Epidemiology and transmission characteristics of early COVID-19 cases, 20 January-19 March 2020, in Bavaria, Germany.
TL;DR: In this article, the authors describe the epidemiology and transmission characteristics of early coronavirus disease 2019 (COVID-19) cases in Bavaria, Germany, reported from 20 January-19 March 2020.
Abstract: Severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) led to a significant disease burden and disruptions in health systems. We describe the epidemiology and transmission characteristics of early coronavirus disease 2019 (COVID-19) cases in Bavaria, Germany. Cases were reverse transcription polymerase chain reaction (RT-PCR)-confirmed SARS-CoV-2 infections, reported from 20 January-19 March 2020. The incubation period was estimated using travel history and date of symptom onset. To estimate the serial interval, we identified pairs of index and secondary cases. By 19 March, 3546 cases were reported. A large proportion was exposed abroad (38%), causing further local transmission. Median incubation period of 256 cases with exposure abroad was 3.8 days (95%CI: 3.5-4.2). For 95% of infected individuals, symptom onset occurred within 10.3 days (95%CI: 9.1-11.8) after exposure. The median serial interval, using 53 pairs, was 3.5 days (95%CI: 3.0-4.2; mean: 3.9, s.d.: 2.2). Travellers returning to Germany had an important influence on the spread of SARS-CoV-2 infections in Bavaria in early 2020. Especially in times of low incidence, public health agencies should identify holiday destinations, and areas with ongoing local transmission, to monitor potential importation of SARS-CoV-2 infections. Travellers returning from areas with ongoing community transmission should be advised to quarantine to prevent re-introductions of COVID-19.
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TL;DR: In Deutschland, a SARS-CoV-2-Infektion diagnostiziert is reported in this article, in which 175.013 Fallen in gesamten Bundesgebiet an were vermehrt.
Abstract: Am 27.01.2020 wurde in Deutschland der erste Fall mit einer SARS-CoV-2-Infektion diagnostiziert. Fur die Beschreibung des Pandemieverlaufs im Jahr 2020 wurden 4 epidemiologisch verschiedene Phasen betrachtet und Daten aus dem Meldesystem gemas Infektionsschutzgesetz (IfSG) sowie hospitalisierte COVID-19-Falle mit schwerer akuter respiratorischer Infektion aus der Krankenhaus-Surveillance eingeschlossen. Phase 0 umfasst den Zeitraum von Kalenderwoche (KW) 5/2020 bis 9/2020, in dem vor allem sporadische Falle <60 Jahre und regional begrenzte Ausbruche beobachtet wurden. Insgesamt wurden 167 Falle ubermittelt, die vorwiegend mild verliefen. Dem schloss sich in Phase 1 (KW 10/2020 bis 20/2020) die erste COVID-19-Welle mit 175.013 Fallen im gesamten Bundesgebiet an. Hier wurden vermehrt Ausbruche in Krankenhausern, Alten- und Pflegeheimen sowie ein zunehmender Anteil an alteren und schwer erkrankten Personen verzeichnet. In Phase 2, dem „Sommerplateau“ mit eher milden Verlaufen (KW 21/2020 bis 39/2020), wurden viele reiseassoziierte COVID-19-Falle im Alter von 15–59 Jahren und einzelne grosere, uberregionale Ausbruche in Betrieben beobachtet. Unter den 111.790 Fallen wurden schwere Verlaufe seltener beobachtet als in Phase 1. Phase 3 (KW 40/2020 bis 8/2021) war gekennzeichnet durch die zweite COVID-19-Welle in Deutschland, die sich zum Jahresende 2020 auf dem Hohepunkt befand. Mit 2.158.013 ubermittelten COVID-19-Fallen und insgesamt deutlich mehr schweren Fallen in allen Altersgruppen verlief die zweite Welle schwerer als die erste Welle. Unabhangig von den 4 Phasen waren v. a. Altere und auch Manner starker von einem schweren Krankheitsverlauf betroffen.
56 citations
TL;DR: In this paper, a random-effect model was used to pool the mean incubation period of COVID-19 globally and in the mainland of China, and the authors used meta-regression to explore the sources of heterogeneity.
Abstract: BACKGROUND: The incubation period is a crucial index of epidemiology in understanding the spread of the emerging Coronavirus disease 2019 (COVID-19). In this study, we aimed to describe the incubation period of COVID-19 globally and in the mainland of China. METHODS: The searched studies were published from December 1, 2019 to May 26, 2021 in CNKI, Wanfang, PubMed, and Embase databases. A random-effect model was used to pool the mean incubation period. Meta-regression was used to explore the sources of heterogeneity. Meanwhile, we collected 11 545 patients in the mainland of China outside Hubei from January 19, 2020 to September 21, 2020. The incubation period fitted with the Log-normal model by the coarseDataTools package. RESULTS: A total of 3235 articles were searched, 53 of which were included in the meta-analysis. The pooled mean incubation period of COVID-19 was 6.0 days (95% confidence interval [CI] 5.6-6.5) globally, 6.5 days (95% CI 6.1-6.9) in the mainland of China, and 4.6 days (95% CI 4.1-5.1) outside the mainland of China (P = 0.006). The incubation period varied with age (P = 0.005). Meanwhile, in 11 545 patients, the mean incubation period was 7.1 days (95% CI 7.0-7.2), which was similar to the finding in our meta-analysis. CONCLUSIONS: For COVID-19, the mean incubation period was 6.0 days globally but near 7.0 days in the mainland of China, which will help identify the time of infection and make disease control decisions. Furthermore, attention should also be paid to the region- or age-specific incubation period.
41 citations
TL;DR: In this article, the effectiveness of the BioNTech-Pfizer (BNT162b2) vaccine to prevent SARS-CoV-2 infection and severe outcomes in octo-and novo-generians in a German state setting was evaluated.
Abstract: Background The efficacy of the BioNTech-Pfizer BNT162b2 vaccination in the elderly (≥80 years) could not be fully assessed in the BioNTech-Pfizer trial due to low numbers in this age group. We aimed to evaluate the effectiveness of the BioNTech-Pfizer (BNT162b2) vaccine to prevent SARS-CoV-2 infection and severe outcomes in octo- and novo-generians in a German state setting. Methods and findings A prospective observational study of 708,187 persons aged ≥80 years living in Bavaria, Germany, was conducted between Jan 9 to Apr 11, 2021. We assessed the vaccine effectiveness (VE) for two doses of the BNT162b2 vaccine with respect to SARS-CoV-2 infection and related hospitalisations and mortality. Additionally, differences in VE by age groups ≥80 to ≤89 years and ≥90 years were studied. Analyses were adjusted by sex. By the end of follow-up, 63.8% of the Bavarian population ≥80 years had received one dose, and 52.7% two doses, of the BNT162b2 vaccine. Two doses of the BNT162b2 vaccine lowered the proportion of SARS-CoV-2 infections and related outcomes, resulting in VE estimates of 68.3% (95% confidence interval (CI) 65.5%, 70.9%) for infection, 73.2% (95% CI 65.3%, 79.3%) for hospitalisation, and 85.1% (95% CI 80.0%, 89.0%) for mortality. Sex differences in the risk of COVID-19 outcomes observed among unvaccinated persons disappeared after two BNT162b2 vaccine doses. Overall, the BNT162b2 vaccine was equally effective in octo- and novo-genarians. Conclusions Two doses of BioNTech-Pfizer's BNT162b2 vaccine is highly effective against COVID-19 outcomes in elderly persons.
9 citations
TL;DR: In this article, the authors assessed severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) reverse transcriptase-polymerase chain reaction (RT-PCR) diagnostic sensitivity and cycle threshold (Ct) values relative to symptom onset in symptomatic coronavirus disease-2019 (COVID-19) patients from Bavaria, Germany, of whom a subset was repeatedly tested.
Abstract: We assessed severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) reverse transcriptase-polymerase chain reaction (RT-PCR) diagnostic sensitivity and cycle threshold (Ct) values relative to symptom onset in symptomatic coronavirus disease-2019 (COVID-19) patients from Bavaria, Germany, of whom a subset was repeatedly tested. Locally weighted scatterplot smoothing method was used to assess the relationship between symptom onset and Ct-values. Kaplan-Meier plots were used to visualise the empirical probability of detecting viral ribonucleic acid (RNA) over time and estimate the time until clearance of viral RNA among the repeatedly tested patients. Among 721 reported COVID-19 cases, the viral RNA was detected in specimens taken between three days before and up to 48 days after symptom onset. The mean Ct-value was 28.6 (95% confidence interval (CI) 28.2-29.0) with the lowest mean Ct-value (26.2) observed two days after symptom onset. Up to 7 days after symptom onset, the diagnostic sensitivity of the RT-PCR among repeatedly sampled patients (n = 208) remained above 90% and decreased to 50% at day 12 (95% CI 10.5-21.5). Our data provide valuable estimates to optimise the timing of sampling of individuals for SARS-CoV-2 detection. A considerable proportion of specimens sampled before symptom onset had Ct-values comparable with Ct-values after symptom onset, suggesting the probability of presymptomatic transmission.
6 citations
TL;DR: In this paper, the authors performed a nationwide registry study to assess potential associations between occupation (history) and colon cancer, including also those occupations with known increased exposure to gastrointestinal pathogens like Salmonella.
Abstract: Objectives While colon cancer (CC) risk is associated with several lifestyle-related factors, including physical inactivity, smoking and diet, the contribution of occupation to CC morbidity remains largely unclear. Growing evidence indicates that gastrointestinal infections like salmonellosis could contribute to CC development. We performed a nationwide registry study to assess potential associations between occupation (history) and CC, including also those occupations with known increased exposure to gastrointestinal pathogens like Salmonella. Methods Person-level occupational data for all residents in The Netherlands were linked to CC diagnosis data. Differences in the incidence of (overall, proximal and distal) CC among occupational sectors and risk groups were tested for significance by calculating standardised incidence ratios (SIRs) with 95% CIs using the general population as reference group. Effects of gender, age, exposure duration and latency were also assessed. Results Significant differences in CC incidence were observed only for a few occupational sectors, including the manufacturing of rubber and plastics, machinery and leather, the printing sector and the information service sector (SIRs 1.06-1.88). No elevated risk of CC was observed among people with increased salmonellosis risk through occupational exposure to live animals, manure or among those working in the sale of animal-derived food products (SIRs 0.93-0.95, 0.81-0.95 and 0.93-1.09 for overall, proximal and distal CC, respectively). Conclusions The results of this study suggest that occupation in itself provides a relatively small contribution to CC incidence. This is consistent with previous studies where a similar degree of variation in risk estimates was observed. The lack of an association with the high-risk occupations for salmonellosis might be due to higher levels of physical activity, a known protective factor for CC and other diseases, of people working in the agricultural sector, which might outweigh the potential Salmonella-associated risk of CC.
3 citations
References
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TL;DR: Copyright (©) 1999–2012 R Foundation for Statistical Computing; permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and permission notice are preserved on all copies.
Abstract: Copyright (©) 1999–2012 R Foundation for Statistical Computing. Permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and this permission notice are preserved on all copies. Permission is granted to copy and distribute modified versions of this manual under the conditions for verbatim copying, provided that the entire resulting derived work is distributed under the terms of a permission notice identical to this one. Permission is granted to copy and distribute translations of this manual into another language, under the above conditions for modified versions, except that this permission notice may be stated in a translation approved by the R Core Team.
272,030 citations
TL;DR: There is evidence that human-to-human transmission has occurred among close contacts since the middle of December 2019 and considerable efforts to reduce transmission will be required to control outbreaks if similar dynamics apply elsewhere.
Abstract: Background The initial cases of novel coronavirus (2019-nCoV)–infected pneumonia (NCIP) occurred in Wuhan, Hubei Province, China, in December 2019 and January 2020. We analyzed data on the...
13,101 citations
01 Jan 2006
TL;DR: Platform-independent and open source igraph aims to satisfy all the requirements of a graph package while possibly remaining easy to use in interactive mode as well.
Abstract: There is no other package around that satisfies all the following requirements: •Ability to handle large graphs efficiently •Embeddable into higher level environments (like R [6] or Python [7]) •Ability to be used for quick prototyping of new algorithms (impossible with “click & play” interfaces) •Platform-independent and open source igraph aims to satisfy all these requirements while possibly remaining easy to use in interactive mode as well.
8,850 citations
TL;DR: Detailed virological analysis of nine cases of coronavirus disease 2019 (COVID-19) provides proof of active replication of the SARS-CoV-2 virus in tissues of the upper respiratory tract.
Abstract: Coronavirus disease 2019 (COVID-19) is an acute infection of the respiratory tract that emerged in late 20191,2. Initial outbreaks in China involved 13.8% of cases with severe courses, and 6.1% of cases with critical courses3. This severe presentation may result from the virus using a virus receptor that is expressed predominantly in the lung2,4; the same receptor tropism is thought to have determined the pathogenicity—but also aided in the control—of severe acute respiratory syndrome (SARS) in 20035. However, there are reports of cases of COVID-19 in which the patient shows mild upper respiratory tract symptoms, which suggests the potential for pre- or oligosymptomatic transmission6–8. There is an urgent need for information on virus replication, immunity and infectivity in specific sites of the body. Here we report a detailed virological analysis of nine cases of COVID-19 that provides proof of active virus replication in tissues of the upper respiratory tract. Pharyngeal virus shedding was very high during the first week of symptoms, with a peak at 7.11 × 108 RNA copies per throat swab on day 4. Infectious virus was readily isolated from samples derived from the throat or lung, but not from stool samples—in spite of high concentrations of virus RNA. Blood and urine samples never yielded virus. Active replication in the throat was confirmed by the presence of viral replicative RNA intermediates in the throat samples. We consistently detected sequence-distinct virus populations in throat and lung samples from one patient, proving independent replication. The shedding of viral RNA from sputum outlasted the end of symptoms. Seroconversion occurred after 7 days in 50% of patients (and by day 14 in all patients), but was not followed by a rapid decline in viral load. COVID-19 can present as a mild illness of the upper respiratory tract. The confirmation of active virus replication in the upper respiratory tract has implications for the containment of COVID-19. Detailed virological analysis of nine cases of coronavirus disease 2019 (COVID-19) provides proof of active replication of the SARS-CoV-2 virus in tissues of the upper respiratory tract.
5,840 citations
TL;DR: The results support current proposals for the length of quarantine or active monitoring of persons potentially exposed to SARS-CoV-2, although longer monitoring periods might be justified in extreme cases.
Abstract: Using news reports and press releases from provinces, regions, and countries outside Wuhan, Hubei province, China, this analysis estimates the length of the incubation period of COVID-19 and its pu...
5,215 citations