Evaluation of predictive models to determine final outcome for feedlot cattle based on information available at first treatment for bovine respiratory disease.

OBJECTIVE: To evaluate predictive model ability to determine whether an animal finished the feeding period using data known at first treatment for bovine respiratory disease (BRD). Additional comparisons evaluated the potential benefits of predictions by adding weather data, utilizing balancing techniques, and creating models for individual feedyards. ANIMALS: This retrospective study included animal, pen, and feedyard data from 12 US feedyards from 2016 to 2021. The final dataset consisted of 96,382 BRD cases of which 14.2% did not finish the feeding phase. PROCEDURES: Five predictive models were trained and underwent threshold probability adjustment to maximize F1 score. Model performance was evaluated using accuracy, sensitivity specificity, positive and negative predictive values, and area under the receiver operating characteristics curve (AUC). RESULTS: Overall, model performance was low with a median AUC value of 0.675. The addition of weather data had little effect on AUC but resulted in more variation in sensitivity and specificity. Resampling the dataset had a limited effect on performance. Individual feedlot models had higher AUC values than others with the decision tree typically performing best in most feedyards. CLINICAL RELEVANCE: Results indicated some utility of predictive models evaluating BRD cases to predict cattle that did not finish the feeding phase. These models could be valuable in assisting health providers making decisions on individual cases.

Female crash fatality risk relative to males for similar physical impacts.

OBJECTIVE: This paper estimates the latest trends regarding the effect of sex on driver-side or right-front passenger-side occupant fatalities in fatal crashes. The focus is on how recent model year (MY) light vehicles with advanced occupant protection technologies compare to older vehicles without these protections in terms of female fatality risk relative to males. METHODS: Data from the Fatality Analysis Reporting System (FARS) from 1975 to 2019 is used to calculate estimates of female fatality risk relative to males using logistic regression models and the double-pair comparison method. These estimates are calculated in various groups of MY vehicles and occupant protection systems. Occupant protection systems observed are the use of seat belts, and the availability of dual air bags, pretensioners and load limiters in the vehicles. All vehicles used include occupants age 16 to 96. Occupants studied include front-row occupants (drivers and right-front (RF) passengers). The average between drivers and RF passengers is also calculated. RESULTS: Incremental female fatality risk estimates versus males are reduced in newer MY vehicles. Incremental relative risks for female front-row occupants (average of drivers and right-front passengers) are found to be 19.9% (± 1.3) in fatal crashes in MY 1960-1999 vehicles, and 9.4% (± 2.2) percent in MY 2000-2020 vehicles. The difference in fatality risk between females and males is further reduced when looking at MY 2010-2020 vehicles (6.3 ± 5.4%) compared to MY 1960-2009 vehicles (18.3 ± 1.2%). Incremental fatality risk estimates also decrease in vehicles with newer generations of occupant protection systems regardless of MY. When occupants are belted in vehicles with the latest generation of modern occupant protection systems (dual air bags, seat belt pretensioners and load limiters), the estimated female fatality risk relative to males (average of drivers and right-front passengers) becomes 5.8% (± 3.8), which is lower than for belted occupants in vehicles without those occupant protections. CONCLUSIONS: The disparity in fatality risk between males and females for the same physical impacts is reduced for later MY vehicles, as well as vehicles with more advanced occupant protection systems.

Evaluation of First Treatment Timing, Fatal Disease Onset, and Days from First Treatment to Death Associated with Bovine Respiratory Disease in Feedlot Cattle.

Bovine respiratory disease (BRD) is a frequent beef cattle syndrome. Improved understanding of the timing of BRD events, including subsequent deleterious outcomes, promotes efficient resource allocation. This study's objective was to determine differences in timing distributions of initial BRD treatments (Tx1), days to death after initial treatment (DTD), and days after arrival to fatal disease onset (FDO). Individual animal records for the first BRD treatment (n = 301,721) or BRD mortality (n = 19,332) were received from 25 feed yards. A subset of data (318-363 kg; steers/heifers) was created and Wasserstein distances were used to compare temporal distributions of Tx1, FDO, and DTD across genders (steers/heifers) and the quarter of arrival. Disease frequency varied by quarter with the greatest Wasserstein distances observed between Q2 and Q3 and between Q2 and Q4. Cattle arriving in Q3 and Q4 had earlier Tx1 events than in Q2. Evaluating FDO and DTD revealed the greatest Wasserstein distance between cattle arriving in Q2 and Q4, with cattle arriving in Q2 having later events. Distributions of FDO varied by gender and quarter and typically had wide distributions with the largest 25-75% quartiles ranging from 20 to 80 days (heifers arriving in Q2). The DTD had right-skewed distributions with 25% of cases occurring by days 3-4 post-treatment. Results illustrate temporal disease and outcome patterns are largely right-skewed and may not be well represented by simple arithmetic means. Knowledge of typical temporal patterns allows cattle health managers to focus disease control efforts on the correct groups of cattle at the appropriate time.

Sustained Low Incidence of Severe and Fatal COVID-19 Following Widespread Infection Induced Immunity after the Omicron (BA.1) Dominant in Gauteng, South Africa: An Observational Study.

We conducted an epidemiologic survey to determine the seroprevalence of SARS-CoV-2 anti-nucleocapsid (anti-N) and anti-spike (anti-S) protein IgG from 1 March to 11 April 2022 after the BA.1-dominant wave had subsided in South Africa and prior to another wave dominated by the BA.4 and BA.5 (BA.4/BA.5) sub-lineages. We also analysed epidemiologic trends in Gauteng Province for cases, hospitalizations, recorded deaths, and excess deaths were evaluated from the inception of the pandemic through 17 November 2022. Despite only 26.7% (1995/7470) of individuals having received a COVID-19 vaccine, the overall seropositivity for SARS-CoV-2 was 90.9% (95% confidence interval (CI), 90.2 to 91.5) at the end of the BA.1 wave, and 64% (95% CI, 61.8 to 65.9) of individuals were infected during the BA.1-dominant wave. The SARS-CoV-2 infection fatality risk was 16.5-22.3 times lower in the BA.1-dominant wave compared with the pre-BA.1 waves for recorded deaths (0.02% vs. 0.33%) and estimated excess mortality (0.03% vs. 0.67%). Although there are ongoing cases of COVID-19 infections, hospitalization and death, there has not been any meaningful resurgence of COVID-19 since the BA.1-dominant wave despite only 37.8% coverage by at least a single dose of COVID-19 vaccine in Gauteng, South Africa.

Trends of the COVID-19 dynamics in 2022 and 2023 vs. the population age, testing and vaccination levels.

Introduction: The population, governments, and researchers show much less interest in the COVID-19 pandemic. However, many questions still need to be answered: why the much less vaccinated African continent has accumulated 15 times less deaths per capita than Europe? or why in 2023 the global value of the case fatality risk is almost twice higher than in 2022 and the UK figure is four times higher than the global one? Methods: The averaged daily numbers of cases DCC and death DDC per million, case fatality risks DDC/DCC were calculated for 34 countries and regions with the use of John Hopkins University (JHU) datasets. Possible linear and non-linear correlations with the averaged daily numbers of tests per thousand DTC, median age of population A, and percentages of vaccinations VC and boosters BC were investigated. Results: Strong correlations between age and DCC and DDC values were revealed. One-year increment in the median age yielded 39.8 increase in DCC values and 0.0799 DDC increase in 2022 (in 2023 these figures are 5.8 and 0.0263, respectively). With decreasing of testing level DTC, the case fatality risk can increase drastically. DCC and DDC values increase with increasing the percentages of fully vaccinated people and boosters, which definitely increase for greater A. After removing the influence of age, no correlations between vaccinations and DCC and DDC values were revealed. Discussion: The presented analysis demonstrates that age is a pivot factor of visible (registered) part of the COVID-19 pandemic dynamics. Much younger Africa has registered less numbers of cases and death per capita due to many unregistered asymptomatic patients. Of great concern is the fact that COVID-19 mortality in 2023 in the UK is still at least 4 times higher than the global value caused by seasonal flu.

Demographics of COVID-19 hospitalisations and related fatality risk patterns.

The assessment of hospitalisations and intensive care is crucial for planning health care resources needed over the course of the coronavirus disease 2019 (COVID-19) pandemic. Nonetheless, comparative empirical assessments of COVID-19 hospitalisations and related fatality risk patterns on a large scale are lacking. This paper exploits anonymised, individual-level data on SARS-CoV-2 confirmed infections collected and harmonized by the European Centre for Disease Prevention and Control to profile the demographics of COVID-19 hospitalised patients across nine European countries during the first pandemic wave (February - June 2020). We estimate the role of demographic factors for the risk of in-hospital mortality, and present a case study exploring individuals' comorbidities based on a subset of COVID-19 hospitalised patients available from the Dutch health system. We find that hospitalisation rates are highest among individuals with confirmed SARS-CoV-2 infection who are not only older than 70 years, but also 50-69 years. The latter group has a longer median time between COVID-19 symptoms' onset and hospitalisation than those aged 70+ years. Men have higher hospitalisation rates than women at all ages, and particularly above age 50. Consistently, men aged 50-59 years have a probability of hospitalisation almost double than women do. Although the gender imbalance in hospitalisation remains above age 70, the gap between men and women narrows at older ages. Comorbidities play a key role in explaining selection effects of COVID-19 confirmed positive cases requiring hospitalisation. Our study contributes to the evaluation of the COVID-19 burden on the demand of health-care during emergency phases. Assessing intensity and timing dimensions of hospital admissions, our findings allow for a better understanding of COVID-19 severe outcomes. Results point to the need of suitable calibrations of epidemiological projections and (re)planning of health services, enhancing preparedness to deal with infectious disease outbreaks.

Age-Dependent Effects of COVID-19 Vaccine and of Healthcare Burden on COVID-19 Deaths, Tokyo, Japan.

COVID-19 vaccine effectiveness against death in Japan remains unknown. Furthermore, although evidence indicates that healthcare capacity influences case-fatality risk (CFR), it remains unknown whether this relationship is mediated by age. With a modeling study, we analyzed daily COVID-19 cases and deaths during January-August 2021 by using Tokyo surveillance data to jointly estimate COVID-19 vaccine effectiveness against death and age-specific CFR. We also examined daily healthcare operations to determine the association between healthcare burden and age-specific CFR. Among fully vaccinated patients, vaccine effectiveness against death was 88.6% among patients 60-69 years of age, 83.9% among patients 70-79 years of age, 83.5% among patients 80-89 years of age, and 77.7% among patients >90 years of age. A positive association of several indicators of healthcare burden with CFR among patients >70 years of age suggested an age-dependent effect of healthcare burden on CFR in Japan.

The association between data collected in IIHS side crash tests and real-world driver death risk.

OBJECTIVE: The Insurance Institute for Highway Safety (IIHS) side crash test has led to crashworthiness improvements, and both overall and component ratings have been shown to be associated with real-world death risk. The objective of the current study was to investigate how crash test measurements, on which component ratings are based, are associated with real-world death risk. METHODS: Driver deaths and police-reported crash involvements were extracted from national crash databases for left-impact crashes of passenger vehicles with standard-feature, head-protecting side airbags for calendar years 2000-2016. Risk of driver death in left-impact crashes was estimated as the number of driver deaths divided by the number of driver police-reported crash involvements. Logistic regression was used to estimate the association between crash test measurements and death risk, controlling for driver and vehicle information. RESULTS: All crash test measurements investigated were associated with driver death risk. For instance, a 10 cm reduction in B-pillar intrusion, a measure of post-crash occupant survival space, was associated with 30% lower driver death risk. For most measures, at least 75% of study vehicles were within the good rating boundary for that measure, and still these measures were associated with driver death risk. Fewer than half of study vehicles earned a good rating for B-pillar intrusion. CONCLUSION: Because performance in measures collected in the IIHS side crash test are strongly associated with real-world driver death risk, one of the ways the crash test program could continue to encourage crashworthiness improvements is by requiring stronger performance on these measures.

Unexposed populations and potential COVID-19 hospitalisations and deaths in European countries as per data up to 21 November 2021.

We estimate the potential remaining COVID-19 hospitalisation and death burdens in 19 European countries by estimating the proportion of each country's population that has acquired immunity to severe disease through infection or vaccination. Our results suggest many European countries could still face high burdens of hospitalisations and deaths, particularly those with lower vaccination coverage, less historical transmission and/or older populations. Continued non-pharmaceutical interventions and efforts to achieve high vaccination coverage are required in these countries to limit severe COVID-19 outcomes.

Differences in the case fatality risks associated with SARS-CoV-2 Delta and non-Delta variants in relation to vaccine coverage: An early ecological study in the United Kingdom.

The circulation of SARS-CoV-2 Delta (i.e., B.1.617.2) variants challenges the pandemic control. Our analysis showed that in the United Kingdom (UK), the reported case fatality ratio (CFR) decreased from May to July 2021 for non-Delta variant, whereas the decreasing trends of the CFR of Delta variant appeared weak and insignificant. The association between vaccine coverage and CFR might be stratified by different circulating variants. Due to the limitation of ecological study design, the interpretation of our results should be treated with caution.

Risk factors associated with severe hospital burden of COVID-19 disease in Regione Lombardia: a cohort study.

BACKGROUND: Understanding the risk factors associated with hospital burden of COVID-19 is crucial for healthcare planning for any future waves of infection. METHODS: An observational cohort study is performed, using data on all PCR-confirmed cases of COVID-19 in Regione Lombardia, Italy, during the first wave of infection from February-June 2020. A multi-state modelling approach is used to simultaneously estimate risks of progression through hospital to final outcomes of either death or discharge, by pathway (via critical care or not) and the times to final events (lengths of stay). Logistic and time-to-event regressions are used to quantify the association of patient and population characteristics with the risks of hospital outcomes and lengths of stay respectively. RESULTS: Risks of severe outcomes such as ICU admission and mortality have decreased with month of admission (for example, the odds ratio of ICU admission in June vs March is 0.247 [0.120-0.508]) and increased with age (odds ratio of ICU admission in 45-65 vs 65 + age group is 0.286 [0.201-0.406]). Care home residents aged 65 + are associated with increased risk of hospital mortality and decreased risk of ICU admission. Being a healthcare worker appears to have a protective association with mortality risk (odds ratio of ICU mortality is 0.254 [0.143-0.453] relative to non-healthcare workers) and length of stay. Lengths of stay decrease with month of admission for survivors, but do not appear to vary with month for non-survivors. CONCLUSIONS: Improvements in clinical knowledge, treatment, patient and hospital management and public health surveillance, together with the waning of the first wave after the first lockdown, are hypothesised to have contributed to the reduced risks and lengths of stay over time.

SARS-CoV-2 infections in 165 countries over time.

BACKGROUND: Understanding the dynamics of the COVID-19 pandemic and evaluating the efficacy of control measures requires knowledge of the number of infections over time. This number, however, often differs from the number of confirmed cases because of a large fraction of asymptomatic infections and different testing strategies. METHODS: This study uses death count statistics, age-dependent infection fatality risks, and stochastic modeling to estimate the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections among adults (aged 20 years or older) in 165 countries over time, from early 2020 until June 25, 2021. The accuracy of the approach is confirmed through comparison with previous nationwide seroprevalence surveys. RESULTS: The estimates presented reveal that the fraction of infections that are detected vary widely over time and between countries, and hence confirmed cases alone often yield a false picture of the pandemic. As of June 25, 2021, the nationwide cumulative fraction of SARS-CoV-2 infections (cumulative infections relative to population size) was estimated as 98% (95% confidence interval [CI] 93-100%) for Peru, 83% (95% CI 61-94%) for Brazil, and 36% (95% CI 23-61%) for the United States. CONCLUSIONS: The time-resolved estimates presented expand the possibilities to study the factors that influenced and still influence the pandemic's progression in 165 countries.

Geographical risk of fatal and non-fatal injuries among adults in Norway.

INTRODUCTION: A rural gradient in trauma mortality disfavoring remote inhabitants is well known. Previous studies have shown higher risk of traumatic deaths in rural areas in Norway, combined with a paradoxically decreased prevalence of non-fatal injuries. We investigated the risk of fatal and severe non-fatal injuries among all adults in Norway during 2002-2016. METHODS: All traumatic injuries and deaths among persons with a residential address in Norway from 2002-2016 were included. Data were collected from the Norwegian National Cause of Death Registry and the Norwegian Patient Registry. All cases were stratified into six groups of centrality based on Statistics Norway's classification system, from most urban (group one) to least urban/most rural (group six). Mortality and injury rates were calculated per 100,000 inhabitants per year. RESULTS: The mortality rate differed significantly among the centrality groups (p<0.05). The rate was 64.2 per 100,000 inhabitants/year in the most urban group and 78.6 per 100,000 inhabitants/year in the most rural group. The lowest mortality rate was found in centrality group 2 (57.9 per 100,000 inhabitants/year). For centrality group 6 versus group 2, the risk of death was increased (relative risk, 1.36; 95%CI: 1.11-1.66; p<0.01). The most common causes of death were transport injury, self-harm, falls, and other external causes. The steepest urban-rural gradient was seen for transport injuries, with a relative risk of 3.32 (95%CI: 1.81-6.10; p<0.001) for group 6 compared with group 1. There was a significantly increasing risk for severe non-fatal injuries from urban to rural areas. Group 2 had the lowest risk for non-fatal injuries (1531 per 100,000 inhabitants/year) and group 6 the highest (1803 per 100,000 inhabitants/year). The risk for non-fatal injuries increased with increasing rurality, with a relative risk of 1.07 (95%CI: 1.02-1.11; p<0.01) for group 6 versus group 1. CONCLUSIONS: Fatal and non-fatal injury risks increased in parallel with increasing rurality. The lowest risk was in the second most urban region, followed by the most urban (capital) region, yielding a J-shaped risk curve. Transport injuries had the steepest urban-rural gradient.

Estimating case fatality risk of severe Yellow Fever cases: systematic literature review and meta-analysis.

BACKGROUND: Case fatality risk (CFR), commonly referred to as a case fatality ratio or rate, represents the probability of a disease case being fatal. It is often estimated for various diseases through analysis of surveillance data, case reports, or record examinations. Reported CFR values for Yellow Fever vary, offering wide ranges. Estimates have not been found through systematic literature review, which has been used to estimate CFR of other diseases. This study aims to estimate the case fatality risk of severe Yellow Fever cases through a systematic literature review and meta-analysis. METHODS: A search strategy was implemented in PubMed and Ovid Medline in June 2019 and updated in March 2021, seeking reported severe case counts, defined by fever and either jaundice or hemorrhaging, and the number of those that were fatal. The searches yielded 1,133 studies, and title/abstract review followed by full text review produced 14 articles reporting 32 proportions of fatal cases, 26 of which were suitable for meta-analysis. Four studies with one proportion each were added to include clinical case data from the recent outbreak in Brazil. Data were analyzed through an intercept-only logistic meta-regression with random effects for study. Values of the I2 statistic measured heterogeneity across studies. RESULTS: The estimated CFR was 39 % (95 % CI: 31 %, 47 %). Stratifying by continent showed that South America observed a higher CFR than Africa, though fewer studies reported estimates for South America. No difference was seen between studies reporting surveillance data and studies investigating outbreaks, and no difference was seen among different symptom definitions. High heterogeneity was observed across studies. CONCLUSIONS: Approximately 39 % of severe Yellow Fever cases are estimated to be fatal. This study provides the first systematic literature review to estimate the CFR of Yellow Fever, which can provide insight into outbreak preparedness and estimating underreporting.

Meta-analysis and adjusted estimation of COVID-19 case fatality risk in India and its association with the underlying comorbidities.

Management of coronavirus disease 2019 (COVID-19) in India is a top government priority. However, there is a lack of COVID-19 adjusted case fatality risk (aCFR) estimates and information on states with high aCFR. Data on COVID-19 cases and deaths in the first pandemic wave and 17 state-specific geodemographic, socio-economic, health and comorbidity-related factors were collected. State-specific aCFRs were estimated, using a 13-day lag for fatality. To estimate country-level aCFR in the first wave, state estimates were meta-analysed based on inverse-variance weighting and aCFR as either a fixed- or random-effect. Multiple correspondence analyses, followed by univariable logistic regression, were conducted to understand the association between aCFR and geodemographic, health and social indicators. Based on health indicators, states likely to report a higher aCFR were identified. Using random- and fixed-effects models, cumulative aCFRs in the first pandemic wave on 27 July 2020 in India were 1.42% (95% CI 1.19%-1.70%) and 2.97% (95% CI 2.94%-3.00%), respectively. At the end of the first wave, as of 15 February 2021, a cumulative aCFR of 1.18% (95% CI 0.99%-1.41%) using random and 1.64% (95% CI 1.64%-1.65%) using fixed-effects models was estimated. Based on high heterogeneity among states, we inferred that the random-effects model likely provided more accurate estimates of the aCFR for India. The aCFR was grouped with the incidence of diabetes, hypertension, cardiovascular diseases and acute respiratory infections in the first and second dimensions of multiple correspondence analyses. Univariable logistic regression confirmed associations between the aCFR and the proportion of urban population, and between aCFR and the number of persons diagnosed with diabetes, hypertension, cardiovascular diseases and stroke per 10,000 population that had visited NCD (Non-communicable disease) clinics. Incidence of pneumonia was also associated with COVID-19 aCFR. Based on predictor variables, we categorised 10, 17 and one Indian state(s) expected to have a high, medium and low aCFR risk, respectively. The current study demonstrated the value of using meta-analysis to estimate aCFR. To decrease COVID-19 associated fatalities, states estimated to have a high aCFR must take steps to reduce co-morbidities.

Case fatality risk of the SARS-CoV-2 variant of concern B.1.1.7 in England, 16 November to 5 February.

The SARS-CoV-2 B.1.1.7 variant of concern (VOC) is increasing in prevalence across Europe. Accurate estimation of disease severity associated with this VOC is critical for pandemic planning. We found increased risk of death for VOC compared with non-VOC cases in England (hazard ratio: 1.67; 95% confidence interval: 1.34-2.09; p < 0.0001). Absolute risk of death by 28 days increased with age and comorbidities. This VOC has potential to spread faster with higher mortality than the pandemic to date.

Different SARS-CoV-2 haplotypes associate with geographic origin and case fatality rates of COVID-19 patients.

The current pandemic of COVID-19 is caused by the SARS-CoV-2 virus for which many variants at the Single Nucleotide Polymorphism (SNP) level have now been identified. We show here that different allelic variants among 692 SARS-CoV-2 genome sequences display a statistically significant association with geographic origin (p < 0.000001) and COVID-19 case severity (p = 0.016). Geographic variation in itself is associated with both case severity and allelic variation especially in strains from Indian origin (p < 0.000001). Using an new alternative bioinformatics approach we were able to confirm that the presence of the D614G mutation correlates with increased case severity in a sample of 127 sequences from a shared geographic origin in the US (p = 0.018). While leaving open the question on the pathogenesis mechanism involved, this suggests that in specific geographic locales certain genotypes of the virus are more pathogenic than others. We here show that viral genome polymorphisms may have an effect on case severity when other factors are controlled for, but that this effect is swamped out by these other factors when comparing cases across different geographic regions.

Case Fatality Risk of the First Pandemic Wave of Coronavirus Disease 2019 (COVID-19) in China.

BACKGROUND: To assess the case fatality risk (CFR) of COVID-19 in mainland China, stratified by region and clinical category, and estimate key time-to-event intervals. METHODS: We collected individual information and aggregated data on COVID-19 cases from publicly available official sources from 29 December 2019 to 17 April 2020. We accounted for right-censoring to estimate the CFR and explored the risk factors for mortality. We fitted Weibull, gamma, and log-normal distributions to time-to-event data using maximum-likelihood estimation. RESULTS: We analyzed 82 719 laboratory-confirmed cases reported in mainland China, including 4632 deaths and 77 029 discharges. The estimated CFR was 5.65% (95% confidence interval [CI], 5.50-5.81%) nationally, with the highest estimate in Wuhan (7.71%) and lowest in provinces outside Hubei (0.86%). The fatality risk among critical patients was 3.6 times that of all patients and 0.8-10.3-fold higher than that of mild-to-severe patients. Older age (odds ratio [OR], 1.14 per year; 95% CI, 1.11-1.16) and being male (OR, 1.83; 95% CI, 1.10-3.04) were risk factors for mortality. The times from symptom onset to first healthcare consultation, to laboratory confirmation, and to hospitalization were consistently longer for deceased patients than for those who recovered. CONCLUSIONS: Our CFR estimates based on laboratory-confirmed cases ascertained in mainland China suggest that COVID-19 is more severe than the 2009 H1N1 influenza pandemic in hospitalized patients, particularly in Wuhan. Our study provides a comprehensive picture of the severity of the first wave of the pandemic in China. Our estimates can help inform models and the global response to COVID-19.

Epidemiology of SARS-CoV-2.

PURPOSE: SARS-CoV-2 is a recently emerged ß-coronavirus. Here we present the current knowledge on its epidemiologic features. METHODS: Non-systematic review. RESULTS: SARS-CoV-2 replicates in the upper and lower respiratory tract. It is mainly transmitted by droplets and aerosols from asymptomatic and symptomatic infected subjects. The consensus estimate for the basis reproduction number (R0) is between 2 and 3, and the median incubation period is 5.7 (range 2-14) days. Similar to SARS and MERS, superspreading events have been reported, the dispersion parameter (kappa) is estimated at 0.1. Most infections are uncomplicated, and 5-10% of patients are hospitalized, mainly due to pneumonia with severe inflammation. Complications are respiratory and multiorgan failure; risk factors for complicated disease are higher age, hypertension, diabetes, chronic cardiovascular, chronic pulmonary disease and immunodeficiency. Nosocomial and infections in medical personnel have been reported. Drastic reductions of social contacts have been implemented in many countries with outbreaks of SARS-CoV-2, leading to rapid reductions. Most interventions have used bundles, but which of the measures have been more or less effective is still unknown. The current estimate for the infection's fatality rate is 0.5-1%. Using current models of age-dependent infection fatality rates, upper and lower limits for the attack rate in Germany can be estimated between 0.4 and 1.6%, lower than in most European countries. CONCLUSIONS: Despite a rapid worldwide spread, attack rates have been low in most regions, demonstrating the efficacy of control measures.