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Background The infection fatality rate (IFR) of the Coronavirus Disease 2019 (COVID-19) is one of the most discussed figures in the context of this pandemic. In contrast to the case fatality rate (CFR), the IFR depends on the total number of infected individuals – not just on the number of confirmed cases. In order to estimate the IFR, several seroprevalence studies have been or are currently conducted. Methods Using German COVID-19 surveillance data and age-group specific IFR estimates from multiple international studies, this work investigates time-dependent variations in effective IFR over the course of the pandemic. Three different methods for estimating (effective) IFRs are presented: (a) population-averaged IFRs based on the assumption that the infection risk is independent of age and time, (b) effective IFRs based on the assumption that the age distribution of confirmed cases approximately reflects the age distribution of infected individuals, and (c) effective IFRs accounting for age- and time-dependent dark figures of infections. Results Effective IFRs in Germany are estimated to vary over time, as the age distributions of confirmed cases and estimated infections are changing during the course of the pandemic. In particular during the first and second waves of infections in spring and autumn/winter 2020, there has been a pronounced shift in the age distribution of confirmed cases towards older age groups, resulting in larger effective IFR estimates. The temporary increase in effective IFR during the first wave is estimated to be smaller but still remains when adjusting for age- and time-dependent dark figures. A comparison of effective IFRs with observed CFRs indicates that a substantial fraction of the time-dependent variability in observed mortality can be explained by changes in the age distribution of infections. Furthermore, a vanishing gap between effective IFRs and observed CFRs is apparent after the first infection wave, while an increasing gap can be observed during the second wave. Conclusions The development of estimated effective IFR and observed CFR reflects the changing age distribution of infections over the course of the COVID-19 pandemic in Germany. Further research is warranted to obtain timely age-stratified IFR estimates, particularly in light of new variants of the virus.

Introduction Denmark is one of the safest places for childbirth, yet some women report dissatisfaction with their maternity care. However, some negative birth experiences may remain unreported due to thresholds for complaining. The study aimed to identify patterns of unreported negative birth experiences and to quantify the extent of these dark figures. Material and Methods A survey was distributed to 3081 women who gave birth at a Danish hospital in 2022, resulting in 1022 responses (response rate = 33.2%). The women reported their birth experiences in categories based on the Healthcare Complaints Analysis Tool (HCAT), specifying problems, harm caused, and whether they had filed a complaint or intended to. Dark figure ratios regarding problems and harm levels were calculated by comparing unreported negative experiences to formally filed complaints based on the survey responses, covering each problem type and harm level. Results Of the 1022 respondents, 336 (32.9%) women reported negative birth experiences, yet only 26 women had filed complaints. The remaining 310 unreported cases comprised 787 problems across HCAT categories. The most frequent problems were about communication and quality. The highest dark figure ratios were found within the management domain comprising institutional processes (13.0) and environment (9.9). The dark figure ratios showed an inverse relationship with harm severity, being highest for minimal (19.5) and minor (21.2) harm levels and decreasing for moderate (5.5), major (4.8) and catastrophic (0.3) harm levels. Conclusions This study demonstrates a substantial underestimation of negative birth experiences when relying solely on formal complaints, with dark figure ratios ranging from 4.8 to 13, depending on the issue. The inverse relationship between harm severity and dark figure ratios suggests a threshold for filing a complaint, as the likelihood of reporting increases with greater harm. These findings provide novel insights into unreported maternity care experiences, highlighting the need to integrate patient experiences into healthcare improvements. Patient complaints represent only a fraction of problems experienced during childbirth. Among 336 women with negative birth experiences, only 26 filed complaints, revealing a dark figure with up to 13 times more unreported issues. Integrating complaint data with dark figure estimates enables a more accurate assessment of the true scope and nature of patient‐perceived problems.

A victim's decision to report the incidence of crime to the police is a significant determinant in the fight against dark figures in official crime data. When victims decline to disclose crimes to the police, the criminal justice system's capabilities are severely undermined, and one of its most vital functions (to deter crime) is undermined. However, not reporting an incidence of crime to the police is subjective decision victims mostly make based on personal analysis of \"cost\" and \"benefits\" associated with such report. Therefore, to understand victims' rational decisions in crime reporting, binary logistic regression is used to predict the likelihood of reporting the incident of crime to the police using the assumptions of rational choice theory, and data from National Crime Panel Victimization Data (2018). The findings of the study showed that victims would be willing to report the incidence of a crime if they can recognize the identity of the offender and if such crimes are considered serious/dangerous. Victims may feel danger in situations like this and be \"compelled\" to report the crime to the police because of the high cost associated with not reporting. However, not when the same crime is committed repeatedly.

A reduction in property crime has been a central feature of criminological discussion in the last 25 years, and numerous studies have used police statistics to identify a drop throughout the Western world. However, fraud, which is included in a broad definition of property crime, has typically not been considered in the analysis. This study examines fraud in the Spanish and European context to further understanding of its nature, prevalence, evolution and role in the overall panorama of property crime. Furthermore, the present study explores the extent to which we are experiencing widespread fraud underreporting to police and the implications of this for crime control policy. To this end, the present paper analyses secondary data provided by the Spanish Ministry of Interior, Spanish and European central banking authorities as well as large-scale victimization surveys from a number of European countries. In contrast to other property crimes, the findings indicate that cyber fraud is rising and that reporting is considerably lower. Some of the main reasons for reporting or not reporting fraud victimization are also identified. The dark figure of fraud suggests the design and evaluation of policing and crime prevention policies based solely on police statistics may be inadequate.

Background/Objectives: Epidemiological modeling is a vital tool for managing pandemics, including SARS-CoV-2. Advances in the understanding of epidemiological dynamics and access to new data sources necessitate ongoing adjustments to modeling techniques. In this study, we present a significantly expanded and updated version of our previous SARS-CoV-2 model formulated as input–output non-linear dynamical systems (IO-NLDS). Methods: This updated framework incorporates age-dependent contact patterns, immune waning, and new data sources, including seropositivity studies, hospital dynamics, variant trends, the effects of non-pharmaceutical interventions, and the dynamics of vaccination campaigns. Results: We analyze the dynamics of various datasets spanning the entire pandemic in Germany and its 16 federal states using this model. This analysis enables us to explore the regional heterogeneity of model parameters across Germany for the first time. We enhance our estimation methodology by introducing constraints on parameter variation among federal states to achieve this. This enables us to reliably estimate thousands of parameters based on hundreds of thousands of data points. Conclusions: Our approach is adaptable to other epidemic scenarios and even different domains, contributing to broader pandemic preparedness efforts.

Google Trends (GT) data could potentially supplement traditional crime measurement strategies, allowing criminologists to better understand crime statistics on a macro level. This study assesses the validity of GT crime estimates. The findings indicate that GT data are reliable for estimating MVT, larceny, and rape. Additionally, we illustrate how to use GT to identify places with high rates of unreported offenses. The results of this study demonstrate the feasibility of leveraging open-source big data such as GT to supplement traditional sources of crime data, particularly for categories of crime with substantial underreporting rates. Results suggest the GT rape measure may be a more accurate estimate of the true incidence of rape than the measure drawn from the Uniform Crime Report (UCR). The limitations associated with the use of GT to generate estimates of crime are also discussed.

This research centres on the unreported cases of violent crimes against people with same-sex attraction and their reasons for not reporting crimes to the police. Despite the existence of legal protections, several crimes against LGBTQ+ individuals go unreported, creating a significant gap in the understanding of the true extent of this issue. A qualitative purposive sampling was utilised, and semi-structured interviews were carried out with 15 participants who have been victims of crimes and reside in Durban KwaZulu-Natal. The findings indicate that individuals who are victimised due to their sexual orientation choose not to report crimes to the police due to reasons such as not trusting the police, shame and blaming themselves for the crimes, and fear of their families finding out about their sexuality. The study proposes that the police are sensitised on matters related to sexual orientation and how to handle such cases effectively.

PurposeThis study aims to use a novel data set of 636 murderers sentenced to death in California to investigate homicide offenses that are committed but not prosecuted or officially solved, a concept known as the dark figure of crime.Design/methodology/approachUaing appellate records from the Supreme Court of California, which contain extensive information about the offender’s background, criminal offense history and mental health diagnoses, it was revealed that one-third of the offenders in the sample have additional homicide offenses for which they likely bear responsibility, but were not prosecuted.FindingsMost of these involve one or two additional homicides, though a wide range was observed spanning 0 to 93 additional victims. Those with a dark figure of murder and unsolved homicides had substantially more prior arrests, convictions and prison incarcerations and were higher in psychopathy, sexual sadism, homicidal ideation and gang involvement than offenders without a dark figure. Psychopathy and homicidal ideation were the most robust predictors of both the presence and magnitude of a dark figure of murder and unsolved homicides, whereas sexual sadism was inconsistently associated.Originality/valueA disproportionate amount of the unsolved murders in the USA are likely perpetrated by the most pathological types of offenders, those with extensive antisocial careers and severe externalizing psychopathology.

PurposeResearch on women who sexually abuse children is relatively scarce and tends to rely on small or unrepresentative convenience samples. The purpose of the current descriptive study is to examine characteristics female perpetrators of child sexual abuse using a large and contemporary dataset.Design/methodology/approachThis study analyzes data collected by the National Child Abuse and Neglect Data System, which is a census of all child protective services investigations or assessments conducted in all 50 states, as well as in the District of Columbia and Puerto Rico from October 1, 2018, to September 30, 2019.FindingsOnly substantiated cases of sexual abuse were analyzed (n = 51,442 cases). Overall, 7.6% of the perpetrators were female, though the percentage of female perpetrators varied dramatically across states from less than 1% to over 36%. Female perpetrators tended to have younger victims than did male perpetrators. For children aged 2 or less, female perpetrators constituted approximately 20% of the abusers. Female perpetrators were more likely to victimize male and female children, whereas male perpetrators predominantly had female victims. More female perpetrators had a prior finding of maltreatment than did male perpetrators (32.3% vs 23.5%).Research limitations/implicationsThese findings add to the limited research base on female perpetrators of child sexual abuse and highlight avenues for further research into the differences between male and female sexual abusers.Originality/valueThis study is a replication of previous research but also provides additional novel findings.

Current European research estimates the number of undetected active SARS-CoV-2 infections (dark figure) to be two- to 130-fold the number of detected cases. We revisited the population-wide antigen tests in Slovakia and South Tyrol and calculated the dark figure of active cases in the vulnerable populations and the number of undetected active cases per detected active case at the time of the population-wide tests. Our analysis follows three steps: using the sensitivities and specificities of the used antigen tests, we first calculated the number of test-positive individuals and the proportion of actual positives in those who participated in the antigen tests. We then calculated the dark figure in the total population of Slovakia and South Tyrol, respectively. Finally, we calculated the ratio of the dark figure in the vulnerable population to the number of newly detected infections through PCR tests. Per one positive PCR result, another 0.15 to 0.71 cases must be added in South Tyrol and 0.01 to 1.25 cases in Slovakia. The dark figure was in both countries lower than assumed by earlier studies.