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Disparities in COVID-19 Vaccination in Belgium
No full textBackground:
The COVID-19 pandemic highlighted the links between socio-economic disparities and health inequalities, notably with respect to vaccination. In this context, the present contribution investigated the association between COVID-19 vaccination and demographic and socio-economic factors in Belgium at area and individual levels.
Methods:
The Belgian vaccine register for the COVID-19 vaccination campaign (VACCINNET+) was linked at individual level with demographic and socio-economic variables from the DEMOBEL database. For all adult individuals tested for SARS-CoV-2 (LINK-VACC sample), demographic and socio-economic indicators were derived and their impact on vaccination coverages at an aggregated geographical level (municipality) was quantified via the use of a composite factor. The same indicators were calculated for the full Belgian population for comparison purposes.
In a second step, a multilevel approach was considered by fitting hierarchical logistic regression models to the individual level LINK-VACC data to disentangle the individual and municipality effects allowing to evaluate the added value of the availability of individual level data in this context.
Results:
The composite factor built from income deciles, migration background, and household composition shows consistent results with earlier findings based on individual level data for similar indicators. Indeed, it was seen at the individual level that persons with lower household incomes, a migration background, and/or belonging to a household with only one adult were less likely to be vaccinated, and these inequalities translate into disparities observed at the municipality level.
The hierarchical models show that taking into account municipality effects when analyzing individual level data does not dramatically change the estimates related to demographic and socio-economic indicators in this case. However, they provide a more accurate description by modelling explicitly part of the variability related to the neighborhood.
Conclusion:
The most important effects observed at the individual level are reflected in the aggregated data at the municipality level. Multilevel analyses show that most of the demographic and socio-economic impacts on vaccination are captured at the individual level. Nevertheless, accounting for area level in individual level analyses improves the overall description.</p
West Nile virus monitoring in Flanders (Belgium) during 2022–2023 reveals endemic Usutu virus circulation in the wild bird population
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Impact of extreme weather events on the occurrence of infectious diseases in Belgium from 2011 to 2021.
No full textThe role of meteorological factors, such as rainfall or temperature, as key players in the transmission and survival of infectious agents is poorly understood. The aim of this study was to compare meteorological surveillance data with epidemiological surveillance data in Belgium and to investigate the association between intense weather events and the occurrence of infectious diseases. Meteorological data were aggregated per Belgian province to obtain weekly average temperatures and rainfall per province and categorized according to the distribution of the variables. Epidemiological data included weekly cases of reported pathogens responsible for gastroenteritis, respiratory, vector-borne and invasive infections normalized per 100 000 population. The association between extreme weather events and infectious events was determined by comparing the mean weekly incidence of the considered infectious diseases after each weather event that occurred after a given number of weeks. Very low temperatures were associated with higher incidences of influenza and parainfluenza viruses, , rotavirus and invasive and infections, whereas very high temperatures were associated with higher incidences of , spp., spp., parasitic gastroenteritis and infections. Very heavy rainfall was associated with a higher incidence of respiratory syncytial virus, whereas very low rainfall was associated with a lower incidence of adenovirus gastroenteritis. This work highlights not only the relationship between temperature or rainfall and infectious diseases but also the most extreme weather events that have an individual influence on their incidence. These findings could be used to develop adaptation and mitigation strategies.</p
Genomic comparison between and and analysis of peptide-based biomarkers for serodiagnosis.
No full textIn recent years, there has been an increase in the number of reported cases of infection in various animals, which can interfere with the ante-mortem diagnosis of animal tuberculosis caused by . In this study, whole genome sequencing (WGS) was used to search for protein-coding genes to distinguish from . In addition, the population structure of the available genomic WGS datasets is described, including three novel Belgian isolates from infections in alpacas. Candidate genes were identified by examining the presence of the regions of difference and by a pan-genome analysis of the available WGS data. A total of 80 genes showed presence-absence variation between the two species, including genes encoding Proline-Glutamate (PE), Proline-Proline-Glutamate (PPE), and Polymorphic GC-Rich Sequence (PE-PGRS) proteins involved in virulence and host interaction. Filtering based on predicted subcellular localization, sequence homology and predicted antigenicity resulted in 28 proteins out of 80 that were predicted to be potential antigens. As synthetic peptides are less costly and variable than recombinant proteins, an approach was performed to identify linear and discontinuous B-cell epitopes in the selected proteins. From the 28 proteins, 157 B-cell epitope-based peptides were identified that discriminated between and species. Although confirmation by testing is still required, these candidate synthetic peptides containing B-cell epitopes could potentially be used in serological tests to differentiate cases of from infection, thus reducing misdiagnosis in animal tuberculosis surveillance.</p
High pathogenic avian influenza A(H5) viruses of clade 2.3.4.4b in Europe-Why trends of virus evolution are more difficult to predict.
No full textSince 2016, A(H5Nx) high pathogenic avian influenza (HPAI) virus of clade 2.3.4.4b has become one of the most serious global threats not only to wild and domestic birds, but also to public health. In recent years, important changes in the ecology, epidemiology, and evolution of this virus have been reported, with an unprecedented global diffusion and variety of affected birds and mammalian species. After the two consecutive and devastating epidemic waves in Europe in 2020-2021 and 2021-2022, with the second one recognized as one of the largest epidemics recorded so far, this clade has begun to circulate endemically in European wild bird populations. This study used the complete genomes of 1,956 European HPAI A(H5Nx) viruses to investigate the virus evolution during this varying epidemiological outline. We investigated the spatiotemporal patterns of A(H5Nx) virus diffusion to/from and within Europe during the 2020-2021 and 2021-2022 epidemic waves, providing evidence of ongoing changes in transmission dynamics and disease epidemiology. We demonstrated the high genetic diversity of the circulating viruses, which have undergone frequent reassortment events, providing for the first time a complete overview and a proposed nomenclature of the multiple genotypes circulating in Europe in 2020-2022. We described the emergence of a new genotype with gull adapted genes, which offered the virus the opportunity to occupy new ecological niches, driving the disease endemicity in the European wild bird population. The high propensity of the virus for reassortment, its jumps to a progressively wider number of host species, including mammals, and the rapid acquisition of adaptive mutations make the trend of virus evolution and spread difficult to predict in this unfailing evolving scenario.</p
The economic burden of type 2 diabetes on the public healthcare system in Kenya: a cost of illness study
No full textBACKGROUND: The burden of chronic non-communicable diseases (NCDs) is a growing public health concern. The availability of cost-of-illness data, particularly public healthcare costs for NCDs, is limited in Sub-Saharan Africa (SSA), yet such data evidence is needed for policy action.
OBJECTIVE: The objective of this study was to estimate the economic burden of type 2 diabetes (T2D) on Kenya’s public healthcare system in 2021 and project costs for 2045.
METHODS: This was a cost-of-illness study using the prevalence-based bottom-up costing approach to estimate the economic burden of T2D in the year 2021. We further conducted projections on the estimated costs for the year 2045. The costs were estimated corresponding to the care, treatment, and management of diabetes and some diabetes complications based on the primary data collected from six healthcare facilities in Nairobi and secondary costing data from previous costing studies in low and middle-income countries (LMICs). The data capture and costing analysis were done in Microsoft Excel 16, and sensitivity analysis was conducted on all the parameters to estimate the cost changes.
RESULTS: The total cost of managing T2D for the healthcare system in Kenya was estimated to be US 635 million (KES 74,521 million) in 2021. This was an increase of US 2 million (KES 197 million) considering the screening costs of undiagnosed T2D in the country. The major cost driver representing 59% of the overall costs was attributed to T2D complications, with nephropathy having the highest estimated costs of care and management (US 332 million (KES 36, 457 million). The total cost for T2D was projected to rise to US 1.6 billion (KES 177 billion) in 2045.
CONCLUSION: This study shows that T2D imposes a huge burden on Kenya’s healthcare system. There is a need for government and societal action to develop and implement policies that prevent T2D, and appropriately plan care for those diagnosed with T2D.</p
Occurrence and Synthesis Pathways of (Suspected) Genotoxic α,β-Unsaturated Carbonyls in Chocolate and Other Commercial Sweet Snacks.
No full textα,β-Unsaturated carbonyls are highly reactive and described as structural alerts for genotoxicity. Ten of them (either commercially available or synthesized here by combinatorial chemistry) were first investigated throughout the chocolate-making process by solvent-assisted flavor evaporation (SAFE) coupled to GC-MS/SIM. Monitored α,β-unsaturated aldehydes were formed during chocolate production, primarily through aldol condensation of Strecker aldehydes triggered by bean roasting. Notably, levels of 2-phenylbut-2-enal (up to 399 μg·kg) and 5-methyl-2-phenylhex-2-enal (up to 216 μg·kg) increased up to 40-fold. Dry conching caused evaporation of α,β-unsaturated carbonyls, while wet conching partially restored or increased their levels due to cocoa butter addition. Further analyses showed that α,β-unsaturated aldehydes also occurred in most commercial sweet snacks (up to 16 μg·kg), although often at lower concentrations than in roasted cocoa or derived chocolates. In the end, none of the monitored α,β-unsaturated aldehydes did raise a health concern compared to current maximum use levels (2-5 mg·kg). On the other hand, much higher levels of genotoxic furan-2()-one were found in crepe and cake samples (up to 4.3 mg·kg).</p