Serological and cellular non-responders in a long-term cross-sectional cohort of SARS-CoV-2-specific PCR-positive individuals

During the first pandemic wave, the dark figure of SARS-CoV-2 exposure was estimated to be high, however, an accelerated loss of antibodies was reported after about 6 months post infection. This study was performed to unveil the group of serological non-responders (NR) in PCR+ individuals 6-9 months after the first pandemic SARS-CoV-2 wave in spring 2020 and to evaluate their specific cellular immune response towards spike-molecule compared to PCR- and not PCR-tested (NT) household contact persons. SARS-CoV-2-specific antibodies were quantified using a commercial ELISA kit. The synergistic binding strength was assessed as relative avidity index (RAI) using ammonium-thiocyanate as chaotropic agent. The specific IFNγ-production in response to spike-protein was determined in spot-forming-units (SFU) by ELISPOT-assay. In PCR- 50.0%, in PCR+ 35.3% and in NT 20.7% had undetectable IgG-anti-SARS-CoV-2 and were considered non-responders (NR). All seropositive responders from the PCR-, 45.5% of PCR+ and 43.0% of NT developed high avidity (RAI>60%). In serological responders, cellular responses were detected in 75.0% PCR-, 75.8% PCR+ and 66.7% NT. In serological NR, positive SFU were found in 75.0% PCR-, 22.2% PCR+ and 17.4% NT. Significantly higher stimulation-indices were seen in PCR+ responders compared to PCR+ serological NR. Our findings showed that also PCR- and household contact persons who were not tested (NT) developed SARS-CoV-2-specific humoral and cellular immune responses. The relatively large proportion of serological non-responders but also the proportion of cellular non-responders within the group of IgG-positive individuals after PCR+ infection underlines the need for COVID-19 vaccinations in the reconvalescent group.

Preventing outlaw biker crime in the Netherlands or just changing the dark figure? Estimating the impact of the Dutch whole-of-government approach on outlaw biker crime using interrupted time series analysis

Confronted with growing public concern about violence and other serious crime committed by outlaw motorcycle clubs, in 2012 the Dutch government launched a whole-of-government approach to discourage club membership and organized criminal behaviour. The whole-of-government approach included a zero tolerance policy towards crimes committed by outlaw bikers and increased law enforcement and prosecutorial attention towards members of outlaw motorcycle groups (OMCG members) and their support clubs. In this study, we estimate the effects of the whole-of-government approach on the level of prosecutorial charges levied against the Dutch biker population. We do so by applying (quasi-experimental) interrupted time series analysis to the conviction data available on 1617 Dutch OMCG members and 473 support club members in four recorded crime categories: overall crime, violent crime, organized crime and traffic offences. Although caveats remain, results indicate that the whole-of-government approach has a causal effect on the criminal involvement of OMCG and support club members, but that the nature of this effect depends on the type of crime and the subsample in question. Overall crime in the total sample seems unaffected by the approach, whereas organized crime committed by OMCG members is shown to decrease. We discuss whether the patterns observed are due to behavioural changes in OMCG and support club members, or whether they result from changes in police practices and, consequently, a changing dark figure of crime. We conclude our article with some reflections on future research.

Intimate Partner Violence during the COVID-19 Pandemic: A Review of the Phenomenon from Victims’ and Help Professionals’ Perspectives

Social isolation is considered one of the main risk factors leading to intimate partner violence episodes; this evidence also emerged during the application of stay-at-home policies to contain the COVID-19 pandemic. For this reason, we aimed to collect data on intimate partner violence over the last year, comparing data reported by victims with data collected by help professionals. In accordance with PRISMA guidelines, through keywords related to abuse, pandemic and containment measures, 3174 articles were identified for screening. After full-text reading and risk of bias analysis, 19 studies were included, and a thematic synthesis was conducted according to two categories: “studies with victims” and “studies with help professionals”. The results of the present review showed that there were significant differences between the data provided by victims and the data collected by health care facilities and police departments; additionally, differences among different forms and severity of victimization emerged. The results have been discussed according to the literature; in particular, we reflected on how containment measures have apparently made it more difficult for victims to report, thus making the existence of the dark figure of crime even more salient.

Estimates and determinants of SARS-CoV-2 seroprevalence and infection fatality ratio using latent class analysis: the population-based Tirschenreuth study in the hardest-hit German county in spring 2020

SARS-CoV-2 infection fatality ratios (IFR) remain controversially discussed with implications for political measures, but the number of registered infections depends on testing strategies and deduced case fatality ratios (CFR) are poor proxies for IFR. The German county of Tirschenreuth suffered a severe SARS-CoV-2 outbreak in spring 2020 with particularly high CFR. To estimate seroprevalence, dark figure, and IFR for the Tirschenreuth population aged ≥14 years in June/July 2020 with misclassification error control, we conducted a population-based study, including home visits for elderly, and analyzed 4203 participants for SARS-CoV-2 antibodies via three antibody tests (64% of our random sample). Latent class analysis yielded 8.6% standardized county-wide seroprevalence, dark figure factor 5.0, and 2.5% overall IFR. Seroprevalence was two-fold higher among medical workers and one third among current smokers with similar proportions of registered infections. While seroprevalence did not show an age-trend, the dark figure was 12.2 in the young versus 1.7 for ≥85-year-old. Age-specific IFRs were <0.5% below 60 years of age, 1.0% for age 60-69, 13.2% for age 70+, confirming a previously reported age-model for IFR. Senior care homes accounted for 45% of COVID-19-related deaths, reflected by an IFR of 7.5% among individuals aged 70+ and an overall IFR of 1.4% when excluding senior care home residents from our computation. Our data underscore senior care home infections as key determinant of IFR additionally to age, insufficient targeted testing in the young, and the need for further investigations on behavioral or molecular causes of the fewer infections among current smokers.

Spotlight on the dark figure: Exhibiting dynamics in the case detection ratio of COVID-19 infections in Germany

The case detection ratio of COVID-19 infections varies over time due to changing testing capacities, modified testing strategies and also, apparently, due to the dynamics in the number of infected itself. In this paper we investigate these dynamics by jointly looking at the reported number of detected COVID-19 infections with non-fatal and fatal outcomes in different age groups in Germany. We propose a statistical approach that allows us to spotlight the case detection ratio and quantify its changes over time. With this we can adjust the case counts reported at different time points so that they become comparable. Moreover we can explore the temporal development of the real number of infections, shedding light on the dark number. The results show that the case detection ratio has increased and, depending on the age group, is four to six times higher at the beginning of the second wave compared to what it was at the peak of the first wave. The true number of infection in Germany in October was considerably lower as during the peak of the first wave, where only a small fraction of COVID-19 infections were detected. Our modelling approach also allows quantifying the effects of different testing strategies on the case detection ratio. The analysis of the dynamics in the case detection rate and in the true infection figures enables a clearer picture of the course of the COVID-19 pandemic.

Tamna i svijetla strana tamne brojke kriminala: o izazovima istraživanja nepoznanica i blagoslovu neznanja

In the paper at hand the authors critically analyse the state of the art in the research into the dark figure of crime, as well as the conceptual and methodological challenges that are inherent to this kind of research. They do so based on current international, foreign and domestic studies, with the goal of highlighting not only the commonly stressed ‘dark side’ of the dark figure of crime, but also in order to raise awareness of its almost completely disregarded ‘bright side’. In this regard the bright side of the dark figure of crime relates to the thesis of the so-called preventive effect of ignorance (germ. Präventivwirkung des Nichtwissens) and presents a phenomenon with a vastly important positive function which has thus far been completely neglected in the domestic criminological and criminal law discourse. This function basically ensures that the criminal justice response to criminal behaviour is perceived as comprehensive and effective. Without such perception the general preventive effect, as envisaged by criminal law, would be unsubstantial. By highlighting the dark figure’s bright side, the authors on the one hand aspire to make a scientific contribution to the comprehensiveness of the discourse about the dark figure of crime in Croatia, while on the other hand they illustrate the unsolvable conceptual and almost unavoidable methodological challenges which are inherent to the attempts of shedding light upon the dark figure of crime. The authors’ intention is neither to devalorize dark figure research in general, nor to bring about resignation with regard to enterprises seeking to reveal the dark figure of certain types of crime by means of victimisation or self-report studies. It is rather the intention of the authors to comprehensively and critically examine the dark figure phenomenon in all its complexity, vividness and mutual interwovenness with the criminal justice actors, and while doing so to neither underestimate the dark figure’s negative cognitive effects, nor to ignore its overly positive function in the service of norm stabilisation and sustaining the repressive system, as well as society as a whole.

Measuring the Dark Figure of Crime in Geographic Areas: Small Area Estimation from the Crime Survey for England and Wales

For decades, criminologists have been aware of the severe consequences of the dark figure of police records for crime prevention strategies. Crime surveys are developed to address the limitations of police statistics as crime data sources, and estimates produced from surveys can mitigate biases in police data. This paper produces small area estimates of crimes unknown to the police at local and neighbourhood levels from the Crime Survey for England and Wales to explore the geographical inequality of the dark figure of crime. The dark figure of crime is larger not only in small cities that are deprived but also in wealthy municipalities. The dark figure is also larger in suburban, low-housing neighbourhoods with large concentrations of unqualified citizens, immigrants and non-Asian minorities.