Determinants of Dutch public health professionals' intention to use digital contact tracing support tools: A cross-sectional online questionnaire study

Contact tracing (CT) can be a resource intensive task for public health services. To alleviate their workload and potentially accelerate the CT-process, public health professionals (PHPs) may transfer some tasks in the identification, notification, and monitoring of contacts to cases and their contacts themselves, using 'digital contact tracing support tools' (DCTS-tools). In this study, we aimed to identify determinants of PHPs' intention to use DCTS-tools. Between February and April 2022, we performed a cross-sectional online questionnaire study among PHPs involved in CT for COVID-19 in the Netherlands. We built three random forest models to identify determinants of PHPs' intention to use DCTS-tools for the identification, notification, and monitoring of contacts, respectively. The online questionnaire was completed by 641 PHPs. Most respondents had a positive intention towards using DCTS-tools for the identification (64.5%), notification (58%), and monitoring (55.2%) of contacts. Random forest models were able to correctly predict the intention of 81%, 80%, and 81% of respondents to use DCTS-tools for the identification, notification, and monitoring of contacts, respectively. Top-determinants of having a positive intention are the anticipated effect of DCTS-tools on the feasibility and efficiency of CT (speed, workload, difficulty), the degree to which PHPs anticipated that cases and contacts may find it pleasant and may be willing to participate in CT using DCTS-tools, and the degree to which PHPs anticipated that cases and contacts are sufficiently supported in CT when using DCTS-tools. Most PHPs have a positive intention to involve cases and their contacts in the identification, notification, and monitoring stages of the CT-process through DCTS-tools. The identified top-determinants should be prioritized in the (future) development and implementation of DCTS-tools in public health practice. Citizens' perspectives on the use of DCTS-tools should be investigated in future research.

A Bayesian inference method to estimate transmission trees with multiple introductions; applied to SARS-CoV-2 in Dutch mink farms

Knowledge of who infected whom during an outbreak of an infectious disease is important to determine risk factors for transmission and to design effective control measures. Both whole-genome sequencing of pathogens and epidemiological data provide useful information about the transmission events and underlying processes. Existing models to infer transmission trees usually assume that the pathogen is introduced only once from outside into the population of interest. However, this is not always true. For instance, SARS-CoV-2 is suggested to be introduced multiple times in mink farms in the Netherlands from the SARS-CoV-2 pandemic among humans. Here, we developed a Bayesian inference method combining whole-genome sequencing data and epidemiological data, allowing for multiple introductions of the pathogen in the population. Our method does not a priori split the outbreak into multiple phylogenetic clusters, nor does it break the dependency between the processes of mutation, within-host dynamics, transmission, and observation. We implemented our method as an additional feature in the R-package phybreak. On simulated data, our method correctly identifies the number of introductions, with an accuracy depending on the proportion of all observed cases that are introductions. Moreover, when a single introduction was simulated, our method produced similar estimates of parameters and transmission trees as the existing package. When applied to data from a SARS-CoV-2 outbreak in Dutch mink farms, the method provides strong evidence for independent introductions of the pathogen at 13 farms, infecting a total of 63 farms. Using the new feature of the phybreak package, transmission routes of a more complex class of infectious disease outbreaks can be inferred which will aid infection control in future outbreaks.

Citizen involvement in COVID-19 contact tracing with digital tools: a qualitative study to explore citizens' perspectives and needs

BACKGROUND

Contact tracing (CT) is a key strategy when dealing with outbreaks of infectious diseases such as COVID-19. The scale of the COVID-19 pandemic has often left public health professionals (PHPs), who are responsible for the execution of CT, unable to keep up with the rapid and largescale spread of the virus. To enhance or support its execution, and potentially lower the workload for PHPs, citizens may be more actively involved in CT-tasks that are commonly executed by PHPs (referred to as 'self-led CT'). There is limited insight into citizens' perspectives on and needs for self-led CT for COVID-19. This study aims to explore the perspectives and needs of Dutch citizens on taking more responsibilities in the execution of CT for COVID-19, potentially through the use of digital tools.

METHODS

An exploratory qualitative study was performed, in which online semi-structured interviews were conducted. Questions were based on the Reasoned Action Approach and Health Belief Model. Interviews were audio-recorded and transcribed verbatim. A thematic analysis was conducted to identify citizens' perspectives and needs to participate in self-led CT.

RESULTS

We conducted 27 interviews with Dutch citizens. Seven main themes were identified from the interviews: 1) 'Citizens' perspectives on self-led CT are influenced by prior experiences with regular CT', 2) 'Citizens' felt responsibilities and the perceived responsibilities of the PHS in CT shape their perspectives on self-led CT', 3) 'Anticipated impacts of self-led CT on the CT-process', 4) 'Citizens' attitude towards the application of self-led CT depends on their own perceived skills and the willingness and skills of others', 5) 'Shame and social stigma may hamper participation in self-led CT', 6) 'Concerns about privacy and data security: a barrier for self-led CT', and 7) 'Citizens' perspectives and anticipated needs for the implementation and application of self-led CT in practice'.

CONCLUSIONS

Most interviewees hold a positive attitude towards self-led CT and using digital tools for this purpose. However, their intention for self-led CT may depend on various factors, such as prior experiences with regular CT, and their perceived self-efficacy to participate. Perspectives and needs of citizens should be considered for the future implementation of self-led CT in practice.

Identifying Sexually Transmitted Infection Risk Groups Based on Behavioral and Psychological Characteristics Among Heterosexuals During the COVID-19 Pandemic

BACKGROUND

Measures to reduce coronavirus disease (COVID-19) transmission may impact sexual health. We aimed to examine the impact of COVID-19 on sexual behavior and sexually transmitted infection (STI) testing and to characterize individuals who were at high STI risk.

METHODS

Dutch heterosexual males and females who participated in a cohort study in 2016 to 2018 were invited to fill out 2 questionnaires again in 2020 (age, 21-28 years). We used behavioral and psychological data from: prelockdown (September 2019 to February 2020), lockdown (March to May 2020), and postlockdown (June to August 2020). Behavior change was compared between subgroups identified with latent class analysis.

RESULTS

Four latent classes were identified (n = 238). Individuals in class 1 (48% of study population) and class 2 (36%) were at low STI risk and reported mostly steady partnerships. Individuals in class 3 (9%) and class 4 (7%) reported multiple casual partners prelockdown. Class 4 was characterized by lower condom use and health goals, negative infection prevention attitudes, and higher impulsiveness compared with class 3. Furthermore, same/increased partner numbers during lockdown (class 3, 18%; class 4, 56%) and postlockdown (class 3, 36%; class 4, 42%) compared with prelockdown was often reported. Of individuals who wanted an STI test during the pandemic, 62% in class 3 and 56% in class 4 did not get tested, mainly because they were unable to get an appointment.

CONCLUSIONS

A subgroup of individuals, characterized by low health goals, negative infection prevention attitudes, and high impulsiveness, engaged in high-risk behavior during the pandemic. Identifying these individuals may help provide appropriate health care during strict lockdowns and after relaxation of measures.

Time for change: Transitions between HIV risk levels and determinants of behavior change in men who have sex with men

As individual sexual behavior is variable over time, the timing of interventions might be vital to reducing HIV transmission. We aimed to investigate transitions between HIV risk levels among men who have sex with men (MSM), and identify determinants associated with behavior change. Participants in a longitudinal cohort study among HIV-negative MSM (Amsterdam Cohort Studies) completed questionnaires about their sexual behavior during biannual visits (2008-2017). Visits were assigned to different HIV risk levels, based on latent classes of behavior. We modelled transitions between risk levels, and identified determinants associated with these transitions at the visit preceding the transition using multi-state Markov models. Based on 7,865 visits of 767 participants, we classified three risk levels: low (73% of visits), medium (22%), and high risk (5%). For MSM at low risk, the six-month probability of increasing risk was 0.11. For MSM at medium risk, the probability of increasing to high risk was 0.08, while the probability of decreasing to low risk was 0.33. For MSM at high risk, the probability of decreasing risk was 0.43. Chemsex, erection stimulants and poppers, high HIV risk perception, and recent STI diagnosis were associated with increased risk at the next visit. High HIV risk perception and young age were associated with decreasing risk. Although the majority of MSM showed no behavior change, a considerable proportion increased HIV risk. Determinants associated with behavior change may help to identify MSM who are likely to increase risk in the near future and target interventions at these individuals, thereby reducing HIV transmission.

Effectiveness of contact tracing apps for SARS-CoV-2: a rapid systematic review

OBJECTIVE

To systematically review evidence on effectiveness of contact tracing apps (CTAs) for SARS-CoV-2 on epidemiological and clinical outcomes.

DESIGN

Rapid systematic review.

DATA SOURCES

EMBASE (OVID), MEDLINE (PubMed), BioRxiv and MedRxiv were searched up to 28 October 2020.

STUDY SELECTION

Studies, both empirical and model-based, assessing effect of CTAs for SARS-CoV-2 on reproduction number (R), total number of infections, hospitalisation rate, mortality rate, and other epidemiologically and clinically relevant outcomes, were eligible for inclusion.

DATA EXTRACTION

Empirical and model-based studies were critically appraised using separate checklists. Data on type of study (ie, empirical or model-based), sample size, (simulated) time horizon, study population, CTA type (and associated interventions), comparator and outcomes assessed, were extracted. The most important findings were extracted and narratively summarised. Specifically for model-based studies, characteristics and values of important model parameters were collected.

RESULTS

2140 studies were identified, of which 17 studies (2 empirical, 15 model-based studies) were eligible and included in this review. Both empirical studies were observational (non-randomised) studies and at high risk of bias, most importantly due to risk of confounding. Risk of bias of model-based studies was considered low for 12 out of 15 studies. Most studies demonstrated beneficial effects of CTAs on R, total number of infections and mortality rate. No studies assessed effect on hospitalisation. Effect size was dependent on model parameters values used, but in general, a beneficial effect was observed at CTA adoption rates of 20% or higher.

CONCLUSIONS

CTAs have the potential to be effective in reducing SARS-CoV-2 related epidemiological and clinical outcomes, though effect size depends on other model parameters (eg, proportion of asymptomatic individuals, or testing delays), and interventions after CTA notification. Methodologically sound comparative empirical studies on effectiveness of CTAs are required to confirm findings from model-based studies.

Estimating regional prevalence of chronic hepatitis C with a capture-recapture analysis

Background

The hepatitis C virus (HCV) infection is a candidate disease for micro-elimination. Accurate baseline HCV prevalence estimation is essential to monitor progress to micro-elimination but can be methodologically challenging in low-endemic regions like the Netherlands due to lack of disaggregated data by age or risk-groups on the number of chronic HCV patients (i.e. HCV RNA positive). This study estimates the number of patients that has had a chronic HCV infection (ever-chronic) in the Utrecht region of the Netherlands.

Methods

In the Utrecht province in the Netherlands, positive HCV tests from the period 2001–2015 from one diagnostic center and four hospital laboratories were collected. A two-source capture-recapture method was used to analyze the overlap between the two registries (with 92% HCV RNA and 8% HCV immunoblot confirmed infections) to obtain the number of ever-chronic HCV infections in the Utrecht region. The Utrecht region was defined as an area with a 25 km radius from the Utrecht city center. The current viremic HCV prevalence was calculated by taking into account the proportion of cured and deceased HCV patients from a local HCV retrieval (REACH) project.

Results

The estimated number of ever-chronic HCV patients was 1245 (95% CI 1164–1326) and would indicate a prevalence of 0.10 (95% CI 0.09–0.10) in the Utrecht region. This is 30% (95% CI 21–38%) more than the number of known HCV patients in the records. The ever-chronic HCV prevalence was highest in the 1960–1969 age cohort (0.16; 95% CI 0.14–0.18). Since 50% of the HCV patients were cured or deceased in the REACH-project, the number of current viremic HCV patients was estimated at 623 individuals in the Utrecht region (prevalence 0.05%).

Conclusion

The results of this study suggest a low ever-chronic and current HCV prevalence in the Utrecht area in the Netherlands, but other studies need to confirm this.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-06324-z.

Modelling the impact of tailored behavioural interventions on chlamydia transmission

Behavioural interventions tailored to psychological characteristics of an individual can effectively achieve risk-reducing behaviour. The impact of tailored interventions on population-level chlamydia prevalence is unknown. We aimed to assess the impact on overall chlamydia prevalence five years after the introduction of an intervention aimed at increasing self-efficacy, social norms, attitudes and intentions towards condom use (i.e., condom intervention), and an intervention aimed at increasing health goals and decreasing impulsiveness (i.e., impulsiveness intervention). A pair model, informed by longitudinal psychological and behavioural data of young heterosexuals visiting sexual health centers, with susceptible-infected-susceptible structure was developed. The intervention effect was defined as an increased proportion of each subgroup moving to the desired subgroup (i.e., lower risk subgroup). Interventions tailored to subgroup-specific characteristics, assuming differential intervention effects in each subgroup, more effectively reduced overall chlamydia prevalence compared to non-tailored interventions. The most effective intervention was the tailored condom intervention, which was assumed to result in a relative reduction in chlamydia prevalence of 18% versus 12% in the non-tailored scenario. Thus, it is important to assess multiple psychological and behavioural characteristics of individuals. Tailored interventions may be more successful in achieving risk-reducing behaviour, and consequently, reduce chlamydia prevalence more effectively.

Applications and Recruitment Performance of Web-Based Respondent-Driven Sampling: Scoping Review

Background

Web-based respondent-driven sampling is a novel sampling method for the recruitment of participants for generating population estimates, studying social network characteristics, and delivering health interventions. However, the application, barriers and facilitators, and recruitment performance of web-based respondent-driven sampling have not yet been systematically investigated.

Objective

Our objectives were to provide an overview of published research using web-based respondent-driven sampling and to investigate factors related to the recruitment performance of web-based respondent-driven sampling.

Methods

We conducted a scoping review on web-based respondent-driven sampling studies published between 2000 and 2019. We used the process evaluation of complex interventions framework to gain insights into how web-based respondent-driven sampling was implemented, what mechanisms of impact drove recruitment, what the role of context was in the study, and how these components together influenced the recruitment performance of web-based respondent-driven sampling.

Results

We included 18 studies from 8 countries (high- and low-middle income countries), in which web-based respondent-driven sampling was used for making population estimates (n=12), studying social network characteristics (n=3), and delivering health-related interventions (n=3). Studies used web-based respondent-driven sampling to recruit between 19 and 3448 participants from a variety of target populations. Studies differed greatly in the number of seeds recruited, the proportion of successfully recruiting participants, the number of recruitment waves, the type of incentives offered to participants, and the duration of data collection. Studies that recruited relatively more seeds, through online platforms, and with less rigorous selection procedures reported relatively low percentages of successfully recruiting seeds. Studies that did not offer at least one guaranteed material incentive reported relatively fewer waves and lower percentages of successfully recruiting participants. The time of data collection was shortest in studies with university students.

Conclusions

Web-based respondent-driven sampling can be successfully applied to recruit individuals for making population estimates, studying social network characteristics, and delivering health interventions. In general, seed and peer recruitment may be enhanced by rigorously selecting and motivating seeds, offering at least one guaranteed material incentive, and facilitating adequate recruitment options regarding the target population’s online connectedness and communication behavior. Potential trade-offs should be taken into account when implementing web-based respondent-driven sampling, such as having less opportunities to implement rigorous seed selection procedures when recruiting many seeds, as well as issues around online rather than physical participation, such as the risk of cheaters participating repeatedly.

Prediction of human active mobility in rural areas: development and validity tests of three different approaches

BACKGROUND/AIM

Active mobility may play a relevant role in the assessment of environmental exposures (e.g. traffic-related air pollution, livestock emissions), but data about actual mobility patterns are work intensive to collect, especially in large study populations, therefore estimation methods for active mobility may be relevant for exposure assessment in different types of studies. We previously collected mobility patterns in a group of 941 participants in a rural setting in the Netherlands, using week-long GPS tracking. We had information regarding personal characteristics, self-reported data regarding weekly mobility patterns and spatial characteristics. The goal of this study was to develop versatile estimates of active mobility, test their accuracy using GPS measurements and explore the implications for exposure assessment studies.

METHODS

We estimated hours/week spent on active mobility based on personal characteristics (e.g. age, sex, pre-existing conditions), self-reported data (e.g. hours spent commuting per bike) or spatial predictors such as home and work address. Estimated hours/week spent on active mobility were compared with GPS measured hours/week, using linear regression and kappa statistics.

RESULTS

Estimated and measured hours/week spent on active mobility had low correspondence, even the best predicting estimation method based on self-reported data, resulted in a R² of 0.09 and Cohen's kappa of 0.07. A visual check indicated that, although predicted routes to work appeared to match GPS measured tracks, only a small proportion of active mobility was captured in this way, thus resulting in a low validity of overall predicted active mobility.

CONCLUSIONS

We were unable to develop a method that could accurately estimate active mobility, the best performing method was based on detailed self-reported information but still resulted in low correspondence. For future studies aiming to evaluate the contribution of home-work traffic to exposure, applying spatial predictors may be appropriate. Measurements still represent the best possible tool to evaluate mobility patterns.

The impact of STI test results and face-to-face consultations on subsequent behavior and psychological characteristics

Sexually transmitted infection (STI) testing without face-to-face counselling is increasingly offered at sexual health centers (SHC), and ordering self-sampling tests online is becoming more popular. However, the impact of testing without counselling on behavior is unknown. We examine the impact of STI testing with and without consultation and the combined effect of a positive test result and treatment consultation, on behavioral and psychological characteristics over time. Data from a longitudinal study among heterosexual SHC visitors aged 18-24 years was used. The impact of a test consultation (participants who tested chlamydia negative with vs. without consultation) and treatment consultation/positive test result (participants who tested chlamydia positive vs. negative), was assessed by comparing behavioral and psychological characteristics before testing (baseline), and at three-week and six-month follow-up, using generalized estimating equation models. Changes after testing were similar between participants who tested chlamydia negative with and without test consultation, namely decreased risk perception, shame, number of partners, and increased knowledge. However, participants who tested chlamydia positive reported stronger increases in health goals and intentions towards condom use, and stronger decreases in the number of partners and stigma, compared to participants who tested negative. Furthermore, condom use increased in chlamydia positive, and decreased in chlamydia negative participants. A treatment consultation/positive test result had a risk-reducing impact on behavioral and psychological characteristics, whereas the impact of a test consultation was limited. Since the majority of young heterosexuals test chlamydia negative, alternative interventions (e.g., online) achieving risk-reducing behavior change targeted to individuals who tested negative are needed.

Hepatitis B prevention: Can we learn from the response to HIV/AIDS?

Mirjam Kretzschmar and Marianne van der Sande discuss the accompanying research study by Anna McNaughton and colleagues on strategies to reduce the burden of hepatitis B in African countries.

Clustering of chronic hepatitis B screening intentions in social networks of Moroccan immigrants in the Netherlands

Background

Early detection, identification, and treatment of chronic hepatitis B through screening is vital for those at increased risk, e.g. born in hepatitis B endemic countries. In the Netherlands, Moroccan immigrants show low participation rates in health-related screening programmes. Since social networks influence health behaviour, we investigated whether similar screening intentions for chronic hepatitis B cluster within social networks of Moroccan immigrants.

Methods

We used respondent-driven sampling (RDS) where each participant (“recruiter”) was asked to complete a questionnaire and to recruit three Moroccans (“recruitees”) from their social network. Logistic regression analyses were used to analyse whether the recruiters’ intention to request a screening test was similar to the intention of their recruitees.

Results

We sampled 354 recruiter-recruitee pairs: for 154 pairs both participants had a positive screening intention, for 68 pairs both had a negative screening intention, and the remaining 132 pairs had a discordant intention to request a screening test. A tie between a recruiter and recruitee was associated with having the same screening intention, after correction for sociodemographic variables (OR 1.70 [1.15–2.51]).

Conclusions

The findings of our pilot study show clustering of screening intention among individuals in the same network. This provides opportunities for social network interventions to encourage participation in hepatitis B screening initiatives.

Double trouble: modelling the impact of low risk perception and high-risk sexual behaviour on chlamydia transmission

Risk perception plays an important role in testing behaviour for sexually transmitted infections, but is rarely included in mathematical models exploring the impact of testing. We explored the impact of incorporating sexual behaviour (SB), risk perception (RP) and differential testing uptake in SB-RP groups on prevalence, using chlamydia as an example. We developed a pair model with a susceptible-infected-susceptible structure representing heterosexuals aged 16-26 years. The effect of testing on chlamydia prevalence was compared between a model with only SB (SB model) and a model with SB and RP (SB-RP model). In the SB-RP model, a scenario without differential testing uptake in SB-RP groups was compared to scenarios with differential testing uptake in SB-RP groups. Introducing testing into the SB-RP model resulted in a slightly smaller reduction in chlamydia prevalence (-38.0%) as compared to the SB model (-40.4%). In the SB-RP model, the scenario without differential testing uptake in SB-RP groups overestimated the reduction in chlamydia prevalence (with 4.8%), especially in the group with high SB and low RP (19.8%). We conclude that mathematical models incorporating RP and differential testing uptake in SB-RP groups improve the impact assessment of testing and treatment on chlamydia prevalence.

A Multidimensional Approach to Assessing Infectious Disease Risk: Identifying Risk Classes Based on Psychological Characteristics

Prevention of infectious diseases depends on health-related behavior, which is often influenced by psychological characteristics. However, few studies assessing health-related behavior have examined psychological characteristics to identify risk groups, and this multidimensional approach might improve disease risk assessment. We aimed to characterize subgroups based on psychological characteristics and examine their influence on behavior and disease risk, using chlamydia as a case study. Selected participants (heterosexuals aged 18–24 years and females aged 18–24 years who had sex with both men and women) in a Dutch longitudinal cohort study (the Mathematical Models Incorporating Psychological Determinants: Control of Chlamydia Transmission (iMPaCT) Study) filled out a questionnaire and were tested for chlamydia (2016–2017). Latent class analysis was performed to identify risk classes using psychological predictors of chlamydia diagnosis. Two classes were identified: class 1 (n = 488; 9% chlamydia diagnosis) and class 2 (n = 325; 13% chlamydia diagnosis). The proportion of participants with high shame, high impulsiveness, and lower perceived importance of health was higher in class 2 than in class 1. Furthermore, persons in class 2 were more likely to be male and to report condomless sex compared with class 1, but the number of recent partners was comparable. Thus, risk classes might be distinguished from each other by psychological characteristics beyond sexual behavior. Therefore, the impact of the same intervention could differ, and tailoring interventions based on psychological characteristics might be necessary to reduce chlamydia prevalence most effectively.

Who drops out and when? Predictors of non-response and loss to follow-up in a longitudinal cohort study among STI clinic visitors

Introduction

Response rates in health research are declining, and low response rates could result in biased outcomes when population characteristics of participants systematically differ from the non-respondents. Few studies have examined key factors of non-response beyond demographic characteristics, such as behavioral and psychological factors. The aim of the current study was to identify predictors of non-response and loss to follow-up in a longitudinal sexual health study.

Materials and methods

A longitudinal cohort study (iMPaCT) was conducted from November 2016 to July 2018 among heterosexual STI clinic visitors aged 18–24 years. At four different time points in one year, data was collected on sexual behavior, psychological determinants and chlamydia infections. The national STI surveillance database provided data on demographic, behavioral and sexual health-related characteristics for non-respondents. Predictors of non-response at baseline and of loss to follow-up were identified using multivariable logistic regression analyses.

Results

In total, 13,658 STI clinic visitors were eligible to participate, of which 1,063 (8%) participated. Male gender, low/medium education level, young age (≤ 20 years) and having a non-Dutch migration background were significant predictors of non-response at baseline. Furthermore, non-respondents at baseline were more likely to report STI-related symptoms, to have been notified by a partner, to have had condomless sex, and to have had ≤ 2 partners in the past six months, compared to participants. Psychological predictors of loss to follow-up differed between STI clinic regions, but low perceived importance of health at baseline was associated with loss to follow-up in all regions. The baseline chlamydia positivity rate was significantly higher in the non-respondents (17%) compared to the participants (14%), but was not a predictor of loss to follow-up.

Discussion

Targeted recruitment aimed at underrepresented groups in the population based on demographic, behavioral and psychological characteristics, might be necessary to decrease loss to follow-up, and to prevent non-response bias in health research.

A stochastic simulation model to study respondent-driven recruitment

Respondent-driven detection is a chain recruitment method used to sample contact persons of infected persons in order to enhance case finding. It starts with initial individuals, so-called seeds, who are invited for participation. Afterwards, seeds receive a fixed number of coupons to invite individuals with whom they had contact during a specific time period. Recruitees are then asked to do the same, resulting in successive waves of contact persons who are connected in one recruitment tree. However, often the majority of participants fail to invite others, or invitees do not accept an invitation, and recruitment stops after several waves. A mathematical model can help to analyse how various factors influence peer recruitment and to understand under which circumstances sustainable recruitment is possible. We implemented a stochastic simulation model, where parameters were suggested by empirical data from an online survey, to determine the thresholds for obtaining large recruitment trees and the number of waves needed to reach a steady state in the sample composition for individual characteristics. We also examined the relationship between mean and variance of the number of invitations sent out by participants and the probability of obtaining a large recruitment tree. Our main finding is that a situation where participants send out any number of coupons between one and the maximum number is more effective in reaching large recruitment trees, compared to a situation where the majority of participants does not send out any invitations and a smaller group sends out the maximum number of invitations. The presented model is a helpful tool that can assist public health professionals in preparing research and contact tracing using online respondent-driven detection. In particular, it can provide information on the required minimum number of successfully sent invitations to reach large recruitment trees, a certain sample composition or certain number of waves.

Study protocol of the iMPaCT project: a longitudinal cohort study assessing psychological determinants, sexual behaviour and chlamydia (re)infections in heterosexual STI clinic visitors

Background

Chlamydia trachomatis (chlamydia), the most commonly reported sexually transmitted infection (STI) in the Netherlands, can lead to severe reproductive complications. Reasons for the sustained chlamydia prevalence in young individuals, even in countries with chlamydia screening programs, might be the asymptomatic nature of chlamydia infections, and high reinfection rates after treatment. When individuals are unaware of their infection, preventive behaviour or health-care seeking behaviour mostly depends on psychological determinants, such as risk perception. Furthermore, behaviour change after a diagnosis might be vital to reduce reinfection rates. This makes the incorporation of psychological determinants and behaviour change in mathematical models estimating the impact of interventions on chlamydia transmission especially important. Therefore, quantitative real-life data to inform these models is needed.

Methods

A longitudinal cohort study will be conducted to explore the link between psychological and behavioural determinants and chlamydia (re)infection among heterosexual STI clinic visitors aged 18–24 years. Participants will be recruited at the STI clinics of the public health services of Amsterdam, Hollands Noorden, Kennemerland, and Twente. Participants are enrolled for a year, and questionnaires are administrated at four time points: baseline (before an STI consultation), three-week, six-month and at one-year follow-up. To be able to link psychological and behavioural determinants to (re)infections, participants will be tested for chlamydia at enrolment and at six-month follow-up. Data from the longitudinal cohort study will be used to develop mathematical models for curable STI incorporating these determinants to be able to better estimate the impact of interventions.

Discussion

This study will provide insights into the link between psychological and behavioural determinants, including short-term and long-term changes after diagnosis, and chlamydia (re)infections. Our mathematical model, informed by data from the longitudinal cohort study, will be able to estimate the impact of interventions on chlamydia prevalence, and identify and prioritise successful interventions for the future. These interventions could be implemented at STI clinics tailored to psychological and behavioural characteristics of individuals.

Trial registration

Dutch Trial Register NTR-6307. Retrospectively registered 11-nov-2016.

A systematic knowledge synthesis on the spatial dimensions of Q fever epidemics

From 2007 through 2010, the Netherlands experienced the largest Q fever epidemic ever reported. This study integrates the outcomes of a multidisciplinary research programme on spatial airborne transmission of Coxiella burnetii and reflects these outcomes in relation to other scientific Q fever studies worldwide. We have identified lessons learned and remaining knowledge gaps. This synthesis was structured according to the four steps of quantitative microbial risk assessment (QMRA): (a) Rapid source identification was improved by newly developed techniques using mathematical disease modelling; (b) source characterization efforts improved knowledge but did not provide accurate C. burnetii emission patterns; (c) ambient air sampling, dispersion and spatial modelling promoted exposure assessment; and (d) risk characterization was enabled by applying refined dose–response analyses. The results may support proper and timely risk assessment and risk management during future outbreaks, provided that accurate and structured data are available and exchanged readily between responsible actors.

Social networks in relation to self-reported symptomatic infections in individuals aged 40-75 - the Maastricht study

Background

Most infections are spread through social networks (detrimental effect). However, social networks may also lower infection acquisition (beneficial effect). This study aimed to examine associations between social network parameters and prevalence of self-reported upper and lower respiratory, gastrointestinal and urinary tract infections in a population aged 40–75.

Methods

In this population-based cross-sectional cohort study (N = 3004, mean age 60.0 ± 8.2 years, 49% women), infections within the past two months were assessed by self-administered questionnaires. Social network parameters were assessed using a name generator questionnaire. To examine the associated beneficial and detrimental network parameters, univariable and multivariable logistic regression was used.

Results

Participants reported an average of 10 people (alters) with whom they had 231 contacts per half year. Prevalences were 31.1% for upper respiratory, 11.5% for lower respiratory, 12.5% for gastrointestinal, and 5.7% for urinary tract infections. Larger network size, and a higher percentage of alters that were friends or acquaintances were associated with higher odds of upper respiratory, lower respiratory and/or gastrointestinal infections (detrimental). A higher total number of contacts, higher percentages of alters of the same age, and higher percentages of family members/acquaintances were associated with lower odds of upper respiratory, lower respiratory and/or gastrointestinal infections (beneficial).

Conclusion

We identified both detrimental and beneficial associations of social network parameters with the prevalence of infections. Our findings can be used to complement mathematical models on infection spread, as well as to optimize current infectious disease control.

Electronic supplementary material

The online version of this article (10.1186/s12879-018-3197-3) contains supplementary material, which is available to authorized users.

Pneumonia risk of people living close to goat and poultry farms - Taking GPS derived mobility patterns into account

We previously observed an increased incidence of pneumonia in persons living near goat and poultry farms, using animal presence around the home to define exposure. However, it is unclear to what extent individual mobility and time spent outdoors close to home contributes to this increased risk. Therefore, the aim of the current study was to investigate the role of mobility patterns and time spent outdoors in the vicinity of goat or poultry farms in relation to pneumonia risk. In a rural Dutch cohort, 941 members logged their mobility using GPS trackers for 7 days. Pneumonia was diagnosed in 83 subjects (participants reported that pneumonia had been diagnosed by a medical doctor, or recorded in EMR from general practitioners, 2011-2014). We used logistic regression to evaluate pneumonia-risk by presence of goat farms within 500 and 1000 m around the home and around GPS-tracks (only non-motorised mobility), also we evaluated whether more time spent outdoors increased pneumonia-risks. We observed a clearly increased risk of pneumonia among people living in close proximity to goat farms, ORs increased with closer distances of homes to farms (500 m: 6.2 (95% CI 2.2-16.5) 1000 m: 2.5 (1.4-4.3)) The risk increased for individuals who spent more time outdoors close to home, but only if homes were close to goat farms (within 500 m and often outdoors: 12.7 (3.6-45.4) less often: 2.0 (0.3-9.2), no goat farms and often outdoors: 1.0 (0.6-1.6)). For poultry we found no increased risks. Pneumonia-risks increased when people lived near goat farms, especially when they spent more time outdoors, mobility does not seem to add to these risks.

Cost-effectiveness of human papillomavirus vaccination in Germany

BACKGROUND

The aim of this study was to assess the cost-effectiveness of human papillomavirus (HPV) vaccination in addition to the current cervical cancer screening programme in Germany using a dynamic transmission model.

METHODS

Based on a mathematical model simulating the transmission dynamics and the natural history of HPV infection and associated diseases (cervical intraepithelial neoplasia, cervical cancer, and genital warts), we estimated the epidemiological and economic consequences of HPV vaccination with both the quadrivalent and bivalent vaccines. In our base case analysis, we assessed the cost-effectiveness of vaccinating 12-year-old girls with a 3-dose schedule. In sensitivity analysis, we also evaluated the use of a 2-dose schedule and assessed the impact of vaccinating boys.

RESULTS

From a health care payer perspective, incremental cost-effectiveness ratios (ICERs) of a 3-dose schedule were €34,249 per quality-adjusted life year (QALY) for the bivalent and €14,711 per QALY for the quadrivalent vaccine. Inclusion of indirect costs decreased ICERs by up to 40%. When adopting a health care payer perspective, ICERs of a 2-dose approach decreased to €19,450 per QALY for the bivalent and to €3645 per QALY for the quadrivalent vaccine. From a societal perspective, a 2-dose approach using the quadrivalent vaccine was a cost-saving strategy while using the bivalent vaccine resulted in an ICER of €13,248 per QALY. Irrespective of the perspective adopted, additional vaccination of boys resulted in ICERs exceeding €50,000 per QALY, except for scenarios with low coverage (20%) in girls.

CONCLUSIONS

Our model results suggest that routine HPV vaccination of 12-year-old girls with three doses is likely to be cost-effective in Germany. Due to the additional impact on genital warts, the quadrivalent vaccine appeared to be more cost-effective than the bivalent vaccine. A 2-dose schedule of the quadrivalent vaccine might even lead to cost savings when adopting a societal perspective. The cost-effectiveness of additional vaccination of boys was highly dependent on the coverage in girls.

Mobility assessment of a rural population in the Netherlands using GPS measurements

Background

The home address is a common spatial proxy for exposure assessment in epidemiological studies but mobility may introduce exposure misclassification. Mobility can be assessed using self-reports or objectively measured using GPS logging but self-reports may not assess the same information as measured mobility. We aimed to assess mobility patterns of a rural population in the Netherlands using GPS measurements and self-reports and to compare GPS measured to self-reported data, and to evaluate correlates of differences in mobility patterns.

Method

In total 870 participants filled in a questionnaire regarding their transport modes and carried a GPS-logger for 7 consecutive days. Transport modes were assigned to GPS-tracks based on speed patterns. Correlates of measured mobility data were evaluated using multiple linear regression. We calculated walking, biking and motorised transport durations based on GPS and self-reported data and compared outcomes. We used Cohen’s kappa analyses to compare categorised self-reported and GPS measured data for time spent outdoors.

Results

Self-reported time spent walking and biking was strongly overestimated when compared to GPS measurements. Participants estimated their time spent in motorised transport accurately. Several variables were associated with differences in mobility patterns, we found for instance that obese people (BMI > 30 kg/m²) spent less time in non-motorised transport (GMR 0.69–0.74) and people with COPD tended to travel longer distances from home in motorised transport (GMR 1.42–1.51).

Conclusions

If time spent walking outdoors and biking is relevant for the exposure to environmental factors, then relying on the home address as a proxy for exposure location may introduce misclassification. In addition, this misclassification is potentially differential, and specific groups of people will show stronger misclassification of exposure than others. Performing GPS measurements and identifying explanatory factors of mobility patterns may assist in regression calibration of self-reports in other studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12942-017-0103-y) contains supplementary material, which is available to authorized users.

Use of a Dose-Response Model to Study Temporal Trends in Spatial Exposure to Coxiella burnetii: Analysis of a Multiyear Outbreak of Q Fever

The Netherlands underwent a large Q fever outbreak between 2007 and 2009. In this paper, we study spatial and temporal Coxiella burnetii exposure trends during this large outbreak as well as validate outcomes against other published studies and provide evidence to support hypotheses on the causes of the outbreak. To achieve this, we develop a framework using a dose-response model to translate acute Q fever case incidence into exposure estimates. More specifically, we incorporate a geostatistical model that accounts for spatial and temporal correlation of exposure estimates from a human Q fever dose-response model to quantify exposure trends during the outbreak. The 2051 cases, with the corresponding age, gender and residential addresses, reside in the region with the highest attack rates during the outbreak in the Netherlands between 2006 and 2009. We conclude that the multiyear outbreak in the Netherlands is caused by sustained release of infectious bacteria from the same sources, which suggests that earlier implementation of interventions may have prevented many of the cases. The model predicts the risk of infection and acute symptomatic Q fever from multiple exposure sources during a multiple-year outbreak providing a robust, evidence-based methodology to support decision-making and intervention design.

Tracking social contact networks with online respondent-driven detection: who recruits whom?

Background

Transmission of respiratory pathogens in a population depends on the contact network patterns of individuals. To accurately understand and explain epidemic behaviour information on contact networks is required, but only limited empirical data is available. Online respondent-driven detection can provide relevant epidemiological data on numbers of contact persons and dynamics of contacts between pairs of individuals. We aimed to analyse contact networks with respect to sociodemographic and geographical characteristics, vaccine-induced immunity and self-reported symptoms.

Methods

In 2014, volunteers from two large participatory surveillance panels in the Netherlands and Belgium were invited for a survey. Participants were asked to record numbers of contacts at different locations and self-reported influenza-like-illness symptoms, and to invite 4 individuals they had met face to face in the preceding 2 weeks. We calculated correlations between linked individuals to investigate mixing patterns.

Results

In total 1560 individuals completed the survey who reported in total 30591 contact persons; 488 recruiter-recruit pairs were analysed. Recruitment was assortative by age, education, household size, influenza vaccination status and sentiments, indicating that participants tended to recruit contact persons similar to themselves. We also found assortative recruitment by symptoms, reaffirming our objective of sampling contact persons whom a participant may infect or by whom a participant may get infected in case of an outbreak. Recruitment was random by sex and numbers of contact persons. Relationships between pairs were influenced by the spatial distribution of peer recruitment.

Conclusions

Although complex mechanisms influence online peer recruitment, the observed statistical relationships reflected the observed contact network patterns in the general population relevant for the transmission of respiratory pathogens. This provides useful and innovative input for predictive epidemic models relying on network information.

Electronic supplementary material

The online version of this article (doi:10.1186/s12879-015-1250-z) contains supplementary material, which is available to authorized users.

Enhancing Syndromic Surveillance With Online Respondent-Driven Detection

OBJECTIVES

We investigated the feasibility of combining an online chain recruitment method (respondent-driven detection) and participatory surveillance panels to collect previously undetected information on infectious diseases via social networks of participants.

METHODS

In 2014, volunteers from 2 large panels in the Netherlands were invited to complete a survey focusing on symptoms of upper respiratory tract infections and to invite 4 individuals they had met in the preceding 2 weeks to take part in the study. We compared sociodemographic characteristics among panel participants, individuals who volunteered for our survey, and individuals recruited via respondent-driven detection.

RESULTS

Starting from 1015 panel members, the survey spread through all provinces of the Netherlands and all age groups in 83 days. A total of 433 individuals completed the survey via peer recruitment. Participants who reported symptoms were 6.1% (95% confidence interval = 5.4, 6.9) more likely to invite contact persons than were participants who did not report symptoms. Participants with symptoms invited more symptomatic recruits to take part than did participants without symptoms.

CONCLUSIONS

Our findings suggest that online respondent-driven detection can enhance identification of symptomatic patients by making use of individuals' local social networks.

Hepatitis C virus treatment as prevention among injecting drug users: who should we cure first?

BACKGROUND AND AIMS

Treatment of injecting drug users (IDU) for hepatitis C virus (HCV) infection may prevent onward transmission. Treating individuals who often share injecting equipment is most likely to prevent new infections. However, these high-risk IDU are also more likely to become re-infected than low-risk IDU. We investigated to which group treatment is best targeted.

DESIGN

We modelled the expected benefits per treatment of one chronically HCV-infected IDU in a population of low- and high-risk IDU. The benefits of treating one low- or one high-risk IDU were compared.

MEASUREMENTS

Benefits included the probability for the treated IDU to become and remain uninfected, as well as the expected number of prevented infections to others (i.e. we quantified the total expected decrease in chronic infections).

FINDINGS

We found a threshold in HCV-RNA prevalence above which treating low-risk IDU, and below which treating high-risk IDU, resulted in the greatest benefits. This threshold was at 50% of exchanged syringes being HCV contaminated. When 42% of IDU engaged in high-risk behaviour (borrowing and lending out syringes 7.3 times more frequently than low-risk IDU), the corresponding threshold of HCV-RNA prevalence among IDU was at 32%. Larger-risk heterogeneity led to a lower corresponding threshold among IDU. A combination of HCV treatment and 50% risk reduction was best directed at high-risk IDU for prevalence among syringes up to 59%. The threshold was marginally sensitive to changes in disease and treatment variables.

CONCLUSIONS

When more than half of all exchanged syringes in a population of injecting drug users (IDU) are contaminated by hepatitis C virus, it is most efficient to treat low-risk IDU first. Below this threshold, it is most efficient to treat high-risk IDU first.

Exposure to low doses of Coxiella burnetii caused high illness attack rates: Insights from combining human challenge and outbreak data

BACKGROUND

As a major zoonotic pathogen, characterization of the infectivity and pathogenicity of Coxiella burnetii is essential to understand Q-fever epidemiology.

OBJECTIVES

We want to extend a recently published human dose response model based on experimental challenge of young adult males to include other age groups and both genders. Additionally, we can estimate the spatial distribution of exposure based on observed outbreak data.

METHODS

Dose response assessment based on human challenge, is extended by including outbreak data, using location of cases as a proxy for exposure. This allows estimation of the influence of age and gender on the probability of developing symptoms of acute respiratory illness.

RESULTS

In an outbreak in Switzerland, in 1983, exposure to C. burnetii was shown to depend strongly on distance from the source. The susceptibility of males to develop Q-fever decreases with age, while in females, middle-aged women appear to have the lowest risk.

CONCLUSIONS

The published dose response model for Q-fever, based on experimental challenge of a small group of human volunteers, has been updated with data from a well studied outbreak. Infectivity estimates remain high, and even low doses (of 10 or fewer organisms) cause a high risk of illness.

A two-phase within-host model for immune response and its application to serological profiles of pertussis

We present a simple phenomenological within-host model describing both the interaction between a pathogen and the immune system and the waning of immunity after clearing of the pathogen. We implement the model into a Bayesian hierarchical framework to estimate its parameters for pertussis using Markov chain Monte Carlo methods. We show that the model captures some essential features of the kinetics of titers of IgG against pertussis toxin. We identify a threshold antibody level that separates a large increase in antibody level upon infection from a small increase and accordingly might be interpreted as a threshold separating clinical from subclinical infections. We contrast predictions of the model with observations reported in the literature and based on independent data and find a remarkable correspondence.

Measuring underreporting and under-ascertainment in infectious disease datasets: a comparison of methods

BACKGROUND

Efficient and reliable surveillance and notification systems are vital for monitoring public health and disease outbreaks. However, most surveillance and notification systems are affected by a degree of underestimation (UE) and therefore uncertainty surrounds the 'true' incidence of disease affecting morbidity and mortality rates. Surveillance systems fail to capture cases at two distinct levels of the surveillance pyramid: from the community since not all cases seek healthcare (under-ascertainment), and at the healthcare-level, representing a failure to adequately report symptomatic cases that have sought medical advice (underreporting). There are several methods to estimate the extent of under-ascertainment and underreporting.

METHODS

Within the context of the ECDC-funded Burden of Communicable Diseases in Europe (BCoDE)-project, an extensive literature review was conducted to identify studies that estimate ascertainment or reporting rates for salmonellosis and campylobacteriosis in European Union Member States (MS) plus European Free Trade Area (EFTA) countries Iceland, Norway and Switzerland and four other OECD countries (USA, Canada, Australia and Japan). Multiplication factors (MFs), a measure of the magnitude of underestimation, were taken directly from the literature or derived (where the proportion of underestimated, under-ascertained, or underreported cases was known) and compared for the two pathogens.

RESULTS

MFs varied between and within diseases and countries, representing a need to carefully select the most appropriate MFs and methods for calculating them. The most appropriate MFs are often disease-, country-, age-, and sex-specific.

CONCLUSIONS

When routine data are used to make decisions on resource allocation or to estimate epidemiological parameters in populations, it becomes important to understand when, where and to what extent these data represent the true picture of disease, and in some instances (such as priority setting) it is necessary to adjust for underestimation. MFs can be used to adjust notification and surveillance data to provide more realistic estimates of incidence.

Online respondent-driven sampling for studying contact patterns relevant for the spread of close-contact pathogens: a pilot study in Thailand

Background

Information on social interactions is needed to understand the spread of airborne infections through a population. Previous studies mostly collected egocentric information of independent respondents with self-reported information about contacts. Respondent-driven sampling (RDS) is a sampling technique allowing respondents to recruit contacts from their social network. We explored the feasibility of webRDS for studying contact patterns relevant for the spread of respiratory pathogens.

Materials and Methods

We developed a webRDS system for facilitating and tracking recruitment by Facebook and email. One-day diary surveys were conducted by applying webRDS among a convenience sample of Thai students. Students were asked to record numbers of contacts at different settings and self-reported influenza-like-illness symptoms, and to recruit four contacts whom they had met in the previous week. Contacts were asked to do the same to create a network tree of socially connected individuals. Correlations between linked individuals were analysed to investigate assortativity within networks.

Results

We reached up to 6 waves of contacts of initial respondents, using only non-material incentives. Forty-four (23.0%) of the initially approached students recruited one or more contacts. In total 257 persons participated, of which 168 (65.4%) were recruited by others. Facebook was the most popular recruitment option (45.1%). Strong assortative mixing was seen by age, gender and education, indicating a tendency of respondents to connect to contacts with similar characteristics. Random mixing was seen by reported number of daily contacts.

Conclusions

Despite methodological challenges (e.g. clustering among respondents and their contacts), applying RDS provides new insights in mixing patterns relevant for close-contact infections in real-world networks. Such information increases our knowledge of the transmission of respiratory infections within populations and can be used to improve existing modelling approaches. It is worthwhile to further develop and explore webRDS for the detection of clusters of respiratory symptoms in social networks.

[Syndromic surveillance: a finger on the pulse of public health]

Syndromic surveillance is a monitoring methodology in which data from disease indicators are collected and interpreted as quickly as possible (in real time) to get an impression of the current morbidity in the population. In this case 'syndrome' means: behavior, signs and symptoms that may be indicative of an infection, without a proven pathogen, or incidents such as an environmental disaster. Syndromic surveillance has gained momentum in response to various international infectious disease threats, including the outbreak of severe acute respiratory syndrome (SARS) in 2003. In several European countries, syndromic surveillance has been used to monitor the impact of outbreaks or natural disasters and the health of visitors of mass events. Following the outbreak of an infectious disease, syndromic surveillance can be reassuring in the absence of an epidemic. Insight into burden of disease can provide guidance in adjusting care capacity to need. Several syndromic surveillance systems and pilot studies have been set up recently in the Netherlands. The costs, benefits and their best application should be evaluated in the near future.

The pathogen- and incidence-based DALY approach: an appropriate [corrected] methodology for estimating the burden of infectious diseases

In 2009, the European Centre for Disease Prevention and Control initiated the ‘Burden of Communicable Diseases in Europe (BCoDE)’ project to generate evidence-based and comparable burden-of-disease estimates of infectious diseases in Europe. The burden-of-disease metric used was the Disability-Adjusted Life Year (DALY), composed of years of life lost due to premature death (YLL) and due to disability (YLD). To better represent infectious diseases, a pathogen-based approach was used linking incident cases to sequelae through outcome trees. Health outcomes were included if an evidence-based causal relationship between infection and outcome was established. Life expectancy and disability weights were taken from the Global Burden of Disease Study and alternative studies. Disease progression parameters were based on literature. Country-specific incidence was based on surveillance data corrected for underestimation. Non-typhoidal Salmonella spp. and Campylobacter spp. were used for illustration. Using the incidence- and pathogen-based DALY approach the total burden for Salmonella spp. and Campylobacter spp. was estimated at 730 DALYs and at 1,780 DALYs per year in the Netherlands (average of 2005–2007). Sequelae accounted for 56% and 82% of the total burden of Salmonella spp. and Campylobacter spp., respectively. The incidence- and pathogen-based DALY methodology allows in the case of infectious diseases a more comprehensive calculation of the disease burden as subsequent sequelae are fully taken into account. Not considering subsequent sequelae would strongly underestimate the burden of infectious diseases. Estimates can be used to support prioritisation and comparison of infectious diseases and other health conditions, both within a country and between countries.

Human dose response relation for airborne exposure to Coxiella burnetii

Background

The recent outbreak of Q fever in the Netherlands between 2007 and 2009 is the largest recorded Q fever outbreak. Exposure to Coxiella burnetii may cause Q fever but the size of the population exposed during the outbreak remained uncertain as little is known of the infectivity of this pathogen. The quantification of the infectiousness and the corresponding response is necessary for assessing the risk to the population.

Methods

A human challenge study was published in the 1950s but this study quantified the dose of C. burnetii in relative units. Data from a concurrent guinea pig challenge study were combined with a recent study in which guinea pigs were challenged with a similar aerosol route to quantify human exposure. Concentration estimates for C. burnetii are made jointly with estimates of the dose response parameters in a hierarchical Bayesian framework.

Results

The dose for 50% infection (InfD50%) in human subjects is 1.18 bacteria (95% credible interval (CI) 0.76-40.2). The dose for 50% illness (IllD50) in challenged humans is 5.58 (95%CI 0.89-89.0) bacteria. The probability of a single viable C. burnetii causing infection in humans is 0.44 (95%CI 0.044-0.59) and for illness 0.12 (95%CI 0.0006-0.55).

Conclusions

To our knowledge this is the first human dose–response model for C. burnetii. The estimated dose response relation demonstrates high infectivity in humans. In many published papers the proportion of infected individuals developing illness is reported to be 40%. Our model shows that the proportion of symptomatic infections may vary with the exposure dose. This implies that presence of these bacteria in the environment, even in small numbers, poses a serious health risk to the population.

Decline in incidence of HIV and hepatitis C virus infection among injecting drug users in Amsterdam; evidence for harm reduction?

AIMS

In Amsterdam, HIV prevalence has nearly halved among injecting drug users (IDU) since 1990. Hepatitis C virus (HCV) prevalence also declined; HIV and HCV incidence dropped to nearly zero. We examined possible explanations for these time trends, among which the implementation of harm reduction measures aimed at reducing the risk behaviour of IDU.

DESIGN

We used individual-based modelling of the spread of HIV and HCV. Information about demographic parameters was obtained from the Amsterdam Cohort Study (ACS) among drug users. The model included changes in inflow of new IDU and death rates over time, the latter dependent on age and time since HIV seroconversion. We considered different scenarios of risk behaviour.

SETTING

IDU in Amsterdam.

MEASUREMENTS

Simulated HIV and HCV incidence and prevalence were compared with ACS data.

FINDINGS

Assuming that harm reduction measures had led to a strong decrease in risk behaviour over time improved the model fit (squared residuals decreased by 30%). However, substantial incidence and HIV prevalence decline were already reproduced by incorporating demographic changes into the model. In particular, lowered disease spread might be a result of depletion of high-risk IDU among those at risk for disease, and a decrease in the number of high-risk individuals in the population due to HIV-related mortality.

CONCLUSIONS

Marked decreases in HIV and HCV in Amsterdam since 1990 could be due partly to harm reduction measures; however, they may also be attributable largely to changes in the IDU population. Future research aimed at quantifying the benefits of interventions should not neglect the impact of natural epidemic progression and demographic changes.

The efficiency of targeted intervention in limiting the spread of HIV and Hepatitis C Virus among injecting drug users

BACKGROUND

Interventions aimed at minimizing the spread of blood borne infections among Injecting Drug Users (IDU) are impeded by limitations in resources. To enhance their efficiency, it may be beneficial to target specific behavioural subpopulations, distinguished by syringe sharing tendencies.

METHODS

We used mathematical modelling to explore the effects of two types of intervention: removal of individuals from the injecting population and risk decrease at group-level (e.g. distribution of syringes). We computed the direct effects of intervention on the probability of obtaining and spreading infection as a function of baseline risk behaviour. Population level effects of (targeted) intervention were explored using a differential equations model, which incorporated two levels of risk.

RESULTS

Within most scenarios of risk distribution considered, HIV could be substantially reduced or eliminated by targeting high risk IDU only. Conversely, higher incidence reductions for HCV were reached in many scenarios when targeting low risk IDU. The potential for preventing infections by removal of uninfected IDU increases with baseline risk, but so does the probability that an IDU is already infected before being reached by intervention. Decreasing risk is likely to only delay rather than prevent infection for IDU borrowing many syringes, especially for a very infectious disease such as HCV.

CONCLUSIONS

The efficiency of intervention on injecting drug users may be much enhanced by targeting specific risk subgroups. However, the optimal targeting policy depends strongly on the infection under consideration.

Effects of population based screening for Chlamydia infections in the Netherlands limited by declining participation rates

Background

A large trial to investigate the effectiveness of population based screening for chlamydia infections was conducted in the Netherlands in 2008–2012. The trial was register based and consisted of four rounds of screening of women and men in the age groups 16–29 years in three regions in the Netherlands. Data were collected on participation rates and positivity rates per round. A modeling study was conducted to project screening effects for various screening strategies into the future.

Methods and Findings

We used a stochastic network simulation model incorporating partnership formation and dissolution, aging and a sexual life course perspective. Trends in baseline rates of chlamydia testing and treatment were used to describe the epidemiological situation before the start of the screening program. Data on participation rates was used to describe screening uptake in rural and urban areas. Simulations were used to project the effectiveness of screening on chlamydia prevalence for a time period of 10 years. In addition, we tested alternative screening strategies, such as including only women, targeting different age groups, and biennial screening. Screening reduced prevalence by about 1% in the first two screening rounds and leveled off after that. Extrapolating observed participation rates into the future indicated very low participation in the long run. Alternative strategies only marginally changed the effectiveness of screening. Higher participation rates as originally foreseen in the program would have succeeded in reducing chlamydia prevalence to very low levels in the long run.

Conclusions

Decreasing participation rates over time profoundly impact the effectiveness of population based screening for chlamydia infections. Using data from several consecutive rounds of screening in a simulation model enabled us to assess the future effectiveness of screening on prevalence. If participation rates cannot be kept at a sufficient level, the effectiveness of screening on prevalence will remain limited.

Estimating the long-term effects of HPV vaccination in Germany

In Germany, vaccination against the most oncogenic HPV types 16/18 is recommended by the Standing Committee on Vaccination (STIKO) for 12-17 year old girls since March 2007. We developed a dynamic mathematical model for the natural history and transmission of HPV infections to estimate the impact of vaccination on incidence and mortality of cervical cancer and its pre-stages, and on anogenital warts. We focused on an extensive model calibration to epidemiologic data for all stages of the natural history model as well as on a detailed implementation of cervical cancer screening modalities in Germany. Our model predicts first a substantial reduction of cervical cancer incidence and mortality over the next 30 years, which is mainly attributable to an increase in screening participation in the 1990s and not to HPV vaccination, followed by a further reduction attributable to vaccination. Over the next 100 years, HPV vaccination will prevent approximately 37% of cervical cancer cases even if vaccination coverage is only 50% (as currently observed in Germany). Consideration of cross-protection results in a further reduction of approximately 7% of all cervical cancer cases for the bivalent and about 5% for the quadrivalent vaccine in our model. Vaccination of boys was only reasonable if moderate to high vaccination coverage in girls was not achieved. Strategies should be implemented in Germany to increase HPV vaccination coverage among girls thereby making better use of the demonstrated benefits of the vaccine.

Effects of an ageing population and the replacement of immune birth cohorts on the burden of hepatitis A in the Netherlands

BACKGROUND

In populations in which the incidence of hepatitis A virus (HAV) infection has declined due to socio-economic improvements, better sanitation and hygiene, and vaccination, birth cohorts who have long-term immunity through exposure early in life are now being replaced by non-immune cohorts, meaning that more cases in the elderly may occur in future. Our goal was to qualitatively investigate the interaction of this cohort effect and demographic change (population ageing) on the estimated disease burden of HAV infection in the Netherlands.

METHODS

We used dynamic MSIR (maternal immunity-susceptible-infectious-recovered) transmission and demographic models to simulate annual HAV incidence over the period 2000-2030, and estimated disease burden using the disability-adjusted life years (DALY) measure and a pre-defined disease progression model. Five scenarios representing different force of infection situations were simulated.

RESULTS

The overall disease burden was projected to decrease over the simulation period in the baseline scenario (310 DALYs in 2000 compared with 67 in 2030). This decreasing trend was absent for the 55+ years age group; 23.5% of all new infections were predicted to occur in the 55+ group in 2030, compared with 5.5% in the 55+ group in 2000.

CONCLUSIONS

In the absence of further public health interventions and under the assumption of a continued steady decline in the force of infection, the HAV disease burden in the Netherlands is predicted to decrease over the coming decades, but with proportionally more of the burden occurring within the increasingly larger segment of the population represented by elderly persons who are no longer naturally immune.

Modeling the transmission risk of emerging infectious diseases through blood transfusion

BACKGROUND

A timely risk assessment is desired to guide decisions on preventive transfusion safety measures during emerging infectious disease (EID) outbreaks. The European Up-Front Risk Assessment Tool (EUFRAT) model was developed to provide quantitative transmission risk estimates of EIDs through blood transfusion.

STUDY DESIGN AND METHODS

The generic model comprises five sequential steps to estimate the infection risks in the blood transfusion chain: 1) the prevalence of infection in the donor population, 2) the risk of obtaining infected donations, 3) infected components, 4) infected blood products, and 5) the risk of transmitting the infection to recipients. The model uses inputs from epidemiologic characteristics of an EID and transfusion practice. The model was applied to data from a recent chikungunya outbreak in Italy.

RESULTS

Based on data from the outbreak peak, an estimated prevalence of 1.07 (95% confidence interval [CI], 0.38-2.03) per 100,000 donors would lead to 0.04 infected donations (95% CI, 0.01-0.10), 0.13 infected blood components, 0.13 infected end products, and 0.0001 severe infections in recipients. This estimated risk can be reduced by increasing the duration of quarantine of the donated blood and becomes zero after 7 or more days of quarantine. The model also estimated the probability of a donor returning from the outbreak area and subsequently donating infected blood in his home country to be 0.30 (95% CI, 0.01-0.65) per 100,000.

CONCLUSION

The model can be used to quantify EID outbreak risks to blood transfusion recipients and the effect of targeted safety interventions and as such support public health decision-making.

Dynamic concurrent partnership networks incorporating demography

We introduce a population model that incorporates From a mathematical point of view we deal with continuous-time Markov chains at the individual level, with the interaction between individuals captured by a global variable describing opportunities for new partnerships. We show that for large time a stationary distribution is attained and we deduce various statistical features of that distribution, with particular attention for concurrency, i.e. the overlap in time of multiple partnerships of one and the same individual. Our ultimate motivation is to model the spread of sexually transmitted infections in the population, for which the present paper serves as a prelude.

Timeliness of contact tracing among flight passengers for influenza A/H1N1 2009

BACKGROUND

During the initial containment phase of influenza A/H1N1 2009, close contacts of cases were traced to provide antiviral prophylaxis within 48 h after exposure and to alert them on signs of disease for early diagnosis and treatment. Passengers seated on the same row, two rows in front or behind a patient infectious for influenza, during a flight of ≥ 4 h were considered close contacts. This study evaluates the timeliness of flight-contact tracing (CT) as performed following national and international CT requests addressed to the Center of Infectious Disease Control (CIb/RIVM), and implemented by the Municipal Health Services of Schiphol Airport.

METHODS

Elapsed days between date of flight arrival and the date passenger lists became available (contact details identified - CI) was used as proxy for timeliness of CT. In a retrospective study, dates of flight arrival, onset of illness, laboratory diagnosis, CT request and identification of contacts details through passenger lists, following CT requests to the RIVM for flights landed at Schiphol Airport were collected and analyzed.

RESULTS

24 requests for CT were identified. Three of these were declined as over 4 days had elapsed since flight arrival. In 17 out of 21 requests, contact details were obtained within 7 days after arrival (81%). The average delay between arrival and CI was 3,9 days (range 2-7), mainly caused by delay in diagnosis of the index patient after arrival (2,6 days). In four flights (19%), contacts were not identified or only after > 7 days. CI involving Dutch airlines was faster than non-Dutch airlines (P < 0,05). Passenger locator cards did not improve timeliness of CI. In only three flights contact details were identified within 2 days after arrival.

CONCLUSION

CT for influenza A/H1N1 2009 among flight passengers was not successful for timely provision of prophylaxis. CT had little additional value for alerting passengers for disease symptoms, as this information already was provided during and after the flight. Public health authorities should take into account patient delays in seeking medical advise and laboratory confirmation in relation to maximum time to provide postexposure prophylaxis when deciding to install contact tracing measures. International standardization of CT guidelines is recommended.

Usefulness of primary care electronic networks to assess the incidence of chlamydia, diagnosed by general practitioners

Background

Chlamydia is the most common curable sexually transmitted infection (STI) in the Netherlands. The majority of chlamydia diagnoses are made by general practitioners (GPs). Baseline data from primary care will facilitate the future evaluation of the ongoing large population-based screening in the Netherlands. The aim of this study was to assess the usefulness of electronic medical records for monitoring the incidence of chlamydia cases diagnosed in primary care in the Netherlands.

Methods

In the electronic records of two regional and two national networks, we identified chlamydia diagnoses by means of ICPC codes (International Classification of Primary Care), laboratory results in free text and the prescription of antibiotics. The year of study was 2007 for the two regional networks and one national network, for the other national network the year of study was 2005. We calculated the incidence of diagnosed chlamydia cases per sex, age group and degree of urbanization.

Results

A large diversity was observed in the way chlamydia episodes were coded in the four different GP networks and how easily information concerning chlamydia diagnoses could be extracted. The overall incidence ranged from 103.2/100,000 to 590.2/100,000. Differences were partly related to differences between patient populations. Nevertheless, we observed similar trends in the incidence of chlamydia diagnoses in all networks and findings were in line with earlier reports.

Conclusions

Electronic patient records, originally intended for individual patient care in general practice, can be an additional source of data for monitoring chlamydia incidence in primary care and can be of use in assessing the future impact of population-based chlamydia screening programs. To increase the usefulness of data we recommend more efforts to standardize registration by (specific) ICPC code and laboratory results across the existing GP networks.

Analysis of timeliness of infectious disease reporting in the Netherlands

Background

Timely reporting of infectious disease cases to public health authorities is essential to effective public health response. To evaluate the timeliness of reporting to the Dutch Municipal Health Services (MHS), we used as quantitative measures the intervals between onset of symptoms and MHS notification, and between laboratory diagnosis and notification with regard to six notifiable diseases.

Methods

We retrieved reporting data from June 2003 to December 2008 from the Dutch national notification system for shigellosis, EHEC/STEC infection, typhoid fever, measles, meningococcal disease, and hepatitis A virus (HAV) infection. For each disease, median intervals between date of onset and MHS notification were calculated and compared with the median incubation period. The median interval between date of laboratory diagnosis and MHS notification was similarly analysed. For the year 2008, we also investigated whether timeliness is improved by MHS agreements with physicians and laboratories that allow direct laboratory reporting. Finally, we investigated whether reports made by post, fax, or e-mail were more timely.

Results

The percentage of infectious diseases reported within one incubation period varied widely, between 0.4% for shigellosis and 90.3% for HAV infection. Not reported within two incubation periods were 97.1% of shigellosis cases, 76.2% of cases of EHEC/STEC infection, 13.3% of meningococcosis cases, 15.7% of measles cases, and 29.7% of typhoid fever cases. A substantial percentage of infectious disease cases was reported more than three days after laboratory diagnosis, varying between 12% for meningococcosis and 42% for shigellosis. MHS which had agreements with physicians and laboratories showed a significantly shorter notification time compared to MHS without such agreements.

Conclusions

Over the study period, many cases of the six notifiable diseases were not reported within two incubation periods, and many were reported more than three days after laboratory diagnosis. An increase in direct laboratory reporting of diagnoses to MHS would improve timeliness, as would the use of fax rather than post or e-mail. Automated reporting systems have to be explored in the Netherlands. Development of standardised and improved measures for timeliness is needed.

High infectivity and pathogenicity of influenza A virus via aerosol and droplet transmission

Influenza virus may be transmitted through the respiratory route by inhalation of an aerosol of non-sedimenting droplets, or by deposition of sedimenting droplets in the upper respiratory tract. Whichever of these is the predominant route for infection with influenza virus has been subject of continuing debate, resulting in detailed studies of aerosol versus droplet exposure. A decisive knowledge gap preventing a satisfying conclusion is absence of a well defined human dose response model for influenza virus. This study uses a hierarchical approach generalizing over twelve human challenge studies collected in a literature search. Distinction is made between aerosol and intranasal inoculation. The results indicate high infectivity via either route, but intranasal inoculation leads to about 20 times lower infectivity than when the virus is delivered in an inhalable aerosol. A scenario study characterizing exposure to airborne virus near a coughing infected person in a room with little ventilation demonstrates that with these dose response models the probabilities of infection by either aerosol or sedimenting droplets are approximately equal. Droplet transmission results in a slightly higher illness risk due to the higher doses involved. Establishing a dose response model for influenza provides a firm basis for studies of interventions reducing exposure to different classes of infectious particles. More studies are needed to clarify the role of different modes of transmission in other settings.

Kinetics of the IgG antibody response to pertussis toxin after infection with B. pertussis

We aimed to provide a quantitative description of decay in pertussis antibody levels to aid in finding a serological estimate of the incidence of pertussis. The serum IgG response against pertussis toxin was studied in a group of clinically diagnosed patients. Individual records consisted of repeated serum IgG measurements at irregular intervals for up to 10 years post diagnosis. These data were analysed with a nonlinear regression model taking into account censoring at upper and lower threshold levels, measurement errors, and individual variation in the shape and magnitude of the immune response. There was considerable variation between individual responses, both in strength (amplitude) and duration (shape). The inverse model relating IgG levels to time from infection (diagnosis) can be applied to cross-sectional IgG data to generate distributions of times from infection, which may be used to calculate infection rates and their variation, in populations sampled for cross-sectional IgG data.