Neighbourhood sociodemographic factors and COVID-19 vaccine uptake in the Netherlands: an ecological analysis.

BACKGROUND: While overall COVID-19 vaccine uptake is high in the Netherlands, it lags behind in certain subpopulations. AIM: We aimed to explore the characteristics of groups with lower COVID-19 vaccine uptake at neighbourhood level to inform the strategy to improve uptake and guide research into barriers for vaccination. METHODS: We performed an ecological study using national vaccination register and socio-demographic data at neighbourhood level. Using univariate and multivariable generalized additive models we examined the (potentially non-linear) effect of each determinant on uptake. We focused on those aged 50 years and older, since they are at highest risk of severe disease. RESULTS: In those over 50 years of age, a higher proportion of individuals with a non-Western migration background and higher voting proportions for right-wing Christian and conservative political parties were at neighbourhood level univariately associated with lower COVID-19 vaccine uptake. In contrast, higher socioeconomic status and higher voting proportions for right-wing liberal, progressive liberal and Christian middle political parties were associated with higher uptake. Multivariable results differed from univariate results in that a higher voting proportion for progressive left-wing political parties was also associated with higher uptake. In addition, with regard to migration background only a Turkish background remained significant. CONCLUSION: We identified determinants associated with COVID-19 vaccine uptake at neighbourhood level and observed heterogeneity in uptake between different subpopulations. Since the goal of vaccination is not only to reduce suffering and death by improving the average uptake, but also to reduce health inequity, it is important to focus on subpopulations with lower uptake.

Proximity to livestock farms and COVID-19 in the Netherlands, 2020-2021.

OBJECTIVES: In the Netherlands, during the first phase of the COVID-19 epidemic, the hotspot of COVID-19 overlapped with the country's main livestock area, while in subsequent phases this distinct spatial pattern disappeared. Previous studies show that living near livestock farms influence human respiratory health and immunological responses. This study aimed to explore whether proximity to livestock was associated with SARS-CoV-2 infection. METHODS: The study population was the population of the Netherlands excluding the very strongly urbanised areas and border areas, on January 1, 2019 (12, 628, 244 individuals). The cases are the individuals reported with a laboratory-confirmed positive SARS-CoV-2 test with onset before January 1, 2022 (2, 223, 692 individuals). For each individual, we calculated distance to nearest livestock farm (cattle, goat, sheep, pig, poultry, horse, rabbit, mink). The associations between residential (6-digit postal-code) distance to the nearest livestock farm and individuals' SARS-CoV-2 status was studied with multilevel logistic regression models. Models were adjusted for individuals' age categories, the social status of the postal code area, particulate matter (PM10)- and nitrogen dioxide (NO2)-concentrations. We analysed data for the entire period and population as well as separately for eight time periods (Jan-Mar, Apr-Jun, Jul-Sep and Oct-Dec in 2020 and 2021), four geographic areas of the Netherlands (north, east, west and south), and for five age categories (0-14, 15-24, 25-44, 45-64 and > 65 years). RESULTS: Over the period 2020-2021, individuals' SARS-CoV-2 status was associated with living closer to livestock farms. This association increased from an Odds Ratio (OR) of 1.01 (95% Confidence Interval [CI] 1.01-1.02) for patients living at a distance of 751-1000 m to a farm to an OR of 1.04 (95% CI 1.04-1.04), 1.07 (95% CI 1.06-1.07) and 1.11 (95% CI 1.10-1.12) for patients living in the more proximate 501-750 m, 251-500m and 0-250 m zones around farms, all relative to patients living further than 1000 m around farms. This association was observed in three out of four quarters of the year in both 2020 and 2021, and in all studied geographic areas and age groups. CONCLUSIONS: In this exploratory study with individual SARS-CoV-2 notification data and high-resolution spatial data associations were found between living near livestock farms and individuals' SARS-CoV-2 status in the Netherlands. Verification of the results in other countries is warranted, as well as investigations into possible underlying exposures and mechanisms.

Increasing incidence of reported scabies infestations in the Netherlands, 2011-2021.

INTRODUCTION: Several Public Health Services and general practitioners in the Netherlands observed an increase in scabies in the Netherlands. Since individual cases of scabies are not notifiable in the Netherlands, the epidemiological situation is mostly unknown. To investigate the scabies incidence in the Netherlands, we described the epidemiology of scabies between 2011 and 2021. METHODS: Two national data sources were analysed descriptively. One data source obtained incidence data of scabies (per 1,000 persons) of persons consulting in primary care from 2011-2020. The other data source captured the number of prescribed scabicides in the Netherlands from 2011-2021. To describe the correlation between the incidence of diagnoses and the number of dispensations between 2011 and 2020, we calculated a correlation coefficient. RESULTS: The incidence of reported scabies has increased by more than threefold the last decade (2011-2020), mainly affecting adolescents and (young) adults. This was also clearly reflected in the fivefold increase in dispensations of scabicide medication during 2011-2021. The incidence and dispensations were at an all-time high in 2021. We found a strong correlation between the reported incidence and the number of dispensations between 2011 and 2020. CONCLUSIONS: More awareness on early diagnosis, proper treatment and treatment of close contacts is needed.

Two Community Clusters of Legionnaires' Disease Directly Linked to a Biologic Wastewater Treatment Plant, the Netherlands.

A biologic wastewater treatment plant was identified as a common source for 2 consecutive Legionnaires' disease clusters in the Netherlands in 2016 and 2017. Sequence typing and transmission modeling indicated direct and long-distance transmission of Legionella, indicating this source type should also be investigated in sporadic Legionnaires' disease cases.

Smooth incidence maps give valuable insight into Q fever outbreaks in The Netherlands.

From 2007 through 2009, The Netherlands faced large outbreaks of human Q fever. Control measures focused primarily on dairy goat farms because these were implicated as the main source of infection for the surrounding population. However, in other countries, outbreaks have mainly been associated with non-dairy sheep and The Netherlands has many more sheep than goats. Therefore, a public discussion arose about the possible role of non-dairy (meat) sheep in the outbreaks. To inform decision makers about the relative importance of different infection sources, we developed accurate and high-resolution incidence maps for detection of Q fever hot spots. In the high incidence area in the south of the country, full postal codes of notified Q fever patients with onset of illness in 2009, were georeferenced. Q fever cases (n = 1,740) were treated as a spatial point process. A 500 x 500 m grid was imposed over the area of interest. The number of cases and the population number were counted in each cell. The number of cases was modelled as an inhomogeneous Poisson process where the underlying incidence was estimated by 2-dimensional P-spline smoothing. Modelling of numbers of Q fever cases based on residential addresses and population size produced smooth incidence maps that clearly showed Q fever hotspots around infected dairy goat farms. No such increased incidence was noted around infected meat sheep farms. We conclude that smooth incidence maps of human notifications give valuable information about the Q fever epidemic and are a promising method to provide decision support for the control of other infectious diseases with an environmental source.

Proximity to goat farms and Coxiella burnetii seroprevalence among pregnant women.

During 2007-2009, we tested serum samples from 2,004 pregnant women living in an area of high Q fever incidence in the Netherlands. Results confirmed that presence of antibodies against Coxiella burnetii is related to proximity to infected dairy goat farms. Pregnant women and patients with certain cardiovascular conditions should avoid these farms.