•Home isolation impacts the dynamics of infection spread via close contacts.•For multiple infections, the dynamic behaviour is interdependent.•The interdependence depends on the epidemiological ...parameters and symptom severity.•The effect on peak time and final size can be both positive and negative.
Behavioral epidemiology, the field aiming to determine the impact of individual behavior on the spread of an epidemic, has gained increased recognition during the last few decades. Behavioral changes due to the development of symptoms have been studied in mono-infections. However, in reality, multiple infections are circulating within the same time period and behavioral changes resulting from contraction of one of the diseases affect the dynamics of the other.
The present study aims at assessing the effect of home isolation on the joint dynamics of two infectious diseases, including co-infection, assuming that the two diseases do not confer cross-immunity. We use an age- and time- structured co-infection model based on partial differential equations. Social contact matrices, describing different mixing patterns of symptomatic and asymptomatic individuals are incorporated into the calculation of the age- and time-specific marginal forces of infection.
Two scenarios are simulated, assuming that one of the diseases has more severe symptoms than the other. In the first scenario, people stay only at home when having symptoms of the most severe disease. In the second scenario, twice as many people stay at home when having symptoms of the most severe disease than when having symptoms of the other disease.
The results show that the impact of home isolation on the joint dynamics of two infectious diseases depends on the epidemiological parameters and properties of the diseases (e.g., basic reproduction number, symptom severity). In case both diseases have a low to moderate basic reproduction number, and there is no home isolation for the less severe disease, the final size of the less severe disease increases with the proportion of symptomatic cases of the most severe disease staying at home, after an initial decrease. This counterintuitive result could be explained by a shift in the peak time of infection of the disease with the most severe symptoms, resulting in a smaller number of people with less contacts at the peak time of the other infection. When twice as many people stay at home when having symptoms of the most severe disease than when having symptoms of the other disease, increasing the proportion staying at home always reduces the final size of both diseases, and the number of co-infections.
In conclusion, when providing advise if people should stay at home in the context of two or more co-circulating diseases, one has to take into account epidemiological parameters and symptom severity.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Previous studies provide evidence for an association between modifications of the gut microbiota in early life and the development of food allergies. We studied the faecal microbiota composition (16S ...rRNA gene amplicon sequencing) and faecal microbiome functionality (metaproteomics) in a cohort of 40 infants diagnosed with cow's milk allergy (CMA) when entering the study. Some of the infants showed outgrowth of CMA after 12 months, while others did not. Faecal microbiota composition of infants was analysed directly after CMA diagnosis (baseline) as well as 6 and 12 months after entering the study. The aim was to gain insight on gut microbiome parameters in relation to outgrowth of CMA. The results of this study show that microbiome differences related to outgrowth of CMA can be mainly identified at the taxonomic level of the 16S rRNA gene, and to a lesser extent at the protein-based microbial taxonomy and functional protein level. At the 16S rRNA gene level outgrowth of CMA is characterized by lower relative abundance of Lachnospiraceae at baseline and lower Bacteroidaceae at visit 12 months.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Parkinson's Disease (PD) and Hutchinson-Gilford Progeria Syndrome (HGPS) are two heterogeneous disorders, which both display molecular and clinical alterations associated with the aging process. ...However, similarities and differences between molecular changes in these two disorders have not yet been investigated systematically at the level of individual biomolecules and shared molecular network alterations.
Here, we perform a comparative meta-analysis and network analysis of human transcriptomics data from case-control studies for both diseases to investigate common susceptibility genes and sub-networks in PD and HGPS. Alzheimer's disease (AD) and primary melanoma (PM) were included as controls to confirm that the identified overlapping susceptibility genes for PD and HGPS are non-generic.
We find statistically significant, overlapping genes and cellular processes with significant alterations in both diseases. Interestingly, the majority of these shared affected genes display changes with opposite directionality, indicating that shared susceptible cellular processes undergo different mechanistic changes in PD and HGPS. A complementary regulatory network analysis also reveals that the altered genes in PD and HGPS both contain targets controlled by the upstream regulator CDC5L.
Overall, our analyses reveal a significant overlap of affected cellular processes and molecular sub-networks in PD and HGPS, including changes in aging-related processes that may reflect key susceptibility factors associated with age-related risk for PD.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
SimpactCyan is an open-source simulator for individual-based models in HIV epidemiology. Its core algorithm is written in C++ for computational efficiency, while the R and Python interfaces aim to ...make the tool accessible to the fast-growing community of R and Python users. Transmission, treatment and prevention of HIV infections in dynamic sexual networks are simulated by discrete events. A generic "intervention" event allows model parameters to be changed over time, and can be used to model medical and behavioural HIV prevention programmes. First, we describe a more efficient variant of the modified Next Reaction Method that drives our continuous-time simulator. Next, we outline key built-in features and assumptions of individual-based models formulated in SimpactCyan, and provide code snippets for how to formulate, execute and analyse models in SimpactCyan through its R and Python interfaces. Lastly, we give two examples of applications in HIV epidemiology: the first demonstrates how the software can be used to estimate the impact of progressive changes to the eligibility criteria for HIV treatment on HIV incidence. The second example illustrates the use of SimpactCyan as a data-generating tool for assessing the performance of a phylodynamic inference framework.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
HIV viral load (VL) is an important predictor of HIV progression and transmission. Anti-retroviral therapy (ART) has been reported to reduce HIV transmission by lowering VL. However, apart from this ...beneficial effect, increased levels of population mean set-point viral load (SPVL), an estimator for HIV virulence, have been observed in men who have sex with men (MSM) in the decade following the introduction of ART in The Netherlands. Several studies have been devoted to explain these counter-intuitive trends in SPVL. However, to our knowledge, none of these studies has investigated an explanation in which it arises as the result of a sexually transmitted infection (STI) co-factor in detail.
In this study, we adapted an event-based, individual-based model to investigate how STI co-infection and sexual risk behaviour affect the evolution of HIV SPVL in MSM before and after the introduction of ART.
The results suggest that sexual risk behaviour has an effect on SPVL and indicate that more data are needed to test the effect of STI co-factors on SPVL. Furthermore, the observed trends in SPVL cannot be explained by sexual risk behaviour and STI co-factors only.
We recommend to develop mathematical models including also factors related to viral evolution as reported earlier in the literature. However, this requires more complex models, and the collection of more data for parameter estimation than what is currently available.
•We used an individual-based model to study viral load (VL) trends in MSM.•Study of the influence of sexual risk behaviour and STI co-factor on set point VL.•Set point VL trends in the literature cannot be explained by these two factors only.•We recommend to also include viral evolution to model VL trends.•This however requires more data than what is currently available.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Abstract
Model comparisons have been widely used to guide intervention strategies to control infectious diseases. Agreement between different models is crucial for providing robust evidence for ...policy-makers because differences in model properties can influence their predictions. In this study, we compared models implemented by two individual-based model simulators for HIV epidemiology in a heterosexual population with Herpes simplex virus type-2 (HSV-2). For each model simulator, we constructed four models, starting from a simplified basic model and stepwise including more model complexity. For the resulting eight models, the predictions of the impact of behavioural interventions on the HIV epidemic in Yaoundé-Cameroon were compared. The results show that differences in model assumptions and model complexity can influence the size of the predicted impact of the intervention, as well as the predicted qualitative behaviour of the HIV epidemic after the intervention. These differences in predictions of an intervention were also observed for two models that agreed in their predictions of the HIV epidemic in the absence of that intervention. Without additional data, it is impossible to determine which of these two models is the most reliable. These findings highlight the importance of making more data available for the calibration and validation of epidemiological models.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
The increasing prevalence of IgE‐mediated cow's milk allergy (CMA) in childhood is a worldwide health concern. There is a growing awareness that the gut microbiome (GM) might play an important role ...in CMA development. Therefore, treatment with probiotics and prebiotics has gained popularity. This systematic review provides an overview of the alterations of the GM, metabolome, and immune response in CMA children and animal models, including post‐treatment modifications. MEDLINE, PubMed, Scopus, and Web of Science were searched for studies on GM in CMA‐diagnosed children, published before 1 March 2023. A total of 21 articles (13 on children and 8 on animal models) were included. The studies suggest that the GM, characterized by an enrichment of the Clostridia class and reductions in the Lactobacillales order and Bifidobacterium genus, is associated with CMA in early life. Additionally, reduced levels of short‐chain fatty acids (SCFAs) and altered amino acid metabolism were reported in CMA children. Commonly used probiotic strains belong to the Bifidobacterium and Lactobacillus genera. However, only Bifidobacterium levels were consistently upregulated after the intervention, while alterations of other bacteria taxa remain inconclusive. These interventions appear to contribute to the restoration of SCFAs and amino acid metabolism balance. Mouse models indicate that these interventions tend to restore the Th2/Th1 balance, increase the Treg response, and/or silence the overall pro‐ and anti‐inflammatory cytokine response. Overall, this systematic review highlights the need for multi‐omics‐related research in CMA children to gain a mechanistic understanding of this disease and to develop effective treatments and preventive strategies.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Background & Aims
Patients are not screened adequately for hepatitis C virus infection in Belgium. In the USA, the Center for Disease Control recommends screening for patients born in the babyboom ...period (1945‐1965). In Europe, the babyboom cohort was born between 1955 and 1974, but no screening policy has been targeted to this group. We aimed to study the prevalence of hepatitis C virus in an emergency department population in Belgium and the risk factors associated with hepatitis C virus infection.
Method
We performed a monocentric, cross‐sectional seroprevalence study between January and November 2017 in a large Belgian non‐university hospital. Patients aged 18‐70 years presenting at the emergency department were eligible. Patients completed a risk assessment questionnaire and were screened for hepatitis C virus antibodies (Ab) with reflex hepatitis C virus ribonucleic acid testing.
Results
Of 2970 patients, 2366 (79.7%) agreed to participate. hepatitis C virus Ab prevalence was 1.31%. Twenty‐one (67.7%) hepatitis C virus Ab‐positive patients were born between 1955 and 1974. With a previous treatment uptake of 54.5%, the prevalence of viremia was 0.9% in retrospect; 0.2% were newly diagnosed. The weighted multiple logistic regression model identified males born in the 1955‐1974 cohort, intravenous drug use and high endemic birth country as significant risk factors for hepatitis C virus infection (P < 0.05).
Conclusion
Although the prevalence of hepatitis C virus Ab at the emergency department was higher than previously estimated for the general population in Belgium, the number of newly diagnosed patients with viremia was low. To optimize screening strategies, screening should be offered to males born in the 1955‐1974 cohort, but especially in drug users, the prison population and immigrants from high endemic countries.
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BFBNIB, DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UILJ, UKNU, UL, UM, UPUK
Understanding Parkinson’s disease (PD), in particular in its earliest phases, is important for diagnosis and treatment. However, human brain samples are collected post-mortem, reflecting mainly ...end-stage disease. Because brain samples of mouse models can be collected at any stage of the disease process, they are useful in investigating PD progression. Here, we compare ventral midbrain transcriptomics profiles from
α
-synuclein transgenic mice with a progressive, early PD-like striatal neurodegeneration across different ages using pathway, gene set, and network analysis methods. Our study uncovers statistically significant altered genes across ages and between genotypes with known, suspected, or unknown function in PD pathogenesis and key pathways associated with disease progression. Among those are genotype-dependent alterations associated with synaptic plasticity and neurotransmission, as well as mitochondria-related genes and dysregulation of lipid metabolism. Age-dependent changes were among others observed in neuronal and synaptic activity, calcium homeostasis, and membrane receptor signaling pathways, many of which linked to G-protein coupled receptors. Most importantly, most changes occurred before neurodegeneration was detected in this model, which points to a sequence of gene expression events that may be relevant for disease initiation and progression. It is tempting to speculate that molecular changes similar to those changes observed in our model happen in midbrain dopaminergic neurons before they start to degenerate. In other words, we believe we have uncovered molecular changes that accompany the progression from preclinical to early PD.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
The field of toxicogenomics (the application of '-omics' technologies to risk assessment of compound toxicities) has expanded in the last decade, partly driven by new legislation, aimed at reducing ...animal testing in chemical risk assessment but mainly as a result of a paradigm change in toxicology towards the use and integration of genome wide data. Many research groups worldwide have generated large amounts of such toxicogenomics data. However, there is no centralized repository for archiving and making these data and associated tools for their analysis easily available.
The Data Infrastructure for Chemical Safety Assessment (diXa) is a robust and sustainable infrastructure storing toxicogenomics data. A central data warehouse is connected to a portal with links to chemical information and molecular and phenotype data. diXa is publicly available through a user-friendly web interface. New data can be readily deposited into diXa using guidelines and templates available online. Analysis descriptions and tools for interrogating the data are available via the diXa portal.
http://www.dixa-fp7.eu
d.hendrickx@maastrichtuniversity.nl; info@dixa-fp7.eu
Supplementary data are available at Bioinformatics online.
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