RESUMEN
BACKGROUND: Notifications to the Norwegian Institute of Public Health of outbreaks in Norwegian healthcare institutions are mandatory by law, but under-reporting is suspected due to failure to identify clusters, or because of human or system-based factors. This study aimed to establish and describe a fully automatic, register-based surveillance system to identify clusters of healthcare-associated infections (HAIs) of SARS-CoV-2 in hospitals and compare these with outbreaks notified through the mandated outbreak system Vesuv. METHODS: We used linked data from the emergency preparedness register Beredt C19, based on the Norwegian Patient Registry and the Norwegian Surveillance System for Communicable Diseases. We tested two different algorithms for HAI clusters, described their size and compared them with outbreaks notified through Vesuv. RESULTS: A total of 5033 patients were registered with an indeterminate, probable, or definite HAI. Depending on the algorithm, our system detected 44 or 36 of the 56 officially notified outbreaks. Both algorithms detected more clusters then officially reported (301 and 206, respectively). CONCLUSIONS: It was possible to use existing data sources to establish a fully automatic surveillance system identifying clusters of SARS-CoV-2. Automatic surveillance can improve preparedness through earlier identification of clusters of HAIs, and by lowering the workloads of infection control specialists in hospitals.
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COVID-19 , Infección Hospitalaria , Humanos , COVID-19/epidemiología , SARS-CoV-2 , Infección Hospitalaria/epidemiología , Hospitales , Noruega/epidemiologíaRESUMEN
AIM: The aim of this study was, for the first time, to describe in detail the epidemiology and impact of norovirus outbreaks in healthcare institituions (HCIs) in Norway to identify areas which may improve outbreak response. METHODS: An analysis of all reported norovirus outbreaks in hospitals and long-term-care facilities (LTCFs) was carried out from week 34, 2005 to week 33, 2018. Seasonality, symptoms and number of cases among personnel and patients were described. FINDINGS: A total of 20,544 cases, including 7044 healthcare personnel were reported in 965 outbreaks; 740 from LTCFs and 225 from hospitals. Median number of cases per outbreak was 15, interquartile range (IQR) 8-25 in LTCF; and 17, IQR 10-28 in hospitals. All regions reported outbreaks, with one-third of the municipalities having at least one outbreak in LTCFs during the study period. The start of the outbreak season happened almost four weeks earlier in hospitals than in LTCFs. The estimated average number of working days lost for healthcare personnel per year ranged from 1590 to 1944. CONCLUSIONS: Norovirus outbreaks in Norwegian HCIs appears to have a substantial impact on both hospital and LTCFs all over Norway, especially during the winter months. That up to half of all cases were healthcare professionals emphasizes a need for further focus on infection control. Our results suggest that hospitals, affected first, could alert LTCFs in the area in order to prevent further outbreaks.
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Infecciones por Caliciviridae/epidemiología , Infección Hospitalaria/epidemiología , Brotes de Enfermedades , Instituciones de Salud , Humanos , Noruega/epidemiología , Prevalencia , Topografía MédicaRESUMEN
BACKGROUND: In 2011-2012, the European Centre for Disease Prevention and Control (ECDC) initiated the first European point prevalence survey (PPS) of healthcare-associated infections (HCAIs) in addition to targeted surveillance of the incidence of specific types of HCAI such as surgical site infections (SSIs). AIM: To investigate whether national and multi-country SSI incidence can be estimated from ECDC PPS data. METHODS: In all, 159 hospitals were included from 15 countries that participated in both ECDC surveillance modules, aligning surgical procedures in the incidence surveillance to corresponding specialties from the PPS. National daily prevalence of SSIs was simulated from the incidence surveillance data, the Rhame and Sudderth (R&S) formula was used to estimate national and multi-country SSI incidence from the PPS data, and national incidence per specialty was predicted using a linear model including data from the PPS. FINDINGS: The simulation of daily SSI prevalence from incidence surveillance of SSIs showed that prevalence fluctuated randomly depending on the day of measurement. The correlation between the national aggregated incidence estimated with R&S formula and observed SSI incidence was low (correlation coefficient = 0.24), but specialty-specific incidence results were more reliable, especially when the number of included patients was large (correlation coefficients ranging from 0.40 to 1.00). The linear prediction model including PPS data had low proportion of explained variance (0.40). CONCLUSION: Due to a lack of accuracy, use of PPS data to estimate SSI incidence is recommended only in situations where incidence surveillance of SSIs is not performed, and where sufficiently large samples of PPS data are available.
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Infección Hospitalaria/epidemiología , Infección de la Herida Quirúrgica/epidemiología , Métodos Epidemiológicos , Europa (Continente)/epidemiología , Femenino , Humanos , Incidencia , Masculino , PrevalenciaRESUMEN
1-Chloro-3-(3,4-difluorophenoxy)-2-propanol was kinetically resolved by lipase-catalyzed esterification with vinyl butanoate in organic medium to yield the (S)-butanoate and the (R)-alcohol as the remaining substrate. In an enantioconvergent synthesis the mixture was subject to Mitsunobu esterification in one pot which converted the (R)-alcohol to the (S)-ester. The (S)-butanoate was hydrolyzed by lipase catalysis to give (S)-1-chloro-3-(3,4-difluorophenoxy)-2-propanol. The two enantiopure chiral building blocks were used for synthesis of Lubeluzole and its enantiomer respectively.