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1.
J Infect Dis ; 229(1): 282-293, 2024 Jan 12.
Artigo em Inglês | MEDLINE | ID: mdl-37665210

RESUMO

BACKGROUND: Nonbacteremic community-acquired pneumonia (CAP) is a leading presentation of severe pneumococcal disease in adults. Serotype-specific urinary antigen detection (UAD) assay can detect serotypes causing pneumococcal CAP, including nonbacteremic cases, and guide recommendations for use of higher valency pneumococcal conjugate vaccines (PCVs). METHODS: Adult CAP serotype distribution studies that used both Pfizer UADs (UAD1, detects PCV13 serotypes; UAD2, detects PCV20 non-PCV13 serotypes plus 2, 9N, 17F, and 20) were identified by review of an internal study database and included if results were published. The percentages of all-cause radiologically confirmed CAP (RAD + CAP) due to individual or grouped (PCV13, PCV15, and PCV20) serotypes as detected from culture or UAD were reported. RESULTS: Six studies (n = 2, United States; n = 1 each, Germany, Sweden, Spain, and Greece) were included. The percentage of RAD + CAP among adults ≥18 years with PCV13 serotypes equaled 4.6% to 12.9%, with PCV15 serotypes 5.9% to 14.5%, and with PCV20 serotypes 7.8% to 23.8%. The percentage of RAD + CAP due to PCV15 and PCV20 serotypes was 1.1-1.3 and 1.3-1.8 times higher than PCV13 serotypes, respectively. CONCLUSIONS: PCV13 serotypes remain a cause of RAD + CAP among adults even in settings with pediatric PCV use. Higher valency PCVs among adults could address an important proportion of RAD + CAP in this population.


Assuntos
Infecções Comunitárias Adquiridas , Infecções Pneumocócicas , Pneumonia Pneumocócica , Adulto , Humanos , Criança , Streptococcus pneumoniae , Pneumonia Pneumocócica/epidemiologia , Pneumonia Pneumocócica/prevenção & controle , Sorogrupo , Infecções Pneumocócicas/prevenção & controle , Infecções Comunitárias Adquiridas/epidemiologia , Vacinas Pneumocócicas , Vacinas Conjugadas
2.
Infect Dis Ther ; 13(4): 953-963, 2024 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-38499832

RESUMO

INTRODUCTION: Estimating respiratory syncytial virus (RSV) burden in adults is challenging because of non-specific symptoms, infrequent standard-of-care testing, resolution of viral shedding before seeking medical care, test positivity that varies by specimen site in the upper airway and lower diagnostic test sensitivity compared to children. Conducting prospective observational studies to assess RSV burden in adults is time- and resource-intensive. Thus, model-based approaches can be applied using existing data to obtain more accurate estimates of RSV burden. This protocol establishes essential elements for estimating RSV incidence rate in adults using a time series model-based approach. It can be tailored to specific databases and applied globally across countries, enabling estimation of local RSV disease burden to inform public health decision-making, including immunization policy. METHODS: Data are analysed using a quasi-Poisson regression model, considering the effect of baseline trends and pathogen co-circulation, stratified by age and risk status. Pathogen co-circulation is represented by viral proxies defined based on ICD code groupings indicating RSV and influenza-specific hospitalizations, lagged 0 up to 4 weeks based on the model selection. A final model is constructed in two steps: optimization of the time trend (using p-values) and selection of the viral proxy lag time (using test statistics, to prioritize the most biologically plausible option). The yearly incidence rate and percentage of events attributable to RSV are estimated from the final model. Confidence intervals are calculated using residual bootstrapping. PLANNED OUTCOMES: Outcomes to be modelled are based on administrative ICD code groupings and include the number of cardiorespiratory, respiratory and cardiovascular events in a specific care setting (e.g., general practitioner visit, emergency department visit, hospitalization and death). Cardiovascular events are limited to those for which existing evidence suggests an association with RSV infection. Additional secondary outcomes are constructed as a subset of the primary outcomes based on specific ICD code groups.

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