Country-specific optimization strategy for testing through contact tracing can help maintain a low reproduction number ($$R_{0}$$) during unlock

In response to the COVID19 pandemic, many countries have implemented lockdowns in multiple phases to ensure social distancing and quarantining of the infected subjects. Subsequent unlocks to reopen the economies started next waves of infection and imposed an extra burden on quarantine to keep the reproduction number ($$R_{0}$$ R 0 ) < 1. However, most countries could not effectively contain the infection spread, suggesting identification of the potential sources weakening the effect of lockdowns could help design better informed lockdown-unlock cycles in the future. Here, through building quantitative epidemic models and analyzing the metadata of 50 countries from across the continents we first found that the estimated value of $$R_{0}$$ R 0 , adjusted w.r.t the distribution of medical facilities and virus clades correlates strongly with the testing rates in a country. Since the testing capacity of a country is limited by its medical resources, we investigated if a cost–benefit trade-off can be designed connecting testing rate and extent of unlocking. We present a strategy to optimize this trade-off in a country specific manner by providing a quantitative estimate of testing and quarantine rates required to allow different extents of unlocks while aiming to maintain $$R_{0} < 1$$ R 0 < 1 . We further show that a small fraction of superspreaders can dramatically increase the number of infected individuals even during strict lockdowns by strengthening the positive feedback loop driving infection spread. Harnessing the benefit of optimized country-specific testing rates would critically require minimizing the movement of these superspreaders via strict social distancing norms, such that the positive feedback driven switch-like exponential spread phase of infection can be avoided/delayed.

Simulation study reveals factors that affect the predominance of SARS-CoV-2 novel variant

The novel variants of the SARS-CoV-2 are a great global concern for the ongoing COVID-19 pandemic. However, how the novel variants predominate and replace existing strains remains elusive. In this study, I simulated the infection spread to investigate what kinds of viral, immunological, and epidemiological factors affect the predominance of SARS-CoV-2 novel variants. The results showed that the increase of the transmissibility of the novel variant substantially enhanced the predominance probability. In addition, the increasing trend of the infection spread, the large case number of the epidemic, and the ability of immune escape of the novel variant increased the predominance probability. A small number of cases and a decreasing trend of an entire epidemic, including not only the novel variant but also earlier strains, are especially important to reduce the chance of the predominance of the novel variant and delay the process. Good control of the COVID-19 epidemic could make the disease burden small and sequester the spread of the SARS-CoV-2 novel variants.

Score estimate of covid-19 risks as per socio-hygienic and behavioral indicators

Epidemiologic situation remains a serious concern all over the world due to the coronavirus infection spread. It is vital to adhere to measure of non-specific COVID-19 prevention. According to literature data, the highest risks of the infection spread occur in public transport, retail outlets where foods and nonfoods are sold, medical organizations, and chemists’ shops. Our research objects were socio-hygienic and behavioral indicators that were risk factors of the coronavirus infection. Our research aim was to substantiate a score estimate of the COVID-19 contagion risk based on socio-hygienic and behavioral indicators. Questioning was applied to determine frequency of visiting public places and adherence to basic measurements of non-specific COVID-19 prevention; overall, 400 respondents took part in it. A questionnaire was developed by experts of the De-partment of General Hygiene at Sechenov University and contained questions aimed at revealing informative signs (risk factors) of the coronavirus infection spread. Cluster analysis was applied to group respondents’ questions and to identify informative signs for further development of a scale showing risk categories. Factor analysis in a form of principal component analysis was applied to questions that had the highest number of statistically significant indicators of Spearman’s correlation coefficient. We developed a procedure for assessing risks of COVID-19 contagion according to socio-hygienic and behavioral in-dicators and substantiated risk categories. The most significant risk factors were indicators related to mandatory mask wearing when visiting specific social objects (risk objects); when taking trips by various means of public transport and duration of such trips; keeping social distance when visiting social objects. We performed score estimate of risk categories regarding COVID-19 contagion.

Import of Russian regions under conditions of COVID-19

The article examines the import activities of the subjects of the Russian Federation in the context of the coronavirus infection spread, analyses the import dynamics for 2019–2021, and constructs a regression model of panel data confirming the relationship between imports and the number of COVID-19 cases. It has been found that the number of cases of COVID-19 is directly impact on the import. Import volumes, in value terms, for the period 2019–2021, show a steady increase, which can be explained by an increase in mortality in the Russia, socio-economic consequences associated with the spread of COVID-19, and anticovidal sanitary and epidemiological restrictions.

Knowledge and Awareness of the Coronavirus Disease and Perceptions Towards Ophthalmic Practice Among Ophthalmologists

Objective: To investigate the level of awareness of ophthalmologists towards COVID-19 and their perceptions towards infection control in ophthalmic practice. Methods: A web-based survey was conducted using Google Forms during the month of December 2020. All ophthalmologists practicing in Sudan were invited to participate in the study. Participants who did not agree to the terms of the electronic consent form presented at the beginning of the questionnaire as well as those who did not complete the survey, were excluded from the analysis. Knowledge of causes, symptoms, and methods of transmission of COVID-19; ophthalmologists’ attitudes and perceptions towards COVID-19 and clinical practice, including contact lens practice, were assessed using a set of 26 multiple-choice close-ended questions. Results: Of the 307 participants, 77.4% were in the age range 30-40 years and 73% were contact lens practitioners. While 96.1% acknowledged the scientific name of COVID-19, 46.9% were aware of its cause. Ophthalmologists aged 40-50 years were more likely to agree that air-puffing tonometer risks infection spread (OR 1.62, 95% CI: 0.27-9.70, p<0.01). Ophthalmologists aged 30-40 years were more likely to agree that a slit lamp shield would reduce infection risk (OR 1.52, 95% CI: 0.33-6.96, p<0.01). Contact lens practitioners were more likely to perceive that frequent replacement contact lens use can increase the infection spread (OR 2.64, 95% CI: 1.17-5.94, p<0.01). Conclusion: Ophthalmologists in Sudan demonstrated a mixed level of knowledge of the causes, symptoms, and modes of transmission of COVID-19. While the majority were able to identify the protective measures generally required by medical practitioners and patients, there was a limited level of knowledge regarding protective measures specific to ophthalmic practices, especially when dealing with contact lenses. Official national guidelines about safe ophthalmic service provision during the COVID-19 pandemic are recommended.

Effect of COVID-19 Pandemic Control Measures on Diagnoses of Hematologic Cancer Among CMS Population in 2020

Introduction Measures taken to mitigate infection spread during the 2020 COVID-19 pandemic are considered to have caused significant unintended consequences on other diseases. Large decreases in the numbers of symptomatic and asymptomatic people presenting for diagnosis of heart disease, diabetes and cancer have been observed. A recent analysis of solid tumors showed up to 70% reduction in the number of patients presenting for diagnosis. The potential exists for significantly increased morbidity and mortality for these missed or delayed presenting patients. Further, it is important to determine whether infection spread mitigation measures affected the diagnostic testing and treatment decisions for these patients. This study aimed to determine whether pandemic control measures affected presentation, testing and treatment of patients across eight different hematologic cancers. Methods CMS claims data were analyzed for the presence of diagnostic (DX) ICD 10 codes indicative of hematologic cancer. Patients with a DX code first appearing in 2019 or in 2020 were selected to provide newly diagnosed pre-COVID-19 and during COVID-19 cohorts for comparison, with unique patient counts being calculated for each month. A "COVID-19 dip" i.e. a decrease in the number of patients was calculated as the change in number of patients diagnosed in a given month relative to the number for JAN2020. Dip duration was calculated only when the decrease was &gt;10% of the JAN2020 figure. Patients who received treatment via a "J" code Healthcare Common Procedure Coding System (HCPCS) code were extracted from the cohorts and the time taken from initial diagnosis to first treatment calculated. Results Eight hematologic cancers: AML, CLL, CML, HEME (a group of different hematologic cancers), Hodgkins (HOG), Myelodysplasia (MDS), Non-Follicular Lymphomas (NFL), and Non-Hodgkins Lymphoma (NHL) showed a decrease in the number of patients being diagnosed during the early part of 2020 (Fig.1) Fig.1. Change in new patient diagnoses for selected hematologic cancers as a proportion of their JAN2020 value There was some variation in the depth and duration of the COVID-19 dip (Table 1) with MDS having both the longest and deepest dip. Median depth and duration of the dip was 33% and 3.5 months, respectively, with all dips starting either in FEB or MAR2020. Table 1. Duration and depth of COVID-19 dips for selected hematological cancers The proportions of patients receiving therapy via J HCPCS code (JRX) are shown in Table 2 Table 2. Proportions of patients receiving J code therapy Conclusions The decline in new patient diagnoses for heme cancers during the period when COVID-19 control measures were implemented is similar to that seen with solid tumors, although the depth of the COVID-19 dip was generally larger in the latter. There is no evidence of "catch up" diagnosis occurring i.e. patients missing from Q2 2020 are not reappearing en masse in subsequent quarters. The decline for MDS patients has, except for SEP to OCT2020, remained. Collectively, (depending on the calculation method), the COVID-19 dip for these eight heme cancers represents 16,584-33,671 patients who will likely have significantly increased rates of morbidity and mortality due to delayed diagnosis. Analysis of J code treatments show little difference between the proportions of patients receiving these treatments in 2020 compared to 2019 suggesting that at least some aspects of treatment e.g. infused chemotherapy, IO drugs for these patients was relatively unchanged by pandemic control measures. It also suggests that the main cause for decreased patient numbers treated is due to decreased testing for diagnosis, rather than not being treated once diagnosed. This aligns with findings from studies in the US and UK. The results of this study indicate that there may be a "backlog" of tens of thousands of people with cancer whose diagnosis has been significantly delayed and who urgently need to be identified in order to get on proper treatment to lessen the impact of that delay. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

Impact of the stringency of lockdown measures on covid-19: A theoretical model of a pandemic

Background How effective have lockdowns been at reducing the covid-19 infection and mortality rates? Lockdowns influence contact among persons within or between populations including restricting travel, closing schools, prohibiting public gatherings, requiring workplace closures, all designed to slow the contagion of the virus. The purpose of the present study was to assess the impact of lockdown measures on the spread of covid-19 and test a theoretical model of the covid-19 pandemic employing structural equation modelling. Methods Lockdown variables, population demographics, mortality rates, infection rates, and health were obtained for eight countries: Austria, Belgium, France, Germany, Italy, Netherlands, Spain, and the United Kingdom. The dataset, owid-covid-data.csv, was downloaded on 06/01/2020 from: https://github.com/owid/covid-19-data/tree/master/public/data. Infection spread and mortality data were depicted as logistic growth and analyzed with stepwise multiple regression. The overall structure of the covid-19 data was explored through factor analyses leading to a theoretical model that was tested using latent variable path analysis. Results Multiple regression indicated that the time from lockdown had a small but significant effect (β = 0.112, p< 0.01) on reducing the number of cases per million. The stringency index produced the most important effect for mortality and infection rates (β = 0.588,β = 0.702, β = 0.518, β = 0.681; p< 0.01). Exploratory and confirmatory analyses resulted in meaningful and cohesive latent variables: 1) Mortality, 2) Infection Spread, 3) Pop Health Risk, and 4) Health Vulnerability (Comparative Fit Index = 0.91; Standardized Root Mean Square Residual = 0.08). Discussion The stringency index had a large impact on the growth of covid-19 infection and mortality rates as did percentage of population aged over 65, median age, per capita GDP, diabetes prevalence, cardiovascular death rates, and ICU hospital beds per 100K. The overall Latent Variable Path Analysis is theoretically meaningful and coherent with acceptable fit indices as a model of the covid-19 pandemic.

Simulating and visualizing infection spread dynamics with temporal networks

Temporal networks comprehend a widely adopted structure to model interactions involving a domain's instances over time. In the context of infection spread, it could be used to model face-to-face contacts among susceptible and infected individuals. By considering network visualization strategies, one can easily identify who infected whom and when, the epidemics outbreak, and other relevant behaviors. As a consequence, decision making related to the spread speed and magnitude becomes faster and more reliable. This paper presents a visual analytics approach for the simulation and analysis of infection spread dynamics that considers different infection probabilities and different levels of social distancing. We performed our experiments using two real-world social networks that represent school environments and our findings support the need for a high social distancing compliance allied to the adoption of protective measures such as the use of face masks.

Microbiome in Critical illness: An Unconventional and Unknown Ally

Background: The digestive tract represents an interface between the external environment and the body where the interaction of a complex polymicrobial ecology has an important influence on health and disease. The physiological mechanisms that are altered during the hospitalization and in the intensive care unit (ICU) contribute to the pathobiota’s growth. Intestinal dysbiosis occurs within hours of being admitted to ICU. This may be due to different factors, such as alterations of normal intestinal transit, administration of variuos medications or alterations in the intestinal wall which causes a cascade of events that will lead to the increase of nitrates and decrease of oxygen concentration, liberation of free radicals. Objective: This work aims to report the latest updates on the microbiota’s contribution to developing sepsis in patients in the ICU department. In this short review were reviewed the latest scientific findings on the mechanisms of intestinal immune defenses performed both locally and systemically. In addition, we considered it necessary to review the literature to report the current best treatment strategies to prevent the infection spread which can bring systemic infections in patients admitted to ICU. Material and Methods: This review has been written to answer at three main questions: what are the main intestinal flora’s defense mechanisms that help us to prevent the risk of developing systemic diseases on a day-to-day basis? What are the main dysbiosis’ systemic abnormalities? What are the modern strategies that are used in the ICU patients to prevent the infection spread? Using the combination of following keywords: microbiota and ICU, ICU and gut, microbiota and critical illness, microbiota and critical care, microbiota and sepsis, microbiota and infection, gastrointestinal immunity,in the Cochrane Controlled Trials Register, the Cochrane Library, medline and pubmed, google scholar, ovid/wiley. Finally, we reviewed and selected 72 articles. We also consulted the site ClinicalTrials.com to find out studies that are recently conducted or ongoing. Results: The critical illness can alter intestinal bacterial flora leading to homeostasis disequilibrium. Despite numerous mechanisms, such as epithelial cells with calciform cells that together build a mechanical barrier for pathogenic bacteria, the presence of mucous associated lymphoid tissue (MALT) which stimulates an immune response through the production of interferon-gamma (IFN-y) and THN-a or by stimulating lymphocytes T helper-2 produces anti-inflammatory cytokines. But these defenses can be altered following a hospitalization in ICU and lead to serious complications such as acute respiratory distress syndrome (ARDS), health care associated pneumonia (HAP) and ventilator associated pneumonia (VAP), Systemic infection and multiple organ failure (MOF), but also in the development of coronary artery disease (CAD). In addition, the microbiota has a significant impact on the development of intestinal complications and the severity of the SARS-COVID-19 patients. Conclusion: The microbiota is recognized as one of the important factors that can worsen the clinical conditions of patients who are already very frailty in intensive care unit. At the same time, the microbiota also plays a crucial role in the prevention of ICU associated complications. By using the resources, we have available, such as probiotics, symbiotics or fecal microbiota transplantation (FMT), we can preserve the integrity of the microbiota and the GUT, which will later help maintain homeostasis in ICU patients.