Biology subjects

Lipsitch, M.

Publications and source records attributed to Lipsitch, M..

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bioRxiv2018

Modeling Vaccine Trials in Epidemics with Mild and Asymptomatic Infection

Vaccine efficacy against susceptibility to infection (VES), regardless of symptoms, is an important endpoint of vaccine trials for pathogens with a high proportion of asymptomatic infection, as such infections may contribute to onward transmission and outcomes such as Congenital Zika Syndrome. However, estimating VES is resource-intensive. We aim to identify methods to accurately estimate VEs when limited information is available and resources are constrained. We model an individually randomized vaccine trial by generating a network of individuals and simulating an epidemic. The disease natural history follows a Susceptible, Exposed, Infectious and Symptomatic or Infectious and Asymptomatic, Recovered model. We then use seven approaches to estimate VES, and we also estimate vaccine efficacy against progression to symptoms (VEP). A corrected relative risk and an interval censored Cox model accurately estimate VES and only require serologic testing of participants once, while a Cox model using only symptomatic infections returns biased estimates. Only acquiring serological endpoints in a 10% sample and imputing the remaining infection statuses yields unbiased VES estimates across values of R0 and accurate estimates of VEP for higher values. Identifying resource-preserving methods for accurately estimating VES is important in designing trials for diseases with a high proportion of asymptomatic infection.

epidemiology↗

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↗

bioRxiv2018

Estimating the proportion of bystander selection for antibiotic resistance in the US

Bystander selection -- the selective pressures exerted by antibiotics on microbial flora that are not the target pathogen of treatment -- is critical to understanding the total impact of broad-spectrum antibiotic use; however, to our knowledge, this effect has never been quantified. Using the 2010-2011 National Ambulatory Medical Care Survey and National Hospital Ambulatory Medical Care Survey (NAMCS/NHAMCS), the Human Microbiome Project, and additional carriage and etiological data from existing literature, we estimate the magnitude of bystander selection for a range of clinically relevant antibiotic-species pairs as the proportion of all exposures of an antibiotic experienced by a species for conditions in which that species was not the causative pathogen (\"proportion of bystander exposures\"). For outpatient prescribing in the United States, we find that this proportion over all included antibiotics is over 80% for 8 out of 9 organisms of interest. Low proportions of bystander exposure are often associated with infrequent bacterial carriage or a high proportion of antibiotic prescribing focused on conditions caused by the species of interest. Using the proportion of bystander exposures, we roughly estimate that S. aureus and E. coli may benefit from 90.7% and 99.7%, respectively, of the estimated reduction in antibiotic use due to pneumococcal conjugate vaccination, despite not being the pathogen targeted by the vaccine. These results underscore the importance of considering antibiotic exposures to bystanders, in addition to the targeted pathogen, in measuring the impact of antibiotic resistance interventions.\n\nSignificance StatementThe forces that contribute to changing population prevalence of antibiotic resistance are not well understood. Bystander selection -- the inadvertent pressures imposed by antibiotics on the microbial flora other than the pathogen targeted by treatment -- is hypothesized to be a major factor in the propagation of antibiotic resistance, but its extent has not been characterized. We estimate the proportion of bystander exposures across a range of antibiotics and organisms and describe factors driving variability of these proportions. Impact estimates for antibiotic resistance interventions, including vaccination, are often limited to effects on a target pathogen. However, the reduction of antibiotic treatment for illnesses caused by the target pathogen may have the broader potential to decrease bystander selection pressures for resistance on many other organisms.

epidemiology↗

bioRxiv2018

Use of an individual-based model of pneumococcal carriage for planning a randomized trial of a vaccine

For encapsulated bacteria such as Streptococcus pneumoniae, asymptomatic carriage is more common and longer in duration than disease, and hence is often a more convenient endpoint for clinical trials of vaccines against these bacteria. However, using a carriage endpoint entails specific challenges. Carriage is almost always measured as prevalence, whereas the vaccine may act by reducing incidence or duration. Thus, to determine sample size requirements, its impact on prevalence must first be estimated. The relationship between incidence and prevalence (or duration and prevalence) is convex, saturating at 100% prevalence. For this reason, the proportional effect of a vaccine on prevalence is typically less than its proportional effect on incidence or duration. This relationship is further complicated in the presence of multiple pathogen strains. In addition, host immunity to carriage accumulates rapidly with frequent exposures in early years of life, creating potentially complex interactions with the vaccines effect. We conducted a simulation study to predict the impact of an inactivated whole cell pneumococcal vaccine--believed to reduce carriage duration--on carriage prevalence in different age groups and trial settings. We used an individual-based model of pneumococcal carriage that incorporates relevant immunological processes, both vaccine-induced and naturally acquired. Our simulations showed that for a wide range of vaccine efficacies, sampling time and age at vaccination are important determinants of sample size. There is a window of favorable sampling times during which the required sample size is relatively low, and this window is prolonged with a younger age at vaccination, and in a trial setting with lower transmission intensity. These results illustrate the ability of simulation studies to inform the planning of vaccine trials with carriage endpoints, and the methods we present here can be applied to trials evaluating other pneumococcal vaccine candidates or comparing alternative dosing schedules for the existing conjugate vaccines.\n\nAuthor SummaryStreptococcus pneumoniae, a bacterium carried in the nasopharynx of many healthy people, is also a leading cause of bacterial pneumonia, sepsis, and ear infections in children aged five years and younger. Vaccines targeting select strains of S. pneumoniae have been effective, and the development of new vaccines, particularly those that target all strains, can further lower disease burden. For clinical trials of these vaccines, the number of study participants needed depends on the expected effect of the vaccine on a conveniently measured outcome: asymptomatic carriage. The most economical way to test a vaccine for its effect on carriage is by measuring prevalence at a specific time, and comparing vaccinated to unvaccinated participants. The relationship between incidence (or duration) and prevalence is complex, and changes with time as children develop natural immunity. We explored this relationship using a mathematical model. Given a vaccine efficacy, our computer simulations predict that fewer study participants are needed if they are vaccinated at a younger age, taken from a population with intermediate levels of transmission, and sampled for carriage at a certain time window: 9 to 18 months after vaccination. Our study illustrates how simulation studies can help plan more efficient vaccine trials.

epidemiology↗

bioRxiv2018

Choices in Vaccine Trial Design for Epidemics of Emerging Infections

The 2014-2016 Ebola epidemic highlighted the lack of consensus on the design of trials for investigational vaccine products in an emergency setting. With the advent of the ring vaccination strategy, it also underscored that the range of design options is evolving according to scientific need and creativity. Ideally, principles and protocols will be drawn up in advance, facilitating expediency and trust, for rapid deployment early in an epidemic. Here, we attempt a summary of the scientific, ethical and feasibility considerations relevant to different trial designs. We focus on four elements of design choices which, in our view, are most fundamental to designing an experimental vaccine trial and for which the most distinctive issues arise in the setting of an emerging infectious disease for which no proven vaccines exist: 1) randomization unit, 2) trial population, 3) comparator intervention and 4) trial implementation. Likewise, we focus on three of several ethical considerations in clinical research, namely the trials social and scientific value, its risk-benefit profile and its participant selection. A catalogue of possible designs to guide trial design choices is offered, along with a systematic evaluation of the benefits and drawbacks of each in given contexts.

epidemiology↗

bioRxiv2017

Effect of antimicrobial treatment for acute otitis media on carriage of Streptococcus pneumoniae with reduced susceptibility to penicillin in a randomized, double-blind, placebo-controlled trial

BackgroundConcerns that antimicrobial treatment may foster selection and transmission of resistant bacterial lineages have led to conflicting guidelines for clinical management of common non-severe infections. However, the impact of antimicrobial treatment on colonization dynamics is poorly understood. We used data from a previously-conducted trial of amoxicillin-clavulanate therapy for acute otitis media (AOM) to understand how antimicrobial treatment impacts the acquisition and clearance of Streptococcus pneumoniae lineages with varying susceptibility to penicillin.\n\nMethods and findingsWe measured impacts of antimicrobial treatment on nasopharyngeal carriage of penicillin-susceptible S. pneumoniae (PSSP) and penicillin-non-susceptible S. pneumoniae (PNSP) lineages at end-of-treatment and 15d, 30d, and 60d after treatment in a previously-conducted randomized, double-blind, placebo-controlled trial. Analyses were not specified in the original protocol. Among children 6-35 months of age with stringently-defined AOM, 162 were assigned amoxicillin-clavulanate, and 160 were assigned placebo. Children who did not show clinical improvement received open-label antimicrobial rescue treatment with amoxicillin-clavulanate irrespective of the randomized treatment assignment, to which both patients and physicians were blinded. The intention-to-treat populations of the intervention and placebo arms thus received care resembling immediate antimicrobial therapy and watchful waiting, respectively. Immediate amoxicillin-clavulanate reduced PSSP carriage prevalence by 88% (95%CI: 76-96%) at end-of-treatment and by 27% (-3-49%) after 60d, but did not measurably alter PNSP carriage prevalence throughout follow-up. By end-of-treatment, 7% of children who carried PSSP at enrollment remained colonized in the amoxicillin-clavulanate arm, compared to 61% of PSSP carriers who received placebo; differences in carriage prevalence persisted at least 60d after treatment among children who carried PSSP at enrollment. Among children not carrying pneumococci at enrollment, amoxicillin-clavulanate reduced PSSP acquisition by >80% over 15d. Among children who carried PNSP at enrollment, no differences in carriage prevalence of S. pneumoniae, PSSP, or PNSP were detected at follow-up visits.\n\nConclusionsIn a setting with low PNSP prevalence, antimicrobial therapy for AOM conferred a selective impact on colonizing S. pneumoniae by accelerating clearance, and delaying acquisition, of penicillin-susceptible lineages. Absolute risk of carrying PNSP was unaffected by treatment (ClinicalTrials.gov: NCT00299455; Funding: NIH/NIGMS).

epidemiology↗

bioRxiv2017

Quantifying biases in test-negative studies of vaccine effectiveness

Test-negative designs have become commonplace in assessments of seasonal influenza vaccine effectiveness. Vaccine effectiveness is measured from the exposure odds ratio (OR) of vaccination among individuals seeking treatment for acute respiratory illness and receiving a laboratory test for influenza infection. This approach is widely believed to correct for differential healthcare-seeking behavior among vaccinated and unvaccinated persons. However, the relation of the measured OR to true vaccine effectiveness is poorly understood. We derive the OR under circumstances of real-world test-negative studies. The OR recovers the true vaccine direct effect when two conditions are met: (1) that individuals vaccination decisions are uncorrelated with exposure or susceptibility to infection, and (2) that vaccination confers \"all-or-nothing\" protection (whereby certain individuals have no protection while others are perfectly protected). Biased effect size estimates arise if either condition is unmet. Such bias may suggest misleading associations of the OR with time since vaccination or the force of infection of influenza. The test-negative design may also fail to correct for differential healthcare-seeking behavior among vaccinated and unvaccinated persons without stringent criteria for enrollment and testing. Our findings demonstrate a need to reassess how data from test-negative studies are interpreted for policy decisions conventionally based on causal inferences.

epidemiology↗

bioRxiv2017

Population genomics of pneumococcal carriage in Massachusetts children following PCV-13 introduction

BackgroundThe 13-valent pneumococcal conjugate vaccine (PCV-13) was introduced in the United States in 2010. Using a large pediatric carriage sample collected from shortly after the introduction of PCV-7 to several years after the introduction of PCV-13, we investigate alterations in the composition of the pneumococcal population following the introduction of PCV-13, evaluating the extent to which the post-vaccination non-vaccine type (NVT) population mirrors that from prior to vaccine introduction and the effect of PCV-13 on vaccine type lineages.\n\nMethods and FindingsDraft genome assemblies from 736 newly sequenced and 616 previously published pneumococcal carriages isolates from children in Massachusetts between 2001 and 2014 were analyzed. Isolates were classified into one of 22 sequence clusters (SCs) on the basis of their core genome sequence. We calculated the SC diversity for each sampling period as the probability that any two randomly drawn isolates from that period belong to different SCs. The sampling period immediately after the introduction of PCV-13 (2011) was found to have higher diversity than preceding (2007) or subsequent (2014) sampling periods (Simpsons D 2007: 0.915 95% CI [0.901, 0.929]; 2011: 0.935 [0.927, 0.942]; 2014: 0.912 [0.901, 0.923]). Amongst NVT isolates, we found the distribution of SCs in 2011 to be significantly different from that in 2007 or 2014 (Fishers Exact Test p=0.018, 0.0078), but did not find a difference comparing 2007 to 2014 (Fishers Exact Test p=0.24), indicating greater similarity between samples separated by a longer time period than between samples from closer time periods. We also found changes in the accessory gene content of the NVT population between 2007 and 2011 to have been reduced by 2014. Amongst the new serotypes targeted by PCV-13, four were present in our sample. The proportion of our sample composed of PCV-13-only vaccine serotypes 19A, 6C, and 7F decreased between 2007 and 2014, but no such reduction was seen for serotype 3. We did, however, observe differences in the genetic composition of the pre- and post-PCV-13 serotype 3 population. Our isolates were collected during discrete sampling periods from a small geographic area, which may limit the generalizability our findings.\n\nConclusionPneumococcal diversity increased immediately following the introduction of PCV-13, but subsequently returned to pre-vaccination levels. This is reflected in the distribution of NVT lineages, and, to a lesser extent, their accessory gene frequencies. As such, there may be a period during which the population is particularly disrupted by vaccination before returning to a more stable distribution. The persistence and shifting genetic composition of serotype 3 is a concern and warrants further investigation.

evolutionary biology↗

bioRxiv2017

Mechanisms that maintain coexistence of antibiotic sensitivity and resistance also promote high frequencies of multidrug resistance

Resistance against different antibiotics appears on the same bacterial strains more often than expected by chance, leading to high frequencies of multidrug resistance. There are multiple explanations for this observation, but these tend to be specific to subsets of antibiotics and/or bacterial species, whereas the trend is pervasive. Here, we consider the question in terms of strain ecology: explaining why resistance to different antibiotics is often seen on the same strain requires an understanding of the competition between strains with different resistance profiles. This work builds on models originally proposed to explain another aspect of strain competition: the stable coexistence of antibiotic sensitivity and resistance observed in a number of bacterial species. We first demonstrate a partial structural similarity in these models of coexistence. We then generalise this unified underlying model to multidrug resistance and show that models with this structure predict high levels of association between resistance to different drugs and high multidrug resistance frequencies. We test predictions from this model in six bacterial datasets and find them to be qualitatively consistent with observed trends. The higher than expected frequencies of multidrug resistance are often interpreted as evidence that these strains are out-competing strains with lower resistance multiplicity. Our work provides an alternative explanation that is compatible with long-term stability in resistance frequencies.\n\nAuthor summaryAntibiotic resistance is a serious public health concern, yet the ecology and evolution of drug resistance are not fully understood. This impacts our ability to design effective interventions to combat resistance. From a public health point of view, multidrug resistance is particularly problematic because resistance to different antibiotics is often seen on the same bacterial strains, which leads to high frequencies of multidrug resistance and limits treatment options. This work seeks to explain this trend in terms of strain ecology and the competition between strains with different resistance profiles. Building on recent work exploring why resistant bacteria are not out-competing sensitive bacteria, we show that models originally proposed to explain this observation also predict high multidrug resistance frequencies. These models are therefore a unifying explanation for two pervasive trends in resistance dynamics. In terms of public health, the implication of our results is that new resistances are likeliest to be found on already multidrug resistant strains and that changing patterns of prescription may not be enough to combat multidrug resistance.

evolutionary biology↗

bioRxiv2017

Simulations for Designing and Interpreting Intervention Trials in Infectious Diseases

Here we urge the adoption of a new paradigm for the design and interpretation of intervention trials in infectious diseases, particularly in emerging infectious disease, that more accurately reflects the dynamics of the transmission process. Interventions in infectious diseases can have indirect effects on those not receiving the intervention as well as direct effects on those receiving the intervention. Combinations of interventions can have complex interactions at the population level. These often cannot be adequately addressed with standard study designs and analytic methods. Simulations can help to accurately represent transmission dynamics in an increasingly complex world which is critical for proper trial design and interpretation. Some ethical aspects of a trial can also be quantified using simulations. After a trial has been conducted, simulations can be used to explore possible explanations for the observed effects. A great deal is to be gained through a multidisciplinary approach that builds collaborations among experts in infectious disease dynamics, epidemiology, statistical science, economics, simulation methods and the conduct of clinical trials.

epidemiology↗

bioRxiv2017

Competing effects of indirect protection and clustering on the power of cluster-randomized controlled vaccine trials

Power considerations for trials evaluating vaccines against infectious diseases are complicated by indirect protective effects of vaccination. While cluster-randomized trials (cRCTs) are less statistically efficient than individually randomized trials (iRCT), a cRCTs ability to measure direct and indirect vaccine effects may mitigate the loss of efficiency due to clustering. Within cRCTs, the number and size of clusters affects three determinants of power: the effect size being measured, disease incidence, and intra-cluster correlation. We simulate trials conducted in a collection of small communities to assess how indirect protection and clustering affect the power of cRCTs and iRCTs during an emerging epidemic. Across diverse parameters, we find that within the same trial population, cRCTs are never more powerful than iRCTs, although the difference can be small. We also identify two effects that attenuate the loss of cRCT power traditionally associated with increased cluster size. First, if enrollment of fewer, larger clusters is performed to achieve higher vaccine coverage within vaccinated communities, this increases the effect to be measured and, consequently, power. Second, the greater rate of imported transmission in larger communities may increase the attack rate and similarly mitigate loss of power relative to a trial in many, smaller communities.

epidemiology↗

bioRxiv2017

On the relative role of different age groups during epidemics associated with the respiratory syncytial virus

BackgroundWhile RSV circulation results in high burden of hospitalization, particularly among infants, young children and the elderly, little is known about the role of different age groups in propagating annual RSV epidemics in the community.\n\nMethodsDuring a communicable disease outbreak, some subpopulations may play a disproportionate role during the outbreak's ascent due to increased susceptibility and/or contact rates. Such subpopulations can be identified by considering the proportion that cases in a subpopulation represent among all cases in the population occurring before (Bp) and after the epidemic peak (Ap) to calculate the subpopulation's relative risk, RR=Bp/Ap. We estimated RR for several age groups using data on RSV hospitalizations in the US between 2001-2012 from the Healthcare Cost and Utilization Project (HCUP).\n\nResultsChildren aged 3-4y and 5-6y each had the highest RR estimate for 5/11 seasons in the data, with RSV hospitalization rates in infants being generally higher during seasons when children aged 5-6y had the highest RR estimates. Children aged 2y had the highest RR estimate during one season. RR estimates in infants and individuals aged 11y and older were mostly lower than in children aged 1-10y.\n\nConclusionsThe RR estimates suggest that preschool and young school-age children have the leading relative roles during RSV epidemics. We hope that those results will aid in the design of RSV vaccination policies.

epidemiology↗

bioRxiv2017

Host population structure and treatment frequency maintain balancing selection on drug resistance

It is a truism that antimicrobial drugs select for resistance, but explaining pathogen- and population-specific variation in patterns of resistance remains an open problem. Like other common commensals, Streptococcus pneumoniae has demonstrated persistent coexistence of drug-sensitive and drug-resistant strains. Theoretically, this outcome is unlikely. We modeled the dynamics of competing strains of S. pneumoniae to investigate the impact of transmission dynamics and treatment-induced selective pressures on the probability of stable coexistence. We find that the outcome of competition is extremely sensitive to structure in the host population, although coexistence can arise from age-assortative transmission models with age-varying rates of antibiotic use. Moreover, we find that the selective pressure from antibiotics arises not so much from the rate of antibiotic use per se but from the frequency of treatment: frequent antibiotic therapy disproportionately impacts the fitness of sensitive strains. This same phenomenon explains why serotypes with longer durations of carriage tend to be more resistant. These dynamics may apply to other potentially pathogenic, microbial commensals and highlight how population structure, which is often omitted from models, can have a large impact.

evolutionary biology↗

bioRxiv2017

Weak epistasis may drive adaptation in recombining bacteria

The impact of epistasis on the evolution of multilocus traits depends on recombination. Population genetic theory has been largely developed for eukaryotes, many of which recombine so frequently that epistasis between polymorphisms has not been considered to play a large role in adaptation and has been compared to the fleeting influence of non-heritable effects. Many bacteria also recombine, some to the degree that their populations are described as panmictic or freely recombining. However, whether this recombination is sufficient to limit the ability of selection to act on epistatic contributions to fitness is unknown. We create a sensitive method to quantify homologous recombination in five bacterial pathogens and use these parameter estimates in a multilocus model of bacterial evolution with additive and epistatic effects. We find that even for highly recombining species (e.g. Streptococcus pneumoniae or Helicobacter pylori), selection may act on the cumulative effects of weak (as well as strong) interactions between distant mutations since homologous recombination typically transfers only short segments. Furthermore, whether selection acts more efficiently on physically proximal loci depends on the average recombination tract length. Epistasis may thus play an important role in the adaptive evolution of bacteria and, unlike in eukaryotes, does not need to be strong, involve near loci, or require specific metapopulation dynamics.

evolutionary biology↗

bioRxiv2017

Exploring The Role Of Competition Induced By Non-Vaccine Serotypes For Herd Protection

The competitive pressure from non-vaccine serotypes may have helped pneumococcal conjugate vaccines (PCVs) to limit vaccine serotype (VT) prevalence. We aim to investigate if, consequently, the indirect protection of higher valency vaccines could fall short of the profound effects of current formulations.\n\nWe compare three previously described pneumococcal models harmonized to simulate 20 serotypes with a combined pre-vaccination prevalence in <5y old children of 40%. We simulate vaccines of increasing valency by adding serotypes in order of their competitiveness and explore their ability to reduce VT carriage by 95% within 10 years after introduction.\n\nAll models predict that additional valency will reduce indirect vaccine effects and hence the overall vaccine impact on carriage both in children and adults. Consequently, the minimal effective coverage (efficacy against carriage * vaccine coverage) needed to eliminate vaccine type carriage increases with increasing valency. One model predicts this effect to be modest while the other two predict that high-valency vaccines may struggle to eliminate VT pneumococci unless vaccine efficacy against carriage can be substantially improved. Similar results were obtained when settings of higher transmission intensity and different PCV formulations were explored.\n\nFailure to eliminate carriage as a result of increased valency could lead to overall decreased impact of vaccination if the disease burden caused by the added serotypes is low. Hence a comparison of vaccine formulations of varying valency, and pan-valent formulations in particular, should consider the invasiveness of targeted serotypes, as well as efficacy against carriage.

ecology↗