An ANN-TLBO Model to Predict Cumulative Number of Failures in Software

SummaryWe have evaluated platelet function in different subtypes of von Willebrand disease (vWD) by pushing blood through the capillarysized channels of a glass filter. Patients, including those with type IIB vWD, showed lower than normal platelet retention and increased cumulative number of blood drops passing through the filter as a function of time. In contrast, shear-induced platelet aggregation, measured in the cone-and-plate viscometer, was paradoxically increased in type IIB patients. Treatment with l-desamino-8-D-arginine vasopressin (DDAVP) tended to normalize the filter test in patients with type I-platelet normal and type I-platelet low vWD, but infusion of a factor VUI/von Willebrand factor (vWF) concentrate lacking the largest vWF multimers was without effect in type 3 patients. Experiments with specific monoclonal antibodies demonstrated that the A1 and A3 domains of vWF, as well as the glycoproteins Ibα and Ilb-IIIa on platelets, are required for platelet retention in the filter. Thus, the test may reflect vWF function with regard to both platelet adhesion and aggregation under high shear stress, and provide relevant information on mechanisms involved in primary hemostasis.

Download Full-text

Modeling COVID-19 Growing Trends to Reveal the Differences in the Effectiveness of Non-Pharmaceutical Interventions among Countries in the World (Preprint)

10.2196/preprints.19607 ◽

2020 ◽

Cited By ~ 2

Author(s):

You Chen ◽

Yubo Feng ◽

Chao Yan ◽

Xinmeng Zhang ◽

Cheng Gao

Keyword(s):

Secondary Analysis ◽

Reproduction Rate ◽

Cumulative Number ◽

Linear Regression Models ◽

Growth Data ◽

Dynamic Changes ◽

The World ◽

Four Levels ◽

Almost All ◽

Pharmaceutical Interventions

BACKGROUND Adopting non-pharmaceutical interventions (NPIs) can affect COVID-19 growing trends, decrease the number of infected cases, and thus reduce mortality and healthcare demand. Almost all countries in the world have adopted non-pharmaceutical interventions (NPIs) to control the spread rate of COVID-19; however, it is unclear what are differences in the effectiveness of NPIs among these countries. OBJECTIVE We hypothesize that COVID-19 case growth data reveals the efficacy of NPIs. In this study, we conduct a secondary analysis of COVID-19 case growth data to compare the differences in the effectiveness of NPIs among 16 representative countries in the world. METHODS This study leverages publicly available data to learn patterns of dynamic changes in the reproduction rate for sixteen countries covering Asia, Europe, North America, South America, Australia, and Africa. Furthermore, we model the relationships between the cumulative number of cases and the dynamic reproduction rate to characterize the effectiveness of the NPIs. We learn four levels of NPIs according to their effects in the control of COVID-19 growth and categorize the 16 countries into the corresponding groups. RESULTS The dynamic changes of the reproduction rate are learned via linear regression models for all of the studied countries, with the average adjusted R-squared at 0.96 and the 95% confidence interval as [0.94 0.98]. China, South Korea, Argentina, and Australia are at the first level of NPIs, which are the most effective. Japan and Egypt are at the second level of NPIs, and Italy, Germany, France, Netherlands, and Spain, are at the third level. The US and UK have the most inefficient NPIs, and they are at the fourth level of NPIs. CONCLUSIONS COVID-19 case growth data provides evidence to demonstrate the effectiveness of the NPIs. Understanding the differences in the efficacy of the NPIs among countries in the world can give guidance for emergent public health events. CLINICALTRIAL NA

Download Full-text

Aflibercept in real-life for the treatment of age-related macular degeneration using a treat and extend protocol: The Armada study

European Journal of Ophthalmology ◽

10.1177/11206721211005703 ◽

2021 ◽

pp. 112067212110057

Author(s):

Pierre Gascon ◽

Prithvi Ramtohul ◽

Charles Delaporte ◽

Sébastien Kerever ◽

Danièle Denis ◽

...

Keyword(s):

Macular Degeneration ◽

Real Life ◽

Age Related Macular Degeneration ◽

Cumulative Number ◽

Treat And Extend ◽

Treatment Interval ◽

Age Related ◽

Treatment Naïve ◽

The Mean

Purpose: To report the visual and anatomic outcomes in treatment-naïve neovascular age-related macular degeneration (nAMD) patients treated with aflibercept under a standardized Treat and Extend (T&E) protocol for up to 3 years of follow-up in “real-life” practice. Methods: This retrospective, observational, multicenter study included patients with treatment-naïve nAMD and at least 12 months of follow-up. T&E regimen adjustment was initiated after loading phase. At each visit best-corrected visual acuity (BCVA) and optical coherence tomography parameters were performed. Results: One hundred and thirty-six eyes of 115patients had at least 1 year of follow-up with 114 and 82 eyes completing at least 2 and 3 years of follow-up, respectively (mean follow-up duration: 2.7 ± 1.3 years). Mean age was 78.6 ± 8.6 years old and 52% were women. Mean BCVA increased from 60.6 ± 18.7 letters at diagnosis to 66.9 ± 16.2 letters at 1 year (+6.3 letters, p = 0.003) and remained stable throughout the follow-up period (63.1 ± 20.3 letters (+2.5, p = 0.1) and 64.0 ± 20.1 letters (+3.4, p = 0.27) at 2 and 3 years, respectively). The mean central retinal thickness decreased significantly from 358.2 ± 87.9 µm at baseline to 302 ± 71.7 µm at 12 months and maintained stable after 36 months of follow-up (297.1 ± 76 µm, p < 0.0001). Mean number of injections was 6.6 ± 2.2, 4.8 ± 1.9, and 5.6 ± 1.7 at 1, 2, and 3 years, respectively. Mean cumulative number of 16.4 ± 5.6 injections after 3 years. Mean treatment interval was 6.8 ± 2.5 weeks at 1 year. Eight-week and 12-week treatment interval were achieved in 59.5% and 19.1%, 65.8%, and 36.8% and 69.5% and 41.5% at 1, 2, and 3 years, respectively. Conclusions: Our study demonstrated that intravitreal injections of aflibercept initiated under a standardized T&E for patients with treatment-naïve nAMD allow for significant visual improvement at 12 months, which was maintained over a 3-year follow-up period.

Download Full-text

Reliability modeling for multi-state systems with a protective device considering multiple triggering mechanism

Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability ◽

10.1177/1748006x211013325 ◽

2021 ◽

pp. 1748006X2110133

Author(s):

Xian Zhao ◽

Rong Li ◽

Yu Fan ◽

Qingan Qiu

Keyword(s):

Failure Modes ◽

Operating Time ◽

Replacement Policy ◽

Economic Losses ◽

Residual Lifetime ◽

Cumulative Number ◽

Protective Device ◽

Triggering Mechanism ◽

Safety Critical ◽

Markov Chain Imbedding

Failures of safety-critical systems may result in irretrievable economic losses and significant safety hazards, thus enhancing the reliability of safety-critical system is crucial. As applied widely in engineering fields, protective devices are commonly equipped for the systems operating in shock environment to reduce external damage, which has not been taken into consideration in existing literatures. This paper investigates the reliability of multi-state systems with competing failure patterns supported by a protective device. According to the system failure modes, state-based and shock number-based triggering mechanism of the protective device are developed. That is, the protective device is triggered once the system state or cumulative number of shocks exceeds corresponding critical thresholds respectively. After being triggered, the protective device can reduce the probability of damaging shocks for the system. The protective device fails when the number of consecutive valid shocks reaches a threshold. Based on the constructed model, a finite Markov chain imbedding approach is employed to derive reliability indices including distribution functions of system lifetime and residual lifetime, together with expected operating time of the protective device. Moreover, two age-based replacement policies together with a condition-based replacement policy are developed to accommodate different maintenance scenarios and corresponding optimal solutions are acquired. Numerical illustrations based on the application of cooling systems in engines are presented to validate the results.

Download Full-text

Modelling spreading of an infection using time series by a novel family of models; fitting the time series of the confirmed cases of COVID-19 in China

Epidemiologic Methods ◽

10.1515/em-2020-0013 ◽

2020 ◽

Vol 9 (s1) ◽

Author(s):

Babak Jamshidi ◽

Shahriar Jamshidi Zargaran ◽

Mansour Rezaei

Keyword(s):

Infectious Disease ◽

Time Series ◽

Communicable Disease ◽

Time Series Models ◽

Cumulative Number ◽

The Novel ◽

New Family ◽

Two Samples ◽

Almost All ◽

Number Of Individuals

AbstractIntroductionTime series models are one of the frequently used methods to describe the pattern of spreading an epidemic.MethodsWe presented a new family of time series models able to represent the cumulative number of individuals that contracted an infectious disease from the start to the end of the first wave of spreading. This family is flexible enough to model the propagation of almost all infectious diseases. After a general discussion on competent time series to model the outbreak of a communicable disease, we introduced the new family through one of its examples.ResultsWe estimated the parameters of two samples of the novel family to model the spreading of COVID-19 in China.DiscussionOur model does not work well when the decreasing trend of the rate of growth is absent because it is the main presumption of the model. In addition, since the information on the initial days is of the utmost importance for this model, one of the challenges about this model is modifying it to get qualified to model datasets that lack the information on the first days.

Download Full-text

Polarized nature of the COVID-19 pandemic in Japan: associations with population age structure and behaviours

Tropical Medicine and Health ◽

10.1186/s41182-021-00324-0 ◽

2021 ◽

Vol 49 (1) ◽

Author(s):

Junko Okumura

Keyword(s):

Age Structure ◽

Public Transportation ◽

Perceived Risk ◽

Online Survey ◽

Preventive Measures ◽

Age Groups ◽

Cumulative Number ◽

Population Age Structure ◽

Major Factors ◽

Drinking Places

Abstract Background Although the scale of the coronavirus disease (COVID-19) pandemic was relatively small in Japan compared with the rest of the world, the polarisation of areas into high- and low-COVID-19-incidence areas was observed among the 47 prefectures. The aims of this study were not only identifying the factors associated with the polarised COVID-19 pandemic in Japan but also discussing effective preventive measures. Methods This was an ecological study using online survey data which was cross-sectionally conducted by the author. A total of 6000 respondents who resided in 10 low- and 10 high-COVID-19 incidence prefectures, with a wide gap in terms of COVID-19 incidence, in Japan were recruited. Data on COVID-19 cases and geodemographic information were obtained from official government sites. Statistical analyses were conducted to compare variables between the two areas and age groups. Results This study revealed that that age influenced people’s behaviours and perceptions, except one behaviour of ‘wearing facemasks’. The major factors significantly associated with the cumulative number of COVID-19 cases per 100,000 people were ‘commuting by private automobile’ (adjusted odds ratio [AOR], 0.444; 95% confidence interval [CI], 0.394–0.501), ‘commuting by public transportation’ (AOR, 6.813; 95% CI, 5.567–8.336), ‘washing hands’ (AOR, 1.233; 95% CI, 1.005–1.511), ‘opening windows regularly’ (AOR, 1.248; 95% CI, 1.104–1.412), ‘avoiding crowded places (AOR, 0.757; 95% CI, 0.641–0.893), ‘non-scheduled visits to drinking places’ (AOR, 1.212; 95% CI, 1.054–1.392) and ‘perceived risk of contracting COVID-19’ (AOR, 1.380; 95% CI, 1.180–1.612). These factors were strongly associated with age groups. Conclusions Effective preventive measures for COVID-19 transmission can be developed by understanding the characteristics of populated areas, such as public transportation infrastructure and younger people’s movements and behaviours in relation to the population age structure to contain the current epidemic and protect the most vulnerable elderly people.

Download Full-text

757. Association between cumulative febrile, respiratory and diarrheal illness in the first year of life and neurodevelopmental and growth outcomes among a cohort of children in rural Guatemala

Open Forum Infectious Diseases ◽

10.1093/ofid/ofaa439.947 ◽

2020 ◽

Vol 7 (Supplement_1) ◽

pp. S425-S426

Author(s):

Daniel Olson ◽

Molly Lamb ◽

Amy Connery ◽

Desiree Bauer ◽

Alejandra Paniagua-Avila ◽

...

Keyword(s):

Maternal Education ◽

Febrile Illness ◽

Early Learning ◽

First Year ◽

Cumulative Number ◽

Linear Regression Models ◽

Surveillance Period ◽

Final Study ◽

First Year Of Life ◽

Height For Age

Abstract Background Recurrent infections are associated with neurodevelopmental (ND) delay in infants, but the primary drivers are poorly understood. Leveraging an infant cohort from rural Guatemala designed to evaluate the effects of post-natal Zika virus on ND (DMID 16-0057), we evaluated the association between cumulative illness and ND delay and stunting. Methods Infants enrolled at 0-3 months of age underwent weekly at-home surveillance for caregiver-reported syndromic illness, including cough, fever and vomiting/diarrhea for a 12-month period. Anthropometric assessments and ND testing by Guatemalan psychologists using the Mullen Scales of Early Learning (MSEL) were perforrmed at 12-15 months of age. Multivariable generalized linear regression models were used to test associations between syndromic illness in infancy, 12-15-month MSEL Early Learning Composite (ELC) Score, and stunting (height-for-age < -2 SD) at 12-15 months. Results The cohort (n=425) had a mean enrollment age of 1.3 months; 202 (48%) were female, 387 (91%) self-reported a literate mother, and 301 (71%) were breastfeeding at study completion. Infants had reported illness for a median of 16 weeks during the surveillance period; cough was reported most frequently (median=11 weeks, range=0-37 weeks). Lower maternal education (p=0.007) and literacy (p=0.002) as well as infant age (p=0.007) and male gender (p=0.004) were associated with MSEL ELC Score <85 (-1 SD). After adjusting for gender, breastfeeding, age, and maternal literacy, the cumulative number of weeks with reported cough (p=0.0009), fever (p=0.0001), or any syndromic illness (p=0.0007) were associated with decreased 12-month MSEL ECL Score; there was no association with diarrhea/vomiting (p=0.36). There was no association between caregiver-reported syndromic illnesses (any type) and stunting at final study visit. Conclusion In a cohort of Guatemalan infants, cumulative fever and cough episodes were significantly associated with lower MSEL ELC Score, whereas there was no association with diarrhea/vomiting. In this low-resource community, these findings highlight the potential negative ND consequences of febrile illness and persistent cough in the first year of life. NIAID Contract HHSN272201300015I Task Order HHSN27200013 (Co-PIs: FMM and EJA). Disclosures Molly Lamb, PhD, BioFire (Grant/Research Support) Evan J. Anderson, MD, Sanofi Pasteur (Scientific Research Study Investigator)

Download Full-text

A global association between Covid-19 cases and airborne particulate matter at regional level

Scientific Reports ◽

10.1038/s41598-021-85751-z ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Angelo Solimini ◽

F. Filipponi ◽

D. Alunni Fegatelli ◽

B. Caputo ◽

C. M. De Marco ◽

...

Keyword(s):

Air Pollution ◽

Particulate Matter ◽

Negative Binomial ◽

Numerical Models ◽

Regional Level ◽

Pollution Level ◽

Observation Data ◽

Cumulative Number ◽

Mixed Effect

AbstractEvidences of an association between air pollution and Covid-19 infections are mixed and inconclusive. We conducted an ecological analysis at regional scale of long-term exposure to air-borne particle matter and spread of Covid-19 cases during the first wave of epidemics. Global air pollution and climate data were calculated from satellite earth observation data assimilated into numerical models at 10 km resolution. Main outcome was defined as the cumulative number of cases of Covid-19 in the 14 days following the date when > 10 cumulative cases were reported. Negative binomial mixed effect models were applied to estimate the associations between the outcome and long-term exposure to air pollution at the regional level (PM10, PM2.5), after adjusting for relevant regional and country level covariates and spatial correlation. In total we collected 237,749 Covid-19 cases from 730 regions, 63 countries and 5 continents at May 30, 2020. A 10 μg/m3 increase of pollution level was associated with 8.1% (95% CI 5.4%, 10.5%) and 11.5% (95% CI 7.8%, 14.9%) increases in the number of cases in a 14 days window, for PM2.5 and PM10 respectively. We found an association between Covid-19 cases and air pollution suggestive of a possible causal link among particulate matter levels and incidence of COVID-19.

Download Full-text

Analysis and prediction of the coronavirus disease epidemic in China based on an individual-based model

Scientific Reports ◽

10.1038/s41598-020-76969-4 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Zuiyuan Guo ◽

Dan Xiao

Keyword(s):

Reproduction Number ◽

Control Measures ◽

Cumulative Number ◽

Individual Based Model ◽

Whole Process ◽

Coordinate Descent Algorithm ◽

Initial Stage ◽

The Government ◽

Prevention And Control Measures ◽

And Control

AbstractWe established a stochastic individual-based model and simulated the whole process of occurrence, development, and control of the coronavirus disease epidemic and the infectors and patients leaving Hubei Province before the traffic was closed in China. Additionally, the basic reproduction number (R0) and number of infectors and patients who left Hubei were estimated using the coordinate descent algorithm. The median R0 at the initial stage of the epidemic was 4.97 (95% confidence interval [CI] 4.82–5.17). Before the traffic lockdown was implemented in Hubei, 2000 (95% CI 1982–2030) infectors and patients had left Hubei and traveled throughout the country. The model estimated that if the government had taken prevention and control measures 1 day later, the cumulative number of laboratory-confirmed patients in the whole country would have increased by 32.1%. If the lockdown of Hubei was imposed 1 day in advance, the cumulative number of laboratory-confirmed patients in other provinces would have decreased by 7.7%. The stochastic model could fit the officially issued data well and simulate the evolution process of the epidemic. The intervention measurements nationwide have effectively curbed the human-to-human transmission of severe acute respiratory syndrome coronavirus 2.

Download Full-text

Effectiveness of Government Policies in Controlling COVID-19 in India

International Journal of Health Services ◽

10.1177/0020731420983749 ◽

2020 ◽

pp. 002073142098374

Author(s):

Ashutosh Pandey ◽

Nitin Kishore Saxena

Keyword(s):

Population Density ◽

Rural Areas ◽

Rural Population ◽

Urban Areas ◽

Urban Population ◽

Demographic Factors ◽

Poverty Rate ◽

Government Policies ◽

Cumulative Number ◽

Population Number

The purpose of this study is to find the demographic factors associated with the spread of COVID-19 and to suggest a measure for identifying the effectiveness of government policies in controlling COVID-19. The study hypothesizes that the cumulative number of confirmed COVID-19 patients depends on the urban population, rural population, number of persons older than 50, population density, and poverty rate. A log-linear model is used to test the stated hypothesis, with the cumulative number of confirmed COVID-19 patients up to period [Formula: see text] as a dependent variable and demographic factors as an independent variable. The policy effectiveness indicator is calculated by taking the difference of the COVID rank of the [Formula: see text]th state based on the predicted model and the actual COVID rank of the [Formula: see text]th state[Formula: see text]Our study finds that the urban population significantly impacts the spread of COVID-19. On the other hand, demographic factors such as rural population, density, and age structure do not impact the spread of COVID-19 significantly. Thus, people residing in urban areas face a significant threat of COVID-19 as compared to people in rural areas.

Download Full-text