Biology subjects

Grad, Y. H.

Publications and source records attributed to Grad, Y. H..

36 records · Page 2Linked to original sources

bioRxiv2020

Jointly modeling prevalence, sensitivity and specificity for optimal sample allocation

The design and interpretation of prevalence studies rely on point estimates of the performance characteristics of the diagnostic test used. When the test characteristics are not well defined and a limited number of tests are available, such as during an outbreak of a novel pathogen, tests can be used either for the field study itself or for additional validation to reduce uncertainty in the test characteristics. Because field data and validation data are based on finite samples, inferences drawn from these data carry uncertainty. In the absence of a framework to balance those uncertainties during study design, it is unclear how best to distribute tests to improve study estimates. Here, we address this gap by introducing a joint Bayesian model to simultaneously analyze lab validation and field survey data. In many scenarios, prevalence estimates can be most improved by apportioning additional effort towards validation rather than to the field. We show that a joint model provides superior estimation of prevalence, as well as sensitivity and specificity, compared with typical analyses that model lab and field data separately.

immunology↗

bioRxiv2020

Increased power from bacterial genome-wide association conditional on known effects identifies Neisseria gonorrhoeae macrolide resistance mutations in the 50S ribosomal protein L4

The emergence of resistance to azithromycin complicates treatment of N. gonorrhoeae, the etiologic agent of gonorrhea. Population genomic analyses of clinical isolates have demonstrated that some azithromycin resistance remains unexplained after accounting for the contributions of known resistance mutations in the 23S rRNA and the MtrCDE efflux pump. Bacterial genome-wide association studies (GWAS) offer a promising approach for identifying novel resistance genes but must adequately address the challenge of controlling for genetic confounders while maintaining power to detect variants with lower effect sizes. Compared to a standard univariate GWAS, conducting GWAS conditioned on known resistance mutations with high effect sizes substantially reduced the number of variants that reached genome-wide significance and identified a G70D mutation in the 50S ribosomal protein L4 (encoded by the gene rplD) as significantly associated with increased azithromycin minimum inhibitory concentrations ({beta} = 1.03, 95% CI [0.76, 1.30]). The role and prevalence of these rplD mutations in conferring macrolide resistance in N. gonorrhoeae had been unclear. Here, we experimentally confirmed our GWAS results, identified other resistance-associated mutations in RplD, and showed that in total these RplD binding site mutations are prevalent (present in 5.42% of 4850 isolates) and geographically and temporally widespread (identified in 21/65 countries across two decades). Overall, our findings demonstrate the utility of conditional associations for improving the performance of microbial GWAS and advance our understanding of the genetic basis of macrolide resistance in a prevalent multidrug-resistant pathogen.

microbiology↗

bioRxiv2020

Targeted surveillance strategies for efficient detection of novel antibiotic resistance variants

Genotype-based diagnostics for antibiotic resistance represent a promising alternative to empiric therapy, reducing inappropriate and ineffective antibiotic use. However, because such assays infer resistance phenotypes based on the presence or absence of known genetic markers, their utility will wane in response to the emergence of novel resistance. Maintenance of these diagnostics will therefore require surveillance designed to ensure early detection of novel resistance variants, but efficient strategies to do so remain to be defined. Here, we evaluate the efficiency of targeted sampling approaches informed by patient and pathogen characteristics in detecting genetic variants associated with antibiotic resistance or diagnostic escape in Neisseria gonorrhoeae, focusing on this pathogen because of its high burden of disease, the imminent threat of treatment resistance, and the use and ongoing development of genotype-based diagnostics. We show that incorporating patient characteristics, such as demographics, geographic regions, or anatomical sites of isolate collection, into sampling approaches is not a reliable strategy for increasing variant detection efficiency. In contrast, sampling approaches informed by pathogen characteristics, such as genomic diversity and genomic background, are significantly more efficient than random sampling in identifying genetic variants associated with antibiotic resistance and diagnostic escape.

genomics↗

bioRxiv2020

Increased antibiotic susceptibility in Neisseria gonorrhoeae through adaptation to the cervical environment

Neisseria gonorrhoeae is an urgent public health threat due to rapidly increasing incidence and antibiotic resistance. In contrast with the trend of increasing resistance, clinical isolates that have reverted to susceptibility regularly appear, prompting questions about which pressures compete with antibiotics to shape gonococcal evolution. Here, we used genome-wide association on the largest collection of N. gonorrhoeae isolates to date (n=4852) to identify loss-of-function (LOF) mutations in the efflux pump mtrCDE operon as a mechanism of increased antibiotic susceptibility and demonstrate that these mutations are overrepresented in cervical isolates relative to urethral isolates (odds ratio (OR) = 3.74, 95% CI [1.98-6.70]). In support of a model in which pump expression incurs a fitness cost in this niche, cervical isolates were also enriched relative to urethral isolates in LOF mutations in the mtrCDE activator mtrA (OR = 8.60, 95% CI [4.96-14.57]) and in farA, a subunit of the FarAB efflux pump (OR = 6.25, 95% CI [3.90-9.83]). In total, approximately 2 in 5 cervical isolates (42.6%) contained a LOF mutation in either the efflux pump components mtrC or farA or the activator mtrA. Our findings extend beyond N. gonorrhoeae to other Neisseria: mtrC LOF mutations are rare (<1%) in the primarily nasopharyngeal-colonizing N. meningitidis in a collection of 14,798 genomes but enriched in a heterosexual urethritis-associated lineage (8.6%, p = 9.90x10-5), indicating that efflux pump downregulation contributes broadly to the adaptation of pathogenic Neisseria to the female urogenital tract. Overall, our findings highlight the impact of integrating microbial population genomics with host metadata and demonstrate how host environmental pressures can lead to increased antibiotic susceptibility.

microbiology↗

bioRxiv2019

Quantifying the surveillance required to sustain genetic marker-based antibiotic resistance diagnostics

Diagnostics that minimize the time to selection of an appropriate antibiotic treatment represent an important strategy in addressing the challenge of antimicrobial resistance (AMR). Among this class of diagnostics, the use of pathogen genotype to predict AMR phenotype has been facilitated by advances in rapid sequencing platforms. A longstanding objection to this approach, however, is that the emergence of novel resistance mechanisms will inevitably lead to a decline in the sensitivity of these diagnostics. Here, we show that while the sensitivities of some genetic markers of resistance remain stably high, sensitivities of other markers rapidly decline, as expected, due to the emergence of novel resistance variants. We then present a simple mathematical framework that defines the sampling and phenotypic testing rates needed for early detection of novel resistance variants and thus demonstrate how surveillance can help maintain the sensitivity and utility of sequence-based AMR diagnostics.\n\nOne sentence summaryTargeted sampling strategies are necessary for early detection of novel resistance mechanisms and sustainability of genotype-based detection of novel resistance mechanisms and sustainability of genotype-based diagnostics.

microbiology↗

bioRxiv2019

Comparative Tn-Seq reveals common daptomycin resistance determinants in Staphylococcus aureus despite strain-dependent differences in essentiality of shared cell envelope genes

Antibiotic-resistant Staphylococcus aureus remains a leading cause of antibiotic resistance-associated mortality in the United States. Given the reality of multi-drug resistant infections, it is imperative that we establish and maintain a pipeline of new compounds to replace or supplement our current antibiotics. A first step towards this goal is to prioritize targets by identifying the genes most consistently required for survival across the S. aureus phylogeny. Here we report the first direct comparison of gene essentiality across multiple strains of S. aureus via transposon sequencing. We show that mutant fitness varies by strain in key pathways, underscoring the importance of using more than one strain to differentiate between core and strain-dependent essential genes. Despite baseline differences in gene importance, several pathways, including the lipoteichoic acid pathway, become consistently essential under daptomycin exposure, suggesting core vulnerabilities that can be exploited to resensitize daptomycin-nonsusceptible isolates. We also demonstrate the merit of using transposons with outward-facing promoters capable of overexpressing nearby genes for identifying clinically-relevant gain-of-function resistance mechanisms. Together, the daptomycin vulnerabilities and resistance mechanisms support a mode of action with wide-ranging effects on the cell envelope and cell division. This work adds to a growing body of literature demonstrating the nuanced insights gained by comparing Tn-Seq results across multiple bacterial strains.\n\nAuthor summaryAntibiotic-resistant Staphylococcus aureus kills thousands of people every year in the United States alone. To stay ahead of the looming threat of multidrug-resistant infections, we must continue to develop new antibiotics and find ways of making our current repertoire of antibiotics more effective, including by finding pairs of compounds that perform best when administered together. In the age of next-generation sequencing, we can now use transposon sequencing to find potential targets for new antibiotics on a genome-wide scale, identified as either essential genes or genes that become essential in the presence of an antibiotic. In this work, we created a compendium of genes that are essential across a range of S. aureus strains, as well as those that are essential in the presence of the antibiotic daptomycin. The results will be a resource for researchers working to develop the next generation of antibiotic therapies.

microbiology↗

bioRxiv2019

Evaluation of parameters affecting performance and reliability of machine learning-based antibiotic susceptibility testing from whole genome sequencing data

Prediction of antibiotic resistance phenotypes from whole genome sequencing data by machine learning methods has been proposed as a promising platform for the development of sequence-based diagnostics. However, there has been no systematic evaluation of factors that may influence performance of such models, how they might apply to and vary across clinical populations, and what the implications might be in the clinical setting. Here, we performed a meta-analysis of seven large Neisseria gonorrhoeae datasets, as well as Klebsiella pneumoniae and Acinetobacter baumannii datasets, with whole genome sequence data and antibiotic susceptibility phenotypes using set covering machine classification, random forest classification, and random forest regression models to predict resistance phenotypes from genotype. We demonstrate how model performance varies by drug, dataset, resistance metric, and species, reflecting the complexities of generating clinically relevant conclusions from machine learning-derived models. Our findings underscore the importance of incorporating relevant biological and epidemiological knowledge into model design and assessment and suggest that doing so can inform tailored modeling for individual drugs, pathogens, and clinical populations. We further suggest that continued comprehensive sampling and incorporation of up-to-date whole genome sequence data, resistance phenotypes, and treatment outcome data into model training will be crucial to the clinical utility and sustainability of machine learning-based molecular diagnostics.\n\nAuthor SummaryMachine learning-based prediction of antibiotic resistance from bacterial genome sequences represents a promising tool to rapidly determine the antibiotic susceptibility profile of clinical isolates and reduce the morbidity and mortality resulting from inappropriate and ineffective treatment. However, while there has been much focus on demonstrating the diagnostic potential of these modeling approaches, there has been little assessment of potential caveats and prerequisites associated with implementing predictive models of drug resistance in the clinical setting. Our results highlight significant biological and technical challenges facing the application of machine learning-based prediction of antibiotic resistance as a diagnostic tool. By outlining specific factors affecting model performance, our findings provide a framework for future work on modeling drug resistance and underscore the necessity of continued comprehensive sampling and reporting of treatment outcome data for building reliable and sustainable diagnostics.

microbiology↗

bioRxiv2019

Outpatient antibiotic stewardship interventions: geographic scale and associations between antibiotic use and resistance

Antibiotic use is a key driver of antibiotic resistance. Understanding the quantitative association between antibiotic use and resulting resistance is important for predicting future rates of antibiotic resistance and for designing antibiotic stewardship policy. However, the use-resistance association is complicated by "spillover", in which one populations level of antibiotic use affects another populations level of resistance via the transmission of bacteria between those populations. Spillover is known to have effects at the level of families and hospitals, but it is unclear if spillover is relevant at larger scales. We used mathematical modeling and analysis of observational data to address this question. First, we used dynamical models of antibiotic resistance to predict the effects of spillover. Whereas populations completely isolated from one another do not experience any spillover, we found that if even 1% of interactions are between populations, then spillover may have large consequences: the effect of a change in antibiotic use in one population on antibiotic resistance in that population could be reduced by as much as 50%. Then, we quantified spillover in observational antibiotic use and resistance data from US states and European countries for 3 pathogen-antibiotic combinations, finding that increased interactions between populations were associated with smaller differences in antibiotic resistance between those populations. Thus, spillover may have an important impact at the level of states and countries, which has ramifications for predicting the future of antibiotic resistance, designing antibiotic resistance stewardship policy, and interpreting stewardship interventions.

epidemiology↗

bioRxiv2019

Impact of population structure in the design of RNA-based diagnostics for antibiotic resistance in Neisseria gonorrhoeae

Quantitative assessment of antibiotic-responsive RNA transcripts holds promise for a rapid point of care (POC) diagnostic tool for antimicrobial susceptibility testing. These assays aim to distinguish susceptible and resistant isolates by transcriptional differences upon drug exposure. However, an often-overlooked dimension of designing these tests is that the genetic diversity within a species may yield differential transcriptional regulation independent of resistance phenotype. Here, we use a phylogenetically diverse panel of Neisseria gonorrhoeae and transcriptome profiling coupled with RT-qPCR to test this hypothesis, to identify azithromycin responsive transcripts and evaluate their potential diagnostic value, and to evaluate previously reported diagnostic markers for ciprofloxacin resistance (porB and rpmB). Transcriptome profiling confirmed evidence of population structure in transcriptional response to azithromycin. Taking this population structure into account, we found azithromycin-responsive transcripts overrepresented in susceptible strains compared to resistant strains, and selected four candidate diagnostic transcripts (rpsO, rplN, omp3, and NGO1079) that were the most significantly differentially regulated between phenotypes across drug exposure. RNA signatures for these markers categorically predicted resistance in 19/20 cases, with the one incorrect categorical assignment for an isolate at the threshold of reduced susceptibility. Finally, we found that porB and rpmB expression were not diagnostic of ciprofloxacin resistance in a panel of isolates with unbiased phylogenetic sampling. Overall, our results suggest that RNA signatures as a diagnostic tool are promising for future POC diagnostics; however, development and testing should consider representative genetic diversity of the target pathogen.

microbiology↗

bioRxiv2018

The distribution of antibiotic use and its association with antibiotic resistance

Antibiotic use is a primary driver of antibiotic resistance. However, antibiotic use can be distributed in different ways in a population, and the association between the distribution of use and antibiotic resistance has not been explored. Here we tested the hypothesis that repeated use of antibiotics has a stronger association with population-wide antibiotic resistance than broadly- distributed, low-intensity use. First, we characterized the distribution of outpatient antibiotic use across US states, finding that antibiotic use is uneven and that repeated use of antibiotics makes up a minority of antibiotic use. Second, we compared antibiotic use with resistance for 72 pathogen-antibiotic combinations across states. Finally, having partitioned total use into extensive and intensive margins, we found that intense use had a weaker association with resistance than extensive use. If the use-resistance relationship is causal, these results suggest that reducing total use and selection intensity will require reducing broadly-distributed, low- intensity use.

epidemiology↗

bioRxiv2018

Photo-inactivation of Neisseria gonorrhoeae: A paradigm changing approach for combating antibiotic-resistant gonococcal infection

Neisseria gonorrhoeae is the causative pathogen of the sexually transmitted disease gonorrhea, a disease at risk of becoming untreatable due to increasing antibiotic resistance. There is a critical need for the development of new anti-gonococcal therapies. In this study, we investigated the effectiveness of antimicrobial blue light (aBL), an innovative non-antibiotic approach, for the inactivation of antibiotic-resistant N. gonorrhoeae. Our findings indicated that aBL at 405 nm preferentially inactivated antibiotic-resistant N. gonorrhoeae over the vaginal epithelial cells. Furthermore, no genotoxicity of aBL to the vaginal epithelial cells was observed at the exposure for inactivating N. gonorrhoeae. aBL also effectively inactivated N. gonorrhoeae that had invaded into the vaginal epithelial cells. No gonococcal resistance to aBL developed after 15 successive cycles of sub-therapeutic inactivation. Endogenous aBL-active photosensitizing chromophores (porphyrins and flavins) in N. gonorrhoeae were identified and quantified using ultra performance liquid chromatography, with coproporphyrin being the most abundant endogenous porphyrin species. Taken together, aBL at 405 nm represents a potent potential treatment for gonococcal infections.\n\nOne Sentence SummaryaBL selectively inactivated antibiotic-resistant Neisseria gonorrhoeaen over normal vaginal epithelial cells.

microbiology↗

bioRxiv2018

Co-circulating mumps lineages at multiple geographic scales

Despite widespread vaccination, eleven thousand mumps cases were reported in the United States (US) in 2016-17, including hundreds in Massachusetts, primarily in college settings. We generated 203 whole genome mumps virus (MuV) sequences from Massachusetts and 15 other states to understand the dynamics of mumps spread locally and nationally, as well as to search for variants potentially related to vaccination. We observed multiple MuV lineages circulating within Massachusetts during 2016-17, evidence for multiple introductions of the virus to the state, and extensive geographic movement of MuV within the US on short time scales. We found no evidence that variants arising during this outbreak contributed to vaccine escape. Combining epidemiological and genomic data, we observed multiple co-circulating clades within individual universities as well as spillover into the local community. Detailed data from one well-sampled university allowed us to estimate an effective reproductive number within that university significantly greater than one. We also used publicly available small hydrophobic (SH) gene sequences to estimate migration between world regions and to place this outbreak in a global context, but demonstrate that these short sequences, historically used for MuV genotyping, are inadequate for tracing detailed transmission. Our findings suggest continuous, often undetected, circulation of mumps both locally and nationally, and highlight the value of combining genomic and epidemiological data to track viral disease transmission at high resolution.

genomics↗

bioRxiv2018

Antimicrobial exposure in sexual networks drives divergent evolution in modern gonococci

The sexually transmitted pathogen Neisseria gonorrhoeae is regarded as being on the way to becoming an untreatable superbug. Despite its clinical importance, little is known about its emergence and evolution, and how this corresponds with the introduction of antimicrobials. We present a genome-based phylogeographic analysis of 419 gonococcal isolates from across the globe. Results indicate that modern gonococci originated in Europe or Africa as late as the 16thcentury and subsequently disseminated globally. We provide evidence that the modern gonococcal population has been shaped by antimicrobial treatment of sexually transmitted and other infections, leading to the emergence of two major lineages with different evolutionary strategies. The well-described multi-resistant lineage is associated with high rates of homologous recombination and infection in high-risk sexual networks where antimicrobial treatment is frequent. A second, multi-susceptible lineage associated with heterosexual networks, where asymptomatic infection is more common, was also identified, with potential implications for infection control.

genomics↗

bioRxiv2018

Azithromycin resistance through interspecific acquisition of an epistasis dependent efflux pump component and transcriptional regulator in Neisseria gonorrhoeae

Mosaic interspecifically acquired alleles of the multiple transferable resistance (mtr) efflux pump operon correlate with reduced susceptibility to azithromycin in Neisseria gonorrhoeae in epidemiological studies. However, whether and how these alleles cause resistance is unclear. Here, we use population genomics, transformations, and transcriptional analyses to dissect the relationship between variant mtr alleles and azithromycin resistance. We find that the locus encompassing the mtrR transcriptional repressor and the mtrCDE pump is a hotspot of interspecific recombination introducing alleles from N. meningitidis and N. lactamica into N. gonorrhoeae, with multiple rare haplotypes in linkage disequilibrium at mtrD and the mtr promoter region. Transformations demonstrated that resistance is mediated through epistasis between these two loci and that the full length of the mosaic mtrD allele is required. Gene expression profiling revealed the mechanism of resistance in mosaics couples the novel mtrDalleles with promoter mutations enhancing expression of the pump. Overall, our results demonstrate that epistatic interactions at mtr gained from multiple Neisseria has contributed to azithromycin resistance in the gonococcal population.\n\nAUTHOR SUMMARYNeisseria gonorrhoeae is the sexually transmitted bacterial pathogen responsible for over 100 million cases of gonorrhea worldwide each year. The incidence of reduced susceptibility to the macrolide class antibiotic azithromycin has increased in the past decade; however, a large proportion of the genetic basis of resistance to this drug remains unexplained. Recently, resistance has been shown to be highly associated with mosaic alleles of the multiple transferable resistance (mtr) efflux pump, which have been gained via horizontal gene exchange with other Neisseria. However, if and how these alleles caused resistance was unknown. Here, we demonstrate that resistance has been gained through epistasis between mtrD and the mtr promoter region using evidence from both population genomics and experimental genetic manipulation. Epistasis also acts within the mtrD locus alone, requiring the full length of the gene for phenotypic resistance. Transcriptomic profiling indicates that the mechanism of resistance in mosaics is likely derived from both structural changes to mtrD, coupled with promoter mutations that result in regulatory changes to mtrCDE.

microbiology↗

bioRxiv2018

Trends in outpatient antibiotic prescribing practice among US older adults, 2011-2015: an observational study

Structured abstractO_ST_ABSObjectiveC_ST_ABSTo identify temporal trends in outpatient antibiotic use and antibiotic prescribing practice among older adults.\n\nDesignObservational study using United States Medicare administrative claims during 2011-2015. Trends in antibiotic use were estimated using multivariable regression adjusting for beneficiaries demographic and clinical covariates.\n\nSettingMedicare.\n\nParticipants4.6 million Medicare beneficiaries from a nationwide, 20% sample of fee-forservice Medicare beneficiaries [≥]65 years old.\n\nMain outcome measurementsOverall rates of antibiotic prescription claims, rates of appropriate and inappropriate prescribing, rates for each of the most frequently prescribed antibiotics, and rates of antibiotic claims associated with specific diagnoses.\n\nResultsAntibiotic claims fell from 1362.2 to 1361.6 claims per 1,000 beneficiaries per year during 2011-2015, an overall 0.2% decrease (95% CI 0.07-0.32). Inappropriate antibiotic claims fell from 552 to 533 claims per 1,000 beneficiaries, a 4.1% decrease (CI 3.9-4.3). Individual antibiotics had heterogeneous changes in use. For example, azithromycin claims per beneficiary decreased by 18.4% (CI 18.2-18.7) while levofloxacin claims increased by 28.1% (CI 27.5-28.6). Azithromycin use associated with each of the potentially appropriate and inappropriate respiratory diagnoses we considered decreased, while levofloxacin use associated with each of those diagnoses increased.\n\nConclusionAmong US Medicare beneficiaries, overall antibiotic use and inappropriate use declined modestly, but individual drugs experienced divergent changes in use. Trends in drug use across indications were stronger than trends in use for individual indications, suggesting that guidelines and concerns about antibiotic resistance were not major drivers of change in antibiotic use.

epidemiology↗

bioRxiv2017

Vaccine waning and mumps re-emergence in the United States

Following decades of declining mumps incidence amid widespread vaccination, the United States and other high-income countries have experienced a resurgence in mumps cases over the last decade. Outbreaks affecting vaccinated individuals--and communities with high vaccine coverage--have prompted concerns about the effectiveness of the live attenuated vaccine currently in use: it is unclear if immune protection wanes, or if the vaccine protects inadequately against mumps virus lineages currently circulating. Synthesizing data from epidemiological studies, we estimate that vaccine-derived protection wanes at a timescale of 27 (95%CI: 16 to 51) years. After accounting for this waning, we identify no evidence of changes in vaccine effectiveness over time associated with the emergence of heterologous virus genotypes. Moreover, a mathematical model of mumps transmission validates our findings about the central role of vaccine waning in the re-emergence of cases: outbreaks from 2006 to the present among young adults, and outbreaks occurring in the late 1980s and early 1990s among adolescents, align with peaks in the susceptibility of these age groups attributable to loss of vaccine-derived protection. In contrast, evolution of mumps virus strains escaping pressure would be expected to cause a higher proportion of cases among children. Routine use of a third dose at age 18y, or booster dosing throughout adulthood, may enable mumps elimination and should be assessed in clinical trials.\n\nOne Sentence SummaryThe estimated waning rate of vaccine-conferred immunity against mumps predicts observed changes in the age distribution of mumps cases in the United States since 1967.

epidemiology↗

bioRxiv2017

Despite egg-adaptive mutations, the 2012-13 H3N2 influenza vaccine induced comparable antibody titers to the intended strain

BackgroundInfluenza vaccination aims to prevent infection by influenza virus and reduce associated morbidity and mortality; however, vaccine effectiveness (VE) can be modest, especially for subtype A/H3N2. Failure to achieve consistently high VE has been attributed both to mismatches between the vaccine and circulating influenza strains and to the vaccine's elicitation of protective immunity in only a subset of the population. The low H3N2 VE in 2012-13 was attributed to egg-adaptive mutations that created antigenic mismatch between the intended (A/Victoria/361/2011) and actual vaccine strain (IVR-165).\n\nMethodsWe investigate the basis of the low VE in 2012-2013 by evaluating whether vaccinated and unvaccinated individuals were infected by different viral strains and assessing the serologic responses to A/Victoria/361/2011 and the IVR-165 vaccine strain in an adult cohort before and after vaccination.\n\nResultsWe found no significant genetic differences between the strains that infected vaccinated and unvaccinated individuals. Vaccination increased titers to A/Victoria/361/2011 as much as to IVR-165. These results are consistent with the hypothesis that vaccination served merely to boost preexisting cross-reactive immune responses, which provided limited protection against infection with the circulating influenza strains.\n\nConclusionsIn contrast to suggestive analyses based on ferret antisera, low H3N2 VE in 2012-13 does not appear to be due to the failure of the egg-adapted strain to induce a response to the intended vaccine strain. Instead, low VE might have been caused by the emergence of anti-genically novel influenza strains and low vaccine immunogenicity in a subset of the population.

epidemiology↗

bioRxiv2017

Impact of rapid susceptibility testing and antibiotic selection strategy on the emergence and spread of antibiotic resistance in gonorrhea

BackgroundIncreasing antibiotic resistance limits treatment options for gonorrhea. We examined the extent to which a hypothetical point-of-care (POC) test reporting antibiotic susceptibility profiles could slow the spread of resistance.\n\nMethodsWe developed a deterministic compartmental model describing gonorrhea transmission in a single-sex population with three antibiotics available to treat infections. Probabilities of resistance emergence on treatment and fitness costs associated with resistance were based on characteristics of ciprofloxacin, azithromycin, and ceftriaxone. We evaluated time to 1% and 5% prevalence of resistant strains among all isolates with: (1) empiric treatment (azithromycin plus ceftriaxone), and treatment guided by POC tests determining susceptibility to (2) ciprofloxacin only and (3) all three antibiotics.\n\nFindingsBased on current gonococcal susceptibility patterns in the United States, the model indicated that continued empiric dual antibiotic treatment without POC testing resulted in >5% of isolates being resistant to both azithromycin and ceftriaxone within 15 years. When either POC test was used in 10% of identified cases, this was delayed by 5 years. The three antibiotic POC test delayed the time to reach 1% prevalence of triply-resistant strains by 6 years, while the ciprofloxacin-only test resulted in no delay. Results were less sensitive to assumptions about fitness costs and test characteristics with increasing test uptake. The main limitation of this study is that we made simplifying assumptions to describe gonorrhea transmission and the emergence and spread of resistance in the population.\n\nConclusionsRapid diagnostics that report antibiotic susceptibility have the potential to extend the usefulness of existing antibiotics for treatment of gonorrhea. Monitoring resistance patterns will be critical with the introduction of such tests.

epidemiology↗