Prolonged silent carriage, genomic virulence potential and transmission between staff and patients characterize a neonatal intensive care unit (NICU) outbreak of methicillin-resistant Staphylococcus aureus (MRSA).

BACKGROUND: Methicillin-resistant Staphylococcus aureus (MRSA) is an important pathogen in neonatal intensive care units (NICU) that confers significant morbidity and mortality. OBJECTIVE: Improving our understanding of MRSA transmission dynamics, especially among high-risk patients, is an infection prevention priority. METHODS: We investigated a cluster of clinical MRSA cases in the NICU using a combination of epidemiologic review and whole-genome sequencing (WGS) of isolates from clinical and surveillance cultures obtained from patients and healthcare personnel (HCP). RESULTS: Phylogenetic analysis identified 2 genetically distinct phylogenetic clades and revealed multiple silent-transmission events between HCP and infants. The predominant outbreak strain harbored multiple virulence factors. Epidemiologic investigation and genomic analysis identified a HCP colonized with the dominant MRSA outbreak strain who cared for most NICU patients who were infected or colonized with the same strain, including 1 NICU patient with severe infection 7 months before the described outbreak. These results guided implementation of infection prevention interventions that prevented further transmission events. CONCLUSIONS: Silent transmission of MRSA between HCP and NICU patients likely contributed to a NICU outbreak involving a virulent MRSA strain. WGS enabled data-driven decision making to inform implementation of infection control policies that mitigated the outbreak. Prospective WGS coupled with epidemiologic analysis can be used to detect transmission events and prompt early implementation of control strategies.

Upper airway gene expression shows a more robust adaptive immune response to SARS-CoV-2 in children.

Unlike other respiratory viruses, SARS-CoV-2 disproportionately causes severe disease in older adults whereas disease burden in children is lower. To investigate whether differences in the upper airway immune response may contribute to this disparity, we compare nasopharyngeal gene expression in 83 children (<19-years-old; 38 with SARS-CoV-2, 11 with other respiratory viruses, 34 with no virus) and 154 older adults (>40-years-old; 45 with SARS-CoV-2, 28 with other respiratory viruses, 81 with no virus). Expression of interferon-stimulated genes is robustly activated in both children and adults with SARS-CoV-2 infection compared to the respective non-viral groups, with only subtle distinctions. Children, however, demonstrate markedly greater upregulation of pathways related to B cell and T cell activation and proinflammatory cytokine signaling, including response to TNF and production of IFNγ, IL-2 and IL-4. Cell type deconvolution confirms greater recruitment of B cells, and to a lesser degree macrophages, to the upper airway of children. Only children exhibit a decrease in proportions of ciliated cells, among the primary targets of SARS-CoV-2, upon infection. These findings demonstrate that children elicit a more robust innate and especially adaptive immune response to SARS-CoV-2 in the upper airway that likely contributes to their protection from severe disease in the lower airway.

Workshop-based learning and networking: a scalable model for research capacity strengthening in low- and middle-income countries.

Science education and research have the potential to drive profound change in low- and middle-income countries (LMICs) through encouraging innovation, attracting industry, and creating job opportunities. However, in LMICs, research capacity is often limited, and acquisition of funding and access to state-of-the-art technologies is challenging. The Alliance for Global Health and Science (the Alliance) was founded as a partnership between the University of California, Berkeley (USA) and Makerere University (Uganda), with the goal of strengthening Makerere University's capacity for bioscience research. The flagship program of the Alliance partnership is the MU/UCB Biosciences Training Program, an in-country, hands-on workshop model that trains a large number of students from Makerere University in infectious disease and molecular biology research. This approach nucleates training of larger and more diverse groups of students, development of mentoring and bi-directional research partnerships, and support of the local economy. Here, we describe the project, its conception, implementation, challenges, and outcomes of bioscience research workshops. We aim to provide a blueprint for workshop implementation, and create a valuable resource for bioscience research capacity strengthening in LMICs.

Estimation of Secondary Household Attack Rates for Emergent Spike L452R Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Variants Detected by Genomic Surveillance at a Community-Based Testing Site in San Francisco.

BACKGROUND: Sequencing of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral genome from patient samples is an important epidemiological tool for monitoring and responding to the pandemic, including the emergence of new mutations in specific communities. METHODS: SARS-CoV-2 genomic sequences were generated from positive samples collected, along with epidemiological metadata, at a walk-up, rapid testing site in the Mission District of San Francisco, California during 22 November to 1 December, 2020, and 10-29 January 2021. Secondary household attack rates and mean sample viral load were estimated and compared across observed variants. RESULTS: A total of 12 124 tests were performed yielding 1099 positives. From these, 928 high-quality genomes were generated. Certain viral lineages bearing spike mutations, defined in part by L452R, S13I, and W152C, comprised 54.4% of the total sequences from January, compared to 15.7% in November. Household contacts exposed to the "California" or "West Coast" variants (B.1.427 and B.1.429) were at higher risk of infection compared to household contacts exposed to lineages lacking these variants (0.36 vs 0.29, risk ratio [RR] = 1.28; 95% confidence interval [CI]: 1.00-1.64). The reproductive number was estimated to be modestly higher than other lineages spreading in California during the second half of 2020. Viral loads were similar among persons infected with West Coast versus non-West Coast strains, as was the proportion of individuals with symptoms (60.9% vs 64.3%). CONCLUSIONS: The increase in prevalence, relative household attack rates, and reproductive number are consistent with a modest transmissibility increase of the West Coast variants. Summary: We observed a growing prevalence and modestly elevated attack rate for "West Coast" severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants in a community testing setting in San Francisco during January 2021, suggesting its modestly higher transmissibility.

The impact of the COVID-19 preventive measures on influenza transmission: molecular and epidemiological evidence.

OBJECTIVE: We quantify the impact of COVID-19-related control measures on the spread of human influenza virus H1N1 and H3N2. METHODS: We analyzed case numbers to estimate the end of the 2019-2020 influenza season and compared it with the median of the previous 9 seasons. In addition, we used influenza molecular data to compare within-region and between-region genetic diversity and effective population size from 2019 to 2020. Finally, we analyzed personal behavior and policy stringency data for each region. RESULTS: The 2019-2020 influenza season ended earlier than the median of the previous 9 seasons in all regions. For H1N1 and H3N2, there was an increase in between-region genetic diversity in most pairs of regions between 2019 and 2020. There was a decrease in within-region genetic diversity for 12 of 14 regions for H1N1 and 9 of 12 regions for H3N2. There was a decrease in effective population size for 10 of 13 regions for H1N1 and 3 of 7 regions for H3N2. CONCLUSIONS: We found consistent evidence of a decrease in influenza incidence after the introduction of preventive measures due to COVID-19 emergence.

Upper airway gene expression reveals a more robust innate and adaptive immune response to SARS-CoV-2 in children compared with older adults.

Unlike other respiratory viruses, SARS-CoV-2 disproportionately causes severe disease in older adults and only rarely in children. To investigate whether differences in the upper airway immune response could contribute to this disparity, we compared nasopharyngeal gene expression in 83 children (<19-years-old; 38 with SARS-CoV-2, 11 with other respiratory viruses, 34 with no virus) and 154 adults (>40-years-old; 45 with SARS-CoV-2, 28 with other respiratory viruses, 81 with no virus). Expression of interferon-stimulated genes (ISGs) was robustly activated in both children and adults with SARS-CoV-2 compared to the respective non-viral groups, with only relatively subtle distinctions. Children, however, demonstrated markedly greater upregulation of pathways related to B cell and T cell activation and proinflammatory cytokine signaling, including TNF, IFNγ, IL-2 and IL-4 production. Cell type deconvolution confirmed greater recruitment of B cells, and to a lesser degree macrophages, to the upper airway of children. Only children exhibited a decrease in proportions of ciliated cells, the primary target of SARS-CoV-2, upon infection with the virus. These findings demonstrate that children elicit a more robust innate and adaptive immune response to SARS-CoV-2 infection in the upper airway that likely contributes to their protection from severe disease in the lower airway.

Single mosquito metatranscriptomics identifies vectors, emerging pathogens and reservoirs in one assay.

Mosquitoes are major infectious disease-carrying vectors. Assessment of current and future risks associated with the mosquito population requires knowledge of the full repertoire of pathogens they carry, including novel viruses, as well as their blood meal sources. Unbiased metatranscriptomic sequencing of individual mosquitoes offers a straightforward, rapid, and quantitative means to acquire this information. Here, we profile 148 diverse wild-caught mosquitoes collected in California and detect sequences from eukaryotes, prokaryotes, 24 known and 46 novel viral species. Importantly, sequencing individuals greatly enhanced the value of the biological information obtained. It allowed us to (a) speciate host mosquito, (b) compute the prevalence of each microbe and recognize a high frequency of viral co-infections, (c) associate animal pathogens with specific blood meal sources, and (d) apply simple co-occurrence methods to recover previously undetected components of highly prevalent segmented viruses. In the context of emerging diseases, where knowledge about vectors, pathogens, and reservoirs is lacking, the approaches described here can provide actionable information for public health surveillance and intervention decisions.

Estimation of secondary household attack rates for emergent SARS-CoV-2 variants detected by genomic surveillance at a community-based testing site in San Francisco.

BACKGROUND: Sequencing of the SARS-CoV-2 viral genome from patient samples is an important epidemiological tool for monitoring and responding to the pandemic, including the emergence of new mutations in specific communities. METHODS: SARS-CoV-2 genomic sequences were generated from positive samples collected, along with epidemiological metadata, at a walk-up, rapid testing site in the Mission District of San Francisco, California during November 22-December 2, 2020 and January 10-29, 2021. Secondary household attack rates and mean sample viral load were estimated and compared across observed variants. RESULTS: A total of 12,124 tests were performed yielding 1,099 positives. From these, 811 high quality genomes were generated. Certain viral lineages bearing spike mutations, defined in part by L452R, S13I, and W152C, comprised 54.9% of the total sequences from January, compared to 15.7% in November. Household contacts exposed to "West Coast" variants were at higher risk of infection compared to household contacts exposed to lineages lacking these variants (0.357 vs 0.294, RR=1.29; 95% CI:1.01-1.64). The reproductive number was estimated to be modestly higher than other lineages spreading in California during the second half of 2020. Viral loads were similar among persons infected with West Coast versus non-West Coast strains, as was the proportion of individuals with symptoms (60.9% vs 64.1%). CONCLUSIONS: The increase in prevalence, relative household attack rates, and reproductive number are consistent with a modest transmissibility increase of the West Coast variants; however, additional laboratory and epidemiological studies are required to better understand differences between these variants. SUMMARY: We observed a growing prevalence and elevated attack rate for "West Coast" SARS-CoV-2 variants in a community testing setting in San Francisco during January 2021, suggesting its modestly higher transmissibility.

A minimal model for household-based testing and tracing in epidemics.

In a previous work (Huberet al.2020Phys. Biol.17065010), we discussed virus transmission dynamics modified by a uniform clustering of contacts in the population: close contacts within households and more distant contacts between households. In this paper, we discuss testing and tracing in such a stratified population. We propose a minimal tracing strategy consisting of random testing of the entire population plus full testing of the households of those persons found positive. We provide estimates of testing frequency for this strategy to work.

Upper airway gene expression reveals suppressed immune responses to SARS-CoV-2 compared with other respiratory viruses.

SARS-CoV-2 infection is characterized by peak viral load in the upper airway prior to or at the time of symptom onset, an unusual feature that has enabled widespread transmission of the virus and precipitated a global pandemic. How SARS-CoV-2 is able to achieve high titer in the absence of symptoms remains unclear. Here, we examine the upper airway host transcriptional response in patients with COVID-19 (n = 93), other viral (n = 41) or non-viral (n = 100) acute respiratory illnesses (ARIs). Compared with other viral ARIs, COVID-19 is characterized by a pronounced interferon response but attenuated activation of other innate immune pathways, including toll-like receptor, interleukin and chemokine signaling. The IL-1 and NLRP3 inflammasome pathways are markedly less responsive to SARS-CoV-2, commensurate with a signature of diminished neutrophil and macrophage recruitment. This pattern resembles previously described distinctions between symptomatic and asymptomatic viral infections and may partly explain the propensity for pre-symptomatic transmission in COVID-19. We further use machine learning to build 27-, 10- and 3-gene classifiers that differentiate COVID-19 from other ARIs with AUROCs of 0.981, 0.954 and 0.885, respectively. Classifier performance is stable across a wide range of viral load, suggesting utility in mitigating false positive or false negative results of direct SARS-CoV-2 tests.

A minimal model for household effects in epidemics.

Shelter-in-place and other confinement strategies implemented in the current COVID-19 pandemic have created stratified patterns of contacts between people: close contacts within households and more distant contacts between the households. The epidemic transmission dynamics is significantly modified as a consequence. We introduce a minimal model that incorporates these household effects in the framework of mean-field theory and numerical simulations. We show that the reproduction number R 0 depends on the household size in a surprising way: linearly for relatively small households, and as a square root of size for larger households. We discuss the implications of the findings for the lockdown, test, tracing, and isolation policies.

Clinical features, diagnostics, and outcomes of patients presenting with acute respiratory illness: A retrospective cohort study of patients with and without COVID-19.

BACKGROUND: Most data on the clinical presentation, diagnostics, and outcomes of patients with COVID-19 have been presented as case series without comparison to patients with other acute respiratory illnesses. METHODS: We examined emergency department patients between February 3 and March 31, 2020 with an acute respiratory illness who were tested for SARS-CoV-2. We determined COVID-19 status by PCR and metagenomic next generation sequencing (mNGS). We compared clinical presentation, diagnostics, treatment, and outcomes. FINDINGS: Among 316 patients, 33 tested positive for SARS-CoV-2; 31 without COVID-19 tested positive for another respiratory virus. Among patients with additional viral testing (27/33), no SARS-CoV-2 co-infections were identified. Compared to those who tested negative, patients with COVID-19 reported longer symptoms duration (median 7d vs. 3d, p < 0.001). Patients with COVID-19 were more often hospitalized (79% vs. 56%, p = 0.014). When hospitalized, patients with COVID-19 had longer hospitalizations (median 10.7d vs. 4.7d, p < 0.001) and more often developed ARDS (23% vs. 3%, p < 0.001). Most comorbidities, medications, symptoms, vital signs, laboratories, treatments, and outcomes did not differ by COVID-19 status. INTERPRETATION: While we found differences in clinical features of COVID-19 compared to other acute respiratory illnesses, there was significant overlap in presentation and comorbidities. Patients with COVID-19 were more likely to be admitted to the hospital, have longer hospitalizations and develop ARDS, and were unlikely to have co-existent viral infections. FUNDING: National Center for Advancing Translational Sciences, National Heart Lung Blood Institute, National Institute of Allergy and Infectious Diseases, Chan Zuckerberg Biohub, Chan Zuckerberg Initiative.

Upper airway gene expression differentiates COVID-19 from other acute respiratory illnesses and reveals suppression of innate immune responses by SARS-CoV-2.

We studied the host transcriptional response to SARS-CoV-2 by performing metagenomic sequencing of upper airway samples in 238 patients with COVID-19, other viral or non-viral acute respiratory illnesses (ARIs). Compared to other viral ARIs, COVID-19 was characterized by a diminished innate immune response, with reduced expression of genes involved in toll-like receptor and interleukin signaling, chemokine binding, neutrophil degranulation and interactions with lymphoid cells. Patients with COVID-19 also exhibited significantly reduced proportions of neutrophils and macrophages, and increased proportions of goblet, dendritic and B-cells, compared to other viral ARIs. Using machine learning, we built 26-, 10- and 3-gene classifiers that differentiated COVID-19 from other acute respiratory illnesses with AUCs of 0.980, 0.950 and 0.871, respectively. Classifier performance was stable at low viral loads, suggesting utility in settings where direct detection of viral nucleic acid may be unsuccessful. Taken together, our results illuminate unique aspects of the host transcriptional response to SARS-CoV-2 in comparison to other respiratory viruses and demonstrate the feasibility of COVID-19 diagnostics based on patient gene expression.

Clinical features, diagnostics, and outcomes of patients presenting with acute respiratory illness: a comparison of patients with and without COVID-19.

BACKGROUND: Emerging data on the clinical presentation, diagnostics, and outcomes of patients with COVID-19 have largely been presented as case series. Few studies have compared these clinical features and outcomes of COVID-19 to other acute respiratory illnesses. METHODS: We examined all patients presenting to an emergency department in San Francisco, California between February 3 and March 31, 2020 with an acute respiratory illness who were tested for SARS-CoV-2. We determined COVID-19 status by PCR and metagenomic next generation sequencing (mNGS). We compared demographics, comorbidities, symptoms, vital signs, and laboratory results including viral diagnostics using PCR and mNGS. Among those hospitalized, we determined differences in treatment (antibiotics, antivirals, respiratory support) and outcomes (ICU admission, ICU interventions, acute respiratory distress syndrome, cardiac injury). FINDINGS: In a cohort of 316 patients, 33 (10%) tested positive for SARS-CoV-2; 31 patients, all without COVID-19, tested positive for another respiratory virus (16%). Among patients with additional viral testing, no co-infections with SARS-CoV-2 were identified by PCR or mNGS. Patients with COVID-19 reported longer symptoms duration (median 7 vs. 3 days), and were more likely to report fever (82% vs. 44%), fatigue (85% vs. 50%), and myalgias (61% vs 27%); p<0.001 for all comparisons. Lymphopenia (55% vs 34%, p=0.018) and bilateral opacities on initial chest radiograph (55% vs. 24%, p=0.001) were more common in patients with COVID-19. Patients with COVID-19 were more often hospitalized (79% vs. 56%, p=0.014). Of 186 hospitalized patients, patients with COVID-19 had longer hospitalizations (median 10.7d vs. 4.7d, p<0.001) and were more likely to develop ARDS (23% vs. 3%, p<0.001). Most comorbidities, home medications, signs and symptoms, vital signs, laboratory results, treatment, and outcomes did not differ by COVID-19 status. INTERPRETATION: While we found differences in clinical features of COVID-19 compared to other acute respiratory illnesses, there was significant overlap in presentation and comorbidities. Patients with COVID-19 were more likely to be admitted to the hospital, have longer hospitalizations and develop ARDS, and were unlikely to have co-existent viral infections. These findings enhance understanding of the clinical characteristics of COVID-19 in comparison to other acute respiratory illnesses. .

Investigating Transfusion-related Sepsis Using Culture-Independent Metagenomic Sequencing.

BACKGROUND: Transfusion-related sepsis remains an important hospital infection control challenge. Investigation of septic transfusion events is often restricted by the limitations of bacterial culture in terms of time requirements and low yield in the setting of prior antibiotic administration. METHODS: In 3 gram-negative septic transfusion cases, we performed metagenomic next-generation sequencing (mNGS) of direct clinical blood specimens in addition to standard culture-based approaches utilized for infection control investigations. Pathogen detection leveraged IDSeq, a new open-access microbial bioinformatics portal. Phylogenetic analysis was performed to assess microbial genetic relatedness and understand transmission events. RESULTS: mNGS of direct clinical blood specimens afforded precision detection of pathogens responsible for each case of transfusion-related sepsis and enabled discovery of a novel Acinetobacter species in a platelet product that had become contaminated despite photochemical pathogen reduction. In each case, longitudinal assessment of pathogen burden elucidated the temporal sequence of events associated with each transfusion-transmitted infection. We found that informative data could be obtained from culture-independent mNGS of residual platelet products and leftover blood specimens that were either unsuitable or unavailable for culture or that failed to grow due to prior antibiotic administration. We additionally developed methods to enhance accuracy for detecting transfusion-associated pathogens that share taxonomic similarity to contaminants commonly found in mNGS library preparations. CONCLUSIONS: Culture-independent mNGS of blood products afforded rapid and precise assessment of pathogen identity, abundance, and genetic relatedness. Together, these challenging cases demonstrated the potential for metagenomics to advance existing methods for investigating transfusion-transmitted infections.

Unbiased Metagenomic Sequencing for Pediatric Meningitis in Bangladesh Reveals Neuroinvasive Chikungunya Virus Outbreak and Other Unrealized Pathogens.

The burden of meningitis in low-and-middle-income countries remains significant, but the infectious causes remain largely unknown, impeding institution of evidence-based treatment and prevention decisions. We conducted a validation and application study of unbiased metagenomic next-generation sequencing (mNGS) to elucidate etiologies of meningitis in Bangladesh. This RNA mNGS study was performed on cerebrospinal fluid (CSF) specimens from patients admitted in the largest pediatric hospital, a World Health Organization sentinel site, with known neurologic infections (n = 36), with idiopathic meningitis (n = 25), and with no infection (n = 30), and six environmental samples, collected between 2012 and 2018. We used the IDseq bioinformatics pipeline and machine learning to identify potentially pathogenic microbes, which we then confirmed orthogonally and followed up through phone/home visits. In samples with known etiology and without infections, there was 83% concordance between mNGS and conventional testing. In idiopathic cases, mNGS identified a potential bacterial or viral etiology in 40%. There were three instances of neuroinvasive Chikungunya virus (CHIKV), whose genomes were >99% identical to each other and to a Bangladeshi strain only previously recognized to cause febrile illness in 2017. CHIKV-specific qPCR of all remaining stored CSF samples from children who presented with idiopathic meningitis in 2017 (n = 472) revealed 17 additional CHIKV meningitis cases, exposing an unrecognized meningitis outbreak. Orthogonal molecular confirmation, case-based clinical data, and patient follow-up substantiated the findings. Case-control CSF mNGS surveys can complement conventional diagnostic methods to identify etiologies of meningitis, conduct surveillance, and predict outbreaks. The improved patient- and population-level data can inform evidence-based policy decisions.IMPORTANCE Globally, there are an estimated 10.6 million cases of meningitis and 288,000 deaths every year, with the vast majority occurring in low- and middle-income countries. In addition, many survivors suffer from long-term neurological sequelae. Most laboratories assay only for common bacterial etiologies using culture and directed PCR, and the majority of meningitis cases lack microbiological diagnoses, impeding institution of evidence-based treatment and prevention strategies. We report here the results of a validation and application study of using unbiased metagenomic sequencing to determine etiologies of idiopathic (of unknown cause) cases. This included CSF from patients with known neurologic infections, with idiopathic meningitis, and without infection admitted in the largest children's hospital of Bangladesh and environmental samples. Using mNGS and machine learning, we identified and confirmed an etiology (viral or bacterial) in 40% of idiopathic cases. We detected three instances of Chikungunya virus (CHIKV) that were >99% identical to each other and to a strain previously recognized to cause systemic illness only in 2017. CHIKV qPCR of all remaining stored 472 CSF samples from children who presented with idiopathic meningitis in 2017 at the same hospital uncovered an unrecognized CHIKV meningitis outbreak. CSF mNGS can complement conventional diagnostic methods to identify etiologies of meningitis, and the improved patient- and population-level data can inform better policy decisions.

Sentinel Case of Candida auris in the Western United States Following Prolonged Occult Colonization in a Returned Traveler from India.

Candida auris is an emerging multidrug-resistant yeast with high mortality. We report the sentinel C. auris case on the United States West Coast in a patient who relocated from India. We identified close phylogenetic relatedness to the South Asia clade and ERG11 Y132F and FKS1 S639Y mutations potentially explaining antifungal resistance.

Bergeyella cardium: Clinical Characteristics and Draft Genome of an Emerging Pathogen in Native and Prosthetic Valve Endocarditis.

Bergeyella cardium is a new species in the family Flavobacteriaceae that was recently described in 3 cases of native valve infective endocarditis. We report the first case of B. cardium prosthetic valve endocarditis, provide the first draft genome of this species, and review the microbiologic characteristics of this emerging pathogen.

Serotype-specific immune responses to pneumococcal conjugate vaccine among children are significantly correlated by individual: Analysis of randomized controlled trial data.

BACKGROUND: The magnitude of an individual's serotype-specific immunoglobulin G (IgG) response to a pneumococcal conjugate vaccine (PCV) has been associated with the vaccine's protective efficacy against carriage of pneumococci of that serotype, though the relationship with other serotypes needs to be understood. METHODS: Using immunogenicity data collected during a trial comparing the 7-valent (PCV7) and 13-valent (PCV13) vaccines, we measured associations between serotype-specific IgG levels, and used multiple regressions to identify demographic predictors of response. RESULTS: Vaccine-induced IgG levels were moderately positively correlated with one another, with pairwise correlation coefficients of 0.40-0.70. Principal component analysis of vaccine-serotype responses yielded one principal component indicating general immune responsiveness, and a second principal component mainly describing responses to serotype 14, which was the least correlated with the other responses. Overall, demographic variables explained only 17.0 and 20.4% of the geometric mean PCV7 and PCV13 responses, respectively. In both groups, older age at the first vaccine dose and shorter time from vaccination to antibody measurement were independently associated with stronger geometric mean responses. DISCUSSION: Improved understanding of the nature and causes of variation in immune response may aid in optimizing vaccination schedules and identifying robust correlates of protection.

Quantifying Transmission Heterogeneity Using Both Pathogen Phylogenies and Incidence Time Series.

Heterogeneity in individual-level transmissibility can be quantified by the dispersion parameter k of the offspring distribution. Quantifying heterogeneity is important as it affects other parameter estimates, it modulates the degree of unpredictability of an epidemic, and it needs to be accounted for in models of infection control. Aggregated data such as incidence time series are often not sufficiently informative to estimate k. Incorporating phylogenetic analysis can help to estimate k concurrently with other epidemiological parameters. We have developed an inference framework that uses particle Markov Chain Monte Carlo to estimate k and other epidemiological parameters using both incidence time series and the pathogen phylogeny. Using the framework to fit a modified compartmental transmission model that includes the parameter k to simulated data, we found that more accurate and less biased estimates of the reproductive number were obtained by combining epidemiological and phylogenetic analyses. However, k was most accurately estimated using pathogen phylogeny alone. Accurately estimating k was necessary for unbiased estimates of the reproductive number, but it did not affect the accuracy of reporting probability and epidemic start date estimates. We further demonstrated that inference was possible in the presence of phylogenetic uncertainty by sampling from the posterior distribution of phylogenies. Finally, we used the inference framework to estimate transmission parameters from epidemiological and genetic data collected during a poliovirus outbreak. Despite the large degree of phylogenetic uncertainty, we demonstrated that incorporating phylogenetic data in parameter inference improved the accuracy and precision of estimates.