The estimated disease burden of acute COVID-19 in the Netherlands in 2020, in disability-adjusted life-years.

The impact of COVID-19 on population health is recognised as being substantial, yet few studies have attempted to quantify to what extent infection causes mild or moderate symptoms only, requires hospital and/or ICU admission, results in prolonged and chronic illness, or leads to premature death. We aimed to quantify the total disease burden of acute COVID-19 in the Netherlands in 2020 using the disability-adjusted life-years (DALY) measure, and to investigate how burden varies between age-groups and occupations. Using standard methods and diverse data sources (mandatory notifications, population-level seroprevalence, hospital and ICU admissions, registered COVID-19 deaths, and the literature), we estimated years of life lost (YLL), years lived with disability, DALY and DALY per 100,000 population due to COVID-19, excluding post-acute sequelae, stratified by 5-year age-group and occupation category. The total disease burden due to acute COVID-19 was 286,100 (95% CI: 281,700-290,500) DALY, and the per-capita burden was 1640 (95% CI: 1620-1670) DALY/100,000, of which 99.4% consisted of YLL. The per-capita burden increased steeply with age, starting from 60 to 64 years, with relatively little burden estimated for persons under 50 years old. SARS-CoV-2 infection and associated premature mortality was responsible for a considerable direct health burden in the Netherlands, despite extensive public health measures. DALY were much higher than for other high-burden infectious diseases, but lower than estimated for coronary heart disease. These findings are valuable for informing public health decision-makers regarding the expected COVID-19 health burden among population subgroups, and the possible gains from targeted preventative interventions.

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.

Effects of incomplete inter-hospital network data on the assessment of transmission dynamics of hospital-acquired infections.

In the year 2020, there were 105 different statutory insurance companies in Germany with heterogeneous regional coverage. Obtaining data from all insurance companies is challenging, so that it is likely that projects will have to rely on data not covering the whole population. Consequently, the study of epidemic spread in hospital referral networks using data-driven models may be biased. We studied this bias using data from three German regional insurance companies covering four federal states: AOK (historically "general local health insurance company", but currently only the abbreviation is used) Lower Saxony (in Federal State of Lower Saxony), AOK Bavaria (in Bavaria), and AOK PLUS (in Thuringia and Saxony). To understand how incomplete data influence network characteristics and related epidemic simulations, we created sampled datasets by randomly dropping a proportion of patients from the full datasets and replacing them with random copies of the remaining patients to obtain scale-up datasets to the original size. For the sampled and scale-up datasets, we calculated several commonly used network measures, and compared them to those derived from the original data. We found that the network measures (degree, strength and closeness) were rather sensitive to incompleteness. Infection prevalence as an outcome from the applied susceptible-infectious-susceptible (SIS) model was fairly robust against incompleteness. At incompleteness levels as high as 90% of the original datasets the prevalence estimation bias was below 5% in scale-up datasets. Consequently, a coverage as low as 10% of the local population of the federal state population was sufficient to maintain the relative bias in prevalence below 10% for a wide range of transmission parameters as encountered in clinical settings. Our findings are reassuring that despite incomplete coverage of the population, German health insurance data can be used to study effects of patient traffic between institutions on the spread of pathogens within healthcare networks.

Disease modeling for public health: added value, challenges, and institutional constraints.

Public health policymakers face increasingly complex questions and decisions and need to deal with an increasing quantity of data and information. For policy advisors to make use of scientific evidence and to assess available intervention options effectively and therefore indirectly for those deciding on and implementing public health policies, mathematical modeling has proven to be a useful tool. In some areas, the use of mathematical modeling for public health policy support has become standard practice at various levels of decision-making. To make use of this tool effectively within public health organizations, it is necessary to provide good infrastructure and ensure close collaboration between modelers and policymakers. Based on experience from a national public health institute, we discuss the strategic requirements for good modeling practice for public health. For modeling to be of maximal value for a public health institute, the organization and budgeting of mathematical modeling should be transparent, and a long-term strategy for how to position and develop mathematical modeling should be in place.

Tracking Pseudomonas aeruginosa transmissions due to environmental contamination after discharge in ICUs using mathematical models.

Pseudomonas aeruginosa (P. aeruginosa) is an important cause of healthcare-associated infections, particularly in immunocompromised patients. Understanding how this multi-drug resistant pathogen is transmitted within intensive care units (ICUs) is crucial for devising and evaluating successful control strategies. While it is known that moist environments serve as natural reservoirs for P. aeruginosa, there is little quantitative evidence regarding the contribution of environmental contamination to its transmission within ICUs. Previous studies on other nosocomial pathogens rely on deploying specific values for environmental parameters derived from costly and laborious genotyping. Using solely longitudinal surveillance data, we estimated the relative importance of P. aeruginosa transmission routes by exploiting the fact that different routes cause different pattern of fluctuations in the prevalence. We developed a mathematical model including background transmission, cross-transmission and environmental contamination. Patients contribute to a pool of pathogens by shedding bacteria to the environment. Natural decay and cleaning of the environment lead to a reduction of that pool. By assigning the bacterial load shed during an ICU stay to cross-transmission, we were able to disentangle environmental contamination during and after a patient's stay. Based on a data-augmented Markov Chain Monte Carlo method the relative importance of the considered acquisition routes is determined for two ICUs of the University hospital in Besançon (France). We used information about the admission and discharge days, screening days and screening results of the ICU patients. Both background and cross-transmission play a significant role in the transmission process in both ICUs. In contrast, only about 1% of the total transmissions were due to environmental contamination after discharge. Based on longitudinal surveillance data, we conclude that cleaning improvement of the environment after discharge might have only a limited impact regarding the prevention of P.A. infections in the two considered ICUs of the University hospital in Besançon. Our model was developed for P. aeruginosa but can be easily applied to other pathogens as well.

Attributable deaths and disability-adjusted life-years caused by infections with antibiotic-resistant bacteria in the EU and the European Economic Area in 2015: a population-level modelling analysis.

BACKGROUND: Infections due to antibiotic-resistant bacteria are threatening modern health care. However, estimating their incidence, complications, and attributable mortality is challenging. We aimed to estimate the burden of infections caused by antibiotic-resistant bacteria of public health concern in countries of the EU and European Economic Area (EEA) in 2015, measured in number of cases, attributable deaths, and disability-adjusted life-years (DALYs). METHODS: We estimated the incidence of infections with 16 antibiotic resistance-bacterium combinations from European Antimicrobial Resistance Surveillance Network (EARS-Net) 2015 data that was country-corrected for population coverage. We multiplied the number of bloodstream infections (BSIs) by a conversion factor derived from the European Centre for Disease Prevention and Control point prevalence survey of health-care-associated infections in European acute care hospitals in 2011-12 to estimate the number of non-BSIs. We developed disease outcome models for five types of infection on the basis of systematic reviews of the literature. FINDINGS: From EARS-Net data collected between Jan 1, 2015, and Dec 31, 2015, we estimated 671 689 (95% uncertainty interval [UI] 583 148-763 966) infections with antibiotic-resistant bacteria, of which 63·5% (426 277 of 671 689) were associated with health care. These infections accounted for an estimated 33 110 (28 480-38 430) attributable deaths and 874 541 (768 837-989 068) DALYs. The burden for the EU and EEA was highest in infants (aged <1 year) and people aged 65 years or older, had increased since 2007, and was highest in Italy and Greece. INTERPRETATION: Our results present the health burden of five types of infection with antibiotic-resistant bacteria expressed, for the first time, in DALYs. The estimated burden of infections with antibiotic-resistant bacteria in the EU and EEA is substantial compared with that of other infectious diseases, and has increased since 2007. Our burden estimates provide useful information for public health decision-makers prioritising interventions for infectious diseases. FUNDING: European Centre for Disease Prevention and Control.

Impact of infectious diseases on population health using incidence-based disability-adjusted life years (DALYs): results from the Burden of Communicable Diseases in Europe study, European Union and European Economic Area countries, 2009 to 2013.

Background and aimsThe Burden of Communicable Diseases in Europe (BCoDE) study aimed to calculate disability-adjusted life years (DALYs) for 31 selected diseases in the European Union (EU) and European Economic Area (EEA). Methods: DALYs were estimated using an incidence-based and pathogen-based approach. Incidence was estimated through assessment of data availability and quality, and a correction was applied for under-estimation. Calculation of DALYs was performed with the BCoDE software toolkit without applying time discounting and age-weighting. Results: We estimated that one in 14 inhabitants experienced an infectious disease episode for a total burden of 1.38 million DALYs (95% uncertainty interval (UI): 1.25-1.5) between 2009 and 2013; 76% of which was related to the acute phase of the infection and its short-term complications. Influenza had the highest burden (30% of the total burden), followed by tuberculosis, human immunodeficiency virus (HIV) infection/AIDS and invasive pneumococcal disease (IPD). Men had the highest burden measured in DALYs (60% of the total), adults 65 years of age and over had 24% and children less than 5 years of age had 11%. Age group-specific burden showed that infants (less than 1 year of age) and elderly people (80 years of age and over) experienced the highest burden. Conclusions: These results provide baseline estimates for evaluating infectious disease prevention and control strategies. The study promotes an evidence-based approach to describing population health and assessing surveillance data availability and quality, and provides information for the planning and prioritisation of limited resources in infectious disease prevention and control.

Disability weights for infectious diseases in four European countries: comparison between countries and across respondent characteristics.

Background: In 2015, new disability weights (DWs) for infectious diseases were constructed based on data from four European countries. In this paper, we evaluated if country, age, sex, disease experience status, income and educational levels have an impact on these DWs. Methods: We analyzed paired comparison responses of the European DW study by participants' characteristics with separate probit regression models. To evaluate the effect of participants' characteristics, we performed correlation analyses between countries and within country by respondent characteristics and constructed seven probit regression models, including a null model and six models containing participants' characteristics. We compared these seven models using Akaike Information Criterion (AIC). Results: According to AIC, the probit model including country as covariate was the best model. We found a lower correlation of the probit coefficients between countries and income levels (range rs: 0.97-0.99, P < 0.01) than between age groups (range rs: 0.98-0.99, P < 0.01), educational level (range rs: 0.98-0.99, P < 0.01), sex (rs = 0.99, P < 0.01) and disease status (rs = 0.99, P < 0.01). Within country the lowest correlations of the probit coefficients were between low and high income level (range rs = 0.89-0.94, P < 0.01). Conclusions: We observed variations in health valuation across countries and within country between income levels. These observations should be further explored in a systematic way, also in non-European countries. We recommend future researches studying the effect of other characteristics of respondents on health assessment.

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.

A Software Tool for Estimation of Burden of Infectious Diseases in Europe Using Incidence-Based Disability Adjusted Life Years.

The burden of disease framework facilitates the assessment of the health impact of diseases through the use of summary measures of population health such as Disability-Adjusted Life Years (DALYs). However, calculating, interpreting and communicating the results of studies using this methodology poses a challenge. The aim of the Burden of Communicable Disease in Europe (BCoDE) project is to summarize the impact of communicable disease in the European Union and European Economic Area Member States (EU/EEA MS). To meet this goal, a user-friendly software tool (BCoDE toolkit), was developed. This stand-alone application, written in C++, is open-access and freely available for download from the website of the European Centre for Disease Prevention and Control (ECDC). With the BCoDE toolkit, one can calculate DALYs by simply entering the age group- and sex-specific number of cases for one or more of selected sets of 32 communicable diseases (CDs) and 6 healthcare associated infections (HAIs). Disease progression models (i.e., outcome trees) for these communicable diseases were created following a thorough literature review of their disease progression pathway. The BCoDE toolkit runs Monte Carlo simulations of the input parameters and provides disease-specific results, including 95% uncertainty intervals, and permits comparisons between the different disease models entered. Results can be displayed as mean and median overall DALYs, DALYs per 100,000 population, and DALYs related to mortality vs. disability. Visualization options summarize complex epidemiological data, with the goal of improving communication and knowledge transfer for decision-making.

Burden of Six Healthcare-Associated Infections on European Population Health: Estimating Incidence-Based Disability-Adjusted Life Years through a Population Prevalence-Based Modelling Study.

BACKGROUND: Estimating the burden of healthcare-associated infections (HAIs) compared to other communicable diseases is an ongoing challenge given the need for good quality data on the incidence of these infections and the involved comorbidities. Based on the methodology of the Burden of Communicable Diseases in Europe (BCoDE) project and 2011-2012 data from the European Centre for Disease Prevention and Control (ECDC) point prevalence survey (PPS) of HAIs and antimicrobial use in European acute care hospitals, we estimated the burden of six common HAIs. METHODS AND FINDINGS: The included HAIs were healthcare-associated pneumonia (HAP), healthcare-associated urinary tract infection (HA UTI), surgical site infection (SSI), healthcare-associated Clostridium difficile infection (HA CDI), healthcare-associated neonatal sepsis, and healthcare-associated primary bloodstream infection (HA primary BSI). The burden of these HAIs was measured in disability-adjusted life years (DALYs). Evidence relating to the disease progression pathway of each type of HAI was collected through systematic literature reviews, in order to estimate the risks attributable to HAIs. For each of the six HAIs, gender and age group prevalence from the ECDC PPS was converted into incidence rates by applying the Rhame and Sudderth formula. We adjusted for reduced life expectancy within the hospital population using three severity groups based on McCabe score data from the ECDC PPS. We estimated that 2,609,911 new cases of HAI occur every year in the European Union and European Economic Area (EU/EEA). The cumulative burden of the six HAIs was estimated at 501 DALYs per 100,000 general population each year in EU/EEA. HAP and HA primary BSI were associated with the highest burden and represented more than 60% of the total burden, with 169 and 145 DALYs per 100,000 total population, respectively. HA UTI, SSI, HA CDI, and HA primary BSI ranked as the third to sixth syndromes in terms of burden of disease. HAP and HA primary BSI were associated with the highest burden because of their high severity. The cumulative burden of the six HAIs was higher than the total burden of all other 32 communicable diseases included in the BCoDE 2009-2013 study. The main limitations of the study are the variability in the parameter estimates, in particular the disease models' case fatalities, and the use of the Rhame and Sudderth formula for estimating incident number of cases from prevalence data. CONCLUSIONS: We estimated the EU/EEA burden of HAIs in DALYs in 2011-2012 using a transparent and evidence-based approach that allows for combining estimates of morbidity and of mortality in order to compare with other diseases and to inform a comprehensive ranking suitable for prioritization. Our results highlight the high burden of HAIs and the need for increased efforts for their prevention and control. Furthermore, our model should allow for estimations of the potential benefit of preventive measures on the burden of HAIs in the EU/EEA.

Cost-Effectiveness of Hepatitis C Treatment for People Who Inject Drugs and the Impact of the Type of Epidemic; Extrapolating from Amsterdam, the Netherlands.

BACKGROUND: People who inject drugs (PWID) are disproportionally affected by the hepatitis C virus (HCV) infection. The efficacy of HCV treatment has significantly improved in recent years with the introduction of direct-acting antivirals (DAAs). However, DAAs are more costly than pegylated-interferon and ribavirin (PegIFN/RBV). We aimed to assess the cost-effectiveness of four HCV treatment strategies among PWID and treatment scale-up. METHODS: An individual-based model was used describing HIV and HCV transmission and disease progression among PWID. We considered two epidemiological situations. A declining epidemic, based on the situation in Amsterdam, the Netherlands, and a stable HCV epidemic, as observed in other settings. Data on HCV incidence, prevalence, treatment setting and uptake were derived from observed data among PWID in Amsterdam. We assessed the incremental cost-effectiveness ratio (ICER, costs in €/quality-adjusted life year (QALY)) of four treatment strategies: 1) PegIFN/RBV; 2) sofosbuvir/RBV for genotype 2-3 and dual DAA for genotype 1-4; 3) Dual DAA for all genotypes; 4) Dual DAA with 3x treatment uptake. RESULTS: In both types of epidemic, dual DAA therapy was most cost-effective strategy. In the declining epidemic, dual DAA yielded an ICER of 344 €/QALY while in the stable epidemic dual DAA led to cost-savings. Scaling-up treatment was also highly cost-effective. Our results were robust over a range of sensitivity analyses. CONCLUSION: HCV treatment with DAA-containing regimens is a highly cost-effective intervention among PWID. Based on the economic and population benefits of scaling-up treatment, stronger efforts are needed to achieve higher uptake rates among PWID.

Disease Burden of 32 Infectious Diseases in the Netherlands, 2007-2011.

BACKGROUND: Infectious disease burden estimates provided by a composite health measure give a balanced view of the true impact of a disease on a population, allowing the relative impact of diseases that differ in severity and mortality to be monitored over time. This article presents the first national disease burden estimates for a comprehensive set of 32 infectious diseases in the Netherlands. METHODS AND FINDINGS: The average annual disease burden was computed for the period 2007-2011 for selected infectious diseases in the Netherlands using the disability-adjusted life years (DALY) measure. The pathogen- and incidence-based approach was adopted to quantify the burden due to both morbidity and premature mortality associated with all short and long-term consequences of infection. Natural history models, disease progression probabilities, disability weights, and other parameters were adapted from previous research. Annual incidence was obtained from statutory notification and other surveillance systems, which was corrected for under-ascertainment and under-reporting. The highest average annual disease burden was estimated for invasive pneumococcal disease (9444 DALYs/year; 95% uncertainty interval [UI]: 8911-9961) and influenza (8670 DALYs/year; 95% UI: 8468-8874), which represents 16% and 15% of the total burden of all 32 diseases, respectively. The remaining 30 diseases ranked by number of DALYs/year from high to low were: HIV infection, legionellosis, toxoplasmosis, chlamydia, campylobacteriosis, pertussis, tuberculosis, hepatitis C infection, Q fever, norovirus infection, salmonellosis, gonorrhoea, invasive meningococcal disease, hepatitis B infection, invasive Haemophilus influenzae infection, shigellosis, listeriosis, giardiasis, hepatitis A infection, infection with STEC O157, measles, cryptosporidiosis, syphilis, rabies, variant Creutzfeldt-Jakob disease, tetanus, mumps, rubella, diphtheria, and poliomyelitis. The very low burden for the latter five diseases can be attributed to the National Immunisation Programme. The average disease burden per individual varied from 0.2 (95% UI: 0.1-0.4) DALYs per 100 infections for giardiasis, to 5081 and 3581 (95% UI: 3540-3611) DALYs per 100 infections for rabies and variant Creutzfeldt-Jakob disease, respectively. CONCLUSIONS: For guiding and supporting public health policy decisions regarding the prioritisation of interventions and preventive measures, estimates of disease burden and the comparison of burden between diseases can be informative. Although the collection of disease-specific parameters and estimation of incidence is a process subject to continuous improvement, the current study established a baseline for assessing the impact of future public health initiatives.

Burden of four vaccine preventable diseases in older adults.

BACKGROUND: Implementation of additional targeted vaccinations to prevent infectious diseases in the older adults is under discussion in different countries. When considering the added value of such preventive measures, insight into the current disease burden will assist in prioritization. The aim of this study was derive the first estimates of the disease burden in adults aged 50 years or over in the Netherlands for influenza, pertussis, pneumococcal disease and herpes zoster. METHODS: The average annual disease burden for these four diseases in the Netherlands was calculated for the period 2010-2013 using the disability-adjusted life years (DALY) measure. Disease models and parameters were obtained from previous research. Where possible we adapted these models specifically for older adults and applied age-specific parameters derived from literature. The disease burden based on these adapted models and parameters was compared with the disease burden based on the general population models. RESULTS: The estimated average annual disease burden was from high to low: pneumococcal disease (37,223 DALYs/year), influenza (7941 DALYs/year), herpes zoster (942 DALYs/year), and pertussis (812 DALYs/year). The adaptation of models and parameters specifically for the elderly resulted in a higher disease burden compared to the use of general population models. CONCLUSIONS: Among older adults, the disease burden in the period 2010-2013 was highest for pneumococcal disease, mostly because of high mortality, followed by influenza. Disease burden of herpes zoster and pertussis was relatively low and consisted mostly of years lived with disability. Better information on the course of infectious diseases and long-term consequences would enable more accurate estimation of disease burden in older adults.

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.

To notify or not to notify: decision aid for policy makers on whether to make an infectious disease mandatorily notifiable.

Mandatory notification can be a useful tool to support infectious disease prevention and control. Guidelines are needed to help policymakers decide whether mandatory notification of an infectious disease is appropriate. We developed a decision aid, based on a range of criteria previously used in the Netherlands or in other regions to help decide whether to make a disease notifiable. Criteria were categorised as being effective, feasible and necessary with regard to the relevance of mandatory notification. Expert panels piloted the decision aid. Here we illustrate its use for three diseases (Vibrio vulnificus infection, chronic Q fever and dengue fever) for which mandatory notification was requested. For dengue fever, the expert panel advised mandatory notification; for V. vulnificus infection and chronic Q fever, the expert panel concluded that mandatory notification was not (yet) justified. Use of the decision aid led to a structured, transparent decision making process and a thorough assessment of the advantages and disadvantages of mandatory notification of these diseases. It also helped identify knowledge gaps that required further research before a decision could be made. We therefore recommend use of this aid for public health policy making.

Disability weights for the Global Burden of Disease 2013 study.

BACKGROUND: The Global Burden of Disease (GBD) study assesses health losses from diseases, injuries, and risk factors using disability-adjusted life-years, which need a set of disability weights to quantify health levels associated with non-fatal outcomes. The objective of this study was to estimate disability weights for the GBD 2013 study. METHODS: We analysed data from new web-based surveys of participants aged 18-65 years, completed in four European countries (Hungary, Italy, the Netherlands, and Sweden) between Sept 23, 2013, and Nov 11, 2013, combined with data previously collected in the GBD 2010 disability weights measurement study. Surveys used paired comparison questions for which respondents considered two hypothetical individuals with different health states and specified which person they deemed healthier than the other. These surveys covered 183 health states pertinent to GBD 2013; of these states, 30 were presented with descriptions revised from previous versions and 18 were new to GBD 2013. We analysed paired comparison data using probit regression analysis and rescaled results to disability weight units between 0 (no loss of health) and 1 (loss equivalent to death). We compared results with previous estimates, and an additional analysis examined sensitivity of paired comparison responses to duration of hypothetical health states. FINDINGS: The total analysis sample consisted of 30 230 respondents from the GBD 2010 surveys and 30 660 from the new European surveys. For health states common to GBD 2010 and GBD 2013, results were highly correlated overall (Pearson's r 0·992 [95% uncertainty interval 0·989-0·994]). For health state descriptions that were revised for this study, resulting disability weights were substantially different for a subset of these weights, including those related to hearing loss (eg, complete hearing loss: GBD 2010 0·033 [0·020-0·052]; GBD 2013 0·215 [0·144-0·307]) and treated spinal cord lesions (below the neck: GBD 2010 0·047 [0·028-0·072]; GBD 2013 0·296 [0·198-0·414]; neck level: GBD 2010 0·369 [0·243-0·513]; GBD 2013 0·589 [0·415-0·748]). Survey responses to paired comparison questions were insensitive to whether the comparisons were framed in terms of temporary or chronic outcomes (Pearson's r 0·981 [0·973-0·987]). INTERPRETATION: This study substantially expands the empirical basis for assessment of non-fatal outcomes in the GBD study. Findings from this study substantiate the notion that disability weights are sensitive to particular details in descriptions of health states, but robust to duration of outcomes. FUNDING: European Centre for Disease Prevention and Control, Bill and Melinda Gates Foundation.

Chlamydia screening is not cost-effective at low participation rates: evidence from a repeated register-based implementation study in The Netherlands.

OBJECTIVE: In three pilot regions of The Netherlands, all 16-29 year olds were invited to participate in three annual rounds of Chlamydia screening. The aim of the present study is to evaluate the cost-effectiveness of repeated Chlamydia screening, based on empirical data. METHODS: A mathematical model was employed to estimate the influence of repeated screening on prevalence and incidence of Chlamydial infection. A model simulating the natural history of Chlamydia was combined with cost and utility data to estimate the number of major outcomes and quality-adjusted life-years (QALYs) associated with Chlamydia. Six screening scenarios (16-29 years annually; 16-24 years annually; women only; biennial screening; biennial screening women only; screening every five years) were compared with no screening in two sexual networks, representing both lower ('national network') and higher ('urban network') baseline prevalence. Incremental cost-effectiveness ratios (ICERs) for the different screening scenarios were estimated. Uncertainty and sensitivity analyses were performed. RESULTS: In all scenarios and networks, cost per major outcome averted are above €5000. Cost per QALY are at least €50,000. The default scenario as piloted in the Netherlands was least cost-effective, with ICERs of €232,000 in the national and €145,000 in the urban sexual network. Results were robust in sensitivity analyses. CONCLUSIONS: It is unlikely that repeated rounds of Chlamydia screening will be cost-effective. Only at high levels of willingness to pay for a QALY (>€50,000) screening may be more cost-effective than no screening.

Toward an endgame: finding and engaging people unaware of their HIV-1 infection in treatment and prevention.

Epidemic modeling suggests that a major scale-up in HIV treatment could have a dramatic impact on HIV incidence. This has led both researchers and policymakers to set a goal of an "AIDS-Free Generation." One of the greatest obstacles to achieving this objective is the number of people with undiagnosed HIV infection. Despite recent innovations, new research strategies are needed to identify, engage, and successfully treat people who are unaware of their infection.