Campylobacter infections are increasing and pose a serious public health problem in Denmark. Infections in humans and broiler flocks show similar seasonality, suggesting that climate may play a role in infection. We examined the effects of temperature, precipitation, relative humidity, and hours of sunlight on Campylobacter incidence in humans and broiler flocks by using lag dependence functions, locally fitted linear models, and cross validation methods. For humans, the best model included average temperature and sunlight 4 weeks prior to infection; the maximum temperature lagged at 4 weeks was the best single predictor. For broilers, the average and maximum temperatures 3 weeks prior to slaughter gave the best estimate; the average temperature lagged at 3 weeks was the best single predictor. The combined effects of temperature and sunlight or the combined effects of temperature and relative humidity predicted the incidence in humans equally well. For broiler flock incidence these factors explained considerably less. Future research should focus on elements within the broiler environment that may be affected by climate, as well as the interaction of microclimatic factors on and around broiler farms. There is a need to quantify the contribution of broilers as a source of campylobacteriosis in humans and to further examine the effect of temperature on human incidence after this contribution is accounted for. Investigations should be conducted into food consumption and preparation practices and poultry sales that may vary by season.
1 Abstract The Omicron SARS-CoV-2 variant of concern (VOC lineage B.1.1.529), which became dominant in many countries during early 2022, includes several subvariants with strikingly different genetic characteristics. Several countries, including Denmark, have observed the two Omicron subvariants: BA.1 and BA.2. In Denmark the latter has rapidly replaced the former as the dominant subvariant. Based on nationwide Danish data, we estimate the transmission dynamics of BA.1 and BA.2 following the spread of Omicron VOC within Danish households in late December 2021 and early January 2022. Among 8,541 primary household cases, of which 2,122 were BA.2, we identified a total of 5,702 secondary infections among 17,945 potential secondary cases during a 1-7 day follow-up period. The secondary attack rate (SAR) was estimated as 29% and 39% in households infected with Omicron BA.1 and BA.2, respectively. We found BA.2 to be associated with an increased susceptibility of infection for unvaccinated individuals (Odds Ratio (OR) 2.19; 95%-CI 1.58-3.04), fully vaccinated individuals (OR 2.45; 95%-CI 1.77-3.40) and booster-vaccinated individuals (OR 2.99; 95%-CI 2.11-4.24), compared to BA.1. We also found an increased transmissibility from unvaccinated primary cases in BA.2 households when compared to BA.1 households, with an OR of 2.62 (95%-CI 1.96-3.52). The pattern of increased transmissibility in BA.2 households was not observed for fully vaccinated and booster-vaccinated primary cases, where the OR of transmission was below 1 for BA.2 compared to BA.1. We conclude that Omicron BA.2 is inherently substantially more transmissible than BA.1, and that it also possesses immune-evasive properties that further reduce the protective effect of vaccination against infection, but do not increase its transmissibility from vaccinated individuals with breakthrough infections.
Important differences in excess mortality between European countries during the COVID-19 pandemic have been reported. Understanding the drivers of these differences is essential to pandemic preparedness. We examined patterns in age- and sex-standardized cumulative excess mortality in 13 Western European countries during the first 30 months of the COVID-19 pandemic and the correlation of country-level characteristics of interest with excess mortality. In a timeline analysis, we identified notable differences in seeding events, particularly in early 2020 and when the Alpha variant emerged, likely contributing to notable differences in excess mortality between countries (lowest in Denmark during that period). These differences were more limited from July 2021 onwards. Lower excess mortality was associated with implementing stringent non-pharmaceutical interventions (NPIs) when hospital admissions were still low in 2020 (correlation coefficient rho = 0.65, p = 0.03) and rapid rollout of vaccines in the elderly in early 2021 (rho = − 0.76, p = 0.002). Countries which implemented NPIs while hospital admissions were low tended to experience lower gross domestic product (GDP) losses in 2020 (rho = − 0.55, p = 0.08). Structural factors, such as high trust in the national government (rho = − 0.77, p = 0.002) and low ratio of population at risk of poverty (rho = 0.55, p = 0.05), were also associated with lower excess mortality. These results suggest the benefit of early implementation of NPIs and swift rollout of vaccines to the most vulnerable. Further analyses are required at a more granular level to better understand how these factors impacted excess mortality and help guide pandemic preparedness plans.
Bluetongue is a disease of ruminants which reached Denmark in 2007. We present a process-based stochastic simulation model of vector-borne diseases, where host animals are not confined to a central geographic farm coordinate, but can be distributed onto pasture areas. Furthermore vectors fly freely and display search behavior to locate areas with hosts. We also include wind spread of vectors, host movements and vector seasonality. Results show that temperature and seasonality of vectors determines the period in which an incursion of Bluetongue may lead to epidemic spread in Denmark. Within this period of risk the number of infected hosts is affected by temperature, vector abundance, vector behavior, vectors' ability to locate hosts and use of pasture. These results indicate that restricted grazing during outbreaks can reduce the number of infected hosts and the size of the affected area. The model can be implemented on other vector-borne diseases of grazing animals.
