A Critical Review on Optimization of WEDM Process Using Taguchi Array

Wire electrical release machining (WEDM) innovation has developed at special case rate since it was first applied over long term prior.WEDM is a widely recognized unconventional material cutting process used to manufacture components with complex shapes and profiles of hard materials. In this thermal erosion process, there is no physical contact between the wire tool and work materials. Wire Electrical Discharge Machining (WEDM) is getting more tasks in fields like dies, punches, aero and many more. It is the very difficult task to get optimum process parameters for higher cutting efficiency. In WEDM process rough machining gives lesser accuracy and finish machining gives fine surface finish, but it reduces the machining speed. This review involves process, principle, literature and applications of WEDM using Taguchi array. Keywords: WEDM; Materials; Machine; Cutting efficiency; Optimization process.

Comparing the COVID-19 Responses in Cuba and the United States

The purpose of this analytic essay is to contrast the COVID-19 responses in Cuba and the United States, and to understand the differences in outcomes between the 2 nations. With fundamental differences in health systems structure and organization, as well as in political philosophy and culture, it is not surprising that there are major differences in outcomes. The more coordinated, comprehensive response to COVID-19 in Cuba has resulted in significantly better outcomes compared with the United States. Through July 15, 2021, the US cumulative case rate is more than 4 times higher than Cuba’s, while the death rate and excess death rate are both approximately 12 times higher in the United States. In addition to the large differences in cumulative case and death rates between United States and Cuba, the COVID-19 pandemic has unmasked serious underlying health inequities in the United States. The vaccine rollout presents its own set of challenges for both countries, and future studies can examine the comparative successes to identify effective strategies for distribution and administration. (Am J Public Health. 2021;111(12):2186–2193. https://doi.org/10.2105/AJPH.2021.306526 )

The Failures of an Ideal COVID-19 Vaccine: A Simulation Study

This paper simulates an ideal COVID-19 vaccine that confers immediate sterilizing immunity against all SARS-CoV-2 variants. The purpose was to explore how well this ideal vaccine could protect a population against common conditions (such as vaccine hesitancy) that might impair vaccine effectiveness. Simulations were done with an SEIRS spreadsheet model that ran two parallel subpopulations: one that accepted vaccination, and another that refused it. The two subpopulations could transmit infections to one another. Success was judged by the rate of new cases in the period from 1-5 years after the introduction of the vaccine. Under good conditions, including a small subpopulation that refused vaccination, rapid distribution of the vaccine, duration of vaccinal immunity longer than 12 months, good retention of interest in getting vaccinated after the first year, strict maintenance of nonpharmaceutical interventions (NPIs) such as masking, and new variants with R0s less than 4.0, the vaccine was able to end the epidemic. With violation of these conditions, the post-vaccine era futures ranged from endemic COVID at a low or medium level to rates of COVID cases worse than anything seen in the US up to late 2021. The most important conditions for keeping case rates low were a fast speed of vaccine distribution, a low percentage of the population that refuses vaccination, a long duration of vaccinal immunity, and continuing maintenance of NPIs after vaccination began. On the other hand, a short duration of vaccinal immunity, abandonment of NPIs, and new variants with a high R0 were powerful barriers to disease control. New variants with high R0s were particularly damaging, producing high case rates except when vaccination speed was unrealistically rapid. A recurring finding was that most disease afflicting the vaccinated population in these simulations originated in the unvaccinated population, and cutting off interaction with the unvaccinated population caused a sharp drop in the case rate of the vaccinated population. In conclusion, multiple common conditions can compromise the effectiveness of even an ideal vaccine.

Recurring Spatiotemporal Patterns of COVID-19 in the United States

We analyzed the waxing and waning patterns ('surges') of reported SARS-CoV-2 cases from January 1, 2020 through Oct 31, 2021 in all states and provinces (n = 93) in the USA, Mexico, and Canada, and across all counties (N = 3142) in the USA. A correlation matrix of the 576 x 576 daily case incidence rates in the 50 US states generates a distinctive 'checkerboard' pattern showing that the epidemic has consisted of seven distinct internally coherent spatiotemporal wave patterns, four in the first year of the epidemic, and three thus far in the second year. Geoclustering of state case rate trajectories reveals three dominant co-varying spatial clusters of similar case rate trajectories, in the northeastern, southeastern and central/western regions of the USA. The spatiotemporal patterns of epidemic year 1 have thus far been repeated (p<.001) in epidemic year 2. The 'checkerboard' pattern of the correlation matrix of case trajectories can be closely simulated as three sets of interacting sine waves with annual frequencies of 1:1:2 major cycles per year, corresponding to the northeastern, central/western, and southeastern state clusters. Case incidence patterns in Mexico and Canada have been similar to nearby regions in the southern US and the northern US, respectively. Time lapse videos allow visualization of the wave patterns. These highly structured geographical and temporal patterns, coupled with emerging evidence of annual repetition of these same patterns, show that SARS-CoV-2 case rates are driven at least in part by predictable seasonal factors.

1353. Gonorrhea and Chlamydia Testing and Case Rates Among Women Veterans in the Veterans Health Administration

Background United States (US) rates of sexually transmitted infection (STI) in women, especially gonorrhea and chlamydia, have increased over the past decade. Women Veterans have many risk factors associated with STIs, including high rates of childhood sexual assault, military sexual trauma and intimate partner violence. Despite the availability of effective diagnostic tests and evidence-based guidelines for annual screening among sexually active women under age 25, screening rates for gonorrhea and chlamydia remain low in the US and among Veterans. Methods We performed a retrospective cohort study of all women Veterans in Veterans Health Administration (VHA) care between January 1, 2018 and December 31, 2019 to examine patient characteristics and health system factors associated with gonorrhea and chlamydia testing and case rates among women Veterans in the VHA in 2019. Results Among women under age 25, 21.3% were tested for gonorrhea or chlamydia in 2019. After adjusting for demographic and other health factors, predictors of testing in women under age 25 included Black race (aOR: 2.11 CI: 1.89, 2.36), rural residence (aOR: 0.84, CI: 0.74, 0.95), and cervical cancer screening (aOR: 5.05 CI: 4.59, 5.56). Women under age 25 had the highest infection rates, with an incidence of chlamydia and gonorrhea of 1,950 and 267 cases/100,000, respectively. Incidence of gonorrhea and chlamydia was higher for women with a history of military sexual trauma (MST) (Chlamydia case rate: 265, Gonorrhea case rate: 97/100,000) and those with mental health diagnoses (Chlamydia case rate: 263, Gonorrhea case rate: 72/100,000.) Over a third of chlamydia cases (35.2%) and gonorrhea cases (35.5%) occurred in women who resided in the South Atlantic census division. Chlamydia cases per 100,000 women Veterans seen in VHA (2019) Gonorrhea cases per 100,000 women Veterans seen in VHA (2019) Conclusion Gonorrhea and chlamydia testing remains underutilized among women in the VHA and infection rates are high among younger women. Patient-centered, system-level interventions are urgently needed to address low testing rates. Disclosures All Authors: No reported disclosures

Vaccinating adolescents against SARS-CoV-2 in England: a risk–benefit analysis

Objective To offer a quantitative risk–benefit analysis of two doses of SARS-CoV-2 vaccination among adolescents in England. Setting England. Design Following the risk–benefit analysis methodology carried out by the US Centers for Disease Control, we calculated historical rates of hospital admission, Intensive Care Unit admission and death for ascertained SARS-CoV-2 cases in children aged 12–17 in England. We then used these rates alongside a range of estimates for incidence of long COVID, vaccine efficacy and vaccine-induced myocarditis, to estimate hospital and Intensive Care Unit admissions, deaths and cases of long COVID over a period of 16 weeks under assumptions of high and low case incidence. Participants All 12–17 year olds with a record of confirmed SARS-CoV-2 infection in England between 1 July 2020 and 31 March 2021 using national linked electronic health records, accessed through the British Heart Foundation Data Science Centre. Main outcome measures Hospitalisations, Intensive Care Unit admissions, deaths and cases of long COVID averted by vaccinating all 12–17 year olds in England over a 16-week period under different estimates of future case incidence. Results At high future case incidence of 1000/100,000 population/week over 16 weeks, vaccination could avert 4430 hospital admissions and 36 deaths over 16 weeks. At the low incidence of 50/100,000/week, vaccination could avert 70 hospital admissions and two deaths over 16 weeks. The benefit of vaccination in terms of hospitalisations in adolescents outweighs risks unless case rates are sustainably very low (below 30/100,000 teenagers/week). Benefit of vaccination exists at any case rate for the outcomes of death and long COVID, since neither have been associated with vaccination to date. Conclusions Given the current (as at 15 September 2021) high case rates (680/100,000 population/week in 10–19 year olds) in England, our findings support vaccination of adolescents against SARS-CoV2.

The Symmetric and Asymmetric Time-Varying Causality Relationships Between the COVID-19 Outbreak and the Stock Exchange: The Case of Selected Countries

In this study, the effects of COVID-19 (mortality rate, case rate, and bed capacity) on the stock market was examined within the framework of the efficient market hypothesis. Unlike other studies in the literature, we used the variable of bed capacity besides the mortality rate and case rate variables. The relationship between the mentioned variables, using daily data between December 31 of 2019 and November 10 of 2020, has been analyzed with time-varying symmetric and asymmetric causality tests for China, Germany, the USA, and India. Considering that the responses to positive and negative shocks during the pandemic process may be different and that the results may change depending on time, time-varying symmetric and asymmetric causality tests were used. According to the time-varying symmetric causality test, stock markets in all countries were affected in the period when the cases first appeared. A causal relationship between COVID-19 and country stock markets was found. The results showed that the effects of the case rate and bed capacity on the stock market occurred around the same time in Germany and the United States; however, these dates differed in China and India. According to time-varying asymmetric causality test findings, the asymmetric effect of the pandemic on the stock market in countries emerged during the second wave. The findings showed that the period during which positive and negative information about the pandemic intensified coincided with the period during which the second wave occurred; besides, the results show the effect of this information on the stock market differed as positive and negative shocks.

Human-Network Regions as Effective Geographic Units for Disease Mitigation

Susceptibility to infectious diseases such as COVID-19 depends on how they spread, and many studies have captured the decrease in COVID-19 spread due to reduction in travel. However, less is known about practical geographic boundaries for that limit the spread of COVID-19 to adjacent places. To detect such boundaries, we apply community-detection algorithms to large networks of mobility and social-media connections to construct geographic regions that reflect natural human movement and relationships at the county level for the continental United States. We measure COVID-19 cases, case rates, and case-rate variations across adjacent counties and examine how often COVID-19 crosses the boundaries of these functional regions. We find that regions that we construct using GPS-trace networks and especially commuter networks have the smallest rates of COVID-19 case rates along the boundaries, so these regions may reflect natural partitions in COVID-19 transmission. Conversely, regions that we construct from geolocated Facebook friendships and Twitter connections yield the least effective partitions. Our analysis reveals that regions that are derived from movement flows are more appropriate geographic units than states for making policy decisions about opening areas for activity, assessing vulnerability of populations, and allocating resources. Our insights are also relevant for policy decisions and public messaging in future emergency situations.