The burden of invasive meningococcal disease in the Netherlands, 2011-2020.

INTRODUCTION: Representative information on disease course and outcome of invasive meningococcal disease (IMD) is important because of the shift in meningococcal epidemiology that recently occurred in the Netherlands. With this study, we update earlier research on the burden of IMD in the Netherlands. MATERIAL AND METHODS: We performed a retrospective study using Dutch surveillance data on IMD from July 2011 to May 2020. Clinical information was collected from hospital records. The effect of age, serogroup, and clinical manifestation on disease course and outcome was assessed in multivariable logistic regression analyses. Grouping of infecting isolates was performed by Ouchterlony gel diffusion or by PCR. RESULTS: Clinical information was collected for 278 IMD cases of which the majority had IMD-B (55%), followed by IMD-W (27%), IMD-Y (13%), and IMD-C (5%). Most patients presented with meningitis (32%) or sepsis (30%). Hospitalisation for ≥ 10 days was most frequent among 24-64 year olds (67%). ICU admission was highest among 24-64 year olds (60%), and in case of sepsis (70%), or sepsis plus meningitis (61%). Sequelae at discharge was lower for patients with mild meningococcaemia compared to patients with sepsis plus meningitis (OR: 0.19, 95% CI: 0.07-0.51). The overall case fatality rate was 7%, and was highest for IMD-Y (14%) and IMD-W (13%) patients. CONCLUSIONS: IMD remains a disease with high morbidity and mortality. Sepsis (with or without meningitis) is associated with a more severe disease course and outcome compared to other clinical manifestations. The high disease burden can be partly prevented by meningococcal vaccination.

Biosecurity and antimicrobial use in broiler farms across nine European countries: toward identifying farm-specific options for reducing antimicrobial usage.

Broiler chickens are among the main livestock sectors worldwide. With individual treatments being inapplicable, contrary to many other animal species, the need for antimicrobial use (AMU) is relatively high. AMU in animals is known to drive the emergence and spread of antimicrobial resistance (AMR). High farm biosecurity is a cornerstone for animal health and welfare, as well as food safety, as it protects animals from the introduction and spread of pathogens and therefore the need for AMU. The goal of this study was to identify the main biosecurity practices associated with AMU in broiler farms and to develop a statistical model that produces customised recommendations as to which biosecurity measures could be implemented on a farm to reduce its AMU, including a cost-effectiveness analysis of the recommended measures. AMU and biosecurity data were obtained cross-sectionally in 2014 from 181 broiler farms across nine European countries (Belgium, Bulgaria, Denmark, France, Germany, Italy, the Netherlands, Poland and Spain). Using mixed-effects random forest analysis (Mix-RF), recursive feature elimination was implemented to determine the biosecurity measures that best predicted AMU at the farm level. Subsequently, an algorithm was developed to generate AMU reduction scenarios based on the implementation of these measures. In the final Mix-RF model, 21 factors were present: 10 about internal biosecurity, 8 about external biosecurity and 3 about farm size and productivity, with the latter showing the largest (Gini) importance. Other AMU predictors, in order of importance, were the number of depopulation steps, compliance with a vaccination protocol for non-officially controlled diseases, and requiring visitors to check in before entering the farm. K-means clustering on the proximity matrix of the final Mix-RF model revealed that several measures interacted with each other, indicating that high AMU levels can arise for various reasons depending on the situation. The algorithm utilised the AMU predictive power of biosecurity measures while accounting also for their interactions, representing a first step toward aiding the decision-making process of veterinarians and farmers who are in need of implementing on-farm biosecurity measures to reduce their AMU.

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.