Effect of Pneumococcal Conjugate Vaccine on Pneumonia Incidence Rates among Children 2-59 Months of Age, Mongolia, 2015-2021.

Starting in June 2016, the 13-valent pneumococcal conjugate vaccine (PCV13) was introduced into the routine immunization program of Mongolia by using a 2+1 dosing schedule, phased by district. We used prospective hospital surveillance to evaluate the vaccine's effect on pneumonia incidence rates among children 2-59 months of age over a 6-year period. Of 17,607 children with pneumonia, overall adjusted incidence rate ratios showed decreased primary endpoint pneumonia, very severe pneumonia, and probable pneumococcal pneumonia until June 2021. Results excluding and including the COVID-19 pandemic period were similar. Pneumonia declined in 3 districts that introduced PCV13 with catch-up campaigns but not in the 1 district that did not. After PCV13 introduction, vaccine-type pneumococcal carriage prevalence decreased by 44% and nonvaccine-type carriage increased by 49%. After PCV13 introduction in Mongolia, the incidence of more specific pneumonia endpoints declined in children 2-59 months of age; additional benefits were conferred by catch-up campaigns.

Gaps in the usage and reporting of multiple imputation for incomplete data: findings from a scoping review of observational studies addressing causal questions.

BACKGROUND: Missing data are common in observational studies and often occur in several of the variables required when estimating a causal effect, i.e. the exposure, outcome and/or variables used to control for confounding. Analyses involving multiple incomplete variables are not as straightforward as analyses with a single incomplete variable. For example, in the context of multivariable missingness, the standard missing data assumptions ("missing completely at random", "missing at random" [MAR], "missing not at random") are difficult to interpret and assess. It is not clear how the complexities that arise due to multivariable missingness are being addressed in practice. The aim of this study was to review how missing data are managed and reported in observational studies that use multiple imputation (MI) for causal effect estimation, with a particular focus on missing data summaries, missing data assumptions, primary and sensitivity analyses, and MI implementation. METHODS: We searched five top general epidemiology journals for observational studies that aimed to answer a causal research question and used MI, published between January 2019 and December 2021. Article screening and data extraction were performed systematically. RESULTS: Of the 130 studies included in this review, 108 (83%) derived an analysis sample by excluding individuals with missing data in specific variables (e.g., outcome) and 114 (88%) had multivariable missingness within the analysis sample. Forty-four (34%) studies provided a statement about missing data assumptions, 35 of which stated the MAR assumption, but only 11/44 (25%) studies provided a justification for these assumptions. The number of imputations, MI method and MI software were generally well-reported (71%, 75% and 88% of studies, respectively), while aspects of the imputation model specification were not clear for more than half of the studies. A secondary analysis that used a different approach to handle the missing data was conducted in 69/130 (53%) studies. Of these 69 studies, 68 (99%) lacked a clear justification for the secondary analysis. CONCLUSION: Effort is needed to clarify the rationale for and improve the reporting of MI for estimation of causal effects from observational data. We encourage greater transparency in making and reporting analytical decisions related to missing data.

A comparison of strategies for selecting auxiliary variables for multiple imputation.

Multiple imputation (MI) is a popular method for handling missing data. Auxiliary variables can be added to the imputation model(s) to improve MI estimates. However, the choice of which auxiliary variables to include is not always straightforward. Several data-driven auxiliary variable selection strategies have been proposed, but there has been limited evaluation of their performance. Using a simulation study we evaluated the performance of eight auxiliary variable selection strategies: (1, 2) two versions of selection based on correlations in the observed data; (3) selection using hypothesis tests of the "missing completely at random" assumption; (4) replacing auxiliary variables with their principal components; (5, 6) forward and forward stepwise selection; (7) forward selection based on the estimated fraction of missing information; and (8) selection via the least absolute shrinkage and selection operator (LASSO). A complete case analysis and an MI analysis using all auxiliary variables (the "full model") were included for comparison. We also applied all strategies to a motivating case study. The full model outperformed all auxiliary variable selection strategies in the simulation study, with the LASSO strategy the best performing auxiliary variable selection strategy overall. All MI analysis strategies that we were able to apply to the case study led to similar estimates, although computational time was substantially reduced when variable selection was employed. This study provides further support for adopting an inclusive auxiliary variable strategy where possible. Auxiliary variable selection using the LASSO may be a promising alternative when the full model fails or is too burdensome.

Levels of pneumococcal conjugate vaccine coverage and indirect protection against invasive pneumococcal disease and pneumonia hospitalisations in Australia: An observational study.

BACKGROUND: There is limited empiric evidence on the coverage of pneumococcal conjugate vaccines (PCVs) required to generate substantial indirect protection. We investigate the association between population PCV coverage and indirect protection against invasive pneumococcal disease (IPD) and pneumonia hospitalisations among undervaccinated Australian children. METHODS AND FINDINGS: Birth and vaccination records, IPD notifications, and hospitalisations were individually linked for children aged <5 years, born between 2001 and 2012 in 2 Australian states (New South Wales and Western Australia; 1.37 million children). Using Poisson regression models, we examined the association between PCV coverage, in small geographical units, and the incidence of (1) 7-valent PCV (PCV7)-type IPD; (2) all-cause pneumonia; and (3) pneumococcal and lobar pneumonia hospitalisation in undervaccinated children. Undervaccinated children received <2 doses of PCV at <12 months of age and no doses at ≥12 months of age. Potential confounding variables were selected for adjustment a priori with the assistance of a directed acyclic graph. There were strong inverse associations between PCV coverage and the incidence of PCV7-type IPD (adjusted incidence rate ratio [aIRR] 0.967, 95% confidence interval [CI] 0.958 to 0.975, p-value < 0.001), and pneumonia hospitalisations (all-cause pneumonia: aIRR 0.991 95% CI 0.990 to 0.994, p-value < 0.001) among undervaccinated children. Subgroup analyses for children <4 months old, urban, rural, and Indigenous populations showed similar trends, although effects were smaller for rural and Indigenous populations. Approximately 50% coverage of PCV7 among children <5 years of age was estimated to prevent up to 72.5% (95% CI 51.6 to 84.4) of PCV7-type IPD among undervaccinated children, while 90% coverage was estimated to prevent 95.2% (95% CI 89.4 to 97.8). The main limitations of this study include the potential for differential loss to follow-up, geographical misclassification of children (based on residential address at birth only), and unmeasured confounders. CONCLUSIONS: In this study, we observed substantial indirect protection at lower levels of PCV coverage than previously described-challenging assumptions that high levels of PCV coverage (i.e., greater than 90%) are required. Understanding the association between PCV coverage and indirect protection is a priority since the control of vaccine-type pneumococcal disease is a prerequisite for reducing the number of PCV doses (from 3 to 2). Reduced dose schedules have the potential to substantially reduce program costs while maintaining vaccine impact.

A comparison of multiple imputation strategies for handling missing data in multi-item scales: Guidance for longitudinal studies.

Medical research often involves using multi-item scales to assess individual characteristics, disease severity, and other health-related outcomes. It is common to observe missing data in the scale scores, due to missing data in one or more items that make up that score. Multiple imputation (MI) is a popular method for handling missing data. However, it is not clear how best to use MI in the context of scale scores, particularly when they are assessed at multiple waves of data collection resulting in large numbers of items. The aim of this article is to provide practical advice on how to impute missing values in a repeatedly measured multi-item scale using MI when inference on the scale score is of interest. We evaluated the performance of five MI strategies for imputing missing data at either the item or scale level using simulated data and a case study based on four waves of the Longitudinal Study of Australian Children (LSAC). MI was implemented using both multivariate normal imputation and fully conditional specification, with two rules for calculating the scale score. A complete case analysis was also performed for comparison. Based on our results, we caution against the use of a MI strategy that does not include the scale score in the imputation model(s) when the scale score is required for analysis.

Multiple imputation of semi-continuous exposure variables that are categorized for analysis.

Semi-continuous variables are characterized by a point mass at one value and a continuous range of values for remaining observations. An example is alcohol consumption quantity, with a spike of zeros representing non-drinkers and positive values for drinkers. If multiple imputation is used to handle missing values for semi-continuous variables, it is unclear how this should be implemented within the standard approaches of fully conditional specification (FCS) and multivariate normal imputation (MVNI). This question is brought into focus by the use of categorized versions of semi-continuous exposure variables in analyses (eg, no drinking, drinking below binge level, binge drinking, heavy binge drinking), raising the question of how best to achieve congeniality between imputation and analysis models. We performed a simulation study comparing nine approaches for imputing semi-continuous exposures requiring categorization for analysis. Three methods imputed the categories directly: ordinal logistic regression, and imputation of binary indicator variables representing the categories using MVNI (with two variants). Six methods (predictive mean matching, zero-inflated binomial imputation, and two-part imputation methods with variants in FCS and MVNI) imputed the semi-continuous variable, with categories derived after imputation. The ordinal and zero-inflated binomial methods had good performance across most scenarios, while MVNI methods requiring rounding after imputation did not perform well. There were mixed results for predictive mean matching and the two-part methods, depending on whether the estimands were proportions or regression coefficients. The results highlight the need to consider the parameter of interest when selecting an imputation procedure.

Practical strategies for handling breakdown of multiple imputation procedures.

Multiple imputation is a recommended method for handling incomplete data problems. One of the barriers to its successful use is the breakdown of the multiple imputation procedure, often due to numerical problems with the algorithms used within the imputation process. These problems frequently occur when imputation models contain large numbers of variables, especially with the popular approach of multivariate imputation by chained equations. This paper describes common causes of failure of the imputation procedure including perfect prediction and collinearity, focusing on issues when using Stata software. We outline a number of strategies for addressing these issues, including imputation of composite variables instead of individual components, introducing prior information and changing the form of the imputation model. These strategies are illustrated using a case study based on data from the Longitudinal Study of Australian Children.

Evaluation of the impact of childhood 13-valent pneumococcal conjugate vaccine introduction on adult pneumonia in Ulaanbaatar, Mongolia: study protocol for an observational study.

BACKGROUND: Community-acquired pneumonia is an important cause of morbidity and mortality in adults. Approximately one-third of pneumonia cases can be attributed to the pneumococcus. Pneumococcal conjugate vaccines (PCVs) protect against colonisation with vaccine-type serotypes. The resulting decrease in transmission of vaccine serotypes leads to large indirect effects. There are limited data from developing countries demonstrating the impact of childhood PCV immunisation on adult pneumonia. There are also insufficient data available on the burden and severity of all-cause pneumonia and respiratory syncytial virus (RSV) in adults from low resource countries. There is currently no recommendation for adult pneumococcal vaccination with either pneumococcal polysaccharide vaccine or PCVs in Mongolia. We describe the protocol developed to evaluate the association between childhood 13-valent PCV (PCV13) vaccination and trends in adult pneumonia. METHODS: PCV13 was introduced into the routine childhood immunisation schedule in Mongolia in a phased manner from 2016. In March 2019 we initiated active hospital-based surveillance for adult pneumonia, with the primary objective of evaluating trends in severe hospitalised clinical pneumonia incidence in adults 18 years and older in four districts of Ulaanbaatar. Secondary objectives include measuring the association between PCV13 introduction and trends in all clinically-defined pneumonia, radiologically-confirmed pneumonia, nasopharyngeal carriage of S. pneumoniae and pneumonia associated with RSV or influenza. Clinical questionnaires, nasopharyngeal swabs, urine samples and chest radiographs were collected from enrolled patients. Retrospective administrative and clinical data were collected for all respiratory disease-related admissions from January 2015 to February 2019. DISCUSSION: Establishing a robust adult surveillance system may be an important component of monitoring the indirect impact of PCVs within a country. Monitoring indirect impact of childhood PCV13 vaccination on adult pneumonia provides additional data on the full public health impact of the vaccine, which has implications for vaccine efficiency and cost-effectiveness. Adult surveillance in Mongolia will contribute to the limited evidence available on the burden of pneumococcal pneumonia among adults in low- and middle-income countries, particularly in the Asia-Pacific region. In addition, it is one of the few examples of implementing prospective, population-based pneumonia surveillance to evaluate the indirect impact of PCVs in a resource-limited setting.

Oxygen systems to improve clinical care and outcomes for children and neonates: A stepped-wedge cluster-randomised trial in Nigeria.

BACKGROUND: Improving oxygen systems may improve clinical outcomes for hospitalised children with acute lower respiratory infection (ALRI). This paper reports the effects of an improved oxygen system on mortality and clinical practices in 12 general, paediatric, and maternity hospitals in southwest Nigeria. METHODS AND FINDINGS: We conducted an unblinded stepped-wedge cluster-randomised trial comparing three study periods: baseline (usual care), pulse oximetry introduction, and stepped introduction of a multifaceted oxygen system. We collected data from clinical records of all admitted neonates (<28 days old) and children (28 days to 14 years old). Primary analysis compared the full oxygen system period to the pulse oximetry period and evaluated odds of death for children, children with ALRI, neonates, and preterm neonates using mixed-effects logistic regression. Secondary analyses included the baseline period (enabling evaluation of pulse oximetry introduction) and evaluated mortality and practice outcomes on additional subgroups. Three hospitals received the oxygen system intervention at 4-month intervals. Primary analysis included 7,716 neonates and 17,143 children admitted during the 2-year stepped crossover period (November 2015 to October 2017). Compared to the pulse oximetry period, the full oxygen system had no association with death for children (adjusted odds ratio [aOR] 1.06; 95% confidence interval [CI] 0.77-1.46; p = 0.721) or children with ALRI (aOR 1.09; 95% CI 0.50-2.41; p = 0.824) and was associated with an increased risk of death for neonates overall (aOR 1.45; 95% CI 1.04-2.00; p = 0.026) but not preterm/low-birth-weight neonates (aOR 1.30; 95% CI 0.76-2.23; p = 0.366). Secondary analyses suggested that the introduction of pulse oximetry improved oxygen practices prior to implementation of the full oxygen system and was associated with lower odds of death for children with ALRI (aOR 0.33; 95% CI 0.12-0.92; p = 0.035) but not for children, preterm neonates, or neonates overall (aOR 0.97, 95% CI 0.60-1.58, p = 0.913; aOR 1.12, 95% CI 0.56-2.26, p = 0.762; aOR 0.90, 95% CI 0.57-1.43, p = 0.651). Limitations of our study are a lower-than-anticipated power to detect change in mortality outcomes (low event rates, low participant numbers, high intracluster correlation) and major contextual changes related to the 2016-2017 Nigerian economic recession that influenced care-seeking and hospital function during the study period, potentially confounding mortality outcomes. CONCLUSIONS: We observed no mortality benefit for children and a possible higher risk of neonatal death following the introduction of a multifaceted oxygen system compared to introducing pulse oximetry alone. Where some oxygen is available, pulse oximetry may improve oxygen usage and clinical outcomes for children with ALRI. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry: ACTRN12617000341325.

Sustained Antibody Responses 6 Years Following 1, 2, or 3 Doses of Quadrivalent Human Papillomavirus (HPV) Vaccine in Adolescent Fijian Girls, and Subsequent Responses to a Single Dose of Bivalent HPV Vaccine: A Prospective Cohort Study.

BACKGROUND: The duration of antibody response following reduced human papillomavirus (HPV) vaccine doses has not been determined. We compared the antibody responses in girls previously vaccinated with zero, 1, 2, or 3 doses of quadrivalent HPV vaccine (4vHPV; Gardasil, Merck) 6 years previously. METHODS: A prospective cohort study was undertaken in 200 Fijian girls 15-19 years of age. Approximately equal numbers of girls from 2 main ethnic groups (Fijians of Indian descent [FID] and Indigenous Fijians [iTaukei]) in Fiji were recruited for each dosage groups. Blood was drawn before and 28 days following a single dose of bivalent HPV vaccine (2vHPV; Cervarix, GlaxoSmithKline). We measured neutralizing antibodies (NAb) against HPV-6, -11, -16, and -18 using the pseudovirion-based neutralization assay. RESULTS: After 6 years (before a dose of 2vHPV was given), the geometric mean NAb titers for all 4 HPV types were not statistically different between 2-dose (2D) and 3-dose (3D) recipients: HPV-6 (3D: 2216 [95% confidence interval {CI},1695-2896]; 2D: 1476 [95% CI, 1019-2137]; P = .07), HPV-11 (3D: 4431 [95% CI, 3396-5783]; 2D: 2951 [95% CI, 1984-4390]; P = .09), HPV-16 (3D: 3373 [95% CI, 2511-4530]; 2D: 3275 [95% CI, 2452-4373]; P = .89); HPV-18 (3D: 628 [95% CI: 445-888]; 2D: 606 [95% CI, 462-862]; P = .89), and were higher in FID than iTaukei girls. Although 1-dose recipients had significantly lower NAb titers than 2-/3-dose recipients, their NAb titers were 5- to 30-fold higher than unvaccinated girls. Post-2vHPV NAb titers against HPV-16 and -18 were not statistically different between girls who received 1, 2, or 3 doses of 4vHPV previously. CONCLUSIONS: Two doses of 4vHPV provide similar NAb titers as 3 doses for 6 years, although the clinical significance is unknown. A single dose of 4vHPV elicits antibodies that persisted for at least 6 years, and induced immune memory, suggesting possible protection against HPV vaccine types after a single dose of 4vHPV.

Model checking in multiple imputation: an overview and case study.

BACKGROUND: Multiple imputation has become very popular as a general-purpose method for handling missing data. The validity of multiple-imputation-based analyses relies on the use of an appropriate model to impute the missing values. Despite the widespread use of multiple imputation, there are few guidelines available for checking imputation models. ANALYSIS: In this paper, we provide an overview of currently available methods for checking imputation models. These include graphical checks and numerical summaries, as well as simulation-based methods such as posterior predictive checking. These model checking techniques are illustrated using an analysis affected by missing data from the Longitudinal Study of Australian Children. CONCLUSIONS: As multiple imputation becomes further established as a standard approach for handling missing data, it will become increasingly important that researchers employ appropriate model checking approaches to ensure that reliable results are obtained when using this method.

Posterior predictive checking of multiple imputation models.

Multiple imputation is gaining popularity as a strategy for handling missing data, but there is a scarcity of tools for checking imputation models, a critical step in model fitting. Posterior predictive checking (PPC) has been recommended as an imputation diagnostic. PPC involves simulating "replicated" data from the posterior predictive distribution of the model under scrutiny. Model fit is assessed by examining whether the analysis from the observed data appears typical of results obtained from the replicates produced by the model. A proposed diagnostic measure is the posterior predictive "p-value", an extreme value of which (i.e., a value close to 0 or 1) suggests a misfit between the model and the data. The aim of this study was to evaluate the performance of the posterior predictive p-value as an imputation diagnostic. Using simulation methods, we deliberately misspecified imputation models to determine whether posterior predictive p-values were effective in identifying these problems. When estimating the regression parameter of interest, we found that more extreme p-values were associated with poorer imputation model performance, although the results highlighted that traditional thresholds for classical p-values do not apply in this context. A shortcoming of the PPC method was its reduced ability to detect misspecified models with increasing amounts of missing data. Despite the limitations of posterior predictive p-values, they appear to have a valuable place in the imputer's toolkit. In addition to automated checking using p-values, we recommend imputers perform graphical checks and examine other summaries of the test quantity distribution.

Preventing postnatal depression in new mothers using telephone peer support: protocol for the DAISY (Depression and AnxIety peer Support studY) multi-centre randomised controlled trial.

INTRODUCTION: Postnatal depression affects up to one in six new mothers in Australia each year, with significant impacts on the woman and her family. Prevention strategies can be complicated by a woman's reluctance to seek professional help. Peer support is a promising but inadequately tested early intervention. Very few trials have reported on the efficacy of peer support in the perinatal period and no study has been undertaken in Australia. We will explore if proactive telephone-based peer (mother-to-mother) support, provided to women identified as being at high risk of postnatal depression, impacts on clinically significant depressive symptomatology at 6 months postpartum. METHODS AND ANALYSIS: This is a protocol for a single-blinded, multi-centre, randomised controlled trial conducted in Melbourne, Australia. Eligible women will be recruited from either the postnatal units of two maternity hospitals, or around 4 weeks postpartum at maternal and child health centres within two metropolitan council areas. A total of 1060 (530/group) women will be recruited and randomly allocated (1:1 ratio) to either-usual care, to receive the standard community postpartum services available to them, or the intervention group, to receive proactive telephone-based support from a peer volunteer for 6 months, in addition to standard community services. PRIMARY OUTCOME: clinically significant depressive symptomatology at 6 months postpartum as measured using the Edinburgh Postnatal Depression Scale. SECONDARY OUTCOMES: symptoms of anxiety and/or stress, health-related quality of life, loneliness, perception of partner support, self-rated parenting, child health and development, infant feeding and health service use. The cost-effectiveness of the intervention relative to standard care will also be assessed. ETHICS AND DISSEMINATION: Ethics approval has been obtained from La Trobe University, St. Vincent's Hospital, the Royal Women's Hospital, Northern Health, Victorian Department of Health and Human Services and Victorian Department of Education and Training. Written informed consent will be obtained from all participants before randomisation. Trial results will be disseminated through peer-reviewed publications, conference presentations and a higher degree thesis. TRIAL REGISTRATION NUMBER: ACTRN12619000684123; Australian New Zealand Clinical Trials Registry.

Impact of childhood 13-valent pneumococcal conjugate vaccine introduction on adult pneumonia hospitalisations in Mongolia: a time series analysis.

Background: Few studies have assessed the potential indirect effects of childhood pneumococcal conjugate vaccine (PCV) programs on the adult pneumonia burden in resource-limited settings. We evaluated the impact of childhood PCV13 immunisation on adult all-cause pneumonia following a phased program introduction from 2016. Methods: We conducted a time-series analysis to assess changes in pneumonia hospitalisation incidence at four district hospitals in Mongolia. Adults (≥18 years) that met the clinical case definition for all-cause pneumonia were enrolled. A negative binomial mixed-effects model was used to assess the impact of PCV13 introduction on monthly counts of pneumonia admissions from January 2015-February 2022. We also performed a restricted analysis excluding the COVID-19 pandemic period. All models were stratified by age and assessed separately. Additional analyses assessed the robustness of our findings. Findings: The average annual incidence of all-cause pneumonia hospitalisation was highest in adults 65+ years (62.81 per 10,000 population) and declined with decreasing age. After adjusting for the COVID-19 pandemic period, we found that rates of pneumonia hospitalisation remained largely unchanged over time. We did not observe a reduction in pneumonia hospitalisation in any age group. Results from restricted and sensitivity analyses were comparable to the primary results, finding limited evidence of a reduced pneumonia burden. Interpretation: We did not find evidence of indirect protection against all-cause pneumonia in adults following childhood PCV13 introduction. Direct pneumococcal vaccination and other interventions should be considered to reduce burden of pneumonia among older adults. Funding: Pfizer clinical research collaboration agreement (contract number: WI236621).

Diagnosing problems with imputation models using the Kolmogorov-Smirnov test: a simulation study.

BACKGROUND: Multiple imputation (MI) is becoming increasingly popular as a strategy for handling missing data, but there is a scarcity of tools for checking the adequacy of imputation models. The Kolmogorov-Smirnov (KS) test has been identified as a potential diagnostic method for assessing whether the distribution of imputed data deviates substantially from that of the observed data. The aim of this study was to evaluate the performance of the KS test as an imputation diagnostic. METHODS: Using simulation, we examined whether the KS test could reliably identify departures from assumptions made in the imputation model. To do this we examined how the p-values from the KS test behaved when skewed and heavy-tailed data were imputed using a normal imputation model. We varied the amount of missing data, the missing data models and the amount of skewness, and evaluated the performance of KS test in diagnosing issues with the imputation models under these different scenarios. RESULTS: The KS test was able to flag differences between the observations and imputed values; however, these differences did not always correspond to problems with MI inference for the regression parameter of interest. When there was a strong missing at random dependency, the KS p-values were very small, regardless of whether or not the MI estimates were biased; so that the KS test was not able to discriminate between imputed variables that required further investigation, and those that did not. The p-values were also sensitive to sample size and the proportion of missing data, adding to the challenge of interpreting the results from the KS test. CONCLUSIONS: Given our study results, it is difficult to establish guidelines or recommendations for using the KS test as a diagnostic tool for MI. The investigation of other imputation diagnostics and their incorporation into statistical software are important areas for future research.

Epidemiology of pneumonia in hospitalized adults ≥18 years old in four districts of Ulaanbaatar, Mongolia, 2015-2019.

Background: Community-acquired pneumonia is a leading cause of morbidity and mortality among children and adults worldwide. Adult pneumonia surveillance remains limited in many low- and middle-income settings, resulting in the disease burden being largely unknown. Methods: A retrospective cohort study was conducted by reviewing medical charts for respiratory admissions at four district hospitals in Ulaanbaatar during January 2015-February 2019. Characteristics of community-acquired pneumonia cases were summarized by disease severity and age. To explore factors associated with severe pneumonia, we ran univariable and age-adjusted logistic regression models. Incidence rates were calculated using population denominators. Results: In total, 4290 respiratory admissions met the case definition for clinical pneumonia, including 430 admissions of severe pneumonia. The highest proportion of severe pneumonia admissions occurred in adults >65 years (37.4%). After adjusting for age, there were increased odds of severe pneumonia in males (adjusted odds ratio [aOR]: 1.63; 95% confidence interval [CI]: 1.33-2.00) and those with ≥1 underlying medical condition (aOR: 1.46; 95% CI: 1.14-1.87). The incidence of hospitalized pneumonia in adults ≥18 years increased from 13.49 (95% CI: 12.58-14.44) in 2015 to 17.65 (95% CI: 16.63-18.71) in 2018 per 10,000 population. The incidence of severe pneumonia was highest in adults >65 years, ranging from 9.29 (95% CI: 6.17-13.43) in 2015 to 12.69 (95% CI: 9.22-17.04) in 2018 per 10,000 population. Interpretations: Vaccination and other strategies to reduce the risk of pneumonia, particularly among older adults and those with underlying medical conditions, should be prioritized. Funding: Pfizer clinical research collaboration agreement (contract number: WI236621).

Aerosol Delivery of Palivizumab in a Neonatal Lamb Model of Respiratory Syncytial Virus Infection.

(1) Background: Palivizumab has been an approved preventative monoclonal antibody for respiratory syncytial virus (RSV) infection for over two decades. However, due to its high cost and requirement for multiple intramuscular injections, its use has been limited mostly to high-income countries. Following our previous study showing the successful lung deposition of aerosolised palivizumab in lambs, this current study evaluated the "proof-of-principle" effect of aerosolised palivizumab delivered as a therapeutic to neonatal lambs following RSV infection. (2) Methods: Neonatal lambs were intranasally inoculated with RSV-A2 on day 0 (day 3 post-birth) and treated with aerosolised palivizumab 3 days later (day 3 post-inoculation). Clinical symptoms, RSV viral load and inflammatory response were measured post-inoculation. (3) Results: Aerosolised therapeutic delivery of palivizumab did not reduce RSV viral loads in the nasopharynx nor the bronchoalveolar lavage fluid, but resulted in a modest reduction in inflammatory response at day 6 post-inoculation compared with untreated lambs. (4) Conclusions: This proof-of-principle study shows some evidence of aerosolised palivizumab reducing RSV inflammation, but further studies using optimized protocols are needed in order to validate these findings.

A single dose of quadrivalent HPV vaccine is highly effective against HPV genotypes 16 and 18 detection in young pregnant women eight years following vaccination: an retrospective cohort study in Fiji.

Background: In 2008/9, Fiji vaccinated >30,000 girls aged 9-12 years with the quadrivalent human papillomavirus (4vHPV) vaccine coverage for at least one dose was >60% (one dose only was 14%, two dose only was 13%, three doses was 35%). We calculated vaccine effectiveness (VE) of one, two and three doses of 4vHPV against oncogenic HPV genotypes 16/18, eight years following vaccination. Methods: A retrospective cohort study was undertaken (2015-2019) in pregnant women ≤23 years old, eligible to receive 4vHPV in 2008/9, with confirmed vaccination status. The study was restricted to pregnant women due to the cultural sensitivity of asking about sexual behavior in Fiji. For each participant a clinician collected a questionnaire, vaginal swab and genital warts examination, a median eight (range 6-11) years post vaccination. HPV DNA was detected by molecular methods. Adjusted VE (aVE) against the detection of vaccine HPV genotypes (16/18), the comparison group of non-vaccine genotypes (31/33/35/39/45/51/52/56/58/59/66/68), and genital warts were calculated. Covariates included in the adjusted model were: age, ethnicity and smoking, according to univariate association with any HPV detection. Findings: Among 822 participants the prevalence of HPV 16/18 in the unvaccinated, one, two and three-dose groups were 13.3% (50/376), 2.5% (4/158), 0% (0/99) and 1.6% (3/189), respectively; and for the non-vaccine high-risk genotypes, the detection rate was similar across dosage groups (33.2%-40.4%, p = 0.321). The aVE against HPV 16/18 for one, two and three doses were 81% (95% CI; 48-93%), 100% (95% CI; 100-100%), and 89% (95% CI; 64-96%), respectively. Prevalence of HPV 16/18 was lower among women with longer time since vaccination. Interpretations: A single dose 4vHPV vaccine is highly effective against HPV genotypes 16 and 18 eight years following vaccination. Our results provide the longest duration of protection for reduced dose 4vHPV schedule in a low- or middle-income country in the Western Pacific region. Funding: This study was supported by the Bill & Melinda Gates Foundation and the Department of Foreign Affairs and Trade of the Australian Government and Fiji Health Sector Support Program (FHSSP). FHSSP is implemented by Abt JTA on behalf of the Australian Government.

Synergism and Antagonism of Bacterial-Viral Coinfection in the Upper Respiratory Tract.

Streptococcus pneumoniae (the pneumococcus) is a leading cause of pneumonia in children under 5 years of age. Coinfection by pneumococci and respiratory viruses enhances disease severity. Little is known about pneumococcal coinfections with respiratory syncytial virus (RSV). Here, we developed a novel infant mouse model of coinfection using pneumonia virus of mice (PVM), a murine analogue of RSV, to examine the dynamics of coinfection in the upper respiratory tract, an anatomical niche that is essential for host-to-host transmission and progression to disease. Coinfection increased damage to the nasal tissue and increased production of the chemokine CCL3. Nasopharyngeal pneumococcal density and shedding in nasal secretions were increased by coinfection. In contrast, coinfection reduced PVM loads in the nasopharynx, an effect that was independent of pneumococcal strain and the order of infection. We showed that this "antagonistic" effect was absent using either ethanol-killed pneumococci or a pneumococcal mutant deficient in capsule production and incapable of nasopharyngeal carriage. Colonization with a pneumococcal strain naturally unable to produce capsule also reduced viral loads. The pneumococcus-mediated reduction in PVM loads was caused by accelerated viral clearance from the nasopharynx. Although these synergistic and antagonistic effects occurred with both wild-type pneumococcal strains used in this study, the magnitude of the effects was strain dependent. Lastly, we showed that pneumococci can also antagonize influenza virus. Taken together, our study has uncovered multiple novel facets of bacterial-viral coinfection. Our findings have important public health implications, including for bacterial and viral vaccination strategies in young children. IMPORTANCE Respiratory bacterial-viral coinfections (such as pneumococci and influenza virus) are often synergistic, resulting in enhanced disease severity. Although colonization of the nasopharynx is the precursor to disease and transmission, little is known about bacterial-viral interactions that occur within this niche. In this study, we developed a novel mouse model to examine pneumococcal-viral interactions in the nasopharynx with pneumonia virus of mice (PVM) and influenza. We found that PVM infection benefits pneumococci by increasing their numbers in the nasopharynx and shedding of these bacteria in respiratory secretions. In contrast, we discovered that pneumococci decrease PVM numbers by accelerating viral clearance. We also report a similar effect of pneumococci on influenza. By showing that coinfections lead to both synergistic and antagonistic outcomes, our findings challenge the existing dogma in the field. Our work has important applications and implications for bacterial and viral vaccines that target these microbes.

Effectiveness of 13-valent pneumococcal conjugate vaccine against hypoxic pneumonia and hospitalisation in Eastern Highlands Province, Papua New Guinea: An observational cohort study.

Background: Pneumonia is a leading cause of childhood mortality with Streptococcus pneumoniae a major contributor. Pneumococcal conjugate vaccines (PCVs) have been introduced into immunisation programs in many low- to middle-income countries (LMICs) yet there is a paucity of data evaluating the effectiveness in these settings. We assess the effectiveness of 13-valent PCV (13vPCV) against hypoxic pneumonia, hospitalisation and other clinical endpoints in children <5 years living in Eastern Highlands Province, Papua New Guinea (PNG). Methods: Data from two consecutive prospective observational studies (2013-2019) enrolling children <60 months presenting with pneumonia were included. Hypoxic pneumonia was defined as oxygen saturations <90%. Outcomes included hospitalisation, severe clinical pneumonia and death. 13vPCV status was determined using written records. Logistic regression models were used to estimate the odds ratios of key outcomes by 13vPCV vaccination status adjusted for confounders using inverse probability of treatment weighting. Findings: Data from 2067 children (median age; 9 months [IQR: 5-11]) were included. 739 children (36.1%) were hypoxic and 623 (30.4%) hospitalised. Twelve children (0.6% of total cohort) died in hospital. 670 children (32.7%) were fully 13vPCV-vaccinated. 13vPCV vaccination was associated with a 28.7% reduction (95% confidence interval [CI]: 9.9; 43.6%) in hypoxic pneumonia and a 57.4% reduction (38.0; 70.7%) in pneumonia hospitalisation. Interpretation: 13vPCV vaccination is effective against hypoxic pneumonia and pneumonia hospitalisation in PNG children. Strategies to improve access to and coverage of 13vPCV in PNG and other similar LMICs are urgently required. Funding: Funded by Pfizer Global and the Bill & Melinda Gates Foundation.