Within-host bayesian joint modeling of longitudinal and time-to-event data of Leishmania infection.

The host immune system plays a significant role in managing and clearing pathogen material during an infection, but this complex process presents numerous challenges from a modeling perspective. There are many mathematical and statistical models for these kinds of processes that take into account a wide range of events that happen within the host. In this work, we present a Bayesian joint model of longitudinal and time-to-event data of Leishmania infection that considers the interplay between key drivers of the disease process: pathogen load, antibody level, and disease. The longitudinal model also considers approximate inflammatory and regulatory immune factors. In addition to measuring antibody levels produced by the immune system, we adapt data from CD4+ and CD8+ T cell proliferation, and expression of interleukin 10, interferon-gamma, and programmed cell death 1 as inflammatory or regulatory factors mediating the disease process. The model is developed using data collected from a cohort of dogs naturally exposed to Leishmania infantum. The cohort was chosen to start with healthy infected animals, and this is the majority of the data. The model also characterizes the relationship features of the longitudinal outcomes and time-to-death due to progressive Leishmania infection. In addition to describing the mechanisms causing disease progression and impacting the risk of death, we also present the model's ability to predict individual trajectories of Canine Leishmaniosis (CanL) progression. The within-host model structure we present here provides a way forward to address vital research questions regarding the understanding of the progression of complex chronic diseases such as Visceral Leishmaniasis, a parasitic disease causing significant morbidity worldwide.

Comparison of virus aerosol concentrations across a face shield worn on a healthcare personnel during a simulated patient cough.

BACKGROUND: Patients diagnosed with coronavirus disease 2019 (COVID-19) aerosolize severe acute respiratory coronavirus virus 2 (SARS-CoV-2) via respiratory efforts, expose, and possibly infect healthcare personnel (HCP). To prevent transmission of SARS-CoV-2 HCP have been required to wear personal protective equipment (PPE) during patient care. Early in the COVID-19 pandemic, face shields were used as an approach to control HCP exposure to SARS-CoV-2, including eye protection. METHODS: An MS2 bacteriophage was used as a surrogate for SARS-CoV-2 and was aerosolized using a coughing machine. A simulated HCP wearing a disposable plastic face shield was placed 0.41 m (16 inches) away from the coughing machine. The aerosolized virus was sampled using SKC biosamplers on the inside (near the mouth of the simulated HCP) and the outside of the face shield. The aerosolized virus collected by the SKC Biosampler was analyzed using a viability assay. Optical particle counters (OPCs) were placed next to the biosamplers to measure the particle concentration. RESULTS: There was a statistically significant reduction (P < .0006) in viable virus concentration on the inside of the face shield compared to the outside of the face shield. The particle concentration was significantly lower on the inside of the face shield compared to the outside of the face shield for 12 of the 16 particle sizes measured (P < .05). CONCLUSIONS: Reductions in virus and particle concentrations were observed on the inside of the face shield; however, viable virus was measured on the inside of the face shield, in the breathing zone of the HCP. Therefore, other exposure control methods need to be used to prevent transmission from virus aerosol.

Within-Host Bayesian Joint Modeling of Longitudinal and Time-to-Event Data of Leishmania Infection.

The host immune system plays a significant role in managing and clearing pathogen material during an infection, but this complex process presents numerous challenges from a modeling perspective. There are many mathematical and statistical models for these kinds of processes that take into account a wide range of events that happen within the host. In this work, we present a Bayesian joint model of longitudinal and time-to-event data of Leishmania infection that considers the interplay between key drivers of the disease process: pathogen load, antibody level, and disease. The longitudinal model also considers approximate inflammatory and regulatory immune factors. In addition to measuring antibody levels produced by the immune system, we adapt data from CD4+ and CD8+ T cell proliferation, and expression of interleukin 10, interferon-gamma, and programmed cell death 1 as inflammatory or regulatory factors mediating the disease process. The model is developed using data collected from a cohort of dogs naturally exposed to Leishmania infantum. The cohort was chosen to start with healthy infected animals, and this is the majority of the data. The model also characterizes the relationship features of the longitudinal outcomes and time of death due to progressive Leishmania infection. In addition to describing the mechanisms causing disease progression and impacting the risk of death, we also present the model's ability to predict individual trajectories of Canine Leishmaniosis (CanL) progression. The within-host model structure we present here provides a way forward to address vital research questions regarding the understanding progression of complex chronic diseases such as Visceral Leishmaniasis, a parasitic disease causing significant morbidity worldwide.

Evaluation of face shields used during aerosol generating procedures.

Transnasal flexible laryngoscopy is considered an aerosol generating procedure. A negative pressure face shield (NPFS) was developed to control aerosol from the patient during laryngoscopy. The purpose of this study was to determine the effectiveness of the NPFS at controlling virus aerosol compared to a standard disposable plastic face shield. The face shields were placed on a simulated patient coughing machine. MS2 bacteriophage was used as a surrogate for SARS-CoV-2 and was aerosolized using the coughing machine. The aerosolized virus was sampled on the inside and outside of the face shields. The virus aerosol concentration was not significantly different between the inside and outside of the traditional plastic face shield (p = 0.12). However, the particle concentrations across all particle sizes measured were significantly decreased outside the face shield. The virus and particle concentrations were significantly decreased (p < 0.01) outside the NPFS operating at a flow rate of 38.6 L per minute (LPM). When the NPFS was operated at 10 LPM, virus concentrations were not significantly different (p = 0.09) across the face shield. However, the number particle concentrations across all particle sizes measured were significantly different (p < 0.05).

Bayesian multivariate longitudinal model for immune responses to Leishmania: A tick-borne co-infection study.

While many Bayesian state-space models for infectious disease processes focus on population infection dynamics (eg, compartmental models), in this work we examine the evolution of infection processes and the complexities of the immune responses within the host using these techniques. We present a joint Bayesian state-space model to better understand how the immune system contributes to the control of Leishmania infantum infections over the disease course. We use longitudinal molecular diagnostic and clinical data of a cohort of dogs to describe population progression rates and present evidence for important drivers of clinical disease. Among these results, we find evidence for the importance of co-infection in disease progression. We also show that as dogs progress through the infection, parasite load is influenced by their age, ectoparasiticide treatment status, and serology. Furthermore, we present evidence that pathogen load information from an earlier point in time influences its future value and that the size of this effect varies depending on the clinical stage of the dog. In addition to characterizing the processes driving disease progression, we predict individual and aggregate patterns of Canine Leishmaniasis progression. Both our findings and the application to individual-level predictions are of direct clinical relevance, presenting possible opportunities for application in veterinary practice and motivating lines of additional investigation to better understand and predict disease progression. Finally, as an important zoonotic human pathogen, these results may support future efforts to prevent and treat human Leishmaniosis.

Hierarchical spatiotemporal modeling of human visceral leishmaniasis in Rio Grande do Norte, Brazil.

Visceral leishmaniasis (VL) is a neglected tropical disease that is globally distributed and has the potential to cause very serious illness. Prior literature highlights the emergence and spread of VL is influenced by multiple factors, such as socioeconomic status, sanitation levels or animal and human reservoirs. The study aimed to retrospectively investigate the presence and infectiousness of VL in Rio Grande do Norte (RN), Brazil between 2007 and 2020. We applied a hierarchical Bayesian approach to estimate municipality-specific relative risk of VL across space and time. The results show evidence that lower socioeconomic status is connected to higher municipality-specific VL risk. Overall, estimates reveal spatially heterogeneous VL risks in RN, with a high probability that VL risk for municipalities within the West Potiguar mesoregion are more than double the expected VL risk. Additionally, given the data available, results indicate there is a high probability of increasing VL risk in the municipalities of Natal, Patu and Pau dos Ferros. These findings demonstrate opportunities for municipality-specific public health policy interventions and warrant future research on identifying epidemiological drivers in at-risk regions.

Incorporating infectious duration-dependent transmission into Bayesian epidemic models.

Compartmental models are commonly used to describe the spread of infectious diseases by estimating the probabilities of transitions between important disease states. A significant challenge in fitting Bayesian compartmental models lies in the need to estimate the duration of the infectious period, based on limited data providing only symptom onset date or another proxy for the start of infectiousness. Commonly, the exponential distribution is used to describe the infectious duration, an overly simplistic approach, which is not biologically plausible. More flexible distributions can be used, but parameter identifiability and computational cost can worsen for moderately sized or large epidemics. In this article, we present a novel approach, which considers a curve of transmissibility over a fixed infectious duration. The incorporation of infectious duration-dependent (IDD) transmissibility, which decays to zero during the infectious period, is biologically reasonable for many viral infections and fixing the length of the infectious period eases computational complexity in model fitting. Through simulation, we evaluate different functional forms of IDD transmissibility curves and show that the proposed approach offers improved estimation of the time-varying reproductive number. We illustrate the benefit of our approach through a new analysis of the 1995 outbreak of Ebola Virus Disease in the Democratic Republic of the Congo.

An individual level infectious disease model in the presence of uncertainty from multiple, imperfect diagnostic tests.

Bayesian compartmental infectious disease models yield important inference on disease transmission by appropriately accounting for the dynamics and uncertainty of infection processes. In addition to estimating transition probabilities and reproductive numbers, these statistical models allow researchers to assess the probability of disease risk and quantify the effectiveness of interventions. These infectious disease models rely on data collected from all individuals classified as positive based on various diagnostic tests. In infectious disease testing, however, such procedures produce both false-positives and false-negatives at varying rates depending on the sensitivity and specificity of the diagnostic tests being used. We propose a novel Bayesian spatio-temporal infectious disease modeling framework that accounts for the additional uncertainty in the diagnostic testing and classification process that provides estimates of the important transmission dynamics of interest to researchers. The method is applied to data on the 2006 mumps epidemic in Iowa, in which over 6,000 suspected mumps cases were tested using a buccal or oral swab specimen, a urine specimen, and/or a blood specimen. Although all procedures are believed to have high specificities, the sensitivities can be low and vary depending on the timing of the test as well as the vaccination status of the individual being tested.

Bayesian latent class models for identifying canine visceral leishmaniosis using diagnostic tests in the absence of a gold standard.

BACKGROUND: Like many infectious diseases, there is no practical gold standard for diagnosing clinical visceral leishmaniasis (VL). Latent class modeling has been proposed to estimate a latent gold standard for identifying disease. These proposed models for VL have leveraged information from diagnostic tests with dichotomous serological and PCR assays, but have not employed continuous diagnostic test information. METHODS/PRINCIPAL FINDINGS: In this paper, we employ Bayesian latent class models to improve the identification of canine visceral leishmaniasis using the dichotomous PCR assay and the Dual Path Platform (DPP) serology test. The DPP test has historically been used as a dichotomous assay, but can also yield numerical information via the DPP reader. Using data collected from a cohort of hunting dogs across the United States, which were identified as having either negative or symptomatic disease, we evaluate the impact of including numerical DPP reader information as a proxy for immune response. We find that inclusion of DPP reader information allows us to illustrate changes in immune response as a function of age. CONCLUSIONS/SIGNIFICANCE: Utilization of continuous DPP reader information can improve the correct discrimination between individuals that are negative for disease and those with clinical VL. These models provide a promising avenue for diagnostic testing in contexts with multiple, imperfect diagnostic tests. Specifically, they can easily be applied to human visceral leishmaniasis when diagnostic test results are available. Also, appropriate diagnosis of canine visceral leishmaniasis has important consequences for curtailing spread of disease to humans.

Mutability Patterns Across the Spike Glycoprotein Reveal the Diverging and Lineage-specific Evolutionary Space of SARS-CoV-2.

Mutations in the spike glycoprotein of SARS-CoV-2 allow the virus to probe the sequence space in search of higher-fitness states. New sublineages of SARS-CoV-2 variants-of-concern (VOCs) continuously emerge with such mutations. Interestingly, the sites of mutation in these sublineages vary between the VOCs. Whether such differences reflect the random nature of mutation appearance or distinct evolutionary spaces of spike in the VOCs is unclear. Here we show that each position of spike has a lineage-specific likelihood for mutations to appear and dominate descendent sublineages. This likelihood can be accurately estimated from the lineage-specific mutational profile of spike at a protein-wide level. The mutability environment of each position, including adjacent sites on the protein structure and neighboring sites on the network of comutability, accurately forecast changes in descendent sublineages. Mapping of imminent changes within the VOCs can contribute to the design of immunogens and therapeutics that address future forms of SARS-CoV-2.

Limited Variation between SARS-CoV-2-Infected Individuals in Domain Specificity and Relative Potency of the Antibody Response against the Spike Glycoprotein.

The spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is arranged as a trimer on the virus surface, composed of three S1 and three S2 subunits. Infected and vaccinated individuals generate antibodies against spike, which can neutralize the virus. Most antibodies target the receptor-binding domain (RBD) and N-terminal domain (NTD) of S1; however, antibodies against other regions of spike have also been isolated. The interhost variability in domain specificity and relative neutralization efficacy of the antibodies is still poorly characterized. To this end, we tested serum and plasma samples collected from 85 coronavirus disease 2019 (COVID-19) convalescent subjects. Samples were analyzed using seven immunoassays that employ different domains, subunits, and oligomeric forms of spike to capture the antibodies. Samples were also tested for their neutralization of pseudovirus containing SARS-CoV-2 spike and of replication-competent SARS-CoV-2. While the total amount of anti-spike antibodies produced varied among convalescent subjects, we observed an unexpectedly fixed ratio of RBD- to NTD-targeting antibodies. The relative potency of the response (defined as the measured neutralization efficacy relative to the total level of spike-targeting antibodies) also exhibited limited variation between subjects and was not associated with the overall amount of antispike antibodies produced. These studies suggest that host-to-host variation in the polyclonal response elicited against SARS-CoV-2 spike in early pandemic subjects is primarily limited to the quantity of antibodies generated rather than their domain specificity or relative neutralization potency. IMPORTANCE Infection by SARS-CoV-2 elicits antibodies against various domains of the spike protein, including the RBD and NTD of subunit S1 and against subunit S2. The antibody responses of different infected individuals exhibit different efficacies to inactivate (neutralize) the virus. Here, we show that the observed variation in the neutralizing activity of the antibody responses in COVID-19 convalescent subjects is caused by differences in the amounts of antibodies rather than their recognition properties or the potency of their antiviral activity. These findings suggest that COVID-19 vaccine strategies that focus on enhancing the overall level of the antibodies will likely elicit a more uniformly efficacious protective response.

Mask Effectiveness for Preventing Secondary Cases of COVID-19, Johnson County, Iowa, USA.

In September of 2020, the Iowa Department of Public Health released guidance stating that persons exposed to someone with coronavirus disease (COVID-19) need not quarantine if the case-patient and the contact wore face masks at the time of exposure. This guidance differed from that issued by the Centers for Disease Control and Prevention. To determine the best action, we matched exposure information from COVID-19 case investigations with reported test results and calculated the secondary attack rates (SARs) after masked and unmasked exposures. Mask use by both parties reduced the SAR by half, from 25.6% to 12.5%. Longer exposure duration significantly increased SARs. Masks significantly reduced virus transmission when worn by both the case-patient and the contact, but SARs for each group were higher than anticipated. This finding suggests that quarantine after COVID-19 exposure is beneficial even if parties wore masks.

Maternal transfer of neutralizing antibodies to B. burgdorferi OspA after oral vaccination of the rodent reservoir.

Lyme Disease presents unique challenges for public health. Transfer of protective antibodies between mothers and offspring should occur after vaccination of mice. We present new evidence for maternal transfer of oral vaccine induced neutralizing anti-OspA IgG antibodies to mouse pups mainly through ingestion of colostrum. We found a strong statistical correlation of antibody transfer between mothers that produced the most robust IgG response to OspA and their respective pups. OspA-specific antibody was detected as early as 24 h after birth and protective levels of antibodies lasted until ~5 weeks of age in the majority of pups but persisted in some mice until 9 weeks. This was further supported by detection of neutralizing antibodies in serum of all pups at 2-3 weeks after birth and in some offspring adult mice at 9 weeks of age. A clear association was found between robust antibody responses in mothers and the length of time antibody persisted in the respective pups using a novel longitudinal Bayesian model. These factors are likely to impact the enzootic cycle of B. burgdorferi if reservoir targeted OspA-based vaccination interventions are implemented.

Key Positions of HIV-1 Env and Signatures of Vaccine Efficacy Show Gradual Reduction of Population Founder Effects at the Clade and Regional Levels.

HIV-1 group M was transmitted to humans nearly one century ago. The virus has since evolved to form distinct clades, which spread to different regions of the world. The envelope glycoproteins (Envs) of HIV-1 have rapidly diversified in all infected populations. We examined whether key antigenic sites of Env and signatures of vaccine efficacy are evolving toward similar or distinct structural forms in different populations worldwide. Patterns of amino acid variants that emerged at each position of Env were compared between diverse HIV-1 clades and isolates from different geographic regions. Interestingly, at each Env position, the amino acid in the clade ancestral or regional-founder virus was replaced by a unique frequency distribution (FD) of amino acids. FDs are highly conserved in populations from different regions worldwide and in paraphyletic and monophyletic subclade groups. Remarkably, founder effects of Env mutations at the clade and regional levels have gradually decreased during the pandemic by evolution of each site toward the unique combination of variants. Therefore, HIV-1 Env is evolving at a population level toward well-defined "target" states; these states are not specific amino acids but rather specific distributions of amino acid frequencies. Our findings reveal the powerful nature of the forces that guide evolution of Env and their conservation across different populations. Such forces have caused a gradual decrease in the interpopulation diversity of Env despite an increasing intrapopulation diversity.IMPORTANCE The Env protein of HIV-1 is the primary target in AIDS vaccine design. Frequent mutations in the virus increase the number of Env forms in each population, limiting the efficacy of AIDS vaccines. Comparison of newly emerging forms in different populations showed that each position of Env is evolving toward a specific combination of amino acids. Similar changes are occurring in different HIV-1 subtypes and geographic regions toward the same position-specific combinations of amino acids, often from distinct ancestral sequences. The predictable nature of HIV-1 Env evolution, as shown here, provides a new framework for designing vaccines that are tailored to the unique combination of variants expected to emerge in each virus subtype and geographic region.

Bayesian compartmental models and associated reproductive numbers for an infection with multiple transmission modes.

Zoonotic visceral leishmaniasis (ZVL) is a serious neglected tropical disease that is endemic in 98 countries. ZVL is primarily transmitted via a sand fly vector. In the United States, it is enzootic in some canine populations; it is transmitted from infectious mother to pup transplacentally, and vector-borne transmission is absent. This absence affords a unique opportunity to study (1) vertical transmission dynamics in dogs and (2) the importance of vertical transmission in maintaining an infectious reservoir in the presence of a vector. In this paper, we present Bayesian compartmental models and reproductive number formulations to examine (1) and (2), providing a mechanism to plan and evaluate interventions in regions where both transmission modes are present. First, we propose an individual-level susceptible, infectious, removed (SIR) model to study the effect of maternal infection status during pregnancy on pup infection progression. We provide evidence that pups born to diagnostically positive mothers during pregnancy are more likely to become diagnostically positive both earlier in life, and at some point during their lifetime, than those born to diagnostically negative mothers. Second, we propose a population-level SIR model to study the impact of a vertically maintained reservoir on propagating infection in a naive canine population through emergent vector transmission using simulation studies. We also present reproductive numbers to quantify contributions of vertically infected and vector-infected dogs to maintaining infection in the population. We show that a vertically maintained canine reservoir can propagate infection in a theoretical naive population in the presence of a vector.

Bayesian compartmental model for an infectious disease with dynamic states of infection.

Population-level proportions of individuals that fall at different points in the spectrum [of disease severity], from asymptomatic infection to severe disease, are often difficult to observe, but estimating these quantities can provide information about the nature and severity of the disease in a particular population. Logistic and multinomial regression techniques are often applied to infectious disease modeling of large populations and are suited to identifying variables associated with a particular disease or disease state. However, they are less appropriate for estimating infection state prevalence over time because they do not naturally accommodate known disease dynamics like duration of time an individual is infectious, heterogeneity in the risk of acquiring infection, and patterns of seasonality. We propose a Bayesian compartmental model to estimate latent infection state prevalence over time that easily incorporates known disease dynamics. We demonstrate how and why a stochastic compartmental model is a better approach for determining infection state proportions than multinomial regression is by using a novel method for estimating Bayes factors for models with high-dimensional parameter spaces. We provide an example using visceral leishmaniasis in Brazil and present an empirically-adjusted reproductive number for the infection.

The Evolution of Statistical Methods in Speech, Language, and Hearing Sciences.

Purpose Scientists in the speech, language, and hearing sciences rely on statistical analyses to help reveal complex relationships and patterns in the data collected from their research studies. However, data from studies in the fields of communication sciences and disorders rarely conform to the underlying assumptions of many traditional statistical methods. Fortunately, the field of statistics provides many mature statistical techniques that can be used to meet today's challenges involving complex studies of behavioral data from humans. In this review article, we highlight several techniques and general approaches with promising application to analyses in the speech and hearing sciences. Method The goal of this review article is to provide an overview of potentially underutilized statistical methods with promising application in the speech, language, and hearing sciences. Results We offer suggestions to identify when alternative statistical approaches might be advantageous when analyzing proportion data and repeated measures data. We also introduce the Bayesian paradigm and statistical learning and offer suggestions for when a scientist might consider those methods. Conclusion Modern statistical techniques provide more flexibility and enable scientists to ask more direct and informative research questions.

Essential Statistical Concepts for Research in Speech, Language, and Hearing Sciences.

Purpose Clinicians depend on the accuracy of research in the speech, language, and hearing sciences to improve assessment and treatment of patients with communication disorders. Although this work has contributed to great advances in clinical care, common statistical misconceptions remain, which deserve closer inspection in the field. Challenges in applying and interpreting traditional statistical methods with behavioral data from humans have led to difficulties with replication and reproducibility in other allied scientific fields, including psychology and medicine. The importance of research in our fields of study for advancing science and clinical care for our patients means that the choices of statistical methods can have far-reaching, real-world implications. Method The goal of this article is to provide an overview of fundamental statistical concepts and methods that are used in the speech, language, and hearing sciences. Results We reintroduce basic statistical terms such as the p value and effect size, as well as recommended procedures for model selection and multiple comparisons. Conclusions Research in the speech, language, and hearing sciences can have a profound positive impact on the lives of individuals with communication disorders, but the validity of scientific findings in our fields is enhanced when data are analyzed using sound statistical methods. Misunderstanding or misinterpretation of basic statistical principles may erode public trust in research findings. Recommendations for practices that can help minimize the likelihood of errors in statistical inference are provided. Supplemental Material https://doi.org/10.23641/asha.7849223.

Comorbid infections induce progression of visceral leishmaniasis.

BACKGROUND: Visceral leishmaniasis (VL) is a vector borne zoonotic disease endemic in humans and dogs in Brazil. Due to the increased risk of human infection secondary to the presence of infected dogs, public health measures in Brazil mandate testing and culling of infected dogs. Despite this important relationship between human and canine infection, little is known about what makes the dog reservoir progress to clinical illness, significantly tied to infectiousness to sand flies. Dogs in endemic areas of Brazil are exposed to many tick-borne pathogens, which are likely to alter the immune environment and thus control of L. infantum. RESULTS: A cross-sectional study of 223 dogs from an area of Natal, in the Rio Grande do Norte, Brazil, were studied to determine the association between comorbid tick-borne disease and Leishmania infection in this endemic area. The risk of Leishmania seropositivity was 1.68× greater in dogs with tick-borne disease seropositivity compared to those without (Adjusted RR: 1.68, 95% CI: 1.09-2.61, P = 0.019). A longitudinal study of 214 hunting dogs in the USA was conducted to determine the causal relationship between infection with tick-borne diseases and progression of VL. Hunting dogs were evaluated three times across a full tick season to detect incident infection with tick-borne diseases. A logistic regression model with generalized estimating equations to estimate the parameters was used to determine how exposure to tick-borne disease altered VL progression over these three time points when controlling for other variables. Dogs infected with three or more tick-borne diseases were 11× more likely to be associated with progression to clinical VL than dogs with no tick-borne disease (Adjusted RR: 11.64, 95% CI: 1.22-110.99, P = 0.03). Dogs with exposure to both Leishmania spp. and tick-borne diseases were five times more likely to die during the study period (RR: 4.85, 95% CI: 1.65-14.24, P = 0.0051). CONCLUSIONS: Comorbid tick-borne diseases dramatically increased the likelihood that a dog had clinical L. infantum infection, making them more likely to transmit infection to sand flies and people. As an important consequence, reduction of tick-borne disease exposure through topical or oral insecticides may be an important way to reduce progression and transmissibility of Leishmania infection from the canine reservoir to people.

CFTR Heterozygotes Are at Increased Risk of Respiratory Infections: A Population-Based Study.

BACKGROUND: Patients heterozygous for mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene may be more susceptible to respiratory infections than the general population. METHODS: We conducted a retrospective case-control study using health insurance claims. We identified patients as either highly likely to be CFTR heterozygotes (CF carriers diagnosed during genetic counseling, parents of children with a diagnosis of CF, and children of mothers diagnosed with CF) or likely CFTR heterozygotes (children of CF carriers diagnosed during genetic counseling and parents of CF carriers diagnosed during genetic counseling). Next, we examined the rates of respiratory infections and antimicrobial prescriptions between both groups of CFTR patients and only the highly likely subcohort, compared with age/sex-matched controls. We examined the presence of any claim using McNemar's test and the number of claims using the sign test. RESULTS: CFTR heterozygotes (the pooled highly likely and likely heterozygotes) were more prone to have at least 1 claim for a respiratory infection (odds ratio [OR], 1.28; P = .020) and to have a greater number of claims for respiratory infections (53.5%; P = .043) than controls. Patients in the highly likely cohort were also more prone to have at least 1 claim for a respiratory infection (OR, 1.30; P = .028) and more claims (54.3%; P = .039) than controls. In addition, the highly likely CFTR heterozygotes were more prone to be prescribed an antibiotic used to treat respiratory infections (OR, 1.34; P = .018) and to have more of these prescriptions (54.3%; P = .035) than controls. CONCLUSIONS: Patients heterozygous for CFTR mutations are at higher risk for respiratory infections. Future work to describe clinical outcomes for CFTR heterozygotes is needed.