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JNJ-73763989 is an N-acetylgalactosamine conjugated short interfering RNA combination product consisting of two triggers in clinical development for chronic hepatitis B virus (HBV) infection treatment that induces a selective degradation of all HBV mRNA transcripts. Our aim is to characterize the plasma and liver pharmacokinetics (PK) of JNJ-73763989 after intravenous and subcutaneous administration in recombinant adeno-associated (rAAV) HBV infected mice. Forty-two male rAAV-HBV infected C57Bl/6 mice received JNJ-73763989 doses of 10 mg/kg i.v. or 1, 3 and 10 mg/kg s.c. Plasma and liver concentrations were analyzed simultaneously using nonlinear mixed-effects modeling with the NONMEM 7.4. A population PK model consisting of a two-compartment disposition model with transporter-mediated drug disposition, including internalization to the liver compartment, linear elimination from plasma and liver, and first-order absorption following subcutaneous administration, was suitable to describe both plasma and liver PK. After subcutaneous dosing, absolute bioavailability was complete and flip-flop kinetics were observed. JNJ-73763989 distributes from plasma to liver via transporter-mediated liver internalization in less than 24 hours, with sustained (gt;42 days) liver exposure. The saturation of transporter-mediated liver internalization was hypothesized to be due to asialoglycoprotein receptor saturation. Increasing the dose decreased the relative liver uptake efficiency in mice for intravenously and, to a lesser extent, subcutaneously administered JNJ-73763989. Lower dose levels administered subcutaneously in mice can maximize the proportion of the dose reaching the liver. SIGNIFICANCE STATEMENT: Pharmacokinetic modeling of JNJ-73763989 liver and plasma concentration-time data in mice indicated that the proportion of JNJ-73763989 reaching the liver may be increased by administering lower subcutaneous doses compared to higher intravenous doses. Model-based simulations can be applied to optimize the dose and regimen combination.

Background Exposure–response analyses were conducted to explore the relationship between selected efficacy and safety endpoints and serum phosphate (PO4) concentrations, a potential biomarker of efficacy and safety, in locally advanced or metastatic urothelial carcinoma patients with FGFR alterations treated with erdafitinib. Methods Data from two dosing regimens of erdafitinib in a phase 2 study (NCT02365597), 6 and 8-mg/day with provision for pharmacodynamically guided titration per serum PO4 levels, were analyzed using Cox proportional hazard or logistic regression models. Efficacy endpoints were overall survival (OS), progression-free survival (PFS), and objective response rate (ORR). Safety endpoints were adverse events typical for FGFR inhibitors. Results Exposure-efficacy analyses on 156 patients (6-mg = 68; 8-mg = 88) showed that patients with higher serum PO4 levels within the first 6 weeks showed better OS (hazard ratio 0.57 [95% CI 0.46–0.72] per mg/dL of PO4; p = 0.01), PFS (hazard ratio 0.80 [0.67–0.94] per mg/dL of PO4; p = 0.01), and ORR (odds ratio 1.38 [1.02–1.86] per mg/dL of PO4; p = 0.04). Exposure-safety analyses on 177 patients (6-mg = 78; 8-mg = 99) showed that the incidence of selected adverse events associated with on-target off-tumor effects significantly rose with higher PO4. Conclusions The exploratory relationship between serum PO4 levels and efficacy/safety outcomes supported the use of pharmacodynamically guided dose titration to optimize erdafitinib’s therapeutic benefit/risk ratio. Clinical trial registration number NCT02365597.

Background JNJ-4964 is a TLR7 agonist, which, via a type I interferon (IFN)–dependent mechanism, may enhance host immunity suppressed by persistent exposure to hepatitis B antigens in chronic hepatitis B. Methods PK and PD data were pooled from 2 studies involving 90 participants ( n = 74 JNJ-4964, dose range 0.2–1.8 mg; n = 16 placebo) in a fasted state. Food effects on PK were studied in 24 participants (1.2 or 1.25 mg). A population PK model and PK/PD models were developed to characterize the effect of JNJ-4964 plasma levels on the time course of IFN-α, IFN-γ–inducible protein 10 (IP-10 or CXCL10), IFN-stimulated gene 15 ( ISG15), neopterin and lymphocytes following single and weekly dosing in healthy adults. Covariate effects, circadian rhythms and negative feedback were incorporated in the models. Results A 3-compartment linear PK model with transit absorption adequately described JNJ-4964 PK. Bioavailability was 44.2% in fed state relative to fasted conditions. Indirect response models with maximum effect (Emax) stimulation on production rate constant (kin) described IFN-α, IP-10, ISG15 and neopterin, while a precursor-dependent indirect response model with inhibitory effect described the transient lymphocyte reduction. Emax, EC50 and γ (steepness) estimates varied according to PD markers, with EC50 displaying substantial between-subject variability. Female and Asian race exhibited lower EC50, suggesting higher responsiveness. Conclusions PK/PD models well characterized the time course of immune system markers in healthy adults. Our results supported sex and race as covariates on JNJ-4964 responsiveness, as well as circadian rhythms and negative feedback as homeostatic mechanisms that are relevant in TLR7-induced type I IFN responses.

Background JNJ-73763989 comprises two hepatitis B virus (HBV)-specific, liver-targeted N-galactosamine-conjugated short interfering RNA triggers, JNJ-73763976 and JNJ-73763924. JNJ-73763989 pharmacokinetics, safety and tolerability were assessed in two phase 1 studies: Japanese (NCT04002752), and non-Japanese healthy participants and chronic hepatitis B (CHB) patients also receiving the HBV capsid assembly modulator JNJ-56136379 and a nucleos(t)ide analogue (NA) (NCT03365947). Methods Healthy participant cohorts were double-blind and randomized to receive a single subcutaneous JNJ-73763989 dose (non-Japanese participants, 35, 100, 200, 300 or 400 mg; Japanese participants, 25, 100 or 200 mg) or placebo. JNJ-73763976 and JNJ-73763924 plasma concentrations were assessed over 48 h. CHB patients received JNJ-73763989 200 mg every 4 weeks plus daily oral JNJ-56136379 250 mg and NA in an open-label fashion. Safety and tolerability were assessed through Day 28 (healthy participants) or Day 112 (patients). Results Thirty non-Japanese ( n = 4/dose; placebo, n = 10) and 24 Japanese healthy participants ( n = 6/dose; placebo, n = 6) were randomized. JNJ-73763976 and JNJ-73763924 exposure generally increased in a dose-proportional manner. Mean plasma half-life was 4–9 h. No differences between pharmacokinetic parameters were apparent between non-Japanese and Japanese healthy participants. In the 12 CHB patients, mean JNJ-73763976, JNJ-73763924 and JNJ-56136379 plasma concentrations 2 h post-dose on Day 29 were 663, 269 and 14,718 ng/mL, respectively. In both studies, all adverse events were mild/moderate. Conclusion JNJ-73763976 and JNJ-73763924 had short plasma half-lives and exposure generally increased in a dose-proportional manner; there were no pharmacokinetic differences between Japanese and non-Japanese healthy adults. JNJ-73763989 with or without JNJ-56136379 and NA was generally safe and well tolerated.

Starting in December 2013, West Africa was overwhelmed with the deadliest outbreak of Ebola virus known to date, resulting in more than 27,500 cases and 11,000 deaths. In response to the epidemic, development of a heterologous prime-boost vaccine regimen was accelerated and involved preparation of a phase 3 effectiveness study. While individually randomized controlled trials are widely acknowledged as the gold standard for demonstrating the efficacy of a candidate vaccine, there was considerable debate on the ethical appropriateness of these designs in the context of an epidemic. A suitable phase 3 trial must convincingly ensure unbiased evaluation with sufficient statistical power. In addition, efficient evaluation of a vaccine candidate is required so that an effective vaccine can be immediately disseminated. This manuscript aims to present the statistical and modeling considerations, design rationale and challenges encountered due to the emergent, epidemic setting that led to the selection of a cluster-randomized phase 3 study design under field conditions.

Airborne infectious diseases such as influenza are primarily transmitted from human to human by means of social contacts and thus easily spread within households. Epidemic models, used to gain insight in infectious disease spread and control, typically rely on the assumption of random mixing within households. Until now there was no direct empirical evidence to support this assumption. Here, we present the first social contact survey specifically designed to study contact networks within households. The survey was conducted in Belgium (Flanders and Brussels) in 2010-2011. We analyzed data from 318 households totaling 1266 individuals with household sizes ranging from 2 to 7 members. Exponential-family random graph models (ERGMs) were fitted to the within-household contact networks to reveal the processes driving contact between household members, both on weekdays and weekends. The ERGMs showed a high degree of clustering and, specifically on weekdays, decreasing connectedness with increasing household size. Furthermore, we found that the odds of a contact between father and child is smaller than for any other pair except for older siblings. Epidemic simulation results suggest that within-household contact density is the main driver of differences in epidemic spread between complete and empirical-based household contact networks. The homogeneous mixing assumption may therefore be an adequate characterization of the within-household contact structure for the purpose of epidemic simulation. However, ignoring the contact density when inferring from an epidemic model will result in biased estimates of within-household transmission rates. Further research on the implementation of within-household contact networks in epidemic models is necessary.Significance StatementHouseholds have a pivotal role in the spread of airborne infectious diseases. Households are bridging units between schools and workplaces, and social contacts within households are frequent and intimate, allowing for rapid disease spread. Infectious disease models typically assume that members of a household contact each other randomly. Until now there was no direct empirical evidence to support this assumption. In this paper, we present the first social contact survey specifically designed to study contact networks within households with young children. We investigate which factors drive contacts between household members on one particular day by means of a statistical model. Our results suggest the importance of connectedness within households over heterogeneity in number of contacts.

Background Declining incidence and spatial heterogeneity complicated the design of phase 3 Ebola vaccine trials during the tail of the 2013–16 Ebola virus disease (EVD) epidemic in West Africa. Mathematical models can provide forecasts of expected incidence through time and can account for both vaccine efficacy in participants and effectiveness in populations. Determining expected disease incidence was critical to calculating power and determining trial sample size. Methods In real-time, we fitted, forecasted, and simulated a proposed phase 3 cluster-randomized vaccine trial for a prime-boost EVD vaccine in three candidate regions in Sierra Leone. The aim was to forecast trial feasibility in these areas through time and guide study design planning. Results EVD incidence was highly variable during the epidemic, especially in the declining phase. Delays in trial start date were expected to greatly reduce the ability to discern an effect, particularly as a trial with an effective vaccine would cause the epidemic to go extinct more quickly in the vaccine arm. Real-time updates of the model allowed decision-makers to determine how trial feasibility changed with time. Conclusions This analysis was useful for vaccine trial planning because we simulated effectiveness as well as efficacy, which is possible with a dynamic transmission model. It contributed to decisions on choice of trial location and feasibility of the trial. Transmission models should be utilised as early as possible in the design process to provide mechanistic estimates of expected incidence, with which decisions about sample size, location, timing, and feasibility can be determined.

The duration of the presence of maternal mumps antibodies in a prospective cohort study is presented. Immunoglobulin G against mumps was portioned with a commercial ELISA test (EuroimmunA (R) anti-mumps Virus AT ELISA, Germany) on samples from 213 mother-child pairs at seven time points between pregnancy and 12 months of age. Non-linear mixed models were used to model maternal antibody decay in infants. The model-based median time to loss of antibodies was 3.6 months. The median child-specific time to loss of antibodies in children of naturally immune women (3.8 months) and children of vaccinated women (2.4 months) differed significantly (p = 0.025). The log antibody level of the mother and the log birth weight were correlated with the duration of maternal antibodies in infants (p < 0.0001). Conclusion: Children of vaccinated women loose maternal mumps antibodies significantly earlier in life compared to children of naturally infected women. If early administration (< 12 months) of the combined measles, mumps, and rubella vaccine is needed, maternal mumps antibodies are not expected to interfere with infant humoral vaccine responses.

After a steep monotone rise with age, the seroprevalence profiles for human parvovirus B19 (PVB19) display a decrease or plateau between the ages of 20 and 40, in each of 5 European countries. We investigate whether this phenomenon is induced by waning antibodies for PVB19 and, if this is the case, whether secondary infections are plausible, or whether boosting may occur. Several immunological scenarios are tested for PVB19 by fitting different compartmental dynamic transmission models to serological data using data on social contact patterns. The social contact approach has already been shown informative to estimate transmission rates and the basic reproduction number for infections transmitted predominantly through nonsexual social contacts. Our results show that for 4 countries, model selection criteria favor the scenarios allowing for waning immunity at an age-specific rate over the assumption of lifelong immunity, assuming that the transmission rates are directly proportional to the contact rates. Different views on the evolution of the immune response to PVB19 infection lead to altered estimates of the age-specific force of infection and the basic reproduction number. The scenarios which allow for multiple infections during one lifetime predict a higher frequency of PVB19 infection in pregnant women and of associated fetal deaths. When prevaccination serological data are available, the framework developed in this paper could prove worthwhile to investigate these different scenarios for other infections as well, such as cytomegalovirus.

Dynamic transmission models are essential to design and evaluate control strategies for airborne infections. Our objective was to develop a dynamic transmission model for seasonal influenza allowing to evaluate the impact of vaccinating specific age groups on the incidence of infection, disease and mortality. Projections based on such models heavily rely on assumed ‘input’ parameter values. In previous seasonal influenza models, these parameter values were commonly chosen ad hoc, ignoring between-season variability and without formal model validation or sensitivity analyses. We propose to directly estimate the parameters by fitting the model to age-specific influenza-like illness (ILI) incidence data over multiple influenza seasons. We used a weighted least squares (WLS) criterion to assess model fit and applied our method to Belgian ILI data over six influenza seasons. After exploring parameter importance using symbolic regression, we evaluated a set of candidate models of differing complexity according to the number of season-specific parameters. The transmission parameters (average R0, seasonal amplitude and timing of the seasonal peak), waning rates and the scale factor used for WLS optimization, influenced the fit to the observed ILI incidence the most. Our results demonstrate the importance of between-season variability in influenza transmission and our estimates are in line with the classification of influenza seasons according to intensity and vaccine matching. NG is beneficiary of a postdoctoral grant from the AXA Research Fund. LW acknowledges support from an interdisciplinary doctoral grant of the University of Antwerp (Bijzonder Onderzoeksfonds, BOF). YV acknowledges support from a doctoral grant of Hasselt University (BOF11D04FAEC). NH acknowledges support from the Antwerp University Scientific Chair in Evidence-Based Vaccinology, financed in 2009-2014 by an unrestricted gift from Pfizer. Support from the IAP Research Network P7/06 of the Belgian State (Belgian Science Policy) is gratefully acknowledged. This study was co-financed by the Health Care Knowledge Centre (KCE) of the Belgian Federal government and benefited from discussions held as part of the KCE's expert committee and with Joke Bilcke, Adriaan Blommaert and Pieter Neels. We thank Francoise Wuillaume, Viviane van Casteren and Isabelle Thomas (Scientific Institute for Public Health) for collecting and providing sentinel data on ILI and influenza, and Nancy Thiry for useful discussions. The computational resources and services used in this work were provided by the Hercules Foundation and the Flemish Government - Department EWI. We thank Geert Jan Bex for support with using the VSC cluster.

Introduction: Vaccine coverage data are typically collected through vaccine registers and retrospective surveys. Alternatively, cross-sectional serosurveys enable direct estimation of vaccine coverage from antibody prevalence by exploiting correlated seropositivity for multi-antigen vaccines. Here, we extend previous methods by accounting for temporal antibody decline in estimating vaccine coverage for measles-mumps-rubella vaccine using serial serosurvey data. Methods: We introduce a Markovian cohort model of antibody waning and boosting applied to dichotomous seropositivity data for measles, mumps, and rubella. Simulation studies are used to test model identifiability and to explore bias induced by previous methods that ignore waning. The cohort model is then fitted to three Australian serosurveys, entailing estimates of vaccine coverage from routine and catch-up vaccination as well as waning rates for each antigen. Results: The simulation results show that the cohort model is identifiable and qualitatively captures the decline in seropositivity observed in older children. When fitted to all three Australian surveys, the estimated seroconversion and waning parameters are similar to estimates based on recent meta-analyses, whereas the coverage estimates appear consistent with previous Australian survey-based estimates. Discussion: We show that previous methods of estimating coverage from serological data can be improved by fitting a cohort model with waning and boosting processes to serial serosurvey data, furthermore yielding estimates of more parameters of interest such as rates of waning. In settings where serial serosurvey data is available, our method could be duplicated or applied to related questions such as coverage in routine two-dose schedules or from other combination vaccines.

Background - Few studies have quantified social mixing in remote rural areas of developing countries, where the burden of infectious diseases is usually the highest. Understanding social mixing patterns in those settings is crucial to inform the implementation of strategies for disease prevention and control. We characterized contact and social mixing patterns in rural communities of the Peruvian highlands. Methods and Findings - This cross-sectional study was nested in a large prospective household-based study of respiratory infections conducted in the province of San Marcos, Cajamarca-Peru. Members of study households were interviewed using a structured questionnaire of social contacts (conversation or physical interaction) experienced during the last 24 hours. We identified 9015 reported contacts from 588 study household members. The median age of respondents was 17 years (interquartile range [IQR] 4–34 years). The median number of reported contacts was 12 (IQR 8–20) whereas the median number of physical (i.e. skin-to-skin) contacts was 8.5 (IQR 5–14). Study participants had contacts mostly with people of similar age, and with their offspring or parents. The number of reported contacts was mainly determined by the participants’ age, household size and occupation. School-aged children had more contacts than other age groups. Within-household reciprocity of contacts reporting declined with household size (range 70%-100%). Ninety percent of household contact networks were complete, and furthermore, household members' contacts with non-household members showed significant overlap (range 33%-86%), indicating a high degree of contact clustering. A two-level mixing epidemic model was simulated to compare within-household mixing based on observed contact networks and within-household random mixing. No differences in the size or duration of the simulated epidemics were revealed. Conclusion - This study of rural low-density communities in the highlands of Peru suggests contact patterns are highly assortative. Study findings support the use of within-household homogenous mixing assumptions for epidemic modeling in this setting. This work was supported by the Vanderbilt University CTSA grant UL1 RR024975 from National Institutes of Health, an investigator initiated research grant from Pfizer (IIR WS1898786(0887X1-4492), (http://www.pfizer.com) and grant 02832-9 from the Thrasher Research Fund (www.thrasherresearch.org/default.aspx). NG is beneficiary of a postdoctoral grant from the AXA Research Fund (http://www.axa-research. org/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

The basic reproduction number R0 and the effective reproduction number R are pivotal parameters in infectious disease epidemiology, quantifying the transmission potential of an infection in a population. We estimate both parameters from 13 pre-vaccination serological data sets on varicella zoster virus (VZV) in 12 European countries and from population-based social contact surveys under the commonly made assumptions of endemic and demographic equilibrium. The fit to the serology is evaluated using the inferred effective reproduction number R as a model eligibility criterion combined with AIC as a model selection criterion. For only 2 out of 12 countries, the common choice of a constant proportionality factor is sufficient to provide a good fit to the seroprevalence data. For the other countries, an age-specific proportionality factor provides a better fit, assuming physical contacts lasting longer than 15 min are a good proxy for potential varicella transmission events. In all countries, primary infection with VZV most often occurs in early childhood, but there is substantial variation in transmission potential with R0 ranging from 2.8 in England and Wales to 7.6 in The Netherlands. Two non-parametric methods, the maximal information coefficient (MIC) and a random forest approach, are used to explain these differences in R0 in terms of relevant country-specific characteristics. Our results suggest an association with three general factors: inequality in wealth, infant vaccination coverage and child care attendance. This illustrates the need to consider fundamental differences between European countries when formulating and parameterizing infectious disease models. ES acknowledges support from a Methusalem research grant from the Flemish Government. NG is beneficiary of a postdoctoral grant from the AXA Research Fund. NH acknowledges support from the Antwerp University scientific chair in Evidence-Based Vaccinology, financed in 2009-2014 by an unrestricted gift from Pfizer. AM is currently receiving funding from the European Research Council under the European Union's Seventh Framework Program(FP7/2007-2013)/ERC Starting Grant [Agreement No. 283955]. Support from the IAP Research Network P7/06 of the Belgian State(Belgian Science Policy) is gratefully acknowledged. The computational resources and services used in this work were provided by the Hercules Foundation and the Flemish Government - department EWI. This study was initiated as part of POLYMOD, a European Commission project funded within the Sixth Framework Programme, Contract number: SSP22-CT-2004-502084.

Biomedical studies often generate repeated measures of multiple outcomes on a set of subjects. It may be of interest to develop a biologically intuitive model for the joint evolution of these outcomes while assessing inter-subject heterogeneity. Even though it is common for biological processes to entail non-linear relationships, examples of multivariate non-linear mixed models (MNMMs) are still fairly rare. We contribute to this area by jointly analyzing the maternal antibody decay for measles, mumps, rubella, and varicella, allowing for a different non-linear decay model for each infectious disease. We present a general modeling framework to analyze multivariate non-linear longitudinal profiles subject to censoring, by combining multivariate random effects, non-linear growth and Tobit regression. We explore the hypothesis of a common infant-specific mechanism underlying maternal immunity using a pairwise correlated random-effects approach and evaluating different correlation matrix structures. The implied marginal correlation between maternal antibody levels is estimated using simulations. The mean duration of passive immunity was less than 4months for all diseases with substantial heterogeneity between infants. The maternal antibody levels against rubella and varicella were found to be positively correlated, while little to no correlation could be inferred for the other disease pairs. For some pairs, computational issues occurred with increasing correlation matrix complexity, which underlines the importance of further developing estimation methods for MNMMs. Copyright © 2015 John Wiley & Sons, Ltd.

Many human infectious diseases originate from animals or are transmitted through animal vectors. We aimed to identify factors that are predictive of ownership and touching of animals, assess whether animal ownership influences social contact behavior, and estimate the probability of a major zoonotic outbreak should a transmissible influenza-like pathogen be present in animals, all in the setting of a densely populated European country. A diary-based social contact survey (n = 1768) was conducted in Flanders, Belgium, from September 2010 until February 2011. Many participants touched pets (46%), poultry (2%) or livestock (2%) on a randomly assigned day, and a large proportion of participants owned such animals (51%, 15% and 5%, respectively). Logistic regression models indicated that larger households are more likely to own an animal and, unsurprisingly, that animal owners are more likely to touch animals. We observed a significant effect of age on animal ownership and touching. The total number of social contacts during a randomly assigned day was modeled using weighted-negative binomial regression. Apart from age, household size and day type (weekend versus weekday and regular versus holiday period), animal ownership was positively associated with the total number of social contacts during the weekend. Assuming that animal ownership and/or touching are at-risk events, we demonstrate a method to estimate the outbreak potential of zoonoses. We show that in Belgium animal-human interactions involving young children (0-9 years) and adults (25-54 years) have the highest potential to cause a major zoonotic outbreak.

The effectiveness of childhood immunization programs depends on the vaccination coverage actually achieved. Routinely collected coverage data are not always available, and comparability between countries is often compromised because of different data collection methods. In 2000, Gay developed a method to estimate trivalent vaccination coverage from readily available trivariate serological data on the basis of parametric assumptions related to the rate of seroconversion for each vaccine component and probabilities of natural exposure to infection. Gay's work was indirectly published in a paper by Altmann and Altmann, who derived exact solutions for the parameters on the basis of Gay's modeling equations. In this paper, we propose a general likelihood-based marginal model framework to extend Gay's model by relaxing two of its main assumptions. We use the Bahadur model for trivariate binary data to explicitly account for an association between the disease-specific exposure probabilities. We fit several correlation structures to measles, mumps, and rubella serology from Belgium and Ireland. For both countries, we estimate a small positive pairwise exposure correlation, which improves the fit to the data. However, the effect on the estimated vaccination coverage and its associated variability is fairly moderate. For both Belgium and Ireland, all models reveal that the vaccination coverage achieved during the first 15?years since the introduction of measles, mumps, and rubella immunization is insufficient to eliminate measles. Copyright (C) 2012 John Wiley & Sons, Ltd.

In dynamic models of infectious disease transmission, typically various mixing patterns are imposed on the so-called Who-Acquires-Infection-From-Whom matrix (WAIFW). These imposed mixing patterns are based on prior knowledge of age-related social mixing behavior rather than observations. Alternatively, one can assume that transmission rates for infections transmitted predominantly through non-sexual social contacts, are proportional to rates of conversational contact which can be estimated from a contact survey. In general, however, contacts reported in social contact surveys are proxies of those events by which transmission may occur and there may exist age-specific characteristics related to susceptibility and infectiousness which are not captured by the contact rates. Therefore, in this paper, transmission is modeled as the product of two age-specific variables: the age-specific contact rate and an age-specific proportionality factor, which entails an improvement of fit for the seroprevalence of the varicella-zoster virus (VZV) in Belgium. Furthermore, we address the impact on the estimation of the basic reproduction number, using non-parametric bootstrapping to account for different sources of variability and using multi-model inference to deal with model selection uncertainty. The proposed method makes it possible to obtain important information on transmission dynamics that cannot be inferred from approaches traditionally applied hitherto., 25 pages, 6 figures

Background Until recently, mathematical models of person to person infectious diseases transmission had to make assumptions on transmissions enabled by personal contacts by estimating the so-called WAIFW-matrix. In order to better inform such estimates, a population based contact survey has been carried out in Belgium over the period March-May 2006. In contrast to other European surveys conducted simultaneously, each respondent recorded contacts over two days. Special attention was given to holiday periods, and respondents with large numbers of professional contacts. Methods Participants kept a paper diary with information on their contacts over two different days. A contact was defined as a two-way conversation of at least three words in each others proximity. The contact information included the age of the contact, gender, location, duration, frequency, and whether or not touching was involved. For data analysis, we used association rules and classification trees. Weighted generalized estimating equations were used to analyze contact frequency while accounting for the correlation between contacts reported on the two different days. A contact surface, expressing the average number of contacts between persons of different ages was obtained by a bivariate smoothing approach and the relation to the so-called next-generation matrix was established. Results People mostly mixed with people of similar age, or with their offspring, their parents and their grandparents. By imputing professional contacts, the average number of daily contacts increased from 11.84 to 15.70. The number of reported contacts depended heavily on the household size, class size for children and number of professional contacts for adults. Adults living with children had on average 2 daily contacts more than adults living without children. In the holiday period, the daily contact frequency for children and adolescents decreased with about 19% while a similar observation is made for adults in the weekend. These findings can be used to estimate the impact of school closure. Conclusion We conducted a diary based contact survey in Belgium to gain insights in social interactions relevant to the spread of infectious diseases. The resulting contact patterns are useful to improve estimating crucial parameters for infectious disease transmission models.

Background: Mathematical modelling of infectious disease is increasingly used to help guide public health policy. As directly transmitted infections, such as influenza and tuberculosis, require contact between individuals, knowledge about contact patterns is a necessary pre-requisite of accurate model predictions. Of particular interest is the potential impact of school closure as a means of controlling pandemic influenza (and potentially other pathogens). Methods: This paper uses a population-based prospective survey of mixing patterns in eight European countries to study the relative change in the basic reproduction number (R-0 - the average number of secondary cases from a typical primary case in a fully susceptible population) on weekdays versus weekends and during regular versus holiday periods. The relative change in R-0 during holiday periods and weekends gives an indication of the impact collective school closures (and prophylactic absenteeism) may have during a pandemic. Results: Social contact patterns differ substantially when comparing weekdays to the weekend and regular to holiday periods mainly due to the reduction in work and/or school contacts. For most countries the basic reproduction number decreases from the week to weekends and regular to holiday periods by about 21% and 17%, respectively. However for other countries no significant decrease was observed. Conclusion: We use a large-scale social contact survey in eight different European countries to gain insights in the relative change in the basic reproduction number on weekdays versus weekends and during regular versus holiday periods. The resulting estimates indicate that school closure can have a substantial impact on the spread of a newly emerging infectious disease that is transmitted via close (non sexual) contacts. We thank both referees for their comments which have led to an improved version of the manuscript. This work has been funded by 'SIMID', a strategic basic research project funded by the institute for the Promotion of Innovation by Science and Technology in Flanders (IWT), project number 060081, by POLYMOD, a European Commission project funded within the Sixth Framework Programme, Contract number: SSP22-CT-2004-502084, by the IAP research network nr P6/03 of the Belgian Government (Belgian Science Policy).

Despite long-standing two-dose measles-mumpsrubella (MMR) vaccination, measles outbreaks still occur in highly vaccinated European populations. For instance, large measles outbreaks occurred in France (2008–13), the United Kingdom (2012–13) and the Netherlands (2012). Based on a multicohort model approach, using spatial serological survey data, MMR vaccination coverage data and data on social contacts, we found effective reproduction numbers significantly higher than 1 for measles in Belgium. This indicates that at one of the expected re-introductions, a measles outbreak is likely to spread, especially when it occurs during school term. The predicted average effective reproduction number increased over a 30-year time span from 1.3 to 2.2 and from 1.9 to 3.2 for basic reproduction numbers of 12 and 18, respectively. The expected relative measles incidence was highest in infants under one year of age, in adolescents and young adults. In conclusion, gradually increasing proportions of susceptible adolescents and young adults provide through their highly active social life an avenue for measles to resurge in large outbreaks upon re-introduction in Belgium, especially during school terms. Infants form an important vulnerable group during future measles outbreaks. The authors would like to acknowledge the colleagues of the Flemish Agency for Care and Health, the Scientific Institute of Public Health and the measles elimination committee for fruitful discussions related to this research. NH acknowledges support of the University of Antwerp Scientific Chair in Evidence-based Vaccinology sponsored in 2009-2014 by a gift from Pfizer. SA acknowledges support by the Research Fund of Hasselt University (Grant BOF11NI31). ES and HG acknowledge support from a Methusalem research grant from the Flemish government. NG is beneficiary of a postdoctoral grant from the AXA Research Fund. Support from the IAP Research Network P7/06 of the Belgian State (Belgian Science Policy) is gratefully acknowledged. HT and EL are postdoctoral researchers for the Fund of Scientific Research - Flanders (FWO). The computational resources and services used in this work were provided by the Hercules Foundation and the Flemish Government - department EWI.