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Introduction: A discussion of 'waves' of the COVID-19 epidemic in different countries is a part of the national conversation for many, but there is no hard and fast means of delineating these waves in the available data and their connection to waves in the sense of mathematical epidemiology is only tenuous. Methods: We present an algorithm which processes a general time series to identify substantial, significant and sustained periods of increase in the value of the time series, which could reasonably be described as 'observed waves'. This provides an objective means of describing observed waves in time series. We use this method to synthesize evidence across different countries to study types, drivers and modulators of waves. Results: The output of the algorithm as applied to epidemiological time series related to COVID-19 corresponds to visual intuition and expert opinion. Inspecting the results of individual countries shows how consecutive observed waves can differ greatly with respect to the case fatality ratio. Furthermore, in large countries, a more detailed analysis shows that consecutive observed waves have different geographical ranges. We also show how waves can be modulated by government interventions and find that early implementation of NPIs correlates with a reduced number of observed waves and reduced mortality burden in those waves. Conclusion: It is possible to identify observed waves of disease by algorithmic methods and the results can be fruitfully used to analyse the progression of the epidemic.
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Oxford COVID-19 Database (OxCOVID19 Database) is a comprehensive source of information related to the COVID-19 pandemic. This relational database contains time-series data on epidemiology, government responses, mobility, weather and more across time and space for all countries at the national level, and for more than 50 countries at the regional level. It is curated from a variety of (wherever available) official sources. Its purpose is to facilitate the analysis of the spread of SARS-CoV-2 virus and to assess the effects of non-pharmaceutical interventions to reduce the impact of the pandemic. Our database is a freely available, daily updated tool that provides unified and granular information across geographical regions. Design type Data integration objective Measurement(s) Coronavirus infectious disease, viral epidemiology Technology type(s) Digital curation Factor types(s) Sample characteristic(s) Homo sapiens.
Asunto(s)
COVID-19/epidemiología , Bases de Datos Factuales , SARS-CoV-2/fisiología , COVID-19/terapia , COVID-19/transmisión , Programas de Gobierno , Humanos , Cooperación Internacional , Pandemias , Tiempo (Meteorología)RESUMEN
BACKGROUND: The broad spectrum of oxidative damage DNA biomarkers: urinary excretion of 8-oxodG (8-oxo-7,8-dihydro-2'-deoxyguanosine), 8-oxoGua (8-oxo-7,8-dihydroguanine) as well as the level of oxidative damage DNA in leukocytes, was analyzed in cancer patients and healthy subjects. MATERIAL/METHODS: 222 cancer patients and 134 healthy volunteers were included in the analysis, using methodologies which involve HPLC (high-performance liquid chromatography) prepurification followed by gas chromatography with isotope dilution mass spectrometry detection and HPLC/EC. RESULTS: For the whole patient population (n=222) the median values of 8-oxoGua and 8-oxodG in urine samples were 12.44 (interquartile range: 8.14-20.33) [nmol/24 hr] and 6.05 (3.12-15.38) [nmol/24 hr], respectively. The median values of 8-oxoGua and 8-oxodG in urine samples of the control group (n=85) were 7.7 (4.65-10.15) [nmol/24 hr] and 2.2 (1.7-2.8) [nmol/24 hr], respectively. The level of 8-oxodG in DNA isolated from leukocytes of the patient population (n=179) and of the control group (n=134) was 4.93 (3.46-9.27) per 10'6 dG and 4.46 (3.82-5.31) per 10'6 dG, respectively. CONCLUSIONS: The results suggest that oxidative stress in cancer patients, demonstrated by augmented amounts of these modifications in urine, could be typical not only for affected tissue but also for other tissues and even the whole organism. An assay that enables the determination of levels of basic markers of oxidative stress might be applied in clinical practice as an additional, helpful marker to diagnose cancer.
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Biomarcadores de Tumor/orina , Daño del ADN , Desoxiguanosina/análogos & derivados , Guanina/análogos & derivados , Neoplasias/patología , Neoplasias/orina , Estrés Oxidativo , 8-Hidroxi-2'-Desoxicoguanosina , Estudios de Casos y Controles , ADN de Neoplasias/metabolismo , Desoxiguanosina/orina , Guanina/orina , Humanos , Leucocitos/metabolismoRESUMEN
The aim of this study was to determine whether blood plasma progesterone is a reliable indicator of pregnancy in mink at an early stage of gestation. We also attempted to establish the threshold value of progesterone as a pregnancy indicator. The analysis was carried out at a production farm on 42 standard female mink aged 1 year, which were grouped both according to the observed success of mating ("mated" and "unmated") and the level of blood serum progesterone measured afterwards ("pregnant" and "nonpregnant"). It was next verified whether a particular female had been assigned to the proper group in the first place. An analysis of accuracy of mating success assessment within the group of unmated females revealed that more than one-third of decisions were wrong, since some females that had been considered unmated ultimately whelped. This suggests that mating supervision by farm workers lacks reliability. A progesterone test for verification of such management decisions should limit the risk of err,or. We suggest that progesterone tests could be carried out using the threshold values 1.9 ng/ml and 20 ng/ml in blood sampled on 25 March and 8 April, respectively, although some level of uncertainty should be taken into account.