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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.

Drug resistance testing has been shown to be beneficial for clinical management of HIV type 1 infected patients. Whereas phenotypic assays directly measure drug resistance, the commonly used genotypic assays provide only indirect evidence of drug resistance, the major challenge being the interpretation of the sequence information. We analyzed the significance of sequence variations in the protease and reverse transcriptase genes for drug resistance and derived models that predict phenotypic resistance from genotypes. For 14 antiretroviral drugs, both genotypic and phenotypic resistance data from 471 clinical isolates were analyzed with a machine learning approach. Information profiles were obtained that quantify the statistical significance of each sequence position for drug resistance. For the different drugs, patterns of varying complexity were observed, including between one and nine sequence positions with substantial information content. Based on these information profiles, decision tree classifiers were generated to identify genotypic patterns characteristic of resistance or susceptibility to the different drugs. We obtained concise and easily interpretable models to predict drug resistance from sequence information. The prediction quality of the models was assessed in leave-one-out experiments in terms of the prediction error. We found prediction errors of 9.6 -15.5% for all drugs except for zalcitabine, didanosine, and stavudine, with prediction errors between 25.4% and 32.0%. A prediction service is freely available at http:͞͞cartan.gmd.de͞geno2pheno.html.

Objective The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic challenges national health systems and the global economy. Monitoring of infection rates and seroprevalence can guide public health measures to combat the pandemic. This depends on reliable tests on active and former infections. Here, we set out to develop and validate a specific and sensitive enzyme linked immunosorbent assay (ELISA) for detection of anti-SARS-CoV-2 antibody levels. Methods In our ELISA, we used SARS-CoV-2 receptor-binding domain (RBD) and a stabilized version of the spike (S) ectodomain as antigens. We assessed sera from patients infected with seasonal coronaviruses, SARS-CoV-2 and controls. We determined and monitored IgM-, IgA-and IgG-antibody responses towards these antigens. In addition, for a panel of 22 sera, virus neutralization and ELISA parameters were measured and correlated. Results The RBD-based ELISA detected SARS-CoV-2-directed antibodies, did not cross-react with seasonal coronavirus antibodies and correlated with virus neutralization (R 2 = 0.89). Seroconversion started at 5 days after symptom onset and led to robust antibody levels at 10 days after symptom onset. We demonstrate high specificity (99.3%; N = 1000) and sensitivity (92% for IgA, 96% for IgG and 98% for IgM; > 10 days after PCR-proven infection; N = 53) in serum. Conclusions With the described RBD-based ELISA protocol, we provide a reliable test for seroepidemiological surveys. Due to high specificity and strong correlation with virus neutralization, the RBD ELISA holds great potential to become a preferred tool to assess thresholds of protective immunity after infection and vaccination.