Realization of Coronavirus Testing Kit Using a Combination of a Triangular Photonic Crystal (PhC) Structure and a 412 nm Laser Beam

The design of a Covid-19 testing kit is proposed in this research using a photonic crystal structure (PhC) and a violet laser beam. The basic principle of this structure relies on the phenomenon of absorbance reflectance and transmission at the signal of a 412 nm laser beam. Finally, the transmitted light energy through the PhC structure is the conclusive factor to detect the types of virus which is the function of the reflectance and absorbance. The reflected light energy is computed by plane wave expansion (PWE) whereas the absorbance of light energy is obtained through numerical computation. The notable advantages of this technique are that the virus related to Covid-19 can be recognized by observing the colour of transmitted energy through a photo energy meter. Finally, the outcomes of the research affirm that the sample could be Covid-19 if the output energy would be infrared (IR). Similarly, the sample could be a normal coronavirus, if the output energy would lie within the visible regime.

Pulmonary influenza infection promotes the awakening of dormant metastatic breast cancer cells

Breast cancer is the most common form of cancer and the second cancer-causing death in females. Although remission rates are high if detected early, survival rates drop substantially when breast cancer becomes metastatic. The most common sites of metastatic breast cancer are bone, liver and lung. Respiratory viral infections inflict illnesses on countless people. The latest pandemic caused by the respiratory virus, SARS-CoV-2, has infected more than 600 million worldwide, with documented COVID-related death upward of 1 million in the United States alone. Respiratory viral infections result in increased inflammation with immune cell influx and expansion to facilitate viral clearance. Prior studies have shown that inflammation, including through neutrophils, can contribute to dormant cancer cells reawakening and outgrowth. Moreover, inhibition of IL6 has been shown to decrease breast cancer lung metastasis in mouse models. However, how respiratory viral infections contribute to breast cancer lung metastasis remains to be unraveled. Using MMTV/PyMT and MMTV/NEU mouse models of breast cancer lung metastasis and influenza A virus as a model respiratory virus, we demonstrated that acute influenza infection and the accompanying inflammation and immune cell influx awakens and dramatically increased proliferation and expansion of dormant disseminated cancer cells (DCC) in the lungs. Acute influenza infection leads to immune influx and expansion, including neutrophils and macrophages, with increased proportion of MHCII+ macrophages in early time points, and a sustained decrease in CD206+ macrophages starting 6 days post-infection until 28 days after the initial infection. Additionally, we observed a sustained accumulation of CD4+ T cells around expanding tumor cells for as long as 28 days after the infection. Notably, neutrophil depletion or IL6 knockout reversed the flu-induced dormant cell expansion in the lung. Finally, awakened DCC exhibited downregulation of vimentin immunoreactivity, suggesting a role for phenotypic plasticity in DCC outgrowth following viral infection. In conclusion, we show that respiratory viral infections awaken and increase proliferation of dormant breast cancer cells in the lung, and that depletion of neutrophils or blocking IL6 reverses influenza-induced dormant cell awakening and proliferation.

Expansion of human T cells using xenogeneic free and gamma irradiated human platelet lysate

Commercially available human platelet lysate (hPL) is produced using expired human platelets obtained from accredited blood banks in the United States. These platelets were originally intended for use in patient transfusion. The safety of platelets used in transfusion is managed by the U.S. Food Drug Administration (FDA), as well as the American Association of Blood Banks (AABB). These organizations set standards, including testing for transmissible diseases. The United States record for blood safety is well established, with extremely low rates of disease transmission, making the platelet units used for hPL manufacture low risk. The Covid-19 pandemic has increased awareness of emerging infectious diseases, even though transmission of Covid-19 via blood transfusion has not been documented. For that reason, gamma irradiated hPL offers an additional safety measure in the clinic. Chimeric Antigen Receptor (CAR) expressing T-cells have demonstrated potent clinical efficacy in patients with hematological malignancies. In addition, there are several phase I clinical trials evaluating the use of CAR-T-cells for targeting of solid tumorassociated antigens. Some of the challenging issues found during production of CAR-T cells are the efficiency of T cell transduction to generate CAR-T cells, the expansion of T cells to clinically relevant numbers and the long-term survival in vivo of the therapeutic cells. The use of human platelet lysate has been demonstrated to improve these issues. Our data from experiments performed using human CD3+ from donors demonstrates that human platelet lysates offer an improved performance on T cell expansion versus serum derived products. hPL efficiently promotes T cell expansion, with higher cell yields and lower cell exhaustion rate. Additionally, we efficiently developed a protocol for suspension culture of T cells, which could facilitate the large-scale expansion of allogeneic CAR-T cells.

Coupling Random Forest, Allometric Scaling, and Cellular Automata to Predict the Evolution of LULC under Various Shared Socioeconomic Pathways

Accurately estimating land-use demand is essential for urban models to predict the evolution of urban spatial morphology. Due to the uncertainties inherent in socioeconomic development, the accurate forecasting of urban land-use demand remains a daunting challenge. The present study proposes a modeling framework to determine the scaling relationship between the population and urban area and simulates the spatiotemporal dynamics of land use and land cover (LULC). An allometric scaling (AS) law and a Markov (MK) chain are used to predict variations in LULC. Random forest (RF) and cellular automata (CA) serve to calibrate the transition rules of change in LULC and realize its micro-spatial allocation (MKCA(RF-AS)). Furthermore, this research uses several shared socioeconomic pathways (SSPs) as scenario storylines. The MKCA(RF-AS) model is used to predict changes in LULC under various SSP scenarios in Jinjiang City, China, from 2020 to 2065. The results show that the figure of merit (FoM) and the urban FoM of the MKCA(RF-AS) model improve by 3.72% and 4.06%, respectively, compared with the MKCA(ANN) model during the 2005-2010 simulation period. For a 6.28% discrepancy between the predicted urban land-use demand and the actual urban land-use demand over the period 2005-2010, the urban FoM degrades by 21.42%. The growth of the permanent urban population and urban area in Jinjiang City follows an allometric scaling law with an exponent of 0.933 for the period 2005-2020, and the relative residual and R-2 are 0.0076 and 0.9994, respectively. From 2020 to 2065, the urban land demand estimated by the Markov model is 19.4% greater than the urban area predicted under scenario SSP5. At the township scale, the different SSP scenarios produce significantly different spatial distributions of urban expansion rates. By coupling random forest and allometric scaling, the MKCA(RF-AS) model substantially improves the simulation of urban land use.

Uncovering Hidden Media Framings in Generic Communication Competence Assessments: Is the Face-To-Face Context the Default Framing?

Dispositional communication competencies can be assessed in (a) a generic form that does not include any reference to a particular medium of interaction or in (b) a communication medium-specific version. To date, little is known about the specific media that individuals use as a reference and the weights they assign to them when responding to generic communication items - an important research gap because the use of diverse communication media has risen considerably during the COVID-19 pandemic. Based on media theories, two hypotheses were derived: Generic ratings contain a "hidden" face-to-face (FtF) communication framing that is dominant in the cognitive processing (media naturalness perspective) versus media are equally weighted in the mental aggregate of respondents (adaptation perspective). According to a preregistered study plan, generic and medium-specific communication items were assessed to investigate these hypotheses (referencing FtF, videoconferencing, chat, and e-mail interaction contexts). Training (n = 200) and test (n = 389) datasets were analyzed using latent variable modeling. Results indicated that generic ratings have a strong hidden FtF framing. These hidden framings impact the predictive power of the competencies to explain communication criteria (i.e. communication satisfaction). Exploratory analyses indicated that individual differences in media experience may affect the framings.

Structural Racism, the USPS, and Voting by Mail On- and Off-Reservation in Arizona

During the 2020 election, voting by mail greatly expanded due to concerns with COVID-19. While voting by mail is relatively easy for most individuals, who have United States Postal Service (USPS) residential mail service, it is much more difficult for those with nonstandard mail service. In this article, we examine how decisions made by the USPS in the latter part of the nineteenth and early twentieth centuries have resulted in deeply entrenched structural inequities in the access to mail services on the Navajo Nation in Arizona when compared to rural nonreservation communities. Most (89 percent) of current Post Offices were established during the settler colonial period, during which sites were chosen primarily to advance military objectives and serve the interests of Anglo-American settlers. The resulting inequitable pattern of postal access remains, resulting in inferior mail service on the Navajo Nation and adversely impacting many aspects of life. Post Offices are fewer and farther from each other on reservation communities;there are fewer service hours;and we show in a mail experiment that letters posted on reservations are slower and less likely to arrive. This research fits within the growing body of American political development research on path-dependent processes and "spatial racism" within geography.

Development of a Lymphoid Organ-Chip to Evaluate Covid Vaccine Boosting Strategies

Background: Secondary lymphoid organs provide the adequate microenvironment for the development of antigen (Ag)-specific immune responses. The tight collaboration between CD4+ T cells and B cells in germinal centers is crucial to shape B cell fate and optimize antibody maturation. Dissecting these immune interactions remains challenging in humans, and animal models do not always recapitulate human physiology. To address this issue, we developed an in vitro 3D model of a human lymphoid organ. The model relies on a microfluidic device, enabling primary human cells to self-organize in an extracellular matrix (ECM) under continuous fluid perfusion. We applied this Lymphoid Organ-Chip (LO chip) system to the analysis of B cell recall responses to SARS-CoV-2 antigens. Method(s): We used a two-channel microfluidic Chip S1 from Emulate, where the top channel is perfused with antigen (spike protein or SARS-CoV-2 mRNA vaccine), while the bottom channel contains PBMC (n = 14 independent donors) seeded at high-density in a collagen-based ECM. Immune cell division and cluster formation were monitored by confocal imaging, plasmablast differentiation and spike-specific B cell amplification by flow cytometry, antibody secretion by a cell-based binding assay (S-flow). Result(s): Chip perfusion with the SARS-CoV-2 spike protein for 6 days resulted in the induction CD38hiCD27hi plasmablast maturation compared to an irrelevant BSA protein (P< 0.0001). Using fluorescent spike as a probe, we observed a strong amplification of spike-specific B cell (from 3.7 to 140-fold increase). In line with this rapid memory B cell response, spike-specific antibodies production could be detected as early as day 6 of culture. Spike perfusion also induced CD4+ T cell activation (CD38+ ICOS+), which correlated with the level of B cell maturation. The magnitude of specific B cell amplification in the LO chip was higher than in 2D and 3D static cultures at day 6, showing the added value of 3D perfused culture for the induction of recall responses. Interestingly, the perfusion of mRNA-based SARS-CoV-2 vaccines also led to strong B cell maturation and specific B cell amplification, indicating that mRNA-derived spike could be expressed and efficiently presented in the LO chip. Conclusion(s): We developed a versatile Lymphoid Organ-Chip model suitable for the rapid evaluation of B cell recall responses. The model is responsive to protein and mRNA-encoded antigens, highlighting its potential in the evaluation of SARS-CoV-2 vaccine boosting strategies.

HIGH FAT AND SUGAR DIET INDUCES GUT LEUKOCYTE DISRUPTIONS EXACERBATED BY SARS-CoV-2

Background: The disparity in COVID-19 disease burden between European, Asian, and African countries is notable, with considerably higher morbidity and mortality in many European countries as well as the U.S. Dietary differences between regions could play a role in differential COVID-19 pathogenesis, as Western diets high in fat and sugar have been implicated in enhancing gut damage and pathogenesis during viral infections. Here we investigate the effect of diet on gut immunity and SARS-CoV-2 infection. Method(s): Six pigtail macaques were fed a commercial monkey chow diet, then transitioned to a high fat and sugar chow diet (HFD) for approximately two months prior to infection with Delta strain SARS-CoV-2. Animals were sampled prior to HFD initiation, during HFD administration but prior to infection, and for approximately one month post-infection. HFD was maintained following infection and animals were euthanized at the study conclusion. Result(s): Viral RNA was detected for up to 28 days post-infection in nose swabs, with peak viral load at day 2 at a mean of 8.2x109 copies/mL of swab fluid. Subgenomic RNA (sgRNA, indicating viral replication) decayed more rapidly, with all animals having undetectable sgRNA by day 21, and a lower peak of 2.6x109 copies/mL swab fluid on day 2. Viral RNA load was approximately 3.5 logs greater and sgRNA load approximately 3 logs higher at day 2 than in rhesus macaques infected with WA2020 SARS-CoV-2 and fed standard monkey chow. Mucosal rectal biopsies indicated significantly lower B cell frequencies from baseline to approximately two months following HFD administration (p=0.04, Dunn's), and frequencies had not recovered approximately one month postinfection. GI tract-resident IgG+ B cells were nearly absent at necropsy, with mean frequency 0.03% of total B cells. B cell loss was coupled with modest T cell expansion during HFD administration, though frequencies declined following infection. Furthermore, NK cell frequencies tended to decline from baseline throughout HFD administration, and were further depleted at necropsy one month post-infection. Conclusion(s): SARS-CoV-2 infection can induce lymphopenia, and our sampling of gut mucosal tissue indicates B cell depletion and NK cell loss with a HFD that is further exacerbated by SARS-CoV-2 infection. Excess dietary fat and sugar may disrupt gut barrier integrity and immunity, in turn predisposing the tissue to pathology of viral infection.

Social Vulnerability and Macroeconomic Forecast: A Review from the Current Context.

In the current context, various factors add to the existing social and economic crisis, such as the COVID-19 pandemic and the Russian invasion of Ukraine, which, when articulated with common conflicting facts, increase projections regarding the slowdown in the economy, with an impact on inflation and declines in global economic growth. As part of the adverse effects of these variables, if the increase in the cost of basic products and services was anticipated, the supply chain escaped, food safety, the widening of social gaps, poverty, contributing to the massification of restrictive medicines, increasing vulnerabilities in social and political scenarios, in addition to less dynamism in the global economy, in the availability of food resources, increases in energy prices, inflationary pressure, among others. Previously, this investigative note explores the macroeconomic forecast, taking as reference the informants of the year 2022 brought by the World Bank, the International Monetary Fund, the Economic Committee for Latin America and the Caribbean and the Inter-American Development Bank. (English) [ FROM AUTHOR] En el contexto actual, diversos factores se suman a la crisis social y económica a existente, como la pandemia COVID-19 y la invasión rusa a Ucrania que, al articularse con los hechos conflictivos comunes, aumentan las proyecciones con respecto a la desaceleración de la economía, con incidencia en la inflación y mermas en el crecimiento económico global. Como parte de los efectos adversos de estas va1riables, se prevé el aumento en el costo de los productos y servicios básicos, escasez en la cadena de suministros, inseguridad alimentaria, ampliación de las brechas sociales, de la pobreza, contribuyendo a la toma de medidas restrictivas, aumentando las vulnerabilidades en los escenarios sociales y en materia política, además de un menor dinamismo en la economía global, en la disponibilidad de recursos alimentarios, aumentos de los precios de la energía, presión inflacionaria, entre otros. En virtud de lo anterior, la presente nota de investigación explora la prognosis macroeconómica, tomando como referentes los informes del año 2022 aportados por el Banco Mundial, el Fondo Monetario Internacional, la Comisión Económica para América Latina y el Caribe y el Banco Interamericano de Desarrollo. (Spanish) [ FROM AUTHOR] Copyright of Revista de Filosofía is the property of Revista de Filosofia-Universidad del Zulia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Learning to rank query expansion terms for COVID-19 scholarly search.

OBJECTIVE: With the onset of the Coronavirus Disease 2019 (COVID-19) pandemic, there has been a surge in the number of publicly available biomedical information sources, which makes it an increasingly challenging research goal to retrieve a relevant text to a topic of interest. In this paper, we propose a Contextual Query Expansion framework based on the clinical Domain knowledge (CQED) for formalizing an effective search over PubMed to retrieve relevant COVID-19 scholarly articles to a given information need. MATERIALS AND METHODS: For the sake of training and evaluation, we use the widely adopted TREC-COVID benchmark. Given a query, the proposed framework utilizes a contextual and a domain-specific neural language model to generate a set of candidate query expansion terms that enrich the original query. Moreover, the framework includes a multi-head attention mechanism that is trained alongside a learning-to-rank model for re-ranking the list of generated expansion candidate terms. The original query and the top-ranked expansion terms are posed to the PubMed search engine for retrieving relevant scholarly articles to an information need. The framework, CQED, can have four different variations, depending upon the learning path adopted for training and re-ranking the candidate expansion terms. RESULTS: The model drastically improves the search performance, when compared to the original query. The performance improvement in comparison to the original query, in terms of RECALL@1000 is 190.85% and in terms of NDCG@1000 is 343.55%. Additionally, the model outperforms all existing state-of-the-art baselines. In terms of P@10, the model that has been optimized based on Precision outperforms all baselines (0.7987). On the other hand, in terms of NDCG@10 (0.7986), MAP (0.3450) and bpref (0.4900), the CQED model that has been optimized based on an average of all retrieval measures outperforms all the baselines. CONCLUSION: The proposed model successfully expands queries posed to PubMed, and improves search performance, as compared to all existing baselines. A success/failure analysis shows that the model improved the search performance of each of the evaluated queries. Moreover, an ablation study depicted that if ranking of generated candidate terms is not conducted, the overall performance decreases. For future work, we would like to explore the application of the presented query expansion framework in conducting technology-assisted Systematic Literature Reviews (SLR).

Realization of 20 Monochromatic Laser Beams Using a Photonic Crystal (PhC) Structure via the Principle of Filtering

The current work employs a Si-based one-dimensional (1-D) photonic struc-ture which delivers 20 different types of monochromatic laser beam via the filtering action. The I/P signals are essentially varying from visible to near infrared (NIR) range to justify the work. Though similar types of work related to filtering application are found in the literature, the present research deals with an output laser beam which could be deployed in different pur-poses vis-a-vis dentistry, dermatology, spectroscopy, printing, holography, barcode scanning, etc. The mechanism of this work incorporates 68 layers of SiO and Si-based 1-D optical waveguide along with their configuration where the plane wave expansion (PWE) method does fulfil the basics of the required mathematics to solve out electromagnetic wave equations. Reflec-tance and transmittance characteristics along with the absorbance are the critical parameters that substantiate the said application.

PRISTINE: Semi-supervised Deep Learning Opioid Crisis Detection on Reddit

The drug abuse epidemic has been on the rise in the past few years, particularly after the start of COVID-19 pandemic. Our preliminary observations on Reddit alone show that discussions on drugs from 2018 to 2020 increased between a range of 45% to 200%, and so has the number of unique users participating in those discussions. Existing efforts focused on utilizing social media to distinguish potential drug abuse chats from unharmful chats regardless of what drug is being abused. Others focused on understanding the trends and causes of drug abuse from social media. To this end, we introduce PRISTINE (opioid crisis detection on reddit), our work dynamically detects-and extracts evolving misleading drug names from Reddit comments using reinforced Dynamic Query Expansion (DQE) and constructs a textual Graph Convolutional Network with the aid of powerful pre-trained embeddings to detect which type of drug class a Reddit comment corresponds to. Further, we perform extensive experiments to investigate the effectiveness of our model. © 2022 IEEE.

Robotization and labour demand in post-pandemic era: Microeconomic evidence from China

We study how robotization, namely the "machine substitution” policy, impacts firms' labour demand in the post pandemic era. Using a unique firm-level data set of online job postings in Dongguan, known as "The World Factory” in China, we find that "machine substitution” policy fosters the funded firms to expand their labour demand. The expansion is mainly driven by the growing demand for manufacturing workers, which offsets the reduced demand for service workers. Also, the expansion can be attributed to an increase in the number of employees listed in job postings rather than an increase in position types. Further analysis suggests that this positive impact is mainly attributable to the productivity effect rather than the restatement effect. Furthermore, there is no evidence of heterogeneity by sector or firm size but the effect of the policy varies by regional epidemic severity. Our results not only reveal the labour demand in the Covid-19 but also provide prominent implications for occupational security and steady economic growth. © 2023 Elsevier Inc.

Total Value Adjustment of Multi-Asset Derivatives under Multivariate CGMY Processes

Counterparty credit risk (CCR) is a significant risk factor that financial institutions have to consider in today's context, and the COVID-19 pandemic and military conflicts worldwide have heightened concerns about potential default risk. In this work, we investigate the changes in the value of financial derivatives due to counterparty default risk, i.e., total value adjustment (XVA). We perform the XVA for multi-asset option based on the multivariate Carr–Geman–Madan–Yor (CGMY) processes, which can be applied to a wider range of financial derivatives, such as basket options, rainbow options, and index options. For the numerical methods, we use the Monte Carlo method in combination with the alternating direction implicit method (MC-ADI) and the two-dimensional Fourier cosine expansion method (MC-CC) to find the risk exposure and make value adjustments for multi-asset derivatives.

Computational study of 2D photonic crystal based biosensor for SARS-COV-2 detection

A computational study to design a 2D-photonic crystal (PC) structure with a fluorescence-based biosensor has been demonstrated for the detection of the severe acute respiratory syndrome corona virus 2 (SARS-COV-2) virus in the lungs. The proposed sensor can detect the different concentrations of the virus without any pretreatment of the sample. The virus detection is performed by measuring the mid-gap wavelength from the dispersion diagram and a redshift in the mid-gap wavelength has been observed as the concentration of virus increases in the lung tissue. The plane wave expansion method is used to determine the dispersion diagram of the proposed PC. The interaction of incident light with the proposed PC-based biosensor has been analyzed to evaluate the shift in the mid-gap wavelength. A maximum sensitivity of about 1459.3 nm/RIU is obtained for r/a = 0.45 with a mid-gap wavelength shift of 145.93 nm at n net = 1.49 concentration of SARS-COV-2. Moreover, a very small detection time has been observed with the proposed device as compared to conventional methods. This study provides a simple process to detect the presence of a virus within a short period and could be helpful in the development of a direct and easy-to-use portable detection kit in the future. © 2023 IOP Publishing Ltd.

The Impact of Higher Education Expansion on Subjective Well-Being during the COVID-19 Pandemic: Evidence from Chinese Social Survey

The rage of the COVID-19 pandemic, coupled with the downward trend seen in the economy, has further aggravated the downturn of the job market and diminished people's sense of wellbeing in recent years. To mitigate the detrimental effects of the pandemic on college students' employment, the Chinese government has further expanded the enrollment of postgraduate and undergraduate students. This study leverages data from the 2019 and 2021 waves of the Chinese Social Survey and constructs a difference-in-differences (DID) model to examine the effect of the higher education expansion (HEE) policy, initiated in 1999, on individuals' subjective well-being during the COVID-19 pandemic. The results show that HEE policy could significantly improve individuals' subjective well-being (SWB) during the pandemic, and that social class mobility emerges as a vital mechanism through which HEE policy impacts individuals' SWB. Furthermore, there is a local-ladder effect due to reference dependence, with socio-metric status having a greater impact on SWB than socioeconomic status. This study reveals that the level of an individual's happiness depends largely on whom they are compared with. This implies that the key focus of the HEE policy is to stimulate individuals' potential and motivation for upward social mobility, ultimately enhancing their overall sense of well-being. © 2023 by the authors.

A review of plastic pollution and their treatment technology: A circular economy platform by thermochemical pathway

The rapid expansion of plastic manufacturing industries in last several decades has brought serious concerns over the environmental impacts of plastic wastes. Recent outbreak of Covid-19 drastically increased production, use, and disposal of plastic products. Current management strategies for wasted plastics still rely on landfill and incineration that continue to exacerbate plastic pollution and carbon emissions. Many countries have put forward multifaceted administrative efforts to reduce plastic wastes, but the annual global generation of plastic wastes is still increasing. In techno-society, researchers have been exploring more effective plastic wastes treatment technologies to alleviate environmental impacts of plastic wastes. Such efforts entailed several technical options that can potentially contribute to establishing a circular economy for plastics. Thermochemical process is a prominent example of such techniques. This review presents an overview of the issue of plastic pollution, covering topics including global plastic production, environmental impacts, and toxicity. In addition, the global administrative efforts aimed at reducing plastic pollution are discussed, as well as detection and treatment strategies to establish a circular economy in plastic management. © 2023 Elsevier B.V.

NASEM on long‐term effects of COVID‐19 on children and families

Probably the most devastating loss to a child is the death of a parent. This happened to more than 265,000 children in the United States due to COVID‐19. But there are other losses too, which have also been devastating – when a parent loses a job, which happened often during the pandemic, and in fact, that is still occurring. And there are many other long‐term effects of COVID‐19, some of which were alleviated by extra money from the federal government. That is now drying up as the federal emergency ends.

ICU capacity expansion under uncertainty in the early stages of a pandemic

We propose a general modular approach to support decision-makers' response in the early stages of a pandemic with resource expansion, motivated by the shortage of Covid-19-related intensive care units (ICU) capacity in 2020 in Italy. Our approach uses (1) a stochastic extension of an epidemic model for scenarios of projected infections, (2) a capacity load model to translate infections into scenarios of demand for the resources of interest, and (3) an optimization model to allocate this demand to the projected levels of resources based on different values of investment. We demonstrate this approach with the onset of the first and second Covid-19 waves in three Italian regions, using the data available at that time. For epidemic modeling, we used a parsimonious stochastic susceptible-infected-removed model with a robust estimation procedure based on bootstrap resampling, suitable for a noisy and data-limited environment. For capacity loading, we used a Cox queuing model to translate the projected infections into demand for ICU, using stochastic intensity to capture the variability of the patient arrival process. Finally, we used stochastic dynamic optimization to select the best policy (when and how much to expand) to minimize the expected number of patients denied ICU for any level of investment in capacity expansion and obtain an efficient frontier. The frontier allows a trade-off between investment in additional resources and the number of patients denied intensive care. Moreover, in the panic-driven early days of a pandemic, decision-makers can also obtain the time until which they can postpone action, potentially reducing investment costs without increasing the expected number of denied patients. © 2023 The Authors. Production and Operations Management published by Wiley Periodicals LLC on behalf of Production and Operations Management Society.

Effects of the Affordable Care Act Medicaid Expansions on Mental Health During the COVID-19 Pandemic in 2020-2021.

To examine whether previous Affordable Care Act (ACA) Medicaid expansions had an added effect on the mental health of low-income adults during the COVID-19 pandemic in 2020 and 2021. We use the 2017-2021 Behavioral Risk Factor Surveillance System (BRFSS) data. We use an event study difference-in-differences model to compare the number of days in poor mental health in the past 30 days and the likelihood of frequent mental distress among 18 to 64 year old individuals with household incomes below 100% of the federal poverty level who participated in BRFSS in one of the surveys from 2017 to 2021 and who resided in states that expanded Medicaid by 2016 or states that had not expanded by 2021. We also examine the heterogeneity of the expansion effects across subpopulation groups. We find some evidence that the Medicaid expansion was associated with better mental health during the pandemic for adults younger than 45, females, and non-Hispanic Black and other non-Hispanic non-White individuals. There is some evidence of an added benefit to mental health from Medicaid expansion status during the pandemic for some subgroups among low-income adults, suggesting potential health benefits from Medicaid eligibility during public health and economic crises.