Model-based disease mapping using primary care registry data.

BACKGROUND: Spatial modeling of disease risk using primary care registry data is promising for public health surveillance. However, it remains unclear to which extent challenges such as spatially disproportionate sampling and practice-specific reporting variation affect statistical inference. METHODS: Using lower respiratory tract infection data from the INTEGO registry, modeled with a logistic model incorporating patient characteristics, a spatially structured random effect at municipality level, and an unstructured random effect at practice level, we conducted a case and simulation study to assess the impact of these challenges on spatial trend estimation. RESULTS: Even with spatial imbalance and practice-specific reporting variation, the model performed well. Performance improved with increasing spatial sample balance and decreasing practice-specific variation. CONCLUSION: Our findings indicate that, with correction for reporting efforts, primary care registries are valuable for spatial trend estimation. The diversity of patient locations within practice populations plays an important role.

Using a general practice research database to assess the spatio-temporal COVID-19 risk.

BACKGROUND: In Flanders, general practitioners (GPs) were among the first ones to collect data regarding COVID-19 cases. Intego is a GPs' morbidity registry in primary care with data collected from the electronic medical records from a sample of general practices. The Intego database contain elaborate information regarding patient characteristics, such as comorbidities. At the national level, the Belgian Public Health Institute (Sciensano) recorded all test-confirmed COVID-19 cases, but without other patient characteristics. METHODS: Spatio and spatio-temporal analyses were used to analyse the spread of COVID-19 incidence at two levels of spatial aggregation: the municipality and the health sector levels. Our study goal was to compare spatio-temporal modelling results based on the Intego and Sciensano data, in order to see whether the Intego database is capable of detecting epidemiological trends similar to those in the Sciensano data. Comparable results would allow researchers to use these Intego data, and their wealth of patient information, to model COVID-19-related processes. RESULTS: The two data sources provided comparable results. Being a male decreased the odds of having COVID-19 disease. The odds for the age categories (17,35], (35,65] and (65,110] of being a confirmed COVID-19 case were significantly higher than the odds for the age category [0,17]. In the Intego data, having one of the following comorbidities, i.e., chronic kidney disease, heart and vascular disease, and diabetes, was significantly associated with being a COVID-19 case, increasing the odds of being diagnosed with COVID-19. CONCLUSION: We were able to show how an alternative data source, the Intego data, can be used in a pandemic situation. We consider our findings useful for public health officials who plan intervention strategies aimed at monitor and control disease outbreaks such as that of COVID-19.

Temporal trends in antibiotic prescribing and serious and nonserious infections in children presenting to general practice: a registry-based longitudinal cohort study of 162 507 individuals.

BACKGROUND: It is crucial to understand the trends in paediatric antibiotic prescribing and serious and nonserious infections to improve antibiotic prescribing practices for children in ambulatory care. OBJECTIVES: Assessing trends in paediatric antibiotic prescribing and infection incidence in general practice from 2002 to 2022. METHODS: In this retrospective cohort study using INTEGO network data from 162 507 patients in Flanders (Belgium), we calculated antibiotic prescribing rates and proportions alongside incidence rates of serious and nonserious infections, stratified by age (0-1, 2-6, 7-12 years) and municipality. We performed autoregressive moving average time-series analyses and seasonality analyses. RESULTS: From 2002 to 2022, antibiotic prescribing rate decreased significantly: 584/1000 person-years (PY) (95% CI 571-597) to 484/1000PY (95% CI 478-491); so did antibiotic overall prescribing proportion: 46.3% (95% CI 45.1-47.6) to 23.3% (95% CI 22.9-23.7) (59.3% amoxicillin and 17.8% broad spectrum). Prescribing proportions dropped significantly for nonserious (45.6% to 20.9%) and increased for serious infections (64.1% to 69.8%). Proportions significantly dropped for acute suppurative otitis media (74.7% to 64.1%), upper respiratory tract infections (44.9% to 16.6%), bronchitis/bronchiolitis (73.6% to 44.1%) and acute tonsillopharyngitis (59.5% to 21.7%), while significantly increasing for pneumonia (65.2% to 80.2%). Nonserious and serious infection incidence rates increased from 785/1000PY and 34.2/1000PY to 1223/1000PY and 64.1/1000PY, respectively. Blood and CRP testing proportions increased significantly. CONCLUSIONS: Antibiotic prescribing in general practice for children declined from 2002 to 2022. Further targeted antibiotic stewardship initiatives are needed to reduce the use of broad-spectrum antibiotics and antibiotic prescribing for conditions such as otitis media and bronchitis/bronchiolitis.

SlyB encapsulates outer membrane proteins in stress-induced lipid nanodomains.

The outer membrane in Gram-negative bacteria consists of an asymmetric phospholipid-lipopolysaccharide bilayer that is densely packed with outer-membrane ß-barrel proteins (OMPs) and lipoproteins1. The architecture and composition of this bilayer is closely monitored and is essential to cell integrity and survival2-4. Here we find that SlyB, a lipoprotein in the PhoPQ stress regulon, forms stable stress-induced complexes with the outer-membrane proteome. SlyB comprises a 10 kDa periplasmic ß-sandwich domain and a glycine zipper domain that forms a transmembrane α-helical hairpin with discrete phospholipid- and lipopolysaccharide-binding sites. After loss in lipid asymmetry, SlyB oligomerizes into ring-shaped transmembrane complexes that encapsulate ß-barrel proteins into lipid nanodomains of variable size. We find that the formation of SlyB nanodomains is essential during lipopolysaccharide destabilization by antimicrobial peptides or acute cation shortage, conditions that result in a loss of OMPs and compromised outer-membrane barrier function in the absence of a functional SlyB. Our data reveal that SlyB is a compartmentalizing transmembrane guard protein that is involved in cell-envelope proteostasis and integrity, and suggest that SlyB represents a larger family of broadly conserved lipoproteins with 2TM glycine zipper domains with the ability to form lipid nanodomains.

A longitudinal transition imputation model for categorical data applied to a large registry dataset.

Imputation of longitudinal categorical covariates with several waves and many predictors is cumbersome in terms of implausible transitions, colinearity, and overfitting. We designed a simulation study with data obtained from a general practitioners' morbidity registry in Belgium for three waves, with smoking as the longitudinal covariate of interest. We set varying proportions of data on smoking to missing completely at random and missing not at random with proportions of missingness equal to 10%, 30%, 50%, and 70%. This study proposed a 3-stage approach that allows flexibility when imputing time-dependent categorical covariates. First, multiple imputation using fully conditional specification or multiple imputation for the predictor variables was deployed using the wide format such that previous and future information of the same patient was utilized. Second, a joint Markov transition model for initial, forward, backward, and intermittent probabilities was developed for each imputed dataset. Finally, this transition model was used for imputation. We compared the performance of this methodology with an analyses of the complete data and with listwise deletion in terms of bias and root mean square error. Next, we applied this methodology in a clinical case for years 2017 to 2021, where we estimated the effect of several covariates on the pneumococcal vaccination. This methodological framework ensures that the plausibility of transitions is preserved, overfitting and colinearity issues are resolved, and confounders can be utilized. Finally, a companion R package was developed to enable the replication and easy application of this methodology.

Pneumococcal vaccination coverage and adherence to recommended dosing schedules in adults: a repeated cross-sectional study of the INTEGO morbidity registry.

BACKGROUND: Since 2014, Belgium's Superior Health Council has recommended pneumococcal vaccination for adults aged 19-85 years at increased risk for pneumococcal diseases with a specific vaccine administration sequence and timing. Currently, Belgium has no publicly funded adult pneumococcal vaccination program. This study investigated the seasonal pneumococcal vaccination trends, evolution of vaccination coverage and adherence to the 2014 recommendations. METHODS: INTEGO is a general practice morbidity registry in Flanders (Belgium) that represents 102 general practice centres and comprised over 300.000 patients in 2021. A repeated cross-sectional study was performed for the period between 2017 and 2021. Using adjusted odds ratios computed via multiple logistic regression, the association between an individual's characteristics (gender, age, comorbidities, influenza vaccination status and socioeconomic status) and schedule-adherent pneumococcal vaccination status was assessed. RESULTS: Pneumococcal vaccination coincided with seasonal flu vaccination. The vaccination coverage in the population at risk decreased from 21% in 2017 to 18.2% in 2018 and then started to increase to 23.6% in 2021. Coverage in 2021 was highest for high-risk adults (33.8%) followed by 50- to 85-year-olds with comorbidities (25.5%) and healthy 65- to 85-year-olds (18.7%). In 2021, 56.3% of the high-risk adults, 74.6% of the 50+ with comorbidities persons, and 74% of the 65+ healthy persons had an adherent vaccination schedule. Persons with a lower socioeconomic status had an adjusted odds ratio of 0.92 (95% Confidence Interval (CI) 0.87-0.97) for primary vaccination, 0.67 (95% CI 0.60-0.75) for adherence to the recommended second vaccination if the 13-valent pneumococcal conjugate vaccine was administered first and 0.86 (95% CI 0.76-0.97) if the 23-valent pneumococcal polysaccharide vaccine was administered first. CONCLUSION: Pneumococcal vaccine coverage is slowly increasing in Flanders, displaying seasonal peaks in sync with influenza vaccination campaigns. However, with less than one-fourth of the target population vaccinated, less than 60% high-risk and approximately 74% of 50 + with comorbidities and 65+ healthy persons with an adherent schedule, there is still much room for improvement. Furthermore, adults with poor socioeconomic status had lower odds of primary vaccination and schedule adherence, demonstrating the need for a publicly funded program in Belgium to ensure equitable access.