Old News

New preprint: Estimating the distribution of COVID-19-susceptible, -recovered, and -vaccinated individuals in Germany up to April 2022
New preprint: Estimating the distribution of COVID-19-susceptible, -recovered, and -vaccinated individuals in Germany up to April 2022

After having affected the population for two years, the COVID-19 pandemic has reached a phase where a considerable number of people in Germany have been either infected with a SARS-CoV-2 variant, vaccinated, or both. Yet the full extent to which the population has been in contact with either virus or vaccine remains elusive, particularly on a regional level, because (a) infection counts suffer from under-reporting, and (b) the overlap between the vaccinated and recovered subpopulations is unknown. Since previous infection, vaccination, or especially a combination of both reduce the risk of severe disease, a high share of individuals with SARS-CoV-2 immunity lowers the probability of severe outbreaks that could potentially overburden the public health system once again, given that emerging variants do not escape this reduction in susceptibility. Here, we estimate the share of immunologically naïve individuals by age group for each of the 16 German federal states by integrating an infectious disease model based on weekly incidences of SARS-CoV-2 infections in the national surveillance system and vaccine uptake, as well as assumptions regarding under-ascertainment. We estimate a median share of 7.0% of individuals in the German population have neither been in contact with vaccine nor any variant as of March 31, 2022 (quartile range [3.6%– 9.8%]). For the adult population at higher risk of severe disease, this figure is reduced to 3.5% [1.3%–5.5%] for ages 18–59 and 4.3% [2.7%–5.8%] for ages 60 and above. However, estimates vary between German states mostly due to heterogeneous vaccine uptake. Excluding Omicron infections from the analysis, 16.1% [14.0%–17.8%] of the population in Germany, across all ages, are estimated to be immunologically naïve, highlighting the large impact the Omicron wave had until the beginning of spring in 2022.

New preprint: Evidence for positive long- and short-term effects of vaccinations against COVID-19 in wearable sensor metrics -- Insights from the German Corona Data Donation Project
New preprint: Evidence for positive long- and short-term effects of vaccinations against COVID-19 in wearable sensor metrics -- Insights from the German Corona Data Donation Project

Vaccines are among the most powerful tools used to combat the COVID-19 pandemic. They are highly effective against infection and substantially reduce the risk of severe disease, hospitalization, ICU admission, and death. However, their potential for attenuating long-term effects of a SARS-CoV-2 infection, commonly denoted as Long COVID, remains elusive and is still subject of debate. Such long-term effects can be effectively monitored at the individual level by analyzing physiological data collected by consumer-grade wearable sensors. Here, we investigate changes in resting heart rate, daily physical activity, and sleep duration in response to a SARS-CoV-2 infection stratified by vaccination status. Data was collected over a period of two years in the context of the German Corona Data Donation Project with currently around 190,000 monthly active donors. Compared to their unvaccinated counterparts, we find that vaccinated individuals on average experience smaller changes in their vital data that also return to normal levels more quickly. Likewise, extreme changes in vitals during the acute phase of the disease occur less frequently in vaccinated individuals. Our results solidify evidence that vaccines can mitigate long-term detrimental effects of SARS-CoV-2 infections both in terms of duration and magnitude. Furthermore, they demonstrate the value of large scale, high-resolution wearable sensor data in public health research.

New preprint: Rhythm of relationships in a social fish over the course of a full year in the wild
New preprint: Rhythm of relationships in a social fish over the course of a full year in the wild

Animals are expected to adjust their social behaviour to cope with challenges in their environment. Therefore, for fish populations, in temperate regions with seasonal and daily environmental oscillations, characteristic rhythms of social relationships should be pronounced. To date, most research concerning fish social networks and biorhythms has occurred in artificial laboratory environments or over confined temporal scales of days to weeks. By contrast, little is known about the social networks of wild, freely roaming fish, including how seasonal and diurnal rhythms modulate social networks over the course of a full year. The advent of high-resolution acoustic telemetry enables us to quantify detailed social interactions in the wild over time-scales sufficient to examine seasonal rhythms at whole-ecosystems scales. Our objective was to explore the rhythms of social interactions in a social fish population at various time-scales over one full year in the wild by examining high-resolution snapshots of dynamic social network. To that end, we tracked the behaviour of 36 adult common carp, Cyprinus carpio, in a 25 ha lake and constructed temporal social networks among individuals across various time-scales, where social interactions were defined by proximity. We compared the network structure to a temporally shuffled null model to examine the importance of social attraction, and checked for persistent characteristic groups (“friendships”) over time. The clustering within the carp social network tended to be more pronounced during daytime than nighttime throughout the year. Social attraction, particularly during daytime, was a key driver for interactions. Shoaling behavior substantially increased during daytime in the wintertime, whereas in summer carp interacted less frequently, but the interaction duration increased. Characteristic groups were more common in the summer months and during nighttime, where the social memory of carp lasted up to two weeks. We conclude that social relationships of carp change diurnally and seasonally. These patterns were likely driven by predator avoidance, seasonal shifts in lake temperature, visibility, forage availability and the presence of anoxic zones. The techniques we employed can be applied generally to high-resolution biotelemetry data to reveal social structures across other fish species at ecologically realistic scales.