutely infected or recovered from SARS-CoV-2 along with derived specificities to SARS-CoV-2 epitopes through the use of the MIRA assay (Multiplex Identification of T cell Receptor Antigen Specificity)21.Given the extent of the morbidity and mortality that has been caused by SARS-CoV-2, there has been massive efforts across academia and industry to expedite our knowledge of the disease and its corresponding immune response to develop efficacious therapies and vaccines25. In the study, we sought to answer questions about the immunogenomic factors related to these antigenic determinants that may influence whether an individual develops severe versus mild SARS-CoV-2 infection by studying the T-cell repertoire in individuals during acute infection. By using DeepTCR, a deep learning software/framework for analyzing TCR-Seq26, to analyze the previously published and open access ImmuneCODE database, we show a TCR sequence concept signature (i.e. motif usage) that predicts severe versus mild SARS-CoV-2 infection. This work further provides a framework and example of the future use of artificial intelligence and machine learning for immune repertoire diagnostics and prognostics.While previous studies have focused on the transcriptional and cell profiling differences in severe infection, little work has been done to understand the antigenic determinants of clinical outcomes20. In the original database, there are 7 cohorts of patients or individuals who either were acutely infected or were sampled in the convalescent phase. Of the 7 cohorts, we noted that 5  contained patients who were sampled during active infection. Of these, 3 had clinical outcomes data that pertained to severity of illness . In the COVID-19-ISB cohort, severity of illness was measured via the WHO ordinal scale which grades degree of clinical intervention required for a given patient. In the COVID-19-NIH/NIAID and COVID-10-HUniv12Oct cohorts, there exists a label of whether the patient sampled required an intensive care unit (ICU) admission. However, when examining the proximity of sampling to active infection in the COVID-19-HUniv12Oct cohort, we noted that the majority of individuals admitted to the ICU were sampled after recovery and not during active infection 27.The ISB cohort was collected under the INCOVE project at Providence St. Joseph Health in Seattle, WA while NIH/NIAID was collected in Brescia, Monza and Pavia  during active infection, and provided to the NIAID in Bethesda, MD for DNA extraction. Since these two cohorts came from different parts of the world and institutions, we first wanted to examine how the demographics of the individuals in the two cohorts compared Table . We noteWe first wanted to investigate whether conventional measures of TCR repertoire diversity and abundances were associated with severity of SARS-CoV-2 infection. To do this, we collected sample-level TCR-seq data provided by Adaptive Biotechnologies within the ImmuneCODE database. We first noted when looking at these metrics, that many of them were significantly different in the two cohorts  from DeepTCR  or COVID(-) sequences. We then plotted these sequences by their prediction values to be associated with severe infection across both cohorts of patients  = 0.90, there was a statistically significant enrichment for SARS-CoV-2 specific TCRs in patients with severe infection. Finally, when stratifying the SARS-CoV-2 positive TCRs by open reading frame (ORF) and by CD8 or CD4 specificity, we noted in both cohorts that certain areas of the viral genome had increased likelihood of being targeted in severe infection as well as there also being differences in the CD8 versus CD4 response across multiple ORFs , and the predicted label was the cohort the given sample came from. We found that while not to the same predictive power as when the model was fit to TCR sequences, there still remained the ability for DeepTCR’s repertoire classifier to predict the cohort label from the “epitope repertoire”  or technical sources of variation , we cannot be sure of but the fact that a repertoire model trained on the corresponding “epitope repertoire” also provided predictive power to distinguish the cohorts suggests a relevant biological difference between the cohorts. Furthermore, when looking at the SARS-CoV-2 antigenic signature in both cohorts as it related to the predictive signature of clinical severity, we noted a stronger association between the predictive signature in the ISB to the antigenic signature than in the NIH/NIAID cohort. One possible explanation of this is due to the cohort of patients the MIRA assay was performed. If the MIRA assay patients were collected in the USA, the SARS-CoV-2 response may be different in this demographic versus the Mediterranean Italian cohort in the NIH/NIAID cohort. Ideally, one would have MIRA data matched for the demographics of the cohort one was training the repertoire models on. These results should encourage investigators in the future to study the host-specific factors that could shape the antigen-specific immune response in patients with not only just SARS-CoV-2 but all other insults whether they be pathogenic, autoimmune, or oncological in origin.A few limitations exist in this study that are important when considering the interpretations and conclusions of this work. The first major limitation we found as was highlighted in the cross-validation of the models between cohorts was the predictive signature was not shared between the NIH/NIAID and ISB cohorts. We noted that there are multiple reasons this could be the case. The first reason one must consider when using machine learning models is over-fitting of the model. While this could be playing a role in why the models did not cross-validate, there are several other notable reasons that might explain the lack of generalization. First, as was described in the demographics of the cohorts, these two cohorts were notably different in biological sex and race. Previous studies have revealed differences in clinical outcomes as a function of sex and raceAnother significant limitation, particularly of the ImmuneCODE database is the clinical outcomes data associated with the repertoire data. As was noted, not only do two of the five cohorts with patients who were sampled while acutely infected lack clinical outcomes data, the HUniv12Oct cohort had collected outcomes data at different time points with respect to the peak of infection. Given the nature of how immune responses evolves over the course of infection, further studies should provide more descriptive annotations of when samples were collected with respect to symptom onset, if/when a patient was admitted to the ICU, and if/when they recovered. Furthermore, sampling from multiple time points over the course of illness would also help distinguish host-specific versus disease specific features of the immune repertoire as they relate to clinical outcomes. Since the cohorts of patients we studied here were only sequenced during the acute phase of their infection, one cannot determine if the predictive features were disease of host-specific.In conclusion, SARS-CoV-2 represents an interesting scientific and clinical phenomena where a single pathogen can cause a highly variable clinical presentation, which has led scientists to look for immune related factors that may explain this variable presentation. Here, by applying deep learning of the immune repertoire, we reveal a TCR signature that is predictive of severe versus mild infection, which not only provides insight into the immune response to SARS-CoV-2 but also provides a framework to study host-specific differences in immune repertoire as they relate to clinically relevant outcomes.20. Data was pre-processed and organized to be compatible with DeepTCR. Steps to pre-process and organize data can be found in scripts in the code repository (referenced under Code availability). The data in this study consists of 1) clinical metadata, 2) TCR repertoire data, and 3) antigen-specific TCR data collected via the MIRA assay21. Severity of illness was determined either by whether the individual had an ICU admission (NIH/NIAID) or whether their WHO ordinal scale was greater than 4 (ISB).All data used in this study was collected from the publicly available ImmuneCODE Open Access DatabaseLogistic regression models were fit to predict severity of SARS-CoV-2 infection from aggregate TCR metrics provided under the ImmuneCODE database. Models were implemented with scikit-learn python package and performance was assessed via 2-fold cross-validation with 100 iterations to obtain per-sample prediction. Performance was assessed with Receiver Operating Characteristic (ROC) curves and Area Under Curve (AUC) measurements.DeepTCR’s multiple instance repertoire classifier was used to fit predictive models based on the TCR repertoires of individuals who were acutely infected with SARS-CoV-2 and had documented clinical outcomes in terms of severity of infection. Models were fit in Monte Carlo cross-validation fashion and per-sample predictions were averaged over all Monte Carlo simulations. All DeepTCR hyper-parameters can be found under training scripts within the code repository (referenced under Code availability). Performance was assessed with ROC curves and AUC measurements.https://pypi.org/project/DeepTCR/)26.All statistical tests applied to data were implemented with the scipy.stats module. Classical machine learning techniques and performance metrics were implemented with scikit-learn. Deep learning models were implemented with DeepTCR (v2.0.10) python package (Supplementary Figures.Supplementary Tables.


Effective monitoring of antibiotic resistance genes and their dissemination in environmental ecosystems has been hindered by the cost and efficiency of methods available for the task. We developed the Diversity of Antibiotic Resistance genes and Transfer Elements-Quantitative Monitoring (DARTE-QM), a method implementing TruSeq high-throughput sequencing to simultaneously sequence thousands of antibiotic resistant gene targets representing a full-spectrum of antibiotic resistance classes common to environmental systems. In this study, we demonstrated DARTE-QM by screening 662 antibiotic resistance genes within complex environmental samples originated from manure, soil, and livestock feces, in addition to a mock-community reference to assess sensitivity and specificity. DARTE-QM offers a new approach to studying antibiotic resistance in environmental microbiomes, showing advantages in efficiency and the ability to scale for many samples. This method provides a means of data acquisition that will alleviate some of the obstacles that many researchers in this area currently face. Smith et al. present DARTE-QM, a highthroughput sequencing method for screening environmental DNA samples for antibiotic resistance genes on a broad scale. This method is demonstrated as effective on soil, manure and livestock fecal samples, as well as a synthetic mock-community reference. Characterization of the presence and abundance of ARGs, i.e. the resistome, in environmental microbiome samples has stood as a major challenge for researchers monitoring these events4. Such studies have been impeded by the broad diversity of the genes, their low presence in most natural environments, the difficulty of extracting DNA from microbes in those environments, and their association with mobile genetic elements accounting for approximately one-quarter of the genetic material in these microbiomes5.The global spread of organisms possessing antimicrobial resistance (AMR), and their associated antibiotic-resistant genes (ARGs), has posed an increasing threat to the health of both humans and animals alike6. This approach is dependent on the availability of a gene reference database to classify reads as ARGs sequences but does not require a priori knowledge of which genes constitute the resistome being investigated7. Despite being effective for the task, the cost per sample of employing metagenomic methods to elucidate resistomes often inhibits studies from large-scale analyses. This cost is driven by the necessity of needing to indiscriminately sequence all DNA within an environment, of which the resistome often comprises only a fraction of a percent. Therefore, without sufficient sequencing depth and coverage, ARGs may be either underrepresented or undetected8. Methods to enrich for ARGs in sequencing libraries would allow for increased information per sample9.The genetic diversity of ARGs has made targeted sequencing approaches non-trivial and has led to the application of whole-genome shotgun metagenomic methods for the characterization resistomes10. This approach utilized streptavidin-coated magnetic beads to capture 80-mer bait sequences to target genes of interest. The bait-and-capture method has been well-suited for the characterization of low- and high-abundance ARGs, and has demonstrated the ability to differentiate resistomes from different sample sources11. Another method of targeted gene sequencing that has been used for ARG characterization involves custom primers for performing a PCR-based amplicon library preparation. This type of sequencing has been used extensively in microbiome studies for community profiling via bacterial 16S rRNA genes and combines barcoded adapters to differentiate hundreds of samples pooled in a single library preparation12. It has previously been limited in the number of primers that could be incorporated for a single library, but a more recent version of amplicon library preparation for multiplexed primers now exists and has been implemented for biomarker detection in clinical studies16.In the effort of finding a more efficient means for screening ARGs DNA sequences, a method implementing a bait-and-capture system to identify specific ARG targets was developedDiversity of Antibiotic Resistance genes and Transfer Elements-Quantitative Monitoring (DARTE-QM). Our study was designed to demonstrate that DARTE-QM offers practical application to ARG screening through its ability to simultaneously detect and quantify hundreds of ARGs residing in samples from various environments and that it can achieve high accuracy and sensitivity identifying ARG targets.Our study demonstrates the usage of this multiplexed amplicon library preparation for the detection of ARGs in environmental samples. We have termed our method of implementing this technology the DARTE-QM employed 796 primer pairs designed to target 67 antibiotic-resistant families and 662 ARGs, as well as a synthetic oligonucleotide reference sequence and the V4 region of the 16S rRNA gene, in a multiplexed amplicon library preparation . On account of the numerous and diverse gene targets in the sequencing library, processing of DARTE-QM data required amendment of the traditional microbiome analysis pipelines . While overall, target relative abundances were observed to be similar compared to the theoretical estimates, the quantification of particular ARGs, such as transposon-associated lnuC conferring resistance to lincomycin, were found in higher abundance by DARTE-QM. Meanwhile, others such as mecA conferring methicillin-resistance were found to be underrepresented. There were also some ARGs detected in mock sample libraries that were not found within the mock draft genomes, these 36 ARGs represented 5.8% of all ARG reads from the mock-community samples. With regard to the synthetic oligonucleotide, there was a strong correlation observed reads  between the read abundance produced by DARTE-QM and the experimental concentration.Success for DARTE-QM was evaluated on both specificity and sensitivity, determined using the mock-community microbiomes. Construction of the mock-community from DNA sourced from sequenced genomes allowed for comparison of a theoretical profile Fig.  to our ep = 0.038; manure-A + soil-A, p = 0.035; swine fecal, p < 0.001, pairwise-Wilcoxon). Across all samples, an inverse linear relationship (R2 = 0.68)  portion of variation observed in the resistome profiles. DARTE-QM identified specific ARG patterns which distinguished resistomes sourced from different environmental samples, the most notable of which was within swine fecal samples where a distinctive presence of genes related to lincosamide and aminoglycoside resistance were observed. In the soils, with varied field management histories of swine and bovine manure amendment (soils B and C), we observed distinct characteristics of resistomes as well. Bovine manure-associated soils were found to be enriched with genes associated with resistance to aminoglycosides and sulfanomides, whereas the swine-manure-amended soils were replete with aminoglycoside, lincosamides, and erythromycin-resistance-related genes.DARTE-QM detected 240 ARG targets across all samples in this study . DNA from the same sources were used for sequencing with DARTE-QM study for comparison of the two methods. Metagenomes from the soil samples had an average of 241 ARG reads and were excluded from analysis; DARTE-QM returned a mean abundance of 5839 ARG reads in those same samples. Four swine-manure samples from the metagenome study yielded a mean ARG abundance of 76,226 reads, and the 12 manure-treated soil samples yielded an average of 7377 ARG reads. DARTE-QM produced mean abundances of 32,678 and 13,488 ARG reads in the same samples.Soil-column samples used in this study had been previously characterized through metagenome sequencingux and Mex ARG Classes), which were not targeted by DARTE-QM. A direct comparison of both approaches constrains the metagenomes to those targeted by the primers of DARTE-QM .One limitation of DARTE-QM is that the number of reads that were observed in the dataset but not able to be classified as one of the targeted ARGs. Many of these reads were characterized by the presence of a primer but with no sequence homology to a known sequence. While it is possible that these genes could be non-specific amplification of primers targeting other biological genes, the presence of poly-A and poly-T sequence patterns, like those seen in single-cell amplification24. Artifacts can be filtered through target alignment and classification, with sufficient sequencing coverage, however, future studies aimed at improving the sequencing library preparation and amplification for these sample types would be beneficial. In manure-associated samples, it is likely that the high organic matter content inhibited amplification, and modifications to DNA extraction protocols for its targeted removal should improve performance27. The DNA used in this study had previously been used for amplification of the 16 S SSU rRNA gene and/or metagenome libraries with success. Thus, it also likely that primer optimization would benefit detection of specific ARGs. In this application, DARTE-QM detects hundreds of ARGs simultaneously, increasing the probability for amplification artifacts29. For future studies, optimization for select gene targets would be recommended.Generally, in samples where there was high-quality DNA and fewer unique ARGs , DARTE-QM successfully characterized resistomes. Many of the samples that produced the highest percentage of reads as artifacts and/or failed quality control due to insufficient reads were from soils with a history of manure application or swine fecal samples -IIa, is located on an IncI2 plasmid, which conversely is a low copy number plasmid31, and is consistent with our results. Additionally, there were ARGs identified in mock samples that were not present in draft mock genomes. One explanation for these observations is the mis-assembly or absence of these genes in the draft mock genomes, as ARGs often contain repetitive elements and are difficult to assemble without sufficient coverage. Another possibility is related ARGs not being able to be distinguished by alignment, and the reads being misclassified as the similar gene.In cases where DARTE-QM abundances varied the most from the expected estimates, the gene targets were often associated with plasmids and other mobile elements. Multiple copies of these genes can exist for each individual cell, which would result in the genes being underestimated. For instance, The optimization of future versions of this platform for specific gene targets is possible. In the case of plasmid-associated genes or genes for which amplification failed, PCR conditions could be varied for optimal amplification and specific gene standards could be included for absolute quantification. Further, it is possible to select primers for DARTE-QM to target specific resistance classes, rather than the broad array of targets demonstrated in this study. In comparing DARTE-QM ARGs to those found in similar metagenomes, the ARG classes were found to be largely similar but relative abundances differed. These differences reflect contrast between the two technologies, with DARTE-QM determining relative abundances of ARGs within amplified targeted genes and metagenomes not biased by primer-specific targets. In other words, low abundant genes in metagenomes may be more difficult to detect in metagenomes because of the limits of detection of sequencing coverage and benefit with targeted amplification in DARTE-QM.r2 = 0.91), illustrate that DARTE-QM is affected more by the amount of DNA available for the primer than by the competition between primers to find targets. Finally, comparisons to metagenomes suggested that DARTE-QM could detect similar measures of diversity of ARGs from samples. While the distributions of ARGs within the resistomes varied between DARTE-QM and metagenome resistomes, the differences between environmental sources could be distinguished, and broad patterns of resistance classes were similar. Combined, these results confirm that the primers used for DARTE-QM successfully amplified ARGs despite the potential for interference when simultaneously amplifying multiple gene targets in uniform conditions.There was evidence of DARTE-QM’s ability to quantify ARG presence using the correlation of read count to the varying concentrations of our synthetic oligonucleotide reference in the mock-community samples. Those results, though not a perfect correlation . The ability to affordably scale for numerous genes and samples provides a much-needed resource for not only the field of AMR but for researchers interested in scaling functional gene characterization. Finally, we recognize that this is the first evaluation of DARTE-QM and that there are significant opportunities to further develop this approach for more targeted study. Given the simultaneous amplification of primers in DARTE-QM, we expect that the more specific the gene targets, the more optimized the library preparation can be for reliable quantification.32, associated with 67 antibiotic resistance families. ResFinder was selected on account of its manual curation of genes associated with acquired antibiotic resistance. An additional 409 ARG-associated sequences chosen as well, which had previously demonstrated high prevalence in animal agriculture based on their relative abundance in previously published metagenomes20. To abide with the limitation of the number of allowed primers with the Illumina TruSeq library preparation, later described, the conglomerate of the chosen sequences was ultimately curated to representative sequences that targeted genes deemed of most interest to antibiotic resistance in agriculture. A single 300 bp synthetic oligonucleotide sequence was designed for use as a reference (reference target gene in Supplementary Data 33 to target the V4 variable region of the 16S rRNA gene.Antibiotic resistance gene (ARG) targets for primer design were chosen and aggregated from two sources. There were 2472 sequences were obtained from the ResFinder database 34 product minimum length = 220, product maximum length = 330, Oligo minimum size = 22, oligo maximum size = 30, maximum mismatch = 0, temperature minimum = 55, temperature maximum = 63, hair-pin max = 24, homo-max = 35, assaymax = 30, degenmax = 6, noTEendfileter = T, nopoly3GCfilter = T, polyrunfilter = 4, GCfilter min = 0.15 GCfilter max = 0.8. This produced 1340 primers   and were used for comparisons to DARTE-QM results (10-30 million reads per sample).To evaluate the practical implementation of DARTE-QM using environmental samples, we used 19 environmental samples originating from intrinsic and manure-amended soils, swine manures, effluent from manure-amended soils, and swine fecal samples that passed quality filters. Samples were selected from two previously published studies. In the first study, laboratory soil columns and rainfall simulations were used to evaluate the influence of swine-manure amendment on soils and effluent38 40, requiring a minimum overlap of 10 bp. Merged reads were aligned against our database of targeted sequences using BLAST (v2.10)41. Successful alignment required a minimum of 90 bp and 98% similarity. For paired-end reads that were not able to be merged, each was aligned to the target database individually. If both reads aligned to the same target, the read with the longest alignment was selected as the representative sequence. We defined a successful amplification as a read for which a primer sequence was present, and the amplified sequence aligned to the primer’s intended target with at least 90 bp length and at least 95% identity. Reads identified as having 16S rRNA primers were classified using the RDP Classifier42 with default parameters, and then unpaired reads selected in the same manner as for ARGs.All analysis was done in the statistical language R, unless otherwise stated. DARTE-QM sequences were quality checked using FastQC v0.11.9)1.938  which contributed to the observed resistome variation. Cluster analysis was performed using k-means.erm35 and tetM genes. The forward reads of sequences that aligned to the DARTE-QM gene targets were clustered at 97% sequence similarity with CD-HIT (v4.6.7)43. Clusters containing greater than ten sequences were considered in our results, with representative sequences for each cluster determined by CD-HIT. Alignment was performed and visualized with JalView using ClustalW (v2.11.1.3)44.To evaluate the presence of gene sequence variants, the observations of variants were estimated for sequences associated with the Further information on research design is available in the Transparent Peer Review FileSupplementary InformationDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Supplementary Data 5Supplementary Data 6Supplementary Data 7Supplementary Data 8Reporting Summary


Coronavirus disease 2019 (COVID-19) represents a major challenge in the management of patients with hematologic malignancies. Individuals with plasma cell dyscrasias, including multiple myeloma, are at increased risk of developing severe disease. Furthermore, immunosuppressant agents, which represent an important component of multiple myeloma treatment, may increase the risk of serious infection; thus, treatment regimens may need to be modified in some patients. The pathogenesis of COVID-19 is incompletely understood and much remains to be established regarding cancer care in the setting of this new global health threat. We report a case of multiple myeloma remission that occurred after a single cycle of chemotherapy in a patient with COVID-19. In addition, we discuss possible mechanisms underlying this surprising observation. The findings warrant further investigation and may have important implications for the management of multiple myeloma and other plasma cell dyscrasias in the age of COVID-19. The COVID-19 pandemic, caused by the novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has had a major impact on the care of cancer patients. Cancer patients tend to have higher rates of COVID-19 . The undPatient information: a 76-year-old female was referred to the oncology clinic for further evaluation of abnormal laboratory studies, including serum protein electrophoresis with M-spike elevated at 1.65 g/dL and elevated IgG-type kappa monoclonal protein on immunofixation. She was noted by her primary care physician to have progressively worsening renal function and elevated serum globulin levels over the previous year . There was no significant lymphadenopathy.Diagnostic assessment: a positron emission tomography scan was negative for extramedullary sites of activity or bone disease. Peripheral blood smear showed mild absolute neutropenia. There was no laboratory evidence of anemia or hypercalcemia. Total 24-hour urine protein was 1475 milligrams per day (reference range: 40 - 150 milligrams per day). Serum free light chains were markedly elevated . A single dose of filgrastim 480 mcg was administered. The fevers resolved and the patient was discharged home the following day with a five-day course of levofloxacin 500 mg per os once daily and acyclovir 400 mg per os twice daily and asked to self-quarantine.The patient returned to the emergency department seven days later, now with dyspnea and fatigue in addition to a persistent dry cough, chills, and sore throat. Vital signs were significant for fever (temperature: 101.8°F) and hypoxia . Laboratory studies again showed neutropenia .Therapeutic intervention: she was hospitalized and started on a ten-day course of dexamethasone 6 mg per os daily as well as remdesivir (200 mg once and 100 mg daily for 4 days). In addition, a single unit of convalescent plasma was administered. She was discharged eleven days later after improvement in her respiratory status.Follow-up and outcomes: the patient was seen in the teleoncology clinic seven weeks later, where follow-up laboratory studies showed dramatic improvement in myeloma disease markers  remission in a patient who received a single cycle of CyBorD and subsequent developed COVID-19. The treatment response was confirmed with repeat bone marrow studies and laboratory studies demonstrating improvement in renal function and serum monoclonal protein levels. The kappa/lambda ratio began to decrease to less than 4: 1 after a single cycle of CyBorD and continued to decrease following the diagnosis of COVID-19 . Accordiet al. successful treatment was defined as ≥ 40% of patients achieving a very good partial response or better after four cycles of CyBorD. The Reeder group found an 80% reduction in major protein components after two cycles (eight weeks) of CyBorD therapy. In our patient, a comparable but deep treatment response was seen after only one cycle of CyBorD and subsequent COVID-19. It is therefore conceivable that treatment of the infection and/or the infection itself altered the course of the underlying malignancy.The treatment response demonstrated by our patient is typically observed after four complete cycles of CyBorD therapy . In a raWe postulate that one or several of the pharmacologic agents used in the COVID-19 treatment regimen-including dexamethasone, remdesivir, and convalescent plasma-may have interrupted signaling pathways needed to maintain myeloma cell production and augmented the cytotoxic effects of CyBorD, resulting in dramatic clearance of myeloma cells from the bone marrow. Secretion of IL-6 by bone marrow stromal cells is required for the growth of multiple myeloma cells ; this inAn additional component of the COVID-19 treatment regimen that may have affected the behavior of MM in our patient is convalescent plasma, which is used to increase humoral immunity against structural COVID-19 proteins. MM is characterized by dysfunction in both humoral and cellular immunity, which affects immune surveillance and allows for advancement and escape of clonal cells [in vitro by exploiting intercellular adhesion molecule 1 (ICAM-1) [Augmentation of MM treatment with non-chemotherapeutic agents is not without precedent. Other medications not used in traditional MM therapy have been shown to enhance clearance of myeloma cells from the bone marrow. Examples include metformin, which has been reported to decrease IL-6 expression in MM cell lines when used synergistically with dexamethasone, bortezomib, and pomalidomide . In addi(ICAM-1) . Interes(ICAM-1) . It therFinally, despite the dramatic response, the above factors may not have played a major role at all. It is reasonable to suggest that our patient´s MM was very sensitive to the chemotherapy regimen and thus her remission was unrelated to COVID-19. Larger observational studies are warranted to clearly define this relationship.The effect of COVID-19 and/or COVID-19 treatment on MM remains to be definitively established. Although COVID-19 outcomes among patients with malignancy are generally poor, we describe an unusual case in which MM remission was achieved following a single cycle of CyBorD and subsequent development of COVID-19. The underlying cause of this surprising finding may be related to the COVID-19 treatment regimen-which included dexamethasone and convalescent plasma-or to intrinsic properties of SARS-CoV-2. Modification of dexamethasone dosing in patients with MM may prove beneficial. Furthermore, proteins produced by SARS-CoV-2 may have yet undiscovered oncolytic properties. Future investigation may help to clarify the relationship between COVID-19 and hematologic malignancies.


Proportion of residents aged <15 years, residents with a university degree, residents with secondary education, extra-urban mobility, presence of home for rent, and presence of more than five homes per building were found to increase the risk of SARS-CoV-2 incidence. Conclusion: Routinely collected socio-demographic data can be predictors of SARS-CoV-2 risk infection and they may have a role in mapping high risk micro-areas for virus transmission.Background: The present study analysed SARS-CoV-2 cases observed in Sicily and investigated social determinants that could have an impact on the virus spread. Methods: SARS-CoV-2 cases observed among Sicilian residents between the 1 February 2020 and 15 October 2020 have been included in the analyses. Age, sex, date of infection detection, residency, clinical outcomes, and exposure route have been evaluated. Each case has been linked to the census section of residency and its socio-demographic data. Results: A total of 10,114 patients  were analysed: 45.4% were asymptomatic and 3.62% were deceased during follow-up. Asymptomatic or mild cases were more frequent among young groups. A multivariable analysis found a reduced risk of SARS-CoV-2 cases was found in census sections with higher male prevalence (adj-OR = 0.99, 95% CI = 0.99–0.99;  The emergence of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has significantly changed the lives of a large part of the world population . In justHowever, socio-demographic factors play a crucial role in shaping the pattern of COVID-19 positive cases and deaths across the globe. Some preliminary data would indicate that social determinants and existing health inequities could be linked to SARS-CoV-2 infection diffusion and COVID-19 severity ,5. ZhangUnfortunately, a large proportion of studies evaluated social determinants at a national or regional level, whereas analyses carried out on microdata and at an individual-level could support a more accurate evaluation of the risk. Such data, when available, could provide essential information to support the government’s decision making body to strategically manage health emergencies in the present and in future if similar situations were to arise. In particular, since these conditions specifically put an individual at higher risk of being infected with SARS-CoV-2, populations that are considered to be more vulnerable according to these criteria could be given the resources needed to endure infectious outbreaks.The aim of the present paper was to analyse the characteristics of the first 10,114 cases observed in Sicily, Italy and investigate, from an ecological point of view, some social determinants that could have had an impact on the SARS-CoV-2 spread at a census section level.This study has been carried out by considering all SARS-CoV-2 cases observed among Sicilian residents between the 1 February 2020 and 15 October 2020. Sicily is the largest island in the Mediterranean Sea and one of the most populous (about five million inhabitants) of the 20 regions of Italy. The first case of SARS-CoV-2 in Sicily was observed on 24 February 2020.–Being a resident of Sicily;–Having a laboratory-confirmed SARS-CoV-2 positive result of reverse transcriptase real-time polymerase chain reaction  of nasal, pharyngeal, or nasopharyngeal swabs.In this study, SARS-CoV-2 patients have been considered eligible if they met the following inclusion criteria:SARS-CoV-2 positivity in the previous months have been confirmed according to the notification status in the regional section of the national database collected and updated on a daily basis in the Sicilian region and provided by the Istituto Superiore di Sanità (ISS).For each patient, the following information has been collected: age, sex, date of infection detection, residency, clinical outcomes , and exposure route . The clinical outcome should be considered as the worst clinical situation experienced by each patient during the disease course.n cases/total residents * 100,000) and census sections with SARS-CoV-2 rates higher than the regional value  have been considered at higher risk. The study was conducted according to the principles stated in the Declaration of Helsinki.Patients included in the analyses were anonymized and geocoding was performed by automated information system in accordance with a respect for privacy. Cases were thus attributed to section census and incidence rates were obtained for each small geographic area. Census section data were obtained by the last available census report that has been carried out by the Italian National Institute of Statistics (ISTAT) in 2011 . IndividThe normal distribution of continuous variables was assessed by Shapiro–Wilk test, and since all variables have been found to be non-normally distributed, they have been presented as median and interquartile range (IQR). Categorical variables have been summarized as absolute number (percentage). Incidence rates  and 95% confidence intervals (95% CI) were calculated via Byar’s approximation.Mann–Whitney rank sum test (for non parametric continuos variables) and chi-square test  were used to compare variables between census sections with SARS-CoV-2 rates higher than regional value vs. SARS-CoV-2 rates lower or equal to regional value. A backward stepwise multivariable logistic model was built to determine the association between sociodemographic variables and SARS-CoV-2 rates . The output of the regression model has been summarized as odds ratios (ORs) and 95% confidence intervals (95% CI). In the final regression model, missing variables have been deleted from the analyses.p ≤ 0.05. Analyses were performed using R Software analysis 3.6.1. R Foundation, Vienna, Austria [All statistical tests were two-tailed, and statistical significance was defined as  Austria .As of 15 October 2020, a total of 10,788 SARS-CoV-2 cases were observed in Sicily and 10,114  were residents of Sicily and thus considered in the analyses. For a large majority of patients (61.3%), the route of exposure was not well defined whereas home was the most frequent (15.95%) among those that have been reported. About 45% of all patients were asymptomatic and the fatality rate was 3.62%.From The main investigated socio-demographic risk factors are reported in The emergence of COVID-19 has changed not only the lives of a large part of the world population but also the classical approach of scientific research. The need to construct new knowledge about epidemiology, transmission, clinical characteristics, diagnostics, testing, and screening of this novel virus have required to us to share data in a timely manner. Unfortunately, in this context some issues have been neglected and there is a proportional paucity of studies on socio-demographic factors although some increasing evidence could support the strategic role of these determinants in reducing the diffusion of the outbreak. Our study aimed to investigate this topic and tried to understand the possible role of sociodemographic characteristics in determining SARS-CoV-2 cases in very small geographic areas during a low-incidence period.Our main and most significant finding is that sociodemographic variables, which change geographically, could have a direct impact on the increase in COVID-19 incidence rates. In particular, we found that some factors seem to have a strongly statistically significant impact in reducing the risk of SARS-CoV-2 presence whereas others could increase this risk.Among these latter variables, a particular role was observed for relative frequencies of residents aged < 15 years, home for rent in the census section, and extra-urban mobility. All three of these factors have been independently associated with an increase in the risk of about 10% per percentage increase in each variable. The reasons that could explain these strong associations seem to have both biological plausibility and consistency with some other studies.p < 0.001), although this association was not confirmed by multivariable analyses. However, several studies are suggesting that children could contribute to increasing the risk of SARS-CoV-2 transmission. In particular, children shed viral SARS-CoV-2 RNA (whether viable or not) in a similar manner to adults [As in our study, Ferreira et al.  observedo adults  but, wito adults , exactlyA second important risk factor in this study was the relative presence of home for rent in a census section. In our opinion, and as reported by others , this coAs reported by others, these indices include material circumstances, the social environment, and psychological factors. Thus, these differences may not be primarily driven by income but have more to do with variations in social participation and ability to control life circumstances . The incThe contribution of the social contacts seems to be confirmed by the higher risk in census areas where a higher percentage of residents are involved in extra urban mobility for working activities. Overall, our results showed that some sociodemographic characteristics could affect environmental exposure to social contact with increased rates of COVID-19 infection. In this sense, immigrants could have been subjected to a reduced risk. During the lockdown, immigrants have been at higher risk of job loss or reduced work hours, and it cannot be excluded that they have also reduced their social contacts with the local population. All these conditions could have decreased their risk of getting the SARS-CoV-2 infection, whereas a further difficulty in accessing the healthcare system could have reduced their chances of being tested and notified.A reduced risk of SARS-CoV-2 was also found in the census section with higher male prevalence. We are convinced that this finding could be related to the higher number of social contacts that women are used to having because of cultural roles and gender norms. In this sense, female gender has been associated with a higher likelihood of employment in essential services like health care and service industries  or greatFinally, we have observed higher SARS-CoV-2 incidence rates in census sections with higher relative presence of more than five homes per building. This result could be easily explained by considering that densely populated areas could facilitate community spread of infectious diseases .A major strength of our study is that it has included the total Sicilian population and, thus, our analysis does not suffer from potential selection bias. Moreover, we have considered a phase with low incidence during the which it is expected that the detection rate may be not affected by stress in healthcare facilities.Despite of these strengths, we cannot exclude some important possible limitations. Firstly, sociodemographic data was obtained from a single decennial census of the population that was performed ten years 2011) before the present study. Thus, such classifications are questionable because of the changing composition over time of small geographical areas . Secondl11 beforeDespite the previously reported limitations, this is one of the first studies that evaluates the role of routinely collected socio-demographic data as a predictor of SARS-CoV-2 risk infection. The very high number of included cases  and census areas  makes our estimates of particular interest and suggests that socio-demographic data may play a role in mapping high risk micro-areas for current and future epidemic scenarios. Further analyses and studies could be required for corroborating these findings and increase their generalizability and accuracy during a period with higher incidence rates and more pronounced virus circulation.


For quality, interpretation, reproducibility and sharing value, microscopy images should be accompanied by detailed descriptions of the conditions that were used to produce them. Micro-Meta App is an intuitive, highly interoperable, open-source software tool that was developed in the context of the 4D Nucleome (4DN) consortium and is designed to facilitate the extraction and collection of relevant microscopy metadata as specified by the recent 4DN-BINA-OME tiered-system of Microscopy Metadata specifications. In addition to substantially lowering the burden of quality assurance, the visual nature of Micro-Meta App makes it particularly suited for training purposes. Micro-Meta App is an intuitive, highly interoperable, open-source software tool designed to facilitate the extraction and collection of relevant microscopy metadata as specified by recent community guidelines. Currently, documentation of imaging experiments is seriously impaired by the lack of easy-to-use software tools that facilitate the extraction and collection of relevant microscopy metadata. Micro-Meta App is an intuitive open-source software designed to tackle these issues that has been developed in the context of the 4D Nucleome (4DN) consortium3, and of nascent global bioimaging community organizations, including BioImaging North America (BINA)5 and Quality Assessment and Reproducibility in light microscopy (QUAREP-LiMi)8, whose goal is to improve reproducibility, data quality and sharing value for imaging experiments. The App provides a visual interface for building comprehensive descriptions of the conditions used to produce microscopy datasets as specified by the 4DN-BINA-OME tiered-system of Microscopy Metadata specifications13. To ensure wide adoption by microscope users with different skill levels and needs, Micro-Meta App is ideally suited for training purposes and interoperates closely with MethodsJ2 (refs. 15) and OMERO.mde17, two complementary tools described in parallel manuscripts.For microscopy images to be appropriately interpreted and reproduced, and to satisfying Findable Accessible Interoperable and Reusable (FAIR) principles19 of microscopy results, the establishment of community-driven, documentation and quality control (QC) specifications for light microscopy would make it possible to faithfully interpret scientific claims, facilitate comparisons within and between experiments, foster reproducibility and maximize the likelihood of data reuse25. First and foremost, such information would facilitate the compilation of accurate Methods sections for scientific publications29. Furthermore, it would provide clear guidance to microscope and software manufacturers about what information should be written automatically in the headers of image files during image acquisition to ensure scientific rigor. Finally, machine-actionable versions of the same information30 could be uploaded alongside image-datasets on the growing number of public image data resources43 that allow the deposition of raw image data associated with scientific manuscripts, emulating for light microscopy the successful path that led to genomics community standards48.In addition to providing essential information about the provenance 3 and the CZI-funded BINA5 have recently proposed the 4DN-BINA-OME (NBO) Microscopy Metadata specifications13. These specifications consist of an extension of the Open Microscopy Environment (OME) data model 52, which is organized in three tiers 55 compatible framework, guiding scientists as to what provenance metadata and calibration metrics should be afforded to ensure quality, reproducibility and value for different categories of light microscopy experiments.To promote the development of shared standards, the NIH-funded 4DN57, current tools offer limited functionalities, and are not integrated with community standards. Here, we present a suite of three interoperable software tools  OMERO.mde, which emphasizes the development of flexible, nascent specifications for experimental metadata58 and (2) the ImageJ/Fiji MethodsJ2 plugin15, which automatically generates Methods for scientific publications. Here, we present Micro-Meta App  to easily extract all available metadata from microscope configuration and image files and produce well-documented, high-quality, reproducible and reusable datasets. Despite some advancesta58 and  the Imag52 and, as a consequence, is extremely variable, interfering with quality assessment, reproducibility and meaningful reuse of third-party datasets  and associated with related Microscope.JSON files and image-datasets to ensure proper imaging experiment documentation.To document the conditions used to produce specific image-datasets, ‘Manage Settings’ Figs.  (1) autoIn the absence of tools that expedite image data documentation and QC, the metadata provided by manufacturers often does not align with existing minimal information criteria ows Fig. :In ‘Mana63.Detailed descriptions of the functionality, implementation and documentation material of Micro-Meta App are available in 83. The most striking result  specific problem sets and (2) self-driven exploration of microscope components, functions and imaging modalities. The success of these pilots indicates that Micro-Meta App could be used in online teaching-modules  Training Resources)85 for familiarizing users with the intricacies of specific instrument hardware configurations and for the interactive application of microscopy concepts.Micro-Meta App provides a digital representation of freely configurable microscopes, ideal for microscopy custodians to provide users with a detailed inventory of all available microscopes and for teaching purposes , online training and workshops62, we are developing exchange-sites for microscopy metadata JSON files, similar to ImageJ/Fiji plugin repositories. Furthermore, integration with the Research Resource ID (RRID) effort93 could promote the recognition of microscope configurations as a quantifiable scientific output, providing credit to the work of imaging scientists.Creation of Instrument and Hardware components databases: while engaging with microscopy manufacturers to ensure the full automation of light microscopy data provenance and QC reporting, it will be necessary to engage the community to reduce the burden imposed on individual microscope custodians and users that need to document similar imaging experiments, therefore maximizing their adoption of community standards. For this purpose, and echoing 4DN15) will be adapted to use Micro-Meta App Settings.JSON files as sources of image acquisition settings and QC metadata.Further integration with MethodsJ2: Micro-Meta App will be extended to automatically generate text for scientific publications and MethodsJ2  implementations. The first was designed to facilitate integration of the software into third-party web portals, such as the 4DN-Data Portal)13.JSON schema: a JSON file or a series of files that define the underlying schema, which are used to construct the graphical user interface (GUI) of the application on the basis of the 4DN-BINA-OME Microscopy Metadata specificationsDimensions and coordinates: a JSON file that codifies the dimensions of the canvases used by the Manage Instrument GUI of the Micro-Meta App as well as the position on the canvas occupied by icons representing each microscope hardware component.Icons: a series of SVG files, each containing an icon representing the individual hardware components.For the Micro-Meta App to work, the following elements are generated in advance as described in the following sections and made available via GitHub:98, which implements the BioFormats library52 to allow the user to import known OME metadata directly from the file header of an image data file of interest. To maximize flexibility, these elements can be customized to meet the needs of individual users.In addition, the stand-alone version of Micro-Meta App depends on the 4DN Microscopy Metadata Reader99 is to transform the XML schema definition (XSD) implementation of the 4DN-BINA-OME data model100 into a JSON-based schema, which is subsequently ingested by Micro-Meta App to automatically generate the software GUI and the associated data insertion forms. The XSD to JSON schema converter middleware uses the Xerces2 Java XML Parser101 and W3C Java XML bindings libraries102 to navigate the XSD schema, and produces two kinds of version-aware JSON files:https://github.com/WU-BIMAC/4DNMetadataSchemaXSD2JSONConverter/blob/master/latest/fullSchema.json).A comprehensive JSON file containing an array of schemas for all necessary individual components that constitute the 4DN-BINA-OME data model . This comprehensive JSON file is made available on GitHub and is designed specifically to facilitate the remote loading of the schema by web portal embedded React implementations of the Micro-Meta App. This schema is available as an individual file on GitHub (https://github.com/WU-BIMAC/4DNMetadataSchemaXSD2JSONConverter/tree/master/latest/schemas).A series of JSON files, each containing the schema of individual components, which were designed to be employed by the Electron implementation of the App. These individual schema files are available within a subdirectory of the main repository on GitHub 99 and is ready to be used to implement the ‘snap-in-place’ functionality of the software.This Java-encoded componenthttps://github.com/WU-BIMAC/4DNMetadataSchemaXSD2JSONConverter/tree/master/latest/images)99. Custom-made icons can be similarly generated by developer users and manufacturers for representation of their hardware components within the application.Scalable vector graphic (SVG) files containing icons representing the different microscope hardware components were generated specifically for this project and are made available in a version-aware manner for remote loading from GitHub , case studies (including detailed descriptions of the ‘use at core facilities’ and ‘teaching with Micro-Meta App’ case studies), video 1, Figs. 1–15 and references.Reporting SummarySupplementary Video84 is also available at: https://vimeo.com/557097919. Images labeled with (*) and (**) at minutes 0:16–0:33 of Video 1 are used with permission from the author from Figs. 5 and 6 of Smith et al.100.Video 1 was used as an introduction to Micro-Meta App for use by Graduate Students at the University of Massachusetts Medical School


While microcephaly is a significant adverse outcome of prenatal exposure to the Zika virus (ZIKV), subtle malformations of cortical development (MCD) have been observed in Zika-exposed children (ZEC), including delays in language, cognition, and motor domains, and visual acuity deficits. Interventions within the first 1,000 days of life can significantly improve developmental outcomes. This study examined a 12-week Responsive Caregiving Intervention on neurodevelopmental outcomes in 24-30-month-old ZEC.A randomized controlled trial was implemented in Grenada, West Indies using an existing ZIKV cohort surveillance study. When children in that study turned 24 months, baseline child neurodevelopmental measures and caregiver interviews were administered. Caregivers who agreed to participate in the 12-week Responsive Caregiving Intervention, implemented when children were 24–30 months of age, were randomly assigned to the Intervention or Waitlist Control group. Children in both groups were re-assessed on the neurodevelopmental measures post-intervention.in utero. The programme provides an option for mothers of ZIKV-exposed children who are seeking an evidence-based neurodevelopmental intervention regardless of known impact of the virus on cortical formation.233 children from the ZIKV surveillance study met inclusion criteria, of which n = 80 declined participation, n = 42 did not complete the Intervention, and n = 72 missed follow-up assessments given strict timelines in the study design. The final sample for analysis was N = 13 children in the Intervention group and N = 26 children in the Control group. A GEE model analysis showed significantly higher language (p = 0.021) and positive behaviour (p = 0.005) scores for children in the Intervention group compared to the Control group. The Intervention had a medium effect on child language (d = 0.66) and a large effect on positive behaviour (d = 0.83). A 12-week Responsive Caregiving Intervention Programme significantly improves language and positive behaviour scores in 30-month-old normocephalic children who were exposed to ZIKV NCT04697147).The study was registered with clinicaltrials.gov  in infants is well known. Prenatal Zika virus exposure can also cause more subtle impacts in infant language, cognition, and motor function, and visual acuity, even in the absence of microcephaly. Interventions in the first 1,000 days of life can significantly improve these outcomes in at-risk children. Few studies have been carried out with the aim of improving neurodevelopment in Zika-exposed children. The present study utilized a randomized controlled trial to examine the impact of a 12-week Intervention on neurodevelopmental outcomes in 24-30-month-old Zika-exposed children. Analysis showed significantly higher language and positive behaviour scores among children in the Intervention group compared to children in the Control group. The Intervention used in this study is relatively low-cost and easy to implement. The application of interventions from the global early child development field has implications for governments, policy makers, public health officials, and parents of Zika-exposed children who are seeking effective interventions to mitigate the risk of neurodevelopment delays in those children. The fact that these much-needed interventions already exist and can be rolled out relatively quickly and effectively is encouraging. On 1 February 2016, the World Health Organization (WHO) declared a Public Health Emergency of International Concern (PHEIC) regarding microcephaly and other neurological disorders associated with the Zika virus (ZIKV). While the PHEIC was lifted on 18 November 2016, the WHO still considers the Zika epidemic and the associated complications a significant public health challenge requiring intense action, )While no studies with the specific aim of improving neurodevelopment among ZEC have been carried out in the Caribbean region, other interventions have shown improved outcomes in children who may be at risk for developmental delay in the absence of exposure to ZIKV. One such study is the Jamaican-developed Reach Up Intervention, a home visiting programme that supports mothers’ engagement with their children, thus promoting their children’s development . The effThe Reach Up Intervention involves parental education about early child brain development and techniques for child stimulation to improve developmental outcomes ,31. The Given the emerging evidence about the effectiveness of intervention programmes to improve ECD in low-and-middle-income countries and concerns about the potential subtle neurological impact of ZIKV on child development that can manifest as deficits in cognition, intellectual disabilities and learning disorders later in life, more evidence-based interventions are needed to determine whether neurodevelopment can be improved in ZEC. The present study aimed to examine the impact of a 12-week Responsive Caregiving Intervention on neurodevelopmental outcomes in 24-30-month-old ZEC. We hypothesized that ZEC whose parents received the Responsive Caregiving Intervention would show better neurodevelopmental outcomes at 2.5-year follow-up than those who were allocated to the Waitlist Control group.This study was approved by the St. George’s University Institutional Review Board (#16061). Written informed consent was obtained from all participants. The study was registered with clinicaltrials.gov (NCT04697147).A randomized controlled trial design was implemented to evaluate the impact of a Responsive Caregiving Intervention on children between the ages of 24–30 months in Grenada, West Indies. The sample was derived from an existing ZIKV cohort study in Grenada . When tAll participants in the trial belonged to an ongoing ZIKV cohort study in Grenada, West Indies, with details regarding serum testing and ZIKV status for mothers and infants previously described . For thWritten consent and contact information were obtained from participants who wished to be involved and they were randomized to either Intervention or Control via random numbers table. Participants were contacted by a community health worker (Roving Caregiver) to schedule convenient days/times to complete their intervention sessions. A total of n = 233 parents/caregivers were contacted about participation in the study when their child turned 24-months old and n = 153 agreed and were randomized to either the Intervention or Control group. The intervention was provided to families between 24–29 months of the child’s life.The Responsive Caregiving Intervention used in the current study draws upon the US-based Conscious Discipline (CD) Programme, which has been adapted for and used in the study site  for more than 10 years. CD is a brain-based, trauma informed curriculum emphasizing the importance of social-emotional learning and self-regulation for fostering neurodevelopment in children through behavioural and perceptual change in adults. CD focuses on building a strong social-emotional connection between the child and his/her caregivers, both in home and in school environments. For this intervention, community health workers  were trained in the CD curriculum and visited the homes of the participants over the course of 12 weeks, for a 1-hour session each week, to work with caregiver-child dyads. Both caregiver and child were required to be present for each session. The Roving Caregiver Programme was established in 1992 to deliver stimulation through home visits to at-risk children . In 2014The Control group was not exposed to the Responsive Caregiving Intervention. All ZEC in the Control group were scheduled for neurodevelopmental assessments at 24, 27, and 30 months of age to compare their outcomes to the Responsive Caregiving Intervention group.st Neurodevelopment Assessment (INTER-NDA) [Neurodevelopmental outcomes at 2 years were measured via the INTERGROWTH-21TER-NDA) ,36. The TER-NDA) . It was TER-NDA) . Its 37 TER-NDA) . The INTTER-NDA) . The INTParent demographics and social-environmental assessment were measured via standardized surveys and questions that evaluated environmental conditions that could potentially affect the child’s development. These surveys included demographic and socioeconomic status (SES) questions such as primary caregiver, monthly income and number of persons living in the household, and pre- and post-natal behaviours of the mother. Standardized questionnaires included USDA Food Security Questionnaire ,40, GeneAll data were analyzed using the Statistical Package for the Social Sciences (SPSS) v. 26 (IBM Corp). Mean scores on the outcome measure (INTER-NDA) were converted to standardized scores per the procedure outlined by Fernandes and colleagues  and analT-tests and chi-square analyses were used to compare baseline socio-demographics between Intervention and Control groups. These tests were also used to compare baseline data for those participants who remained in the study and those lost to follow-up. Generalized estimating equation (GEE)  analysesin utero and did not meet inclusion criteria. Additionally, n = 33 children were older than 24 months of age when the intervention study was initiated and were excluded. The remaining n = 233 children met inclusion criteria and their caregivers were approached about participating in the intervention when the child turned 24 months of age. A total of n = 80 (34%) declined participation, leaving n = 153 to be randomly assigned to the Intervention group (n = 89) or Control group (n = 64). Of the n = 89 participants assigned to the Intervention group, n = 24 dropped out due to scheduling conflicts or other reasons. A further n = 18 were removed from the Intervention group for completing fewer than 75% of the intervention classes . Finally, n = 60 children across both groups  missed follow-up assessment sessions, resulting in a lack of neurodevelopmental scores. The remaining n = 51 participants  were considered for analysis. After data cleaning, n = 12 Intervention participants were excluded from the final analysis due to missing INTER-NDA scores . No exclusions were made in the Control group. The final sample size for analysis included n = 13 children in the Intervention group and n = 26 children in the Control group  were eligible to participate in the CD-based Responsive Caregiving Intervention when their child turned 24 months of age . A totalol group .Socio-demographic data collected at baseline for Intervention (n = 13) and Control (n = 26) groups were examined for any significant disparities between the groups. Results showed that the Intervention and Control groups were equivalent across all variables except parental education level . A higheAn analysis to determine the equivalence of the participants who remained in the study to those who were lost to follow-up in both the Intervention and Control groups was run on baseline data. The results indicated that those lost to follow-up were equivalent to those who remained in the Control group of the study, whereas the Intervention group showed some disparity on child age and monthly income. Those lost to follow-up (M = 24.39) in the Intervention group showed a higher child age than those who remained ; and those lost to follow-up in the Intervention group showed higher monthly incomes than those who remained (p = 0.041) . Child aResults of a GEE model analysis showed significantly higher language (p = 0.021) and positive behaviour (p = 0.005) standardized scores on the INTER-NDA for the children in the CD-based Responsive Caregiving Intervention group compared to the children in the Control group . The intin utero. The findings of our study are consistent with previous reports investigating the impact of home-visiting early childhood interventions including those involving children born to low-income families [We have shown that a 12-week Responsive Caregiving Intervention programme significantly improves language and positive behaviour scores in 30-month-old normocephalic children who were exposed to ZIKV families –54, chilfamilies ,53,55–58families ,55. Our families . The 16-families . The stufamilies . A totalfamilies . The resfamilies . Neitherfamilies . No otheThe results of this study are consistent with a recent CD-based Responsive Caregiving Intervention study carried out in Grenada, West Indies . WaechteThe main limitations of the current study are its small final sample size and high levels of attrition between initial contact for inclusion in the study and drop out from the intervention. Moreover, some participants were excluded from analysis due to missing neurodevelopment data post-intervention. Study protocol adherence and lost follow-up are significant limitations that are challenging to overcome and are not uncommon in community-based intervention studies with longitudinal follow-ups . Anotherin utero. While this allowed for a direct comparison of neurodevelopmental outcomes between those who received the Intervention and those in the Control group, it was not possible to determine whether any or all the ZEC in the study had experienced subtle MCDs and/or neurocognitive impairment and/or neurodevelopmental delay because of their exposure to ZIKV. Future studies would need to include ZEC with documented MCDs and/or neurocognitive impairment and/or neurodevelopmental delay to determine whether the intervention can improve neurodevelopmental outcomes in children with ZIKV-related impairment short of microcephaly.All the children in the present study were exposed to ZIKV The CD-based Responsive Caregiving Intervention used in the present study prioritizes the building of social-emotional connections between caregiver and child to improve child neurodevelopment. We hypothesize that the nature of this intervention lends itself to the increase in positive behaviour and language abilities seen in the children randomly assigned to the Intervention group. The intervention used in the present study includes several activities that help forge a relationship between caregiver and child. These activities include singing songs and rhymes, reading stories, allowing, and encouraging the child to express themselves verbally, and equipping children with tools for expressing certain needs and wishes. These activities likely explain the improved language scores amongst our Intervention group.The CD-based Responsive Caregiving Intervention used in the present study and similar interventions can be low-cost and relatively easy to implement. This could lead to more children having access to interventions that can mitigate neurodevelopmental delays in cases of arboviral diseases or otherwise. The cross-translation of evidence-based interventions from the global ECD field has implications for governments, policy makers, public health officials, ECD experts and parents of ZEC who are seeking effective interventions to mitigate the risk of neurodevelopment delays in those children. The fact that these much-needed interventions already exist and can be rolled out relatively quickly and effectively is encouraging. Moreover, the diversity of ECD interventions allows for a selection of programmes that apply best to regional, cultural, and economic variance.S1 Table(DOCX)Click here for additional data file.


A wide range of antimicrobial agents were touted as potential remedies during the COVID-19 pandemic. While both developed and developing countries have recorded an increase in the use of antimicrobial drugs, use and misuse have occurred to a far greater degree in developing countries. This can have deleterious consequences on antimicrobial resistance, especially when various developing countries have already reported the emergence of various drug-resistant organisms even before the pandemic. Telemedicine services, societal and cultural pressures, and bacterial co-infections can predispose to overwhelming antimicrobial prescriptions. The emergence of new multidrug resistance species is a major concern for the developing world especially since health services are already overburdened and lack the diagnostic capabilities and basic amenities for infection prevention and control. This can lead to outbreaks and the rampant spread of such microorganisms. Improper waste management and disposal from hospitals and communities establish freshwater runoffs as hubs of various microorganisms that can predispose to the rise of multidrug-resistant species. Microplastics' ability to act as vectors for antibiotic-resistant organisms is also particularly concerning for lower-middle-income countries. In this review, we aim to study the impact of antimicrobial use during the COVID-19 pandemic and antimicrobial resistance in lower middle-income countries, by understanding various determinants of resistance unique to the developing world and exploring solutions to combat the problem. Introduction2. Determinants of Antimicrobial Resistance in the Developing World3. Antimicrobial Self-Prescription4. Restriction of Health-Care Services5. Social and Cultural Reasons6. Antibiotic Overprescription in Hospitals and Telemedicine7. In Hospital Emergence of Antimicrobial Resistance8. Environmental Factors: Role of Freshwater, Sewerage and Plastic Waste9. Conclusion1. The causative organism of COVID-19, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), is an enveloped, positive-sense single-stranded RNA virus. Various medications have been touted as a remedy for the disease, ranging from homemade concoctions to antimicrobial drugs with potentially severe side effects, such as hydroxychloroquine. Various unsubstantiated claims of several of these medications' efficacy resulted in immediate rampant misuse of such antimicrobial agents among both hospitals and the general population. This has raised concerns for increasing antimicrobial resistance. Whilst extensive literature exists on the impact of antimicrobial use during the COVID-19 pandemic in developed countries, little to no literature is available on lower middle-income countries, where an already fragile antimicrobial regulation infrastructure exists and governing of the availability and selling of antimicrobials is scant. In this review, we aim to study the impact of antimicrobial use during the COVID-19 pandemic and antimicrobial resistance in such countries by understanding various determinants of resistance unique to developing countries. Moreover, we aim to explore possible solutions to combat the problem.As of April 21, 2021, the Coronavirus disease 2019 (COVID-19) has affected more than 143 million people and has caused 3 million deaths worldwide2. The treatment of such superinfections is pertinent to improve COVID-19 prognosis, as secondary bacterial infections have been linked to increased morbidity and mortality3. Such rampant use of antimicrobial agents raises concerns for misuse, that can translate into antimicrobial resistance and the rise of multi-drug resistant organisms that have already been anticipated to be the world's leading cause of death by the year 20504. For example, prophylactic azithromycin may have a possible role in transmitting extensive drug-resistant strains of Salmonella typhi in Pakistan and Bangladesh5. It has already been established that in-hospital transmission of multi-drug resistant organisms further increases the likelihood of resistance development6.A more justified use of antimicrobials in COVID-19 patients is to treat potential superinfections. Risk factors that can add to the burden of bacterial disease include a dysregulated immune response, lowered host defenses, and prolonged in-hospital stay3,7-9. Developing countries also suffer from inadequate hygiene in communities and hospitals, financial constraints, over-the-counter availability of antibiotics, and misinformation on various media, all of which have been implicated as risk factors for antimicrobial resistance10,11.To our knowledge, our study is the first study that discusses the impact of antimicrobial use during the COVID-19 pandemic on the emergence of antimicrobial resistance in developing countries.There are also several contributory factors arising from the general population that promote the development of antimicrobial resistance in the setting of COVID-19 in developing countries. These include inappropriate prescriptions, lack of antimicrobial stewardship practices, and unnecessary self-administration by the publicThe development of antimicrobial resistance in the setting of coronavirus pandemic is attributed to numerous factors . The treAmidst the COVID-19 pandemic, where general public was instructed to maintain social distancing, the utilization of telemedicine also surged. Although convenient for both the patients and physicians, the lack of physical examination by healthcare professionals and unavailability of laboratory parameters for determining the severity of the condition are one of the major causes of excessive prescription of antibiotics.Unsafe disposal of personal protective equipment serves as a possible cause of emergence of antimicrobial resistance. The microplastics derived from healthcare waste act as media for propagation and modifications in bacteria and thereby consequent emergence of resistant species.Due to expenses and techniques associated with standard disposal of personal protective equipment, the waste produced in healthcare setup is usually disposed in sewerage water. The abundance of various antiseptics and other miscellaneous antimicrobial agents in the wastewater can cause various modifications in bacteria secondary to cross-resistance with various substances present in sewerage wastewater. This cross-resistance can possibly result in emergence of more resistant species.12,13. Appreciable increase in the use of antibiotics was observed in Pakistan13, and Bangladesh14, and a vast majority of such use was without the prescription of a health professional14. The most frequently prescribed medications included ivermectin, azithromycin, and doxycycline14, which are key drugs utilized as the mainstay of COVID-19 treatment at the time of the conduction of studies15. This was hypothesized to be abetted by the relative stability in the prices of these medications in developing countries13, which is also supported by the findings of Fernandez et al. who state that the growing unstable financial conditions render more appropriate therapy and supervised medications as unaffordable to several families in developing countries and persuade families to otherwise use readily available and comparatively cheaper antibiotics16. Stemming from the mental stress of lockdown and isolation, there was a general fear of shortage of antibiotics too, that further exacerbated widespread antimicrobial and antibiotics use14, which indeed did cause a shortage of medications as observed in India, Pakistan, Bangladesh, and Malaysia14.During the course of the COVID-19 pandemic, it has been observed in several developing countries that there was a general aversion towards seeking healthcare from hospitals and an inclination towards self-medication and pharmaciesThe problems of self-prescription can be solved by widespread educational programs that spread awareness about the disease and address the mass hysteria and misconceptions that follow such a pandemic.17. Lower middle-income countries were predicted to be the pallbearers and experience the greatest toll due to poorer health care standards, poor antibiotic prescription habits, and greater population densities17. Other generalized factors included the ability of the microbe to spread readily. With strict lockdowns in several regions of the world, this notion was initially accepted. However, in-depth mathematical models proved differently18,19. Strict lockdown measures could cause a temporary 50% reduction in tuberculosis transmission, but principally, due to the accumulation of undetected tuberculosis during this period, there could be an estimated 1.19 million cases and 361,000 deaths in India, 24,700 cases and 12,500 deaths in Kenya, and 4,350 cases and 1,340 deaths in Ukraine in the next five years18. The most significant overall impact of the lockdown on tuberculosis mortality and cases in regions with high antibiotic resistance was the drop in completion of the second-line treatment18. Delayed first presentation of tuberculosis cases most likely due to social stigma surrounding it, as it can present very similar to COVID-19, has been voiced as a major concern18,20-22. This creates a reservoir of undetected tuberculosis that can precipitate new infections of latent tuberculosis18,19, which has been suggested to lead to selection for drug resistance6, whilst deficient tuberculosis management programs can lead to increases in the rates of multi drug resistant tuberculosis (MDR-TB) observed globally23.The burden of antimicrobial resistance during a pandemic has already been suggested to differ for different world regions24. Sociocultural aspects such as uncertainty avoidance, inequalities, gender-bias, and individuals' integration into primary groups highly influence antibiotic use and antibiotic resistance. They argue that it is intrinsic human behavior to avoid being excluded from a higher social group, and deviation of common social rules is often considered a mental disorder in lower middle-income countries. Thus, along with a lack of education on antibiotic resistance and antimicrobial resistant bacteria, people in lower middle-income countries are generally encouraged to partake in antibiotic misuse24.Hernando-Aman et al. argue that lower middle-income countries are more prone to acquire antimicrobial resistant bacteria due to socioeconomic or cultural reasons25. Studies, however, demonstrate a prudent divergence from these guidelines. In one study, antibiotics were prescribed in 72% of COVID-19 cases on the clinical suspicion of a bacterial co-infection. However, only 7% of these patients actually developed bacterial and/ or fungal co-infections, demonstrating the overwhelming unjudicial misuse of antibiotics26. It can also be expected that such statistics may indeed be much higher in the developing world, owing to a multitude of predisposing factors. However, it is not to say that we can completely determine the unjustified use of antibiotics. A lack of controlled longitudinal studies on this particular subject makes it difficult to ascertain if such antimicrobial use was truly unjustified or if it served a protective prophylactic role in reducing the incidence of co-infections.The ideal time to start antibiotics in COVID-19 cases still represents a grey area in clinical guidelines. According to the guidelines laid down by the World Health Organization (WHO), antibiotics should not be administered in uncomplicated cases of COVID-19. They should only be reserved for more severe, complicated cases10. Thus, it is necessary that antimicrobial stewardship principles are strictly adhered to and supervised by regulatory bodies during the COVID-19 pandemic.Antimicrobial stewardship has been introduced to effectively utilize antibiotics, curtail their misuse, and minimize antimicrobial resistance risk. However, poor adherence to antimicrobial stewardship has been reported in several developing countries, and a lack of literature on the subject has made it difficult to understand the cause27. One study describes the significant over-prescription of antibiotics in telemedicine visits as compared to routine clinical visits27. Immune system dysregulation in the setting of COVID-19 has also been noted to alter the clinical manifestations of an underlying bacterial infection28. Thus, the difficulty in accurately assessing a patient requires the physician to extend beyond his/her clinical acumen and utilize laboratory testing to investigate the infection as bacterial in nature. We propose the development of inexpensive, sensitive testing methods that provide rapid diagnosis of bacterial infections. We also propose that doctors in developing countries be educated and encouraged to prescribe antibiotics only according to antimicrobial stewardship principles and WHO guidelines.In lieu of social distancing protocols during the COVID-19 pandemic, telemedicine has been a major preference to clinical visits. This has been noted to impact routine clinical examinations of patients significantly5.While the use of antibiotics in certain patients’ populations can be debated to be justified or unjustified, there exists a large subset of COVID-19 patients in whom the use of antimicrobial agents is crucial. These include those patients in whom a higher incidence of bacterial infections has been observed, notably by multi-drug resistant microorganisms. It has already been established that in-hospital transmission of multi-drug resistant organisms increases the likelihood of development of antimicrobial resistance29,30. By undergoing changes in their genetic material and bypassing active drug pathways, several microorganisms have acquired antimicrobial resistance30. It has also been noted that antimicrobial resistance can induce re-emergence of past microbes as well as new resistant variants that possess increased pathogenicity30.Due to the ever-evolving nature of microorganisms and their interdependence with humans, the environment, and animals, it is not uncommon for diseases, such as COVID-19, Ebola virus disease, and Zika virus, to spread from their zoonotic origin to humans and to cause epidemics and pandemics3. Because Candida species are a significant constituent of the normal human flora, they have been implicated in opportunistic infections in COVID-19 patients31. Nosocomial Candida species were noted to be particularly detrimental even before the COVID-19 pandemic. Thus, various guidelines were devised to minimize its transmission and develop new antifungal agents32,33.A part of COVID-19 patients develops acute respiratory distress syndrome (ARDS), along with potential super-infectionsCandida species has been implicated in causing COVID-19 associated candidiasis31. Such an emergence of a new Candida species has been very concerning, especially since antimicrobial resistance is already ubiquitous31. The mechanism by which Candida causes co-infections in COVID-19 patients is unknown. However, both Candida and SARS-CoV-2 have been found to occur on the same hospital surfaces32, and COVID-19 patients hospitalized in the ICU share the same risk factors, medications, and underlying co-morbidities with 32C. Auris. It has been reported that the fecal fungal microbiome is altered in COVID-19 patients with superimposed fungal infections; this has been noted to increase the transmissibility of Candida infections amongst COVID-19 patients and can even cause outbreaks in hospitals33.During the COVID-19 pandemic, various yeast infections have been elaborated on, but the emergence of a new multi-drug resistant C. Auris has already been noted to be greater in developing countries32. Chowdhary A. et al. postulate this to be due to the overall greater burden of C. Auris in developing countries as a result of poor diagnostic capabilities and inadequate resources for infection prevention and control32. By utilizing all their limited diagnostic capabilities on SARS-CoV-2, overburdened medical facilities in developing countries cannot attend to the diagnosis of other pathogens, such as 32C. Auris. Hence, the issue of multi-drug resistant C. Auris and potential outbreaks are a much greater concern in developing countries than in developed countries32.The incidence of the multi-drug resistant New Delhi Metallo-Beta-Lactamase-Producing Carbapenem-Resistant Enterobacterales (NDM-CRE)34. Enterobacterales species are resistant to the majority of first-line therapeutic agents35. COVID-19 patients, who were previously colonized with NDM-CRE and those who acquired it during the course of hospital stay, were found to have a longer hospital stay attributed to associated complications and antimicrobial resistance34.One of the already established potential causative agents of healthcare-acquired infections in many countries, including developed countries like Italy, is 36.CPE has re-emerged in the light of the COVID-19 pandemic, attributing to inattentive antibiotic prescription and a lack of antimicrobial stewardship36. Other factors include severe lung injury and subsequent mechanical ventilation36.The re-emergence of CPE and superinfection in COVID-19 patients has multiple underlying factors. The most common factor is the use of immunomodulators, such as corticosteroids, in the management of COVID-19 patientsCarbapenem-Resistant Acinetobacter Baumannii (CRAB) during the COVID-19 pandemic37,38. Nosocomial Acinetobacter Baumannii infections has been found to be associated with increased mortality in COVID-19 patients39. These species have been noted to be resistant to both ciprofloxacin and gentamicin, thereby leading to increased morbidity and mortality in COVID-19 patients35.There has been reported to be an increased prevalence of 40,41. It has already been expected that lower middle-income countries are likely to suffer from antimicrobial resistance’s consequences in the post-pandemic era to a much greater degree than developed countries42. Hence, we propose that the use of antibiotics should not decrease, but rather be used more efficiently, centralizing on preventing in-hospital transmission of multi-drug resistant organisms. This can be achieved by observing strict infection control protocol and patient isolation, a scenario that is often below par in the developing world.During the COVID-19 global pandemic, antimicrobial resistance will have long-lasting effects due to increasing resistance, redirection of resources, re-emergence of resistant strains of various infectious agents, and lack of antimicrobial stewardship43-47. They have been found to be hubs of subtherapeutic antibiotics and very high bacterial loads,47and have also recently been found to contain excessive other miscellaneous antimicrobial products such as antibacterial soaps and antiseptics. The presence of antimicrobial agents in the environment can stimulate antimicrobial resistance24,43-46, and cause cross-resistance between antiseptic agents and antimicrobial agents by inducing mutation in the receptors and pathways which cause antimicrobial resistance, leading to the emergence of multidrug-resistant species16,44,45. This explains the emergence of drug-resistant E. Coli collected from sewage treatment plants that were treated using chlorination treatment46.Various studies have reported wastewater to be major hotspots for antimicrobial resistance48. This explains the presence and persistence of SARS-CoV-2 in wastewater, sanitation systems, as well as in the septic tanks of hospitals43. The authors alarm the readers of how much higher concentration and persistence can thus be expected in developing countries43. Only one study has attempted to document the extent of SARS-CoV-2 found in sewage wastewater in a lower middle-income country. It was discovered that there were far more extensive levels of SARS-CoV-2 found that did not correlate with the low number of cases in Quito.Using the WHO’s strategy for removal of SARS-CoV-2 using sodium hypochlorite disinfection, was found that there was only incomplete removal49,50. Superbugs on microplastics have been suggested to enrich the antibiotic-resistant bacteria found on the surfaces of other microplastics, and since developing countries lack the infrastructure and financial capability to dispose of microplastics using modern incineration techniques safely, such microplastics are usually disposed of in wastewater, leading to a cascade of events that culminate in antimicrobial resistance46.The unsafe disposal of plastic personal protective equipment in the environment too has been voiced as a major concern for antibiotic resistance and antimicrobial resistant bacteria. Cultivable antimicrobial resistant bacteria found on the surface of microplastics were found to be 100-5000 times higher than those in water samples, implying the efficient ability of microplastics to act as vectors for antimicrobial resistant bacteria, particularly superbugsThe extensive use of antimicrobial agents during the COVID-19 pandemic has created a serious risk of antimicrobial resistance. Developing countries have already been reporting high levels of resistance even prior to the pandemic. Several contributory factors that are unique to developing countries have gained major traction during the COVID-19 pandemic. Unregulated prescription of antibiotics to the general public, unjudicial use of antibiotics in health care settings for co-infections, negation of the principles of antimicrobial stewardship, the emergence of multidrug resistant microorganisms, freshwater disposal of toxic waste, and inappropriate management of microplastics are all contributing factors towards the emergence of resistance in developing countries. This necessitates emergency intervention to prevent further deterioration of the situation.◊Superinfection can occur in COVID-19 patients secondary to dysregulated immune response, weakened defense mechanisms and prolonged hospital stay◊Most common factors contributing to the antimicrobial resistance during the COVID-19 pandemic are: self-administration of antibiotics, telemedicine, lack of antibacterial stewardship, over-prescription of antibiotic drugs, unsafe hospital waste management and disposal.◊Timely interventions, such as implementation of antimicrobial stewardship, proper waste management, and easily accessible healthcare facilities are imperative to counter evolving antimicrobial resistance in developing countries.