Avian coronavirus-infectious bronchitis virus (AvCoV-IBV) is the causative agent of infectious bronchitis (IB) that has brought great threat and economic losses to the global poultry industry. Rapid and accurate diagnostic methods are very necessary for effective disease monitoring. At the present study, we screened a novel nanobody against IBV-N protein for development of a rapid, simple, sensitive, and specific competitive ELISA for IBV antibody detection in order to enable the assessment of inoculation effect and early warning of disease infection. Using the phage display technology and bio-panning, we obtained 7 specific nanobodies fused with horseradish peroxidase (HRP) which were expressed in culture supernatant of HEK293T cells. Out of which, the nanobody of IBV-N-Nb66-vHRP has highly binding with IBV-N protein and was easily blocked by the IBV positive serums, which was finally employed as an immunoprobe for development of the competitive ELISA (cELISA). In the newly developed cELISA, we reduce the use of enzyme-conjugated secondary antibody, and the time of whole operation process is approximately 1 h. Moreover, the IBV positive serums diluted at 1:1000 can still be detected by the developed cELISA, and it has no cross reactivity with others chicken disease serums including Newcastle disease virus, Fowl adenovirus, Avian Influenza Virus, Infectious bursal disease virus and Hepatitis E virus. The cut-off value of the established cELISA was 36%, and the coefficient of variation of intra- and inter-assay were 0.55–1.65% and 2.58–6.03%, respectively. Compared with the commercial ELISA (IDEXX kit), the agreement rate of two methods was defined as 98% and the kappa value was 0.96, indicating the developed cELISA has high consistency with the commercial ELISA. Taken together, the novel cELISA for IBV antibody detection is a simple, rapid, sensitive, and specific immunoassay, which has the potential to rapidly test IBV antibody contributing to the surveillance and control of the disease. Infectious bronchitis (IB) is caused by the avian coronavirus-infectious bronchitis virus (AvCoV-IBV), which is recognized as a severe threat to the poultry industry globally owing to that it affects chickens of all ages and causes respiratory and nephrotic syndromes in broilers, as well as impairs egg production in layers and breeders ,2,3. AvCAs a rapid, simple and sensitive method, conventional enzyme-linked immunosorbent assay (ELISA) that includes indirect ELISA, blocking ELISA, and competitive ELISA, has been widely used to detect the IBV antibody. To date, whole virus of IBV is used as the coated antigen for developing the ELISA that can detect antibodies against multiple viral structural proteins covering the S and N proteins. Nevertheless, whole IBV particles is tedious for producing procedures including virus proliferation and purification to cause the high price of the commercial ELISA kits, which limits its application . Many stRecently, the nanobody produced from camelids or sharks, which constitutes the smallest antibody unit with perfect antigen-binding characteristics due to a molecular mass of roughly 15 kDa, continues to report for application in pathogens and antibody detection . CompareBased on the natural advantages of nanobodies, we screened the specific nanobodies against N protein of IBV (IBV-N) though five times immunization of Bactrian camels and the phage display technology in this study. Then, the specific nanobodies fused with horseradish peroxidase (HRP) against IBV-N protein were expressed in HEK293T cell lines. As a result, a direct competitive ELISA (cELISA) was developed for detecting the IBV antibody based on the recombinant IBV-N protein and the specific HRP-nanobodies. In this newly developed cELISA, the HRP-nanobodies against IBV-N protein was employed as an immunoprobe for directly compete the coated antigen with the IBV-seropositive sample, which can reduce the use of HRP-conjugate secondary antibody and shorten operation time. Furthermore, the established cELISA has high level of agreement for field samples detection compared with the commercial ELISA kit (IDEXX ELISA kit). It is a rapid, simple and sensitive cELISA to detect IBV antibodies for epidemiological investigation and antibody level monitoring.E. coli strain after ultrasonic lysis (The coding gene of IBV-N protein (H120 strain) was amplified using PCR, and the target fragment band was about 1230 bp a. The reic lysis b. Moreovic lysis c. Then, ic lysis d. After ic lysis d, sugges9 cfu/mL , and the value of OD450nm was read in less than ten minutes using a Multiskan FC microplate reader .Based on the conventional cELISA, the novel antibody detection on basis of the IBV-N-specific RANbodies cELISA was developed by advantage of the HRP-fused nanobodies, which could be directly applied to detect anti-IBV antibody and eliminated the use of HRP-conjugate secondary antibody. All the conditions were optimized with step by step. Firstly, the IBV-N-Nb66-vHRP was determined as the optimal competitive antibody with IBV-seropositive samples for development of the cELISA, in which the ratio of positive samples value/negative sample (0.17) was lower than other RANbodies for developing the cELISA a. SecondTo determine the cut-off value of the cELISA, 72 serum samples from the SPF chickens were performed using the developed cELISA. The results indicated that the average PI (%) of the negative serum samples was 21% with the standard deviation (SD) of the blocking rates determining as 5%, and the cut-off value for cELISA was 36% (21.0% + 3SD) a. In othPositive serums against other chicken disease viruses including NDV, FAdV, AIV, IBDV and HEV were performed for evaluating the specificity of the cELISA. The results showed that only IBV-seropositive samples could compete the coated IBV-N protein with IBV-N-Nb66-vHRP protein, but other positive serums did not b. To detFor evaluating whether the developed cELISA can be used to detect clinical samples, 350 clinical chicken serum samples that involved 150 serum samples with unknown exposure to the IBV virus or vaccine immunization and a total of 200 serum samples form chicken immunized with a live attenuated vaccine strain of H120 strain were used to compare the concordance rate between the developed cELISA and a commercial ELISA kit. For the 150 serum samples with unknown exposure to the IBV virus or vaccine immunization, 83 serum samples were the IBV-positive samples, and 67 serum samples were determined to be the IBV-negative samples using the developed cELISA. Nevertheless, 84 chicken serum samples were diagnosed as the IBV-seropositive samples and 66 samples were determined to IBV-seronegative samples through the commercial ELISA kit . For theAvCoV-IBV is a serious respiratory pathogen, which causes enormous economic losses in the commercial poultry sector worldwide ,16,17. AIn the present study, the nanobodies are introduced for the first time to develop a cELISA for IBV antibody detection in chicken serum samples. Here, a phage display library against IBV-N protein was successfully generated though Bactrian camels’ immunization, and the specific nanobody of IBV-N-Nb66 against IBV-N protein was screened by bio-pinning of the three rounds, which was employed as a competitive immunoprobe for the development of the cELISA. Moreover, the coding gene of IBV-N-Nb66 was easily reconstructed in genetic platform and fused with the horseradish peroxidase for expression in HEK293T cell lines referring to the published reports ,13, finaThe IDEXX kit that the whole virus antigens were coated in 96-well plates can be used to detect the antibody level in vaccination or other exposure to IBV, but it does not distinguish between animals vaccinated against IBV and those naturally exposed. In the present study, both the antibody of unknown exposure to the IBV virus and immunization of H20 strains were detected by the developed cELISA, the coincidence rate was 98% compared with the test results of the commercial ELISA. In summary, the newly established cELISA has great potential to be used for antibody titer evaluation of a live attenuated vaccine strain (H120 strain) in the future.E. coli strain BL21(DE3). The pMECS vector and M13K07 help phage stored at our laboratory were used for VHH library construction. The pCMV-N1-vHRP vector was synthesized using the pEGFP-N1 vector as a backbone in a previous study  × 100% [72 serum samples from the SPF chickens were used to determine the cut-off value of the established cELISA in this study. The percent competitive inhibition (PI) was calculated according to the following formula: PI (%) = [1 −  were diluted to different concentrations  for the cELISA detection. To determine the repeatability of cELISA, six samples selected randomly from the clinical chicken serum were performed for evaluating the intra-assay (between plates) and inter-assay variabilities (within a plate), in which the results were presented as the coefficient of variation (CV), and the CV was the ratio of the SD to the mean OD samples .Randomly collected 150 clinical chicken serum samples with unknown exposure to the IBV virus or vaccine immunization were tested using the developed cELISA and the commercial ELISA kit and each sample was tested three times. A total of 200 serum samples form chicken immunized with a live attenuated vaccine strain of H120 strain were also detected using the two methods. Then, the coincidence rates between cELISA and the commercial ELISA kit were calculated by the ratio of the number of the same decision of two methods to the number of total serum samples.p < 0.05; ** p < 0.01; *** p < 0.001; Using SPSS software, the Kappa values were obtained to determine the coincidence between the developed cELISA and the commercial ELISA kit.At least three times, each experiment was independently replicated. GraphPad Prism version 7.0  was used to present the data, which included a one-way analysis of variance (one-way ANOVA) and Turkey: compare all pairings of columns. All presented data were shown as the mean ± SD, where * In summary, the specific nanobodies against IBV were firstly reported and screened. In addition, the newly developed cELISA based on IBV-N-Nb66-vHRP is a novel, rapid, specific, and low-cost immunoassay for IBV antibody monitoring, which can be used for evaluating the clinical serum samples with its highly specificity, sensitivity and no cross-reactivity with others chicken disease serums.


The emergence of multiple variants of concerns (VOCs) with higher number of Spike mutations have led to enhanced immune escape by the SARS-CoV-2. With the increasing number of vaccination breakthrough (VBT) infections, it is important to understand the possible reason/s of the breakthrough infections.We performed transcriptome sequencing of 57 VBT and unvaccinated COVID-19 patients, followed by differential expression and co-expression analysis of the lncRNAs and the mRNAs. The regulatory mechanism was highlighted by analysis towards repeat element distribution within the co-expressed lncRNAs, followed by repeats driven homologous interaction between the lncRNAs and the promoter regions of genes from the same topologically associated domains (TAD).LUCAT1, MALAT1, ROR1-AS1, UGDH-AS1 and LINC00273 mediated modulation of immune response, whereas MALAT1, NEAT1 and GAS5 regulated inflammatory response in the VBT. LncRNA-mRNA co-expression analysis highlighted 34 lncRNAs interacting with 267 mRNAs. We also observed a higher abundance of Alu, LINE1 and LTRs within the interacting lncRNAs of the VBT patients. These interacting lncRNAs have higher interaction with the promoter region of the genes from the same TAD, compared to the non-interacting lncRNAs with the enrichment of Alu and LINE1 in the gene promoter.We identified 727 differentially expressed lncRNAs (153 upregulated and 574 downregulated) and 338 mRNAs (34 up- and 334 downregulated) in the VBT patients. This includes Significant downregulation and GSEA of the TAD gene suggest Alu and LINE1 driven homologous interaction between the lncRNAs and the TAD genes as a possible mechanism of lncRNA-mediated suppression of innate immune/inflammatory responses and activation of adaptive immune response. The lncRNA-mediated suppression of innate immune/inflammatory responses and activation of adaptive immune response might explain the SARS-CoV-2 breakthrough infections with milder symptoms in the VBT. Besides, the study also highlights repeat element mediated regulation of genes in 3D as another possible way of lncRNA-mediated immune-regulation modulating vaccination breakthroughs milder disease phenotype and shorter hospital stay. On November 26, 2021, WHO declared yet another variant of concern (VOC) B.1.1.529, with an unusually high number of mutations (32 mutations) in the spike region, the main antigenic target of vaccine-elicited antibodies  and the MAX Super Specialty Hospital. Informed consent was obtained from all individuals or their legal guardians.The patients were admitted to a tertiary care center  with confirmed COVID-19 positive status based on qRT-PCR result during February-April 2021. A subset of the COVID-19 positive individuals with very mild symptoms were kept in home isolation under medical observation. Both nasopharyngeal and oropharyngeal swabs were collected in VTM by paramedical staff on the day of hospital admission or sampling during home isolation. Viral RNA from VTM was isolated using QIAmp viral mini kit  and SARS-CoV-2 detection and quantification was performed using TRUPCR SARS-CoV-2 kit , with a cycle threshold of 35. Sequencing of SARS-CoV-2 genome was performed using Illumina COVIDSeq Test (Cat. No 20043675) as per manufacturer’s reference guide (#1000000126053v04) for all the COVID-19 positive individuals to confirm the viral infection. The demographic and clinical details along with COVID-19 vaccination history of the patients were collected from the electronic health record as per standard practices. The individuals were segregated into two groups based on their COVID-19 vaccination status: ® Stranded Total RNA Library Prep Gold (cat. no 20020599) from a total of 250 ng RNA isolated from the naso/oropharyngeal swabs of COVID-19 positive individuals, as per manufacturer’s reference guide (1000000040499 v00) and our previous study  value of ≥ ± 0.9 , and at least one correlation between the differentially expressed lncRNA and mRNA expression was considered to be significant. The correlation coefficient between lncRNA-mRNA was used to filter the candidates for the interaction network. The candidate lncRNAs and mRNAs were scanned against NPInter v4.0 and LncRRIsearch v1.0 to build the interaction network using MCODE and Cytoscape –22. A beThe mRNAs interacting with the lncRNAs were used to perform the GSEA. Fast GSEA (fGSEA) R package was used and GSEA was performed against the KEGG database , 24. A cThe lncRNAs interacting with the mRNAs were used to perform Pathway enrichment analysis. ncPath web server was used to perform the pathway enrichment against KEGG database, and a cut-off of p-adj ≤ 0.05 was applied to select the significant pathways and was visualized using ggplot2 R package .The network interacting lncRNAs were selected for repeat element distribution analysis using RepeatMasker web server . The anaThe protein coding genes present within the same TAD as of the interacting lncRNAs were fetched from the TADKB database . ExperimVaccination Breakthrough (n=28) with ChAdOx1 nCoV-19 vaccination prior to infection and Unvaccinated (n=29) including patients without any prior vaccination. Briefly, after qRT-PCR and sequence-based confirmation of COVID-19 status, we also sequenced the whole transcriptome of the 57 individuals, followed by transcript level differential expression analysis of the lncRNAs, mRNAs, lncRNA-mRNA co-expression analysis, repeat element distribution analysis and lncRNA-gene interaction analysis within the topologically associated domains (TAD). We recruited 57 COVID-19 patients to understand the role of lncRNAs in the vaccination breakthrough infections. The patients were stratified into two groups based on their vaccination status; RdRp gene was significantly lower in the breakthrough infections, indicating a higher viral load in the VBT patients  analysis of the lncRNAs. We identified a total of 727 differentially expressed (DE) lncRNAs , with 153 upregulated and 574 downregulated in the VBT patients . Therefore, to understand the possible lncRNA-mediated gene regulation, we performed DE analysis of the protein coding genes. We identified 338 DE genes , 34 upregulated and 304 downregulated in the VBT compared to the unvaccinated , and within those, majority of the Alus were present on the sense strand. The LINE1 was also significantly higher in the interacting lncRNAs , however, the majority of the LINE1 was present in the antisense strand. Alus are known to modulate immune response by homologous interaction with the immune responsive genes, and to activate interferon response , 49. WhiSince the Alu element was significantly abundant in the interacting lncRNAs, we looked at the sub-classes of Alu elements. We observed that the Alu S, but not Alu J and Alu Y were significantly abundant (p < 0.0001) in the interacting lncRNAs , 56. Sinvia regulatory components. Taking these factors into consideration, we examined the lncRNA interaction with the genes present in the same TAD as the lncRNAs, as well as the existence of repeat elements within the interacting regions, to understand the type of interaction/s  and identified 163 protein coding genes (We then checked for the association between the interacting lncRNAs and the genes from the same TADs. We used Triplex domain finder from Regulatory Genomics Toolbox to find triplex forming sites (TFS) between the lncRNAs and the promoter region of the genes, since interaction at the promoter region regulates gene expression and thereby modulating gene function . We compFinally, we looked at the repeat element abundance at the promoter region of the interacting TAD genes and compared it with the repeat element abundance within the CDS region of the genes. The promoter region was found to have significantly higher abundance of repeats compared to the CDS of the same genes   . The unuresponse 7A. InnaApart from the DE-lncRNAs with known functions with respect to either direct or indirect immune/modulation response modulation, a very large number of lncRNAs still don’t have annotated functions. While the known DE-lncRNAs are suggesting towards a decreased innate immune/inflammatory response and increased adaptive immune response, the pathway enrichment analysis of all the DE-lncRNAs, which essentially utilizes the knowledge-based gene-lncRNA interaction for enrichment, do suggest that the lncRNAs with unknown functions are also relevant to infectious disease etiology. Enrichment of pathways which are not directly associated with the DE-lncRNAs discussed earlier, such as Apoptosis, Hedgehog signalling, VEGF signalling, and Tight junction pathways, and the high number of genes enriched in these pathways suggests a lncRNA-mediated regulation of cellular homeostasis in the infected individuals. Therefore, further understanding of these functionally unannotated lncRNAs holds potential.lnc-FAM153C-5:15, ROR1-AS1:6, LINC01684:22, and UGDH-AS1:11 upregulated in the VBT group, were downregulated in the Severe group compared to Mild or Moderate  with disease severity also reiterates the importance of understanding their function.In our previous study, we have highlighted lncRNA-mediated immune responses modulating COVID-19 differential disease severities . NotablyRepeat elements are known to be involved in the hierarchical gene regulatory activities. Besides, high repeat element abundance is a feature of the lncRNAs. Our previous study as well as few other groups also highlight the role of repeat elements in the infectious disease and its association with disease severity 8,11,33,34]. Previously, we have also shown that in severe COVID-19, repeat element abundance within the DE lncRNAs are higher than their global abundance within the lncRNAs ,11,33,34, 50. IntThe eukaryotic genome is folded in complex chromatins, which is essentially through topologically associating domains (TAD). Within TAD, genes that are present in a distant genomic loci, are actually present in 3D proximity, and have a higher chance of functionally interacting with each other. Often, repeat elements are the key to this interaction, due to their ability to facilitate homologous recombination with their counterparts present within a different gene. The GSEA of the genes present within the TADs of the interacting lncRNAs highlighted the decreased innate immune and inflammatory response in the VBT patients. Majority of the TAD genes were significantly downregulated in the VBT, however, the log2 fold change was low. When we investigated for the functional importance of the association between interacting lncRNAs and these TAD genes, we found that the interacting lncRNAs interact with the promoter region of its TAD genes, and we observed a higher abundance of Alu and LINE1 at the interaction site, both on the lncRNAs and the promoter region of the genes. Few studies reported downregulation of gene expression by repeat element-mediated homologous interaction . This suSNHG16, downregulated in the VBT group, activates adaptive immune responses by CD73. At the same time SNHG16 interacts with the promoter of ST6GALNAC2 gene, which is present within the same TAD. Interestingly, both on the interacting region of SNHG16, and the promoter region of ST6GALNAC2, Alu element was enriched, and ST6GALNAC2 was downregulated in the VBT group. Notably, ST6GALNAC2 was downregulated in the VBT group, and ST6GALNAC2 is involved in innate immune response, thereby suggesting suppression of innate immune response .The authors duly acknowledge all the COVID-19 patients who participated in the study. Authors acknowledge the help and support from Dr. Aradhita Baral towards facilitation as research manager and coordination with the funders. Authors acknowledge the support of Anil Kumar and Nisha Rawat towards COVID-19 sample transport and sample management. Partha Chattopadhyay acknowledged the CSIR for their research fellowship.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


To estimate associations between covid-19 vaccination and long covid symptoms in adults with SARS-CoV-2 infection before vaccination.Observational cohort study.Community dwelling population, UK.28 356 participants in the Office for National Statistics COVID-19 Infection Survey aged 18-69 years who received at least one dose of an adenovirus vector or mRNA covid-19 vaccine after testing positive for SARS-CoV-2 infection.Presence of long covid symptoms at least 12 weeks after infection over the follow-up period 3 February to 5 September 2021.Mean age of participants was 46 years, 55.6% (n=15 760) were women, and 88.7% (n=25 141) were of white ethnicity. Median follow-up was 141 days from first vaccination  and 67 days from second vaccination (83.8% of participants). 6729 participants (23.7%) reported long covid symptoms of any severity at least once during follow-up. A first vaccine dose was associated with an initial 12.8% decrease  in the odds of long covid, with subsequent data compatible with both increases and decreases in the trajectory . A second dose was associated with an initial 8.8% decrease  in the odds of long covid, with a subsequent decrease by 0.8% per week . Heterogeneity was not found in associations between vaccination and long covid by sociodemographic characteristics, health status, hospital admission with acute covid-19, vaccine type (adenovirus vector or mRNA), or duration from SARS-CoV-2 infection to vaccination.The likelihood of long covid symptoms was observed to decrease after covid-19 vaccination and evidence suggested sustained improvement after a second dose, at least over the median follow-up of 67 days. Vaccination may contribute to a reduction in the population health burden of long covid, although longer follow-up is needed. By the end of 2021 in the UK, when 90% of the population had received at least one dose of a covid-19 vaccine, nearly 14 million cases of SARS-CoV-2 had been confirmed, 640 000 patients had been admitted to hospital, and 158 000 had died with covid-19.Population level immunisation against covid-19 began in the UK on 8 December 2020, and both adenovirus vector and mRNA vaccines administered to the population have shown safety and efficacy in trialsGreater evidence is therefore needed on the symptomology of SARS-CoV-2 infection after vaccination, which may facilitate informed decision making among individuals with long covid. To estimate associations between covid-19 vaccination and long covid symptoms in adults infected with SARS-CoV-2 before vaccination, we used data from the Office for National Statistics COVID-19 Infection Survey, a large, community based population survey.Data were obtained from the COVID-19 Infection Survey,Enrolment rates were as high as 51% in the initial pilot phase of the survey from April 2020, when eligible households comprised previous respondents to ONS surveys who had consented to participate in future research. As the sample was expanded and transitioned to random selection from address lists in August 2020, however, the enrolment rate dropped to 12% (see supplementary table 1 for details). Once participants are enrolled into the study, the attrition rate is generally low; using a definition of either formally withdrawing from the study or having not attended the three most recently scheduled follow-up visits, the attrition rate among enrolled survey participants was less than 1% in 2021.A study worker visited each selected household, after verbal agreement to participate had been obtained, to provide written confirmed consent . At the first visit, participants could consent for  follow-up visits every week for the next month and then monthly for 12 months or longer.All participants provided a self-collected nose and throat swab sample for reverse transcription polymerase chain reaction testing at each follow-up visit. Those aged 16 years or older in a random subsample of households , and those in households where another household member previously tested positive for SARS-CoV-2, were invited to provide monthly blood samples for S antibody testing. Participants also reported whether they had tested positive either for SARS-CoV-2 or for antibodies to SARS-CoV-2 outside of the study .At every monthly visit from 3 February 2021, survey participants were asked whether they would describe themselves as currently experiencing long covid—defined as symptoms persisting for at least four weeks from confirmed or suspected SARS-CoV-2 infection that could not be explained by another health condition. This definition uses self-classification of long covid rather than a prespecified symptoms list or clinical diagnosis, and thus reflects participants’ perception of whether their lived experience is consistent with what they understand of the condition. Participants who responded positively to the long covid question were further asked about the extent to which their day-to-day activities were limited as a result and the presence of 21 individual symptoms as part of their experience of long covid  was obtained from self-reported responses to the COVID-19 Infection Survey and linked National Immunisation Management System records, with the latter being prioritised when data conflicted. Concordance between self-reported and National Immunisation Management System data was previously found to be high for vaccination type (98%) and date (95% within ±7 days).The analysis included survey participants aged 18 to 69 years on 3 February 2021. Participants were included if they responded to the survey question on long covid at least once by 5 September 2021 (end of follow-up), received at least one dose of a covid-19 vaccine before or during the follow-up period, and received a positive swab or blood test result for SARS-CoV-2, either through the survey or reported outside of the study, before vaccination. We excluded survey participants who remained unvaccinated by 5 September 2021 because they were likely to differ from those who were vaccinated according to unmeasured characteristics .We defined the time of infection as the date of a first positive swab or antibody test result (ignoring blood test results after first vaccination), or the date when participants first thought they had covid-19 that was later confirmed by a positive test result, whichever was earlier. Although the survey question asks about long covid symptoms persisting for at least four weeks from infection, for this analysis we used a longer 12 week threshold, consistent with the UK clinical case definition of post-covid-19 syndromeParticipants were observed from their first survey follow-up visit that took place after their first SARS-CoV-2 infection and after the long covid question was added to the COVID-19 Infection Survey on 3 February 2021. Follow-up ended on the date of the participants’ final follow-up visit that took place by 5 September 2021.The explanatory variables of interest were first and second doses of an adenovirus vector (ChAdOx1 nCoV-19 (AZD1222), Oxford-AstraZeneca) or mRNA  covid-19 vaccine. The recommended interval between the first and second vaccine doses was 11 to 12 weeks for most participants in the study sample (having been increased from four weeks on 30 December 2020), with a reduction to eight weeks in May 2021 for people in the top nine vaccination priority groups.The primary outcome at each visit was long covid of any severity, with a secondary outcome of long covid resulting in limitation of day-to-day activities ; this definition of functional impairment is standardised across data collections by the UK Government Statistical Service and is designed to measure disability as defined in the Equality Act 2010. We also evaluated the 10 individual symptoms that were most commonly reported over the follow-up period and whether participants were experiencing more than three or more than five of the 21 symptoms included on the survey.As well as time from infection and the vaccination variables to modify the time trajectory of long covid, we adjusted for covariates hypothesised to be related to vaccine type and timingWe compared covariates between participants who received an adenovirus vector vaccine and mRNA vaccine using means and proportions for continuous and categorical variables, respectively. Standardised differences >10% indicated large differences.An individual level interrupted time series approach was used to estimate associations between vaccination variables and outcomes.We explored heterogeneity in associations between vaccination and long covid by interacting all four vaccination variables (change in level and slope after each dose) with each of age group , sex, white or non-white ethnicity, area deprivation fifth group, health status, hospital admission with acute covid-19, vaccine type (adenovirus vector or mRNA), and duration from infection to first vaccination (modelled as a restricted cubic spline). For each outcome, statistically significant interactions were identified at the 5% level after performing Holm-Bonferroni and Benjamini-Yekutieli corrections to P values to account for multiple comparisons across vaccination variables and modifiers. All statistical analyses were performed using R version 3.6.We restricted the sample firstly to participants with at least one observation before and after each vaccination and secondly to those with at least three observations after each vaccination. We omitted follow-up visits within the first week after each vaccination, which may have been influenced by post-vaccine side effects. Survey participants were added who remained unvaccinated by their last follow-up visit during the study period . Because mass testing for SARS-CoV-2 was largely unavailable during the first wave of the pandemic, we excluded participants who were infected before the start of the second wave on 11 September 2020,NAA contributed to this paper both as someone with lived experience of long covid and as a public health researcher. She has previously strongly advocated against the separation of identities of people with long covid who are also scientists, researchers, or health professionals. She has also written on patient involvement in long covid research and the lessons learnt that could apply to other conditions.Although we did not directly involve patients and members of the public more broadly, the study design was informed by views expressed by patient representatives in monthly meetings attended by DA . These meetings were attended by the founders of three major long covid patient support groups in the UK, whose insights on aspects such as the range of long covid symptoms experienced and their relapsing and remitting nature informed the data collected and definitions used in this study.Of 323 685 participants in the COVID-19 Infection Survey aged 18 to 69 years with at least one visit between 3 February and 5 September 2021, 28 356 had test confirmed SARS-CoV-2 at least 12 weeks before their final visit and had been vaccinated post-infection and were therefore included in analysis .Median time to the final follow-up visit was 169 (interquartile range 141-185) days from the first visit and 267 (219-431) days from first SARS-CoV-2 infection. By design, all study participants received their first vaccination by 5 September 2021, 12 971 (45.7%) after the start of the study period on 3 February. Overall, 23 753 (83.8%) participants were double vaccinated by 5 September 2021, with 20 335 (71.7%) receiving their second dose after 3 February, with a median time between doses of 72 (interquartile range 61-77) days (see supplementary figure 2). Supplementary table 4 shows vaccination status during follow-up by age and health status (two of the main vaccination prioritisation determinants). Participants had a median of 4 (interquartile range 2-5) visits over a median of 141 (interquartile range 86-173) days after their first dose and, among those double vaccinated, 2 (1-3) visits over 67 (20-99) days after their second dose.v 51 years) and more likely to be of non-white ethnicity (13.7% v 9.4%), resident in London (27.0% v 22.4%) or Northern Ireland (3.3% v 1.5%), and a patient-facing health or social care worker (17.1% v 6.4%).At the last visit, the mean age of participants was 46 years (standard deviation 14 years), 55.6% (n=15 760) were women, and 88.7% (n=25 141) were of white ethnicity . CompareLong covid symptoms of any severity were reported by 6729 participants (23.7%) at least once during follow-up. Before vaccination, the odds of experiencing long covid changed little over time  at least once during follow-up. A first vaccine dose was associated with an initial 12.3% decrease  in the odds of activity-limiting long covid, followed by an uncertain trajectory  until the second dose was administered. A second vaccine dose was associated with an initial 9.1% decrease  in the odds of activity-limiting long covid, followed by −0.5% per week  until the end of follow-up.To illustrate the impact of each vaccine dose, We found no statistical evidence of differences in post-vaccination long covid trajectories between participants who received an adenovirus vector vaccine and those who received an mRNA vaccine , fig 3 fThe odds of long covid after a first dose of a covid-19 vaccine numerically decreased with duration from SARS-CoV-2 infection, with estimated numerical decreases of 24.8%, 16.5%, and 4.8% for participants who received a first vaccine dose 9, 12, and 15 months after infection (see supplementary figures 4a-b). Duration from infection to first vaccine dose, however, was not a statistically significant moderator of the vaccination-long covid relationship (see supplementary tables 5a-d).We found no statistical evidence of differences in post-vaccination long covid trends according to sociodemographic characteristics  or health related factors  (see supplementary tables 5a-d).The odds of experiencing most symptoms, as well as more than three or more than five symptoms together, initially numerically decreased after each vaccination . After aSimilar to long covid overall, the odds of experiencing most individual symptoms and more than three or more than five symptoms together, numerically decreased after the first vaccine dose. Trends were generally upwards between the first and second vaccine doses, with most returning to a declining or flat trend after the second dose. However, owing to lack of statistical power, the data for most symptoms were compatible with both initial increases and decreases and both upward and downward trends in the likelihood of experiencing symptoms after each vaccine dose (see supplementary table 6).In this community based study of adults aged 18 to 69 years infected with SARS-CoV-2 before vaccination against covid-19, we found that the odds of experiencing long covid symptoms that persisted for at least 12 weeks decreased by an average of 13% after a first covid-19 vaccine dose. It is, however, unclear from the data whether the improvement was sustained until a second vaccine dose was administered. Receiving a second vaccine dose was associated with a further 9% decrease in the odds of long covid, and statistical evidence suggested a sustained improvement after this, at least over the median follow-up of 67 days. Similar findings were obtained when the focus was on long covid severe enough to result in functional impairment.We found no statistical evidence of heterogeneity in the associations between vaccination and long covid symptoms according to vaccine type; duration from infection to first vaccination; sociodemographic characteristics, such as age, sex, ethnicity, and area deprivation; self-reported health status; and hospital admission with acute covid-19. This observational study was unlikely to have been sufficiently powered to detect these associations, however, particularly given the multiplicity of testing, and absence of evidence does not necessarily imply evidence of absence.Our results add to existing evidence on the trajectory of long covid after vaccination. A non-controlled study of 900 social media users found that more than half had experienced an improvement in symptoms after vaccination compared with 7% who reported a deterioration.Vaccination against covid-19 effectively reduces rates of infectionOur principal finding, of a decrease in the likelihood of experiencing long covid symptoms after a second covid-19 vaccine dose, supports hypothesised biological mechanisms. People with long covid who experience dysregulation of the immune system may benefit from autoimmune processes being “reset” by vaccination , while any residual viral reservoir may also be destroyed by the antibody response.The symptom trajectory following the initial decrease after a first vaccine dose was unclear, being compatible with both increasing and decreasing odds of long covid over time. Evidence was, however, found of an increasing trend when the sample was restricted to participants vaccinated during the follow-up period. Relapsing symptoms are common in long covid,UK Government guidelines recommend that people should delay vaccination for four weeks after a positive test result for SARS-CoV-2. Given that we only considered follow-up visits beyond 12 weeks of participants’ first positive test result (as our outcome of interest was long covid symptoms at least 12 weeks after infection), it seems unlikely that this guidance would have affected our analysis. The National Health Service advises patients with ongoing complications of covid-19 to consult their doctor about vaccination, so it is possible that some people with long covid symptoms may choose to delay vaccination until their symptoms resolve, which would induce an association. However, this is unlikely to have affected our analysis, as we found no evidence that study participants with long covid deferred their covid-19 vaccination compared with those without long covid (see supplementary figure 5). Because our study was observational, we cannot rule out the possibility of a change in reported symptoms after vaccination being due to a placebo effect. Although we might expect to observe a post-vaccination relapse in some participants whose symptoms initially improved, our ability to do this was limited by the follow-up available to us (a median of 67 days from the second vaccine dose).The main strength of the study is its use of the ONS COVID-19 Infection Survey, a large survey of about half a million people from the community dwelling population of the UK with longitudinal follow-up. Random sampling from address lists mitigates against selection bias, whereas the prospective design means that survey responses are not subject to outcome recall bias (such as participants overestimating the duration of previously experienced symptoms). All of the survey’s participants are swabbed for SARS-CoV-2 at every follow-up visit, irrespective of symptoms, so our study includes asymptomatic as well symptomatic infections.The study also has limitations. Its observational design means that causality cannot be inferred, and placebo and side effects of vaccination may have contributed to our findings; however, estimates were robust to excluding follow-up visits within the first week of each vaccination, suggesting that the impact of these effects is likely to be small. Although we adjusted for a wide range of potential confounders, unmeasured factors, such as those related to take-up of a second vaccine dose, may remain. The observed changes after vaccination could be related to the relapsing and remitting symptoms experienced by many people living with long covidBy definition, symptoms are self-reported with no other way to assess them. Together with the impact of symptoms on daily life, the presence of symptoms is how WHO defines long covid.Given the staged roll-out of the vaccination programme in the UK, the main determinant of vaccination timing is age, and thus older study participants tended to have longer post-vaccination follow-up time than younger participants; this may have influenced our analysis of effect modification, whereby we found no evidence of heterogeneity in the post-vaccination trajectory of long covid according to age group. The measure of functional impairment recorded on the COVID-19 Infection Survey  did not give a detailed indication of the specific ways that participants’ lives have been affected by long covid or the resulting impact on quality of life. It is possible that the average improvement in long covid symptoms and functional impact may wane with time, and longer term follow-up is required to establish whether the estimated changes after second vaccination are sustained. Follow-up after a booster dose—now widely available in the UK adult population—is also required. The study sample was restricted to participants aged 18 to 69 years, so our findings may not generalise to children or older adults, nor may they apply to people who had not received a vaccine by 5 September 2021, in particular those with vaccine hesitancy because of their long covid symptoms. Furthermore, symptom data were collected prospectively rather than retrospectively, so variable estimates relating to changes in the odds of long covid may not be generalisable to participants who were vaccinated before the long covid question was added to the COVID-19 Infection Survey on 3 February 2021. However, our results were insensitive to inclusion of participants who remained unvaccinated by the end of the study period or to exclusion of those who were vaccinated before the start of the study period.We found that vaccination against covid-19 is associated with a decrease in the likelihood of continuing to experience long covid symptoms in adults aged 18 to 69 years, and this appeared to be sustained after a second vaccine dose. Our results suggest that vaccination of people previously infected may be associated with a reduction in the burden of long covid on population health, at least in the first few months after vaccination. Further research is required to evaluate the long term relationship between vaccination and long covid, in particular the impact of the omicron variant, which has become dominant in the UK, booster doses, now widely available to adults in the population, and reinfections. Studies are also needed to understand the biological mechanisms underpinning any improvements in symptoms after vaccination, which may contribute to the development of therapeutics for long covid.Vaccines against covid-19 are effective at reducing rates of SARS-CoV-2 infection, transmission, hospital admission, and deathThe incidence of long covid may be reduced in those who are infected after vaccination, but the relationship between vaccination and pre-existing long covid symptoms is unclear, as published studies are generally small and with self-selected participantsA first dose of covid-19 vaccine was associated with a reduction in long covid symptoms, and evidence suggested a sustained improvement after a second dose, at least over the median follow-up of 67 days in this studyNo evidence was found of differences in this relationship by sociodemographic characteristics, health related factors, vaccine type, or duration from infection to vaccinationAlthough causality cannot be inferred from this observational evidence, vaccination may contribute to a reduction in the population health burden of long covid


In December 2019 a novel beta-coronavirus (SARS-CoV-2), causing atypical pneumonia, was identified in Wuhan, China. The disease was called COVID-19 and rapidly spread across the globe. World Health Organisation (WHO) declared COVID-19 a pandemic . Cancer patient care is of special concern during the COVID-19 pandemic. Oncology patients are more susceptible to COVID-19 and severe complications because of advanced age, immunosuppression caused by malignancy itself or anticancer therapy and comorbidities. A metaanalysis of 181.323 patients including 23.736 cancer patients from 26 studies showed that cancer patients infected with SARS-CoV-2 have a higher risk of death  [During the quarantine, cancer patients have limited access to healthcare facilities. Despite the fact, that emergency service must be continued without disruption, there are still many cancer patients who are waiting for diagnostic tests or their treatment (radiotherapy or chemotherapy) had already began. lith. POLA – Pagalbos onkologiniams ligoniams asociacija) conducted a flash survey. This organization is the biggest umbrella patient organization in the country, uniting 31 nongovernmental organizations working in the cancer field and representing the interests of cancer patients, and aims to ensure that both patients and their families have access to effective treatment and the best possible informative, social, psychological and mental support. The POLA community flash survey on healthcare access during the COVID-19 pandemic was conducted from May 21st to June 1st. The survey was sent by an e-mail. In total, 670 people responded to the survey and 92.5% of them were cancer patients , 1501 recovered and 78 deaths (in the time of writing this paper). This means that healthcare system should adapt quite well to the current situation because there is no overload. Perhaps strict policy regarding outpatient visits or hospital admissions made more damage than the COVID-19 pandemic itself. Other countries across Europe also reported cancer care services diminished dramatically, including UK, Italy, Germany and others . When thThere are already some guidelines published online to help going through the healthcare system crisis ,7–9. TheIn conclusion, Lithuanian experience during the COVID-19 pandemic shows that the virus transmission can be successfully stopped. However, the price is paid on the account of patients with chronic diseases including cancer because of diminished access to medical care. About a third of patients did not receive any medical care during the quarantine. The balance between the risk of being infected with SARS-CoV-2 and the damage of delayed diagnosis and treatment of cancer can be achieved only with clear communication in the healthcare system and education of cancer patients and healthcare professionals.


Cervical cancer is the fourth most commonly diagnosed cancer worldwide and, in almost all cases is caused by infection with highly oncogenic Human Papillomaviruses (HPVs). On the other hand, inflammation is one of the hallmarks of cancer research. Here, we focused on inflammatory proteins that classify cervical cancer patients by considering individual differences between cancer patients in contrast to conventional treatments. We repurposed anti-inflammatory drugs for therapy of HPV-16 and HPV-18 infected groups, separately. In this study, we employed systems biology approaches to unveil the diagnostic and treatment options from a precision medicine perspective by delineating differential inflammation-associated biomarkers associated with carcinogenesis for both subtypes. We performed a meta-analysis of cervical cancer-associated transcriptomic datasets considering subtype differences of samples and identified the differentially expressed genes (DEGs). Using gene signature reversal on HPV-16 and HPV-18, we performed both signature- and network-based drug reversal to identify anti-inflammatory drug candidates against inflammation-associated nodes. The anti-inflammatory drug candidates were evaluated using molecular docking to determine the potential of physical interactions between the anti-inflammatory drug and inflammation-associated nodes as drug targets. We proposed 4 novels anti-inflammatory drugs  for the treatment of HPV-16, 3 novel drugs for the treatment of HPV-18 , and 5 novel drugs  for the treatment of both subtypes. We proposed anti-inflammatory drug candidates that have the potential to be therapeutic agents for the prevention and/or treatment of cervical cancer. According to data collected worldwide in 2018, cervical cancer was the fourth most commonly diagnosed cancer  and the fourth leading cause of death  . In 2020Vaccines are now being proposed to prevent cervical cancer . VariousDrug repurposing means identifying new therapeutic purposes for existing drugs. Due to its high efficiency in terms of time saving and low cost compared to traditional approaches for drug development, the pharmaceutical research industry is showing great interest in drug repurposing . The inhInflammation is often described as a response to invasive pathogen simulations. When the inflammatory response is absent or cannot be controlled, it results in impaired tissue repair or pathology. For these reasons, inflammation is now referred to as the seventh hallmark of cancer. It was known that inflammation following viral infection promotes the development of cancer . StudiesHere, we repositioned anti-inflammatory drug candidates targeting inflammation-associated hub proteins using two different drug repositioning strategies to treat cervical cancer in a subtype-specific (HPV16 and HPV18) manner. To this end, we used a multistep computational approach . First, Since, our aim was to reveal the appropriate subtype-specific  personalized drugs for cervical cancer, the transcriptomic datasets were evaluated considering the genotypes of the diseased samples. In addition, to avoid undesirable alterations originating from differences in the microarray platforms used, we ensured that the transcriptome datasets were generated using the same platform. With this in mind, we found a total of five transcriptome datasets that corresponded to the HPV16 or HPV18 genotype whose gene expression measurements were performed using the same platform (Affymetrix microarrays). The five transcriptome datasets were as follows: GSE52903 , GSE3900p-value < 0.05 was used as a cut-off to determine the statistical significance of the DEGs. Fold change was used to determine the regulatory pattern of each DEG , and at least 1.5-fold change was considered statistically significant. Further analyses were performed with DEGs that shared at least three of the five HPV16 datasets, referred to as “HPV16-associated DEGs,” while analyses were performed with DEGs that shared at least two of the three HPV18 datasets, referred to as “HPV18-associated DEGs.” In this way, the analysis performed with DEGs that occurred in at least 60% of all datasets.This study used a well-established statistical analysis procedure  to identp-values were determined via Fisher’s Exact Test, and FDR was applied to control p-values. For overrepresentation analyses, an adjusted p-value < 0.05 was considered statistically significant.Overrepresentation analyses were performed using ConsensusPathDB  to deterTo reveal the correlations of gene signatures of drugs, the database CLUE  was usedp-value < 0.01.A web-based transcriptome-driven drug repositioning application tool, geneXpharma , was useAnti-inflammatory drugs were identified through an anatomical therapeutic chemical (ATC) classification system and a literature review. Drugs with ATC codes M01A , H02AB  and N02BA  were selected as anti-inflammatory drugs and obtained from the DrugBank resource (version 5.1.7) . The druThe human protein interactome was derived from a previously published study  containiTo identify the inflammation-associated hub DEGs, we first specified proteins previously associated with inflammation. To this end, proteins classified in the inflammatory response process (GO: 0006954) were screened in QuickGO, a web-based tool for searching Gene Ontology annotations (version 2021-01-08) . In addiThe three-dimensional (3D) crystal structure of the target proteins  was taken from Protein Data Bank (PDB)  when avap-value <0.05 and log2FC >|0.58|). The expression patterns (up- or down-regulation) of the culminated DEGs for five HPV16 transcriptome datasets were numerically almost identical. Namely, a total of 51% of DEGs were up-regulated. In addition, the expression patterns of the culminated DEGs for HPV18 tended to be up-regulated (56%).As a result of the analysis, thousands of individual DEGs were identified according to the criteria we established . Further analyses were performed for HPV16 DEGs culminating in at least three datasets, referred to as “HPV16-associated DEGs” and for HPV18 DEGs common in at least two datasets, referred to as “HPV18-associated DEGs”. A total of 1289 (525 down- and 764 up-regulated) HPV16-associated DEGs and 1167 (401 down- and 766 up-regulated) HPV18-associated DEGs were identified . In addiE. coli infection, and ECM-receptor interaction , a drug repurposing analysis was performed using two different strategies .First, transcriptomic gene signatures corresponding to HPV16- and HPV18-associated DEGs were used as input to query the CLUE database  to assesp-value to each drug, and drugs with a hypergeometric p-value < 0.01 were accepted as significant in the analysis. As a result, we found a total of 611 different drugs for the HPV 16 subtype  the repositioned drugs and their targets were all associated with anti-inflammatory agents, 2) the drug repurposing approach was used with two different strategies, and 3) the differences between HPV16 and HPV18 subtypes were considered in the analysis.Inflammation is linked to cancer and plays an important role in tumor growth and progression through epidemiological studies . As a reAs persistent infections and/or chronic inflammation are the main reasons for cancer development, persistent HPV infection with high risk is undoubtedly crucial for cervical cancer progression. In addition to persistent infection, studies have clearly shown that long-term chronic inflammation contributes to the development of cervical cancer . Given aThe main indications for anti-inflammatory drugs are fever, pain, and inflammation. However, many anti-inflammatory drugs have properties similar to neoplastic agents in that they promote apoptosis, inhibit angiogenesis, and enhance the immune response . TherefoAccording to GLOBOCAN data on cervical cancer, low-income countries have higher mortality and higher incidence . CervicaWe used gene signature and network-based drug repurposing strategies to identify drug candidates. The typical starting point of both strategies was gene signatures derived from cervical cancer transcriptomic data. When repositioning drugs based on gene signatures, we used the effect of reverse expression of the disease state, as in many studies . Howeverin silico analysis. We also identified 3 new HPV18-specific drug candidates  and 5 drug candidates  for the treatment of both subtypes. These five candidate drugs can be highlighted particularly for underdeveloped countries where cervical cancer is very common and subtyping is not routinely done. We reported valuable data for further experimental and clinical efforts, as the proposed anti-inflammatory drug candidates can be used as therapeutics for the prevention and/or treatment of cervical cancer. The major limitation of the study is the lack of experimental validations of the identified anti-inflammatory drugs on the cervical cancer tissue samples or cell lines. Future in vitro studies need to be performed to investigate the effects of the identified drug candidates on cell viability, proliferation, and migration. Moreover, the mechanism of action of these molecules needs to be studied experimentally to elucidate their effects on important molecular signaling pathways such as cell death and cell replication. In addition, the proposed drug candidates can not only be considered as single agent candidates, but can also be used in combination, so that the effect of combination therapy can also be validated by in vitro studies.Although HPV16 and HPV18 are the two viruses responsible for most cases of cervical cancer, they represent different HPV subtypes. The HPV subtypes may have different biological mechanisms and affect cancer progression differently. This natural variability of cancer promotes the development of personalized medicine. The password of personalized medicine stands for the right drug, for the right patient, at the right time, and at the right dose . Althoug


The coronavirus disease 2019 (COVID-19) pandemic has disrupted global health systems and affected the transmission dynamics as well as the surveillance of other infectious diseases. This study described the probable effect of the COVID-19 pandemic on the surveillance and control of leptospirosis in Sri Lanka. With 8,579 reported cases and more than 800 estimated deaths, the Sri Lankan public health surveillance system documented the largest outbreak of leptospirosis in Sri Lankan history in 2020. This was the worst infectious disease outbreak Sri Lanka experienced in 2020, but it was neglected, primarily due to the COVID-19 pandemic. The coronavirus disease 2019 (COVID-19) pandemic has disrupted global health systems, with more than 4.7 million lives already lost and over 234 million cases by the end of September 2021. The excess death rate due to the pandemic may exceed its large direct death toll by more than 50%. In most places, the extra death rate is not accounted for, reported, or documented [Sri Lanka is considered a hot spot for leptospirosis, with an estimated annual incidence of 52.1 per 100,000 population and 730 annual deaths . Since tLeptospira causing different clinical and biochemical manifestations often misdirect the diagnosis of leptospirosis [The reported cases of leptospirosis are considered a gross underestimation and could have been described as part of the COVID-19 pandemic based on previously published causes of underestimations . First, spirosis . Some ofspirosis .Sri Lanka had its first full-scale national lockdown due to COVID-19 from March to May 2020. Since then, movement restrictions and small-scale lockdowns took place until May 2021, when another surge of COVID-19 cases was detected . The totWe postulate that the reported data were subject to considerable reporting bias due to COVID-19. While all districts previously known to have endemic leptospirosis reported a higher incidence, Colombo and Gampaha reported a very low incidence . These 2Unlike the 2008 outbreak of leptospirosis, where a substantial amount of disease investigation took place, the 2020 outbreak heretofore went unnoticed by the healthcare system and researchers. The total number of COVID-19 cases reported in 2020 was 43,289, which is negligible compared to the surge of cases after April 2021 [This study has several limitations. A comprehensive overview of excess deaths due to leptospirosis could be obtained by comparing the CFR from 2020 with those of previous years. However, mortality data on leptospirosis have yet to be made available from the Ministry of Health, Sri Lanka.


The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to evolve and infect individuals. The exterior surface of the SARS-CoV-2 virion is dominated by the spike protein, and the current work examined spike protein biochemical features that have changed during the 3 years in which SARS-CoV-2 has infected humans. Our analysis identified a striking change in spike protein charge, from −8.3 in the original Lineage A and B viruses to −1.26 in most of the current Omicron viruses. We conclude that in addition to immune selection pressure, the evolution of SARS-CoV-2 has also altered viral spike protein biochemical properties, which may influence virion survival and promote transmission. Future vaccine and therapeutic development should also exploit and target these biochemical properties.  •Biochemical features of the SARS-CoV-2 spike protein have changed during the pandemic•Spike charge has steadily increased from −8.3 to −1.26 in Omicron lineages•Multiple spike functions may be altered: epitopes, receptor binding, furin cleavage•Other coronaviruses moving from animals to humans show similar spike charge increases Evolutionary biology; Virology The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of the coronavirus disease 2019 (COVID-19) epidemic, continues to evolve and infect individuals. Similar to other viruses, the SARS-CoV-2 virion biochemical properties play an important role in controlling virus transmission. After replication in an infected individual and release from an infected cell, onward transmission requires survival of the virion to reach susceptible cells in a new host individual initiating the next round of infection. The physical properties of the surface proteins of the virus such as charge, size, hydrophobicity, and folding may influence movement of the virion through the environment, promoting or limiting binding of the virion to the external surfaces. Once reaching a susceptible individual, physical properties of the virion may influence movement within the human airway and determine the ability of an infecting virion to reach target cells to bind, enter, and replicate.,,,,,,Much of the observed spike protein substitutions may be in response to the developing immune response to this new pathogen, which is reflected in substitutions occurring in the immune-exposed S1 domain of the spike protein, and there is ample evidence that many of these spike protein changes allow escape from host immunity.The SARS-CoV-2 spike protein physical features were calculated from spike protein sequences from across 3 years of the COVID-19 epidemic. Features that could be quantitated from the protein sequence were used see , includiA dominant pattern of SARS-CoV-2 evolution during the three years of human adaptation has been the regular appearance and the subsequent regional and then global dominance of lineages. These lineages typically encode a small set of AA changes from earlier lineages, many of which are likely to provide temporary or long-term advantages for the viral lineage. An analysis was performed to identify spike physical features most strongly linked with SARS-CoV-2 lineages . The firChanges in charge of spike protein across the epidemic were investigated. Plotting total spike charge for all genomes per month of the epidemic showed a clear pattern of increase in charge over three years of evolution , panel AThese spike protein charge increases can be attributed to the major successful lineages reported over time B. The B.,Some indication of functional consequences of the observed changes in spike charge can be obtained from the location on the charged AA substitutions in the spike protein. Sets of spike sequences (extracted from the first 300 reported genomes per select lineage) were processed to illustrate the changes to a more negative charge (blue) or more positive charge (orange/red) in the protein relative to the initial Lineage B genome sequences . The ini,The spike charge calculations were performed using a pH value of 7.4; however, the virus may encounter other pH values from 7.5 to 5.7 during human infection see .13,14 AcIt is probable that the spike protein has an upper limit to the AA charge that it can allow for proper folding, assembly, and function. This upper charge value will be determined by the acquisition of optimum virus replication and transmission properties in balance with immune selection. After the regular increase of spike protein charge observed up to the appearance of the Omicron lineages, an indication of a stasis in positively charged AA accumulation is now displayed by SARS-CoV-2 Omicron lineages. The majority of Omicron sub-lineages remain at a spike charge of −1.26 A althoug,,Lastly, we investigated if a similar pattern of spike charge evolution could be observed in other coronaviruses that have made a transition to human transmission. In recent history, several coronaviruses (in addition to SARS-CoV-2) have been observed to jump hosts. For example, coronavirus 229E is commonly detected in humans, and very close coronaviruses have been identified in bats,Infection with coronavirus OC43 is common in humans, and closely related viruses are found in cattle (bovine coronavirus [BCoV]),,,,The commonly known host for the Middle Eastern Respiratory Syndrome coronavirus (MERS-CoV) is dromedary camels; however, zoonosis and serious human infections occur frequentlyConsidering the location of the charge differences in the spike proteins, for coronavirus 229E, the charge increases occurred throughout the protein although there is a slightly higher number of positive changes in the receptor-binding region of the human-infection-derived viruses D. For OC,After three years of the COVID-19 pandemic and with the availability of >14 million SARS-CoV-2 genome sequences, a trend of SARS-CoV-2 spike protein charge can be observed, with successive lineages showing an increase in positive charge over earlier lineages. Over the course of the pandemic, the SARS-CoV-2 spike protein has evolved from a protein with a total charge of −8.28 in the original Lineage A and B viruses to a protein with a total charge of −1.26 in the majority of the currently circulating Omicon lineage viruses. This pattern has been noted previously.This study does not identify a mechanistic basis for the increased spike charge although there are several possible transmission steps that might be promoted by increasing charge. Exposed, positively charged spike AAs should promote interactions with negatively charged cellular structures. Interactions with negatively charged heparin have been reported with SARS-CoV-2 spike,There is likely a limit to the accumulation of positively charged residues in the SARS-CoV-2 spike protein. Functional constraints exist, there may also be penalties associated with non-specific binding due to excess positive charge, and there are certainly charge influences on protein folding and higher order protein interactions.Could these changes in spike charge have occurred by chance and not be a response to selective pressure? Of the 20 standard AAs, only 2 AAs have negatively charged side chains, 2 AAs have positively charged side chains, while the remaining 16 AAs are neutral at pH 7.4. Assuming equal probability of any AA change, there is an 18/20 chance of a negative AA being substituted by a neutral or positively charged AA, and the majority of change opportunities would result in a loss of negative charge. However, natural selection is more complex because the genetic code uses 3 adjacent nucleotides to encode an AA, there are multiple encoding possibilities for each AA, the codon redundancy is not identical for each AA, and the number of nucleotide changes required to produce any particular AA change can be 1, 2, or 3. This has resulted in an evolved protein stability in the genetic code,We asked if the increased charge pattern we report for the Spike protein might extend to other proteins on the SARs-CoV-2 virion. There are 4 structural proteins in the SARS-CoV-2 virion, Spike (S), the orf4 envelope (E) protein, the orf5 membrane (M) protein, and the orf9 nucleoprotein (N), with only S, E, and M proteins exposed on the surface of the virion.Obermeyer et al. documented AA substitutions associated with SARS-CoV-2 fitness.We have summarized the most frequently observed changes in the spike protein in Natural selection could be acting on multiple features of the spike protein. The necessity to avoid host immune responses is likely to be the major selective force acting on the virus. This results in the AA changes, which in turn are determined by epitopes. The selection for increased charge in the spike protein is probably occurring in the background, not as a major shift needed to bypass immune responses. However, the increase in charge may improve survival and transmission in humans in subtle ways, and this advantage, when multiplied over the millions of infections, can provide some of the growth and infection advantages seen by new SARS-CoV-2 variants. It is proposed that the N764K, N856K, and N969K substitutions  may enhance S1-S2 subunit interactions after proteolytic processing of the spike protein, resulting in reduced S1 shedding and improving transmission.In conclusion, our study provides a novel analytical framework to monitor viral evolution through changes in biochemical properties, which can be easily applied to other viruses important to public and global health. We also showed that natural virus evolution is more complicated and may involve multiple factors including immune selection, as well as spike protein biochemical properties. The observation of an increase of SARS-CoV-2 spike protein charge over time provides useful information for future vaccine and therapeutic development.Our analysis was limited to available data, and many of the SARS-CoV-2 genome sequences available have an incomplete spike coding region, which may introduce bias in our analysis. Our conclusions about zoonosis of non-SARS-CoV-2 coronaviruses are limited to available viruses with available sequence data, and for some of the coronavirus, no clear animal source has been identified, or insufficient sequence data are available to explore charge differences. Nonetheless, we believe the analyses reported here are a valid description of the spike charge changes.matthew.cotten@lshtm.ac.uk).Further information should be directed to the lead contact, Matthew Cotten  was retrieved and translated into protein. Features of the spike protein that could be quantitated from the protein sequence were determined using the ProteinAnalysis functions from BioPython.No additional resources were used.


Background: The COVID-19 pandemic increased the complexity of the clinical management and pharmacological treatment of patients presenting with an Acute Coronary Syndrome (ACS). Aim: to explore the incidence and prognostic impact of in-hospital bleeding in patients presenting with ACS before and during the COVID-19 pandemic. Methods: We evaluated in-hospital Thrombolysis In Myocardial Infarction (TIMI) major and minor bleeding among 2851 patients with ACS from 17 Italian centers during the first wave of the COVID-19 pandemic  and in the same period in the previous two years. Results: The incidence of in-hospital TIMI major and minor bleeding was similar before and during the COVID-19 pandemic. TIMI major or minor bleeding was associated with a significant threefold increase in all-cause mortality, with a similar prognostic impact before and during the COVID-19 pandemic. Conclusions: the incidence and clinical impact of in-hospital bleeding in ACS patients was similar before and during the COVID-19 pandemic. We confirmed a significant and sizable negative prognostic impact of in-hospital bleeding in ACS patients. Patients with acute coronary syndrome (ACS) and concomitant Coronavirus Disease 19 (COVID-19) have an increased risk of morbidity and mortality and often represent a vulnerable population ,3,4. A vWe collected data in a multicenter, national, retrospective ACS collaborative registry from 17 high-volume centers in Italy. The study population consisted of all consecutive patients admitted with ACS during 3 time intervals before  and during the first wave of the COVID-19 pandemic in the participating centers . All patients, regardless of whether they underwent percutaneous coronary intervention, were included. Data about demographics, risk factors, previous medical history, procedural information, and in-hospital outcomes were collected. Acute coronary syndrome diagnosis was made following international guidelines ,14. In-ht-test for quantitative variables and chi-square for categorical variables. Univariate and multivariate regression analysis was used to evaluate the association of baseline characteristics with the safety endpoints. Survival analysis using Cox regression was performed to evaluate the prognostic impact of bleeding events in the two study periods, and the heterogeneity of effect was evaluated through interaction testing. Interaction tests were performed with likelihood ratio tests of the null hypothesis that the interaction coefficient was zero. A two-sided probability value < 0.05 was considered significant. All statistical analyses have been computed using SPSS v.26.0 .Continuous variables have been reported as means and standard deviation (SD) or medians and interquartile ranges, as appropriate. Discrete variables have been indicated as counts and percentages. We compared the two groups of patients with ACS included before and during the COVID-19 pandemic (2018–2019 versus [vs.] 2020) to highlight differences in the demographic, procedural, and clinical characteristics using p = 0.005), with no heterogeneity observed for the period before  and during the COVID-19 pandemic  (Pint = 0.49) (Among 2851 patients admitted with acute coronary syndrome (ACS), 2142 (75.1%) were admitted in the period of March–April 2018–2019 before the COVID-19 pandemic and 709 (24.9%) during the first wave of the COVID-19 pandemic in March–April 2020. The hospital stay was 6 ± 5.1 days, and the intrahospital mortality rate was 2.4%. Baseline characteristics of patients included before and after the COVID-19 pandemic are provided in  = 0.49) . The res = 0.49) .Traditional baseline predictors of bleeding in ACS patients were similar in the two study periods.The incidence of major or minor bleeding during hospitalization for ACS was similar both before and during the first wave of the COVID-19 pandemic.In-hospital major or minor bleeding carries a significant and immediate prognostic impact in ACS patients, and this was confirmed also in admissions during the COVID-19 pandemic.The main findings of our study from a large multicenter registry of patients with acute coronary syndrome collected before and during the first wave of the COVID-19 pandemic could be summarized as follows:To the best of our knowledge this is the first report focusing on the incidence and prognostic impact of in-hospital bleeding in ACS patients during the first wave of the COVID-19 pandemic. With the introduction of refined and more potent antithrombotic regimens, the incidence of ischemic complications in patients with ACS has steadily decreased in the last two decades, while in turn the risk of major bleeding has roughly doubled, becoming the most common clinical complication after an ACS .Bleeding complications have been associated with an increase in mortality in an ACS setting ,10,11 wiAmong hospitalized patients with COVID-19, thromboembolism is an important piece of the puzzle . LeveragMultiple national registries confirmed a drastic reduction of roughly 50% of the number of patients presenting with MI compared with the same period in previous years. ,23 In thAlternatively, we could speculate that specific adjustment in the multiple antithrombotic therapy in ACS patients with potential indication to additional therapy for confirmed or suspected COVID-19 could have mitigated the risk of bleeding in this observational cohort. In this setting, patients with indication to oral anticoagulation therapy could have been targeted with less potent antiplatelet agents or with shorter courses of multiple antithrombotic therapies, based on clinician risk perception, which could have limited the risk of bleeding complication despite multiple antithrombotic therapy.Our study has several important limitations that should be acknowledged. First, this is an observational study, hence our findings should be considered hypothesis-generating rather than conclusive. Second, although all patients admitted during the first wave of the COVID-19 pandemic were tested with a specific swab, we included both individuals irrespectively of a confirmed COVID-19 diagnosis or evidence of positive swab. This is relevant, as pharmacologic treatment in this group might have been different. However, our main aim was also to compare predictors of bleeding in patients presenting with ACS both before and during the pandemic. Exploring the frequency and clinical impact of bleeding in a larger population of patients with COVID-19 would be relevant. Importantly, detailed data regarding antithrombotic treatment were not available for all patients included, which limits our ability to explore the relationship between bleeding events and assigned pharmacological therapy. Finally, we only provide outcomes for the in-hospital phase, whereas no information for out-of-hospital events is available. This point is of great importance, and future dedicated studies should target this issue. Nevertheless, this is the first report that focuses on the incidence and prognostic impact of in-hospital bleeding in ACS patients during this unprecedented health crisis, and it could at least partially inform upon the risks of these complications during the in-hospital phase of ACS patients.In our large, multicenter registry of ACS patients included before and during the first wave of the COVID-19 pandemic, we observed a similar incidence and prognostic impact of in-hospital bleeding during both study periods. We confirmed a significant and similar negative prognostic impact of in-hospital bleeding during ACS hospitalization, which should prompt physician awareness of this dangerous complication also in the context of COVID-19 when multiple antithrombotic agents may be needed.


The aftermath of the initial phase of the COVID-19 pandemic may contribute to the widening of disparities in access to colorectal cancer (CRC) screening due to differential disruptions to CRC screening. This comparative microsimulation analysis uses two CISNET CRC models to simulate the impact of ongoing screening disruptions induced by the COVID-19 pandemic on long-term CRC outcomes. We evaluate three channels through which screening was disrupted: delays in screening, regimen switching, and screening discontinuation. The impact of these disruptions on long-term colorectal cancer (CRC) outcomes was measured by the number of Life-years lost due to CRC screening disruptions compared to a scenario without any disruptions. While short-term delays in screening of 3-18 months are predicted to result in minor life-years loss, discontinuing screening could result in much more significant reductions in the expected benefits of screening. These results demonstrate that unequal recovery of screening following the pandemic can widen disparities in colorectal cancer outcomes and emphasize the importance of ensuring equitable recovery to screening following the pandemic. In addition to the over 1 million COVID-19 deaths in the United States,7 There is clear evidence that screening has a major impact on reducing the burden of CRC,9 and that it is cost-effective.11 The current United States Preventive Task Force (USPSTF) report recommends multiple screening options, including annual fecal immunochemical tests (FIT) and colonoscopy every ten years for average-risk individuals.12 However, CRC screening uptake was of concern even before the pandemic, with CRC screening rates well below the goal of 70.5% for Healthy People 2020 and the National Colorectal Cancer Roundtable goal of 80% by 2018.13 Low rates of CRC screening have been exacerbated by the COVID-19 pandemic, and delays in screening will result in delays in diagnosis, stage progression, and increased CRC mortality.CRC remains the second-leading cause of cancer deaths in the United States, with approximately 151,030 new cases and 52,580 deaths estimated in 2022.14 Because of this, the pandemic may contribute to widening disparities in cancer outcomes. A recent analysis using National Health Interview Survey (NHIS) data postulated that unemployment was adversely associated with being up-to-date with screening, with only 16.7% of unemployed individuals participating in recent CRC screenings, only 48.5% of whom were up-to-date with CRC screening.15The pandemic may also further exacerbate existing disparities related to screening. The burden of unemployment and associated loss of access to healthcare care varies across different racial and ethnic groups.The objective of this study is to estimate the impact of ongoing screening and treatment disruptions induced by the COVID-19 pandemic on long-term CRC outcomes. We examine twenty-five scenarios that reflect different levels of pre-pandemic adherence to colonoscopy and FIT screening to assess how unequal recovery in screening may contribute to widening disparities in CRC lifetime outcomes.18 We consider variations on two commonly-used screening strategies in the USPSTF recommendations during the onset of the pandemic in March 202019: Decennial colonoscopy from age 50 to 70 and annual FIT tests from age 50 to 75, with diagnostic colonoscopy after a positive FIT. This paper uses two independently developed microsimulation models of CRC, CRC-SPIN and MISCAN-Colon, to estimate the effects of pandemic-induced disruptions in colonoscopy screening for eight pre-pandemic average-CRC risk population cohorts in the United States. CRC-SPIN and MISCAN-Colon models are part of the National Cancer Institute’s CISNET consortium and describe the natural history of CRC in an unscreened population based on the adenoma-carcinoma sequence. Detailed descriptions of these models and underlying assumptions may be found elsewhere.We simulated eight pre-pandemic population cohorts that represent average-risk individuals in the United States, defined by both cohort members’ age in April 2020 and their pre-pandemic screening regimens: i) Unscreened 50-year-olds (U50), ii) Unscreened 60-year-olds (U60), iii) Colonoscopy screening-adherent 60-year-olds , iv) FIT screening-adherent 60-year-olds  FIT screening semi-adherent 60-year-olds (f60) – those who received biannual FIT tests from age 50 to 56, vi) Unscreened 70-year-olds (U70), vii) Colonoscopy screening-adherent 70-year-olds , and viii) FIT screening-adherent 70-year-olds . We simulated 10 million individuals within each cohort to reduce the stochastic variability in our runs and to ensure sufficient precision in our estimates. For each cohort, we simulated three sets of post-pandemic scenarios: no disruption, delays, and no screening.No-disruption scenarios simulate post-pandemic screening scenarios for each cohort in the counterfactual scenario where no pandemic-induced screening disruptions occurred. In No Disruption scenarios, all these cohorts would have been screened during the pandemic first lockdowns in March 2020. Cohorts with colonoscopy and FIT adherent individuals  continue to follow guideline-recommended strategies strictly, with no delays. Cohorts with delayed initiation  begin screening late but otherwise follow guideline-recommended strategies with no delays but without any additional screening beyond the usual stopping age. Finally, for the FIT-semi-adherent 60-year-olds (f60), we simulate resumption of biannual FIT tests at age 60, continuing to age 75.The delays in screening. Screening colonoscopy and FIT are assumed to be delayed for a set duration of months starting at the onset of the COVID-19 pandemic in April 2020. Short-term screening delays may have occurred for a series of reasons. Firstly, elective procedures were postponed during the first months of the pandemic. The cancelation of elective procedures caused a sharp decline in CRC screening exams during the initial phase of the pandemic.20 To represent the full spectrum of delays caused by the pandemic – either due to cancellation of elective procedures or disruption in access to health care – we consider three sets of delays: a 3, 9, or 18-month delay in screening, which we label as short-term delays. For each delay scenario, the delay was applied on the first post-March 2020 screening exam and carried forward to any subsequent exams.The pandemic has been shown to affect CRC outcomes through long-term delays in CRC screening. While the recovery in screening rates among insured individuals was rapid,21 the pandemic also caused a sharp economic recession. The uneven recovery in labor force participation has potential to cause disparities in access to healthcare in the United States due to unemployment and discontinuation of health insurance. To examine these longer-term effects of the pandemic, we consider scenarios where screening is paused for an extended period. For the 50- and 60-year-old cohorts, we simulated scenarios where screening is discontinued until the start age of Medicare enrollment (65 years). For 70-year-olds, we consider a scenario where screening is only resumed at age 75 – 5 years after the pandemic onset.Secondly, the pandemic may have caused regimen switching – i.e., changing from a colonoscopy screening regimen to one based on FIT tests. There is evidence that during the pandemic some patients switched from colonoscopy to FIT15 to reduce the need for in-person endoscopy procedures. Considering this possibility, we model scenarios where individuals who initially participated in a regimen of screening colonoscopy (C60 and C70) permanently switch from decennial colonoscopy to annual FIT screening as a boundary case. While one might expect pandemic-induced regimen switching to be temporary, permanent switching can serve as a boundary case for our analysis – that is, the effect of short-term regimen switching is expected to be lower than the effect of permanent regimen switching.The pandemic may also affect CRC behavior via screening We also simulate scenarios where screening is completely discontinued after the pandemic onset as the most consequential boundary case scenario. While only a small (unknown) proportion of individuals will discontinue screening after the pandemic, this scenario serves as an upper bound for the worst possible disruption in CRC screening following the pandemic.[pre-pandemic screening cohort] | [post pandemic disruptions].Each of the scenarios simulated in this study results from the combination of a pre-pandemic population cohort, a no-disruption screening scenario that serves as a counterfactual, and one or more screening disruptions . The primary measure used to assess the benefit of CRC screening programs is the expected lifetime life-years gained (LYG) from screening. All outcomes in this study correspond to expected value of life-years across the US population with average CRC risk. This study investigates the extent to which benefits from screening are expected to be lost due to pandemic-induced disruptions to CRC screening. Therefore, we calculated the total number of Life-Years (LY) for each cohort and scenario, including the number of LY under no screening (LYNS) and the number of LY under no disruptions (LYND). LYNS is computed by simulating the cohort in the absence of CRC screening and LYND is computed by simulating the same cohort under an ideal screening scenario where no disruptions to screening happened, as defined in LYL = LYND − LY. The hypothetical number of LY gained (LYG) from screening under no disruptions are no disruptionLYG = LYND − LYNS. Finally, we compute the percentage of life-years gained or lost due to disruption as % LY Lost = 100 * LYL / no disruptionLYG. The first outcome measure (LYL) is an absolute measure of the loss of screening benefit due to pandemic disruptions. The percent LY lost due to disruptions indicates the share of screening benefit lost due to the pandemic. Following previous analyses, we present all outcomes as LY per 1,000 individuals or life days per person. We compute each of those outcomes separately for each model and report the range of outcomes observed across both models.The key outcome estimated in this study is the expected number of LY lost (LYL) due to disruptions in screening, defined as Loss of life due to screening disruptions was the largest for cohorts with severe disruptions after the pandemic . Aside fSimilarly, 60-year-olds are expected to incur a substantial reduction in the benefit of screening if screening is discontinued after the pandemic. Those who started screening at age 50 and stopped after the pandemic are expected to lose 106 to 124 or 92 to 111 LY per 1,000 individuals if pursuing a colonoscopy (C60 | U) or a FIT (F60 | U) screening regimen, respectively. Those who were semi-adherent to FIT screening before the pandemic and discontinued screening (f60 | U) lose even more life-years – from 143 to 149 LY per 1,000 individuals, or 58 to 69 percent of the benefit of screening. Similarly, unscreened 60-year-olds who start screening at age 65 (scenario U60 | C@65) are predicted to lose 42 to 45 LY per 1,000 individuals compared to a scenario where they would have begun screening at age 60 - , and a 20 to 22 percent loss in LYG from screening due to this disruption.Switching the screening regimen from colonoscopy to FIT and short-term delays will cause only a modest reduction in the benefit of screening. For the 60-year-old cohort, switching from colonoscopy to annual FIT after the pandemic with an 18-month delay is expected to result in a loss of 9 to 11 LY per 1000 individuals, a 3 to 4 percent loss relative to a scenario with no change in screening regimen and no delays. Similarly, short-term delays are predicted to cause minimal decreases in the benefits of the screening program. A 3-month delay in colonoscopy screening results in a loss of 0 to 2 LY per 1,000 individuals for the 60-year cohort (scenarios C60 | C3m), whereas a 9- or 18-month delay (C60 | C9m and C60 | C18m) is expected to result in a loss of 0 to 2 or 0 to 3 LY per 1,000 individuals, respectively). The worst-case scenario of a 18-month pause starting in March 2020 (scenario C60 | C18m) resulted in a 0 to 1 percent loss of the benefit of screening.70-year-olds lose fewer life-years due to screening disruptions but can still be affected by the pandemic as they are at greater risk for CRC than younger age groups. When discontinuing screening after the pandemic, 70-year-olds are expected to lose 38 to 87 or 29 to 33 LY per 1,000 individuals due to the pandemic if pursuing a colonoscopy (C70 | U) or FIT (F70 | U) screening regimen, respectively. Unscreened 70-year-olds who only come back to screening at age 75 (scenario U70 | C@75) are expected to lose 49 to 50 LY per 1,000 individuals, a 39 to 43 percent reduction in LYG relative to a scenario where they would have received colonoscopy screening at age 70.70-year-olds who were up to date with their screening and experienced short-term delays of up to 18 months can expect minimal loss of LY due to pandemic-induced CRC screening disruptions, even if they switch to FIT tests after the pandemic. Those who transitioned from colonoscopy to FIT screening at age 70 can expect a reduction of 5 to 7 LY per 1,000 individuals even if a return to FIT screening was delayed by 18 months (scenario C70 | F18m). This reduction in benefit represents a 2 to 3 percent reduction in LYG of colonoscopy-only screening.conditional on colonoscopy sensitivity, the loss of life-years due to pandemic-induced scenarios is similar across sensitivity levels. High colonoscopy sensitivity scenario, whereas it is 217 to 272 under a Low colonoscopy sensitivity scenario  only experience a small loss of life due to short-term delays – up to 3 LY per 1,000 individuals Those who switch from colonoscopy to FIT screening are projected to experience a greater loss of life – from 9 to 11 to LY per 1,000 individuals). If screening is only resumed at age 65  or abandoned, the loss of benefits from screening could be 3 to 11 LY per 1,000 individuals (scenario C60 | C@65). Lastly, discontinuing screening after the pandemic is projected to cause a loss of 106 to 124 LY per 1,000 individuals, a decrease of 36 to 51 percent in the benefit of screening (scenario C60 | U). These results imply that the pandemic will become a disparity-widening mechanism if it differentially affects screening access and or behavior across different population groups. These results also show that the pandemic is unlikely to generate any substantial effect on those whose screening is only interrupted momentarily.22 Moreover, data from the US Census Household Pulse Survey suggests that Black and Hispanic workers were not only more likely to be unemployed but were also more likely to be without unemployment insurance.23 These results provide important clinical insight on the projected impact of these populations which may guide future policy on the aftereffects of the pandemic. Those who were previously uninsured for long periods of time throughout the pandemic should be prioritized to resume timely CRC screening to mitigate the long-term effects postulated in these simulations.These results highlight the potential implications of disruptions to preventative care due to loss of insurance following the pandemic. According to data from the Bureau of Labor Statistics Current Population Survey, more dramatic declines in the number employed during the COVID-19 pandemic were seen in Black, Asian American and Hispanic groups.24 A microsimulation paper based on a Chilean population illustrated similar results with respect to CRC incidence and mortality due to the screening backlog and strained patient care during the pandemic.25 Our results mirror these conclusions and provide new scenarios which consider the aftereffects of loss of healthcare insurance due to disparities magnified by the COVID-19 pandemic.These results also add to the growing evidence of the implications of delayed CRC care following the COVID-19 pandemic. A microsimulation study based on a Canadian population explored scenarios of differing screening delays and transition periods due to attenuated screening volumes and found that a 6-month delay in primary screening could increase CRC incidence by 2,200 cases and 960 more cancer deaths over a lifetime.This analysis presents a series of limitations. First, we do not present population-level estimates of reductions in benefits. While doing so could prove helpful, one would have to estimate how many people will be screened following each scenario we modeled. That would require individual-level data describing the distribution of delays and screening regimen switching in the population after the pandemic, which will not be available for many years. Instead of pursuing a population-level study, we conditioned our estimates on a discrete set of pre-specified disruption scenarios. This approach makes our study feasible but prevents us from making population-level predictions.Second, the scenarios presented in this analysis represent only a subset of the real-world changes in screening due to the pandemic. Even in the absence of a pandemic, individuals may switch from colonoscopy to FIT, and return to colonoscopy screening. To keep this analysis tractable, we restrict the variations considered in this paper to one switch from colonoscopy to FIT. Further, we only consider changes in screening regimens immediately following the COVID-19 pandemic.Third, this analysis only considers uncertainty stemming from structural differences between models and two scenarios of test characteristics and does not evaluate parameter or sampling uncertainty. Our estimates represent the expected value of estimates conditional on scenarios across an average-risk cohort drawn from the general US population. Finally, this analysis focuses on the effects of the pandemic on the primary measure of the benefit of CRC screening - life-years gained from screening. We do not present the effects of disruptions on other secondary measures that will likely be affected, such as cancer incidence and screening utilization.This study quantified the potential effect of a set of disruptions to colonoscopy screening and demonstrated that unequal recovery of CRC screening following the pandemic will predictably widen disparities in CRC outcomes. The COVID-19 pandemic will severely reduce the benefits of CRC screening if it causes screening discontinuation or long-term  delays. Short-term delays of 3-18 months and regime switching from colonoscopy to FIT tests are not expected to have significant consequences.1