An exclusive human milk diet for very low birth weight newborns-A cost-effectiveness and EVPI study for Germany.

OBJECTIVES: Human milk-based fortifiers have shown a protective effect on major complications for very low birth weight newborns. The current study aimed to estimate the cost-effectiveness of an exclusive human milk diet (EHMD) compared to the current approach using cow's milk-based fortifiers in very low birth weight newborns. METHODS: A decision tree model using the health states of necrotising enterocolitis (NEC), sepsis, NEC + sepsis and no complication was used to calculate the cost-effectiveness of an EHMD. For each health state, bronchopulmonary dysplasia (BPD), retinopathy of prematurity (RoP) and neurodevelopmental problems were included as possible complications; additionally, short-bowel syndrome (SBS) was included as a complication for surgical treatment of NEC. The model was stratified into birth weight categories. Costs for inpatient treatment and long-term consequences were considered from a third party payer perspective for the reference year 2017. Deterministic and probabilistic sensitivity analyses were performed, including a societal perspective, discounting rate and all input parameter-values. RESULTS: In the base case, the EHMD was estimated to be cost-effective compared to the current nutrition for very low birth weight newborns with an incremental cost-effectiveness ratio (ICER) of €28,325 per Life-Year-Gained (LYG). From a societal perspective, the ICER is €27,494/LYG using a friction cost approach and €16,112/LYG using a human capital approach. Deterministic sensitivity analyses demonstrated that the estimate was robust against changes in the input parameters and probabilistic sensitivity analysis suggested that the probability EHMD was cost-effective at a threshold of €45,790/LYG was 94.8 percent. CONCLUSION: Adopting EHMD as the standard approach to nutrition is a cost-effective intervention for very low birth weight newborns in Germany.

Population size and self-reported characteristics and sexual preferences of men-who-have-sex-with-men (MSM) in Germany based on social network data.

BACKGROUND: In the absence of detailed information about the population size and behaviour data of men-who-have-sex-with-men (MSM), the estimation of prevalence rates of sexually transmitted infections (STIs) and the design of public health interventions become difficult. The aim of the present study is to estimate the lower boundary of age-specific population sizes and retrieve self-reported information from this population. METHODS: We used publicly accessible data from a large online dating and social network website for MSM in Germany to retrieve data on the age and regional distribution of profiles. The profiles were also stratified by their information on the preferred position during anal intercourse, safer sex, and sexual identity. RESULTS: A total of 464,873 user profiles correspond to an average 15.2 profiles per 1,000 male inhabitants in Germany, varying between 7.6 and 45.6 across federal states. Although the information on the absolute numbers for different age groups is limited by the search engine, age-specific relative frequencies were found to increase from 12.9 in the age group of 18 to 20 year olds to 24.6 profiles per 1,000 male inhabitants in the 28 to 30 year olds. The data shows age-specific trends for safer sex with an increasing easiness of reporting "never" engaging in safer sex or stating that safer sex "needs discussion" with increasing age. Around one third of profile owners stated to be versatile with respect to the preferred position in anal intercourse. All other options ("only bottom", "more bottom", "only top", "more top") were preferred equally likely by roughly 10% of profile owners, respectively. CONCLUSIONS: Online social network or dating sites can provide some information about specific populations in the absence of other data sources. The presented results are the first to report age-specific rates of MSM per 1,000 male inhabitants in Germany and may be useful to estimate age-specific prevalence or incidence rates as well as to inform health promotion activities and modelling studies for MSM in Germany.

How various design decisions on matching individuals in relationships affect the outcomes of microsimulations of sexually transmitted infection epidemics.

Microsimulations are increasingly used to estimate the prevalence of sexually transmitted infections (STIs). These models consist of agents which represent a sexually active population. Matching agents into sexual relationships is computationally intensive and presents modellers with difficult design decisions: how to select which partnerships between agents break up, which agents enter a partnership market, and how to pair agents in the partnership market. The aim of this study was to analyse the effect of these design decisions on STI prevalence. We compared two strategies for selecting which agents enter a daily partnership market and which agent partnerships break up: random selection in which agents are treated homogenously versus selection based on data from a large German longitudinal data set that accounts for sex, sexual orientation and age heterogeneity. We also coupled each of these strategies with one of several recently described algorithms for pairing agents and compared their speed and outcomes. Additional design choices were also considered, such as the number of agents used in the model, increasing the heterogeneity of agents' sexual behaviour, and the proportion of relationships which are casual sex encounters. Approaches which account for agent heterogeneity estimated lower prevalence than less sophisticated approaches which treat agents homogeneously. Also, in simulations with non-random pairing of agents, as the risk of infection increased, incidence declined as the number of agents increased. Our algorithms facilitate the execution of thousands of simulations with large numbers of agents quickly. Fast pair-matching algorithms provide a practical way for microsimulation modellers to account for varying sexual behaviour within the population they are studying. For STIs with high infection rates modellers may need to experiment with different population sizes.