CGR-CUSUM: a continuous time generalized rapid response cumulative sum chart

Rapidly detecting problems in the quality of care is of utmost importance for the well-being of patients. Without proper inspection schemes, such problems can go undetected for years. Cumulative sum (CUSUM) charts have proven to be useful for quality control, yet available methodology for survival outcomes is limited. The few available continuous time inspection charts usually require the researcher to specify an expected increase in the failure rate in advance, thereby requiring prior knowledge about the problem at hand. Misspecifying parameters can lead to false positive alerts and large detection delays. To solve this problem, we take a more general approach to derive the new Continuous time Generalized Rapid response CUSUM (CGR-CUSUM) chart. We find an expression for the approximate average run length (average time to detection) and illustrate the possible gain in detection speed by using the CGR-CUSUM over other commonly used monitoring schemes on a real-life data set from the Dutch Arthroplasty Register as well as in simulation studies. Besides the inspection of medical procedures, the CGR-CUSUM can also be used for other real-time inspection schemes such as industrial production lines and quality control of services. Analysis and Stochastic

Socio-economic burden of COVID-19 in the Russian Federation

Purpose. Assessment of the socio-economic burden of COVID-19 in the Russian Federation (RF). Materials and methods. Identification and assessment of direct medical, direct non-medical costs, as well as indirect costs associated with the development of the coronavirus infection epidemic. When calculating the socio-economic burden, the prevalence-based calculation approach was chosen. The sources of data on the epidemiology of the disease were data from the Ministry of Health and data from the Government of the Russian Federation. Results. The socio-economic burden of COVID-19 in the Russian Federation will amount to 4.6 trillion rubles ($71.1 billion) or 4 % from GDP. In the cost structure, more than half of the costs are direct non-medical expenses (58.62 %), indirect expenses due to GDP losses are 40.65 %, direct medical expenses are only less than 1 % (0.74 %). The results of the sensitivity analysis showed that the extension of the self-isolation period from 1 month to 1.5 and 2 months will lead to an increase in the share of indirect expenses from 40.65 % (1 month) to 56.08 (1.5 months) and 67.76 % (2 months) for all expenses in connection with the COVID-19 epidemic. At the same time, the socio-economic burden of COVID-19 will amount to 6.2 and 8.5 trillion rubles, respectively. Conclusions. The epidemic of a novel coronavirus infection will lead to great economic losses in the Russian society

Socioeconomic and global burden of COVID-19

Relevance. Assessment of the burden of disease provides information on the economic consequences of the disease, allows you to assess the social significance, identify areas that require additional clinical and economic research, changes in methodological approaches to the organization of measures for the prevention, early detection and treatment of diseases.The aim. Assessment of the socioeconomic and global burden of COVID-19 in the Russian Federation (RF).Materials and methods. Identification and assessment of direct medical, direct non-medical, and indirect costs associated with the development of the coronavirus epidemic. When calculating the socioeconomic burden, the variant of calculations was chosen taking into account the prevalence of the disease. The sources of data on the epidemiology of the disease were data from the Ministry of Health and data from the Government of the RF.Results. The socioeconomic burden of COVID-19 in 2020 in the RF amounted to about 5.4 trillion rubles (5 % of nominal GDP in 2020) and was largely due to indirect costs due to GDP losses due to a 1.5-month period of self-isolation. The estimated global burden of disease is more than 4 million YLLs globally, of which in the RF 2,486.30 among men and 1,378.22 YLL among women.Conclusion. The epidemic of the new coronavirus infection has led to colossal economic losses in Russian society. The data presented underscore not only the clinical, but also the economic importance of investing in the development of strategies for the treatment and prevention of new coronavirus infection

High Levels of Sediment Contamination Have Little Influence on Estuarine Beach Fish Communities

While contaminants are predicted to have measurable impacts on fish assemblages, studies have rarely assessed this potential in the context of natural variability in physico-chemical conditions within and between estuaries. We investigated links between the distribution of sediment contamination (metals and PAHs), physico-chemical variables (pH, salinity, temperature, turbidity) and beach fish assemblages in estuarine environments. Fish communities were sampled using a beach seine within the inner and outer zones of six estuaries that were either heavily modified or relatively unmodified by urbanization and industrial activity. All sampling was replicated over two years with two periods sampled each year. Shannon diversity, biomass and abundance were all significantly higher in the inner zone of estuaries while fish were larger on average in the outer zone. Strong differences in community composition were also detected between the inner and outer zones. Few differences were detected between fish assemblages in heavily modified versus relatively unmodified estuaries despite high concentrations of sediment contaminants in the inner zones of modified estuaries that exceeded recognized sediment quality guidelines. Trends in species distributions, community composition, abundance, Shannon diversity, and average fish weight were strongly correlated to physico-chemical variables and showed a weaker relationship to sediment metal contamination. Sediment PAH concentrations were not significantly related to the fish assemblage. These findings suggest that variation in some physico-chemical factors (salinity, temperature, pH) or variables that co-vary with these factors (e.g., wave activity or grain size) have a much greater influence on this fish assemblage than anthropogenic stressors such as contamination

Are We Predicting the Actual or Apparent Distribution of Temperate Marine Fishes?

Planning for resilience is the focus of many marine conservation programs and initiatives. These efforts aim to inform conservation strategies for marine regions to ensure they have inbuilt capacity to retain biological diversity and ecological function in the face of global environmental change – particularly changes in climate and resource exploitation. In the absence of direct biological and ecological information for many marine species, scientists are increasingly using spatially-explicit, predictive-modeling approaches. Through the improved access to multibeam sonar and underwater video technology these models provide spatial predictions of the most suitable regions for an organism at resolutions previously not possible. However, sensible-looking, well-performing models can provide very different predictions of distribution depending on which occurrence dataset is used. To examine this, we construct species distribution models for nine temperate marine sedentary fishes for a 25.7 km2 study region off the coast of southeastern Australia. We use generalized linear model (GLM), generalized additive model (GAM) and maximum entropy (MAXENT) to build models based on co-located occurrence datasets derived from two underwater video methods (i.e. baited and towed video) and fine-scale multibeam sonar based seafloor habitat variables. Overall, this study found that the choice of modeling approach did not considerably influence the prediction of distributions based on the same occurrence dataset. However, greater dissimilarity between model predictions was observed across the nine fish taxa when the two occurrence datasets were compared (relative to models based on the same dataset). Based on these results it is difficult to draw any general trends in regards to which video method provides more reliable occurrence datasets. Nonetheless, we suggest predictions reflecting the species apparent distribution (i.e. a combination of species distribution and the probability of detecting it). Consequently, we also encourage researchers and marine managers to carefully interpret model predictions

Three new species of the Indo-Pacific fish genus Hime (Aulopidae, Aulopiformes), all resembling the type species H. japonica (Günther 1877)

Gomon, Martin F., Struthers, Carl D. (2015): Three new species of the Indo-Pacific fish genus Hime (Aulopidae, Aulopiformes), all resembling the type species H. japonica (Günther 1877). Zootaxa 4044 (3): 371-390, DOI: 10.11646/zootaxa.4044.3.

A review of giant roughies of the genus Hoplostethus (Beryciformes, Trachichthyidae), with descriptions of two new Australasian species

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