Project description:Lyme borreliosis (LB) is the most common tick-borne disease in Germany. Mandatory notification of acute LB manifestations (erythema migrans (EM), neuroborreliosis (NB), and Lyme arthritis (LA)) was implemented in Bavaria on 1 March 2013. We aimed to describe the epidemiological situation and to identify LB risk areas and populations. Therefore, we analyzed LB cases notified from March 2013 to December 2020 and calculated incidence (cases/100,000 inhabitants) by time, place, and person. Overall, 35,458 cases were reported during the study period (EM: 96.7%; NB: 1.7%; LA: 1.8%). The average incidence was 34.3/100,000, but annual incidence varied substantially (2015: 23.2; 2020: 47.4). Marked regional differences at the district level were observed (annual average incidence range: 4-154/100,000). The Bavarian Forest and parts of Franconia were identified as high-risk regions. Additionally, high risk for LB was found in 5-9-year-old males and in 60-69-year-old females. The first group also had the highest risk of a severe disease course. We were able to identify areas and populations in Bavaria with an increased LB risk, thereby providing a basis for targeted measures to prevent LB. Since LB vaccination is currently not available, such measures should comprise (i) avoiding tick bites, (ii) removing ticks rapidly after a bite, and (iii) treating LB early/adequately.
Project description:Lyssaviruses are the causative agents for rabies, a zoonotic and fatal disease. Bats are the ancestral reservoir host for lyssaviruses, and at least three different lyssaviruses have been found in bats from Germany. Across Europe, novel lyssaviruses were identified in bats recently and occasional spillover infections in other mammals and human cases highlight their public health relevance. Here, we report the results from an enhanced passive bat rabies surveillance that encompasses samples without human contact that would not be tested under routine conditions. To this end, 1236 bat brain samples obtained between 2018 and 2020 were screened for lyssaviruses via several RT-qPCR assays. European bat lyssavirus type 1 (EBLV-1) was dominant, with 15 positives exclusively found in serotine bats (Eptesicus serotinus) from northern Germany. Additionally, when an archived set of bat samples that had tested negative for rabies by the FAT were screened in the process of assay validation, four samples tested EBLV-1 positive, including two detected in Pipistrellus pipistrellus. Subsequent phylogenetic analysis of 17 full genomes assigned all except one of these viruses to the A1 cluster of the EBLV-1a sub-lineage. Furthermore, we report here another Bokeloh bat lyssavirus (BBLV) infection in a Natterer's bat (Myotis nattereri) found in Lower Saxony, the tenth reported case of this novel bat lyssavirus.
Project description:The four endemic human coronaviruses HCoV-229E, -NL63, -OC43, and -HKU1 contribute a considerable share of upper and lower respiratory tract infections in adults and children. While their clinical representation resembles that of many other agents of the common cold, their evolutionary histories, and host associations could provide important insights into the natural history of past human pandemics. For two of these viruses, we have strong evidence suggesting an origin in major livestock species while primordial associations for all four viruses may have existed with bats and rodents. HCoV-NL63 and -229E may originate from bat reservoirs as assumed for many other coronaviruses, but HCoV-OC43 and -HKU1 seem more likely to have speciated from rodent-associated viruses. HCoV-OC43 is thought to have emerged from ancestors in domestic animals such as cattle or swine. The bovine coronavirus has been suggested to be a possible ancestor, from which HCoV-OC43 may have emerged in the context of a pandemic recorded historically at the end of the 19th century. New data suggest that HCoV-229E may actually be transferred from dromedary camels similar to Middle East respiratory syndrome (MERS) coronavirus. This scenario provides important ecological parallels to the present prepandemic pattern of host associations of the MERS coronavirus.
Project description:Community protective immunity can affect RNA virus evolution by selecting for new antigenic variants on the scale of years, exemplified by the need of annual evaluation of influenza vaccines. The extent to which this process termed antigenic drift affects coronaviruses remains unknown. Alike the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), seasonal human coronaviruses (HCoV) likely emerged from animal reservoirs as new human pathogens in the past. We therefore analyzed the long-term evolutionary dynamics of the ubiquitous HCoV-229E and HCoV-OC43 in comparison with human influenza A virus (IAV) subtype H3N2. We focus on viral glycoprotein genes that mediate viral entry into cells and are major targets of host neutralizing antibody responses. Maximum likelihood and Bayesian phylogenies of publicly available gene datasets representing about three decades of HCoV and IAV evolution showed that all viruses had similar ladder-like tree shapes compatible with antigenic drift, supported by different tree shape statistics. Evolutionary rates inferred in a Bayesian framework were 6.5 × 10-4 (95% highest posterior density (HPD), 5.4-7.5 × 10-4) substitutions per site per year (s/s/y) for HCoV-229E spike (S) genes and 5.7 × 10-4 (95% HPD, 5-6.5 × 10-4) s/s/y for HCoV-OC43 S genes, which were about fourfold lower than the 2.5 × 10-3 (95% HPD, 2.3-2.7 × 10-3) s/s/y rate for IAV hemagglutinin (HA) genes. Coronavirus S genes accumulated about threefold less (P < 0.001) non-synonymous mutations (dN) over time than IAV HA genes. In both IAV and HCoV, the average rate of dN within the receptor binding domains (RBD) was about fivefold higher (P < 0.0001) than in other glycoprotein gene regions. Similarly, most sites showing evidence for positive selection occurred within the RBD (HCoV-229E, 6/14 sites, P < 0.05; HCoV-OC43, 23/38 sites, P < 0.01; IAV, 13/15 sites, P = 0.08). In sum, the evolutionary dynamics of HCoV and IAV showed several similarities, yet amino acid changes potentially representing antigenic drift occurred on a lower scale in endemic HCoV compared to IAV. It seems likely that pandemic SARS-CoV-2 evolution will bear similarities with IAV evolution including accumulation of adaptive changes in the RBD, requiring vaccines to be updated regularly, whereas higher SARS-CoV-2 evolutionary stability resembling endemic HCoV can be expected in the post-pandemic stage.
Project description:Introduction: Human coronaviruses (HCoVs) circulate endemically in human populations, often with seasonal variation. We describe the long-term patterns of paediatric disease associated with three of these viruses, HCoV-NL63, OC43 and 229E, in coastal Kenya. Methods: Continuous surveillance of pneumonia admissions was conducted at the Kilifi county hospital (KCH) located in the northern coastal region of Kenya. Children aged <5 years admitted to KCH with clinically defined syndromic severe or very severe pneumonia were recruited. Respiratory samples were taken and tested for 15 virus targets, using real-time polymerase chain reaction. Unadjusted odds ratios were used to estimate the association between demographic and clinical characteristics and HCoV positivity. Results: From 2007 to 2019, we observed 11,445 pneumonia admissions, of which 314 (3.9%) tested positive for at least one of the HCoV types surveyed in the study. There were 129 (41.1%) OC43, 99 (31.5%) 229E, 74 (23.6%) NL63 positive cases and 12 (3.8%) cases of HCoV to HCoV coinfection. Among HCoV positive cases, 47% (n=147) were coinfected with other respiratory virus pathogens. The majority of HCoV cases were among children aged <1 year (66%, n=208), though there was was no change in the proportion infected by age. HCoV-OC43 was predominant of the three HCoV types throughout the surveillance period. Evidence for seasonality was not identified. Conclusions: Overall, 4% of paediatric pneumonia admissions were associated with three endemic HCoVs, with a high proportion of cases co-occurring with another respiratory virus, no clear seasonal pattern, and with the age-distribution of cases following that of pneumonia admissions (i.e. highest in infants). These observations suggest, at most, a small severe disease contribution of endemic HCoVs in this tropical setting and offer insight into their potential future burden and epidemiological characteristics.
Project description:Since human coronavirus (HCoVs) was first described in the 1960s, seven strains of respiratory human coronaviruses have emerged and caused human infections. After the emergence of severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV), a pneumonia outbreak of coronavirus disease 2019 (COVID-19) caused by a novel coronavirus (SARS-CoV-2) has represented a pandemic threat to global public health in the 21st century. Without effectively prophylactic and therapeutic strategies including vaccines and antiviral drugs, these three coronaviruses have caused severe respiratory syndrome and high case-fatality rates around the world. In this review, we detail the emergence event, origin and reservoirs of all HCoVs, compare the differences with regard to structure and receptor usage, and summarize therapeutic strategies for COVID-19 that cause severe pneumonia and global pandemic.
Project description:Coronavirus disease 2019 (COVID-19), caused by Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was first reported in Wuhan, China, and rapidly spread throughout the world. This newly emerging pathogen is highly transmittable and can cause fatal disease. More than 35 million cases have been confirmed, with a fatality rate of about 2.9% to October 9, 2020. However, the original and intermediate hosts of SARS-CoV-2 remain unknown. Here, 3160 poultry samples collected from 14 provinces of China between September and December 2019 were tested for SARS-CoV-2 infection. All the samples were SARS-CoV-2 negative, but 593 avian coronaviruses were detected, including 485 avian infectious bronchitis viruses, 72 duck coronaviruses, and 36 pigeon coronaviruses, with positivity rates of 15.35%, 2.28%, and 1.14%, respectively. Our surveillance demonstrates the diversity of avian coronaviruses in China, with higher prevalence rates in some regions. Furthermore, the possibility that SARS-CoV-2 originated from a known avian-origin coronavirus can be preliminarily ruled out. More surveillance of and research into avian coronaviruses are required to better understand the diversity, distribution, cross-species transmission, and clinical significance of these viruses.
Project description:The coronavirus disease 2019 (COVID-19) pandemic resulted in 5,817,385 reported cases and 362,705 deaths worldwide through May, 30, 2020,† including 1,761,503 aggregated reported cases and 103,700 deaths in the United States.§ Previous analyses during February-early April 2020 indicated that age ?65 years and underlying health conditions were associated with a higher risk for severe outcomes, which were less common among children aged <18 years (1-3). This report describes demographic characteristics, underlying health conditions, symptoms, and outcomes among 1,320,488 laboratory-confirmed COVID-19 cases individually reported to CDC during January 22-May 30, 2020. Cumulative incidence, 403.6 cases per 100,000 persons,¶ was similar among males (401.1) and females (406.0) and highest among persons aged ?80 years (902.0). Among 599,636 (45%) cases with known information, 33% of persons were Hispanic or Latino of any race (Hispanic), 22% were non-Hispanic black (black), and 1.3% were non-Hispanic American Indian or Alaska Native (AI/AN). Among 287,320 (22%) cases with sufficient data on underlying health conditions, the most common were cardiovascular disease (32%), diabetes (30%), and chronic lung disease (18%). Overall, 184,673 (14%) patients were hospitalized, 29,837 (2%) were admitted to an intensive care unit (ICU), and 71,116 (5%) died. Hospitalizations were six times higher among patients with a reported underlying condition (45.4%) than those without reported underlying conditions (7.6%). Deaths were 12 times higher among patients with reported underlying conditions (19.5%) compared with those without reported underlying conditions (1.6%). The COVID-19 pandemic continues to be severe, particularly in certain population groups. These preliminary findings underscore the need to build on current efforts to collect and analyze case data, especially among those with underlying health conditions. These data are used to monitor trends in COVID-19 illness, identify and respond to localized incidence increase, and inform policies and practices designed to reduce transmission in the United States.