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Objectives: To analyze the budget impact (BI) of Covid-19 vaccines from a mixed U.S commercial and Medicare payer perspective after depletion of the Federally-Purchased Supply (FPS). Method(s): BI analyses were conducted in a hypothetical one-million member health plan with a mixed commercial (55%) and Medicare (45%) population over a one-year time horizon based on the current (January 2023) Covid-19 vaccine recommendations from the Centers for Disease Control and Prevention (CDC). The two scenarios in the model include 1) the health plan does not pay for Covid-19 vaccines, and 2) after the depletion of FPS, the health plan must cover all costs for Covid-19 vaccines. Model inputs include the market shares of available Covid-19 vaccines in the US as of December 2022, Covid-19 vaccine utilization trends stratified into age groups (<12, 12-17, 18-24, 25-49, 50-64, >=65 years old) between commercial and Medicare populations, and predicted Covid-19 vaccine costs. Model inputs were based on the CDC publicly available data, real world evidence, published literature, and expert opinions. Sensitivity analyses (SA) were conducted to test uncertainties arising from the input values in the model. Result(s): The number of members receiving one primary dose, completed Covid-19 vaccine series, one booster dose and two booster doses was estimated at 9,253, 49,720, 594,933 and 29,387, respectively. The incremental Covid-19 vaccine cost per member per month over one year after depletion of the FPS was $5.92 for the commercial population, $8.93 for the Medicare population, and $7.27 for the total population in the health plan. In the SA, the largest effect was observed for the scenario which varied the percentage of population >=65 years old receiving one booster dose. Conclusion(s): The model results indicate that there will be a high budget impact from a mixed U.S commercial and Medicare perspective after depletion of the FPS of Covid-19 vaccines.Copyright © 2023
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Background: Studies suggest perinatal infection with SARSCoV- 2 can induce adverse birth outcomes, but studies published to date have substantial limitations. Most have identified cases based upon their presentation for clinical care, and very few have examined pandemic-related stress which may also impact adverse birth outcomes. Objective(s): To evaluate the relationships between SARSCoV- 2 infection in pregnancy and pandemic-related stress with birth outcomes. Study Design: We conducted an observational study of 211 mother-newborn dyads in three urban cohorts participating in the Environmental Influences on Child Health Outcomes (ECHO) Program. Serology for SARS-CoV-2 was assessed in a convenience sample of prenatal maternal, cord serum or dried blood spots from births occurring between January 2020-September 2021. Specimens were assessed for IgG, IgM, and IgA antibodies to nucleocapsid, S1 spike, S2 spike, and receptor-binding domain. A Pandemic-related Traumatic Stress (PTS) scale was based on the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition Acute Stress Disorder criteria. Result(s): 36% were positive for at least one antibody type, chiefly IgG. Self-report of infection was not significantly correlated with combined serology. There were no differences in gestational age (GA), birth weight, preterm birth (PTB), or low birth weight (LBW) among seropositive mothers. However, IgM seropositive mothers had children with lower BW (434g, 95% CI: 116- 752), BW Z score-for-GA (0.73 SD, 95% CI 0.10-1.36) and were more likely to deliver preterm (OR 8.75, 95% CI 1.22-62.4). Associations with LBW sustained in sensitivity analyses limited to pre-vaccine samples, and PTS symptoms were not associated with birth outcomes. The addition of PTS did not substantially change associations with BW, although associations with PTB attenuated to near-significance. Conclusion(s): We identified decreased birth weight and increased prematurity in mothers IgM seropositive to SARS-CoV-2, independent of PTS. Though there are limits to interpretation, the data support efforts to prevent SARS-CoV-2 infections in pregnancy.
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Summary Introduction: The SARS-CoV-2 coronavirus, that causes the COVID-19 disease, has become a global public health problem that requires the implementation of rapid and sensitive diagnostic tests. Aim(s): To evaluate and compare the sensitivity of LAMP assay to a standard method and use RT-LAMP for the diagnosis of SARS-CoV-2 in clinical samples from Colombian patients. Method(s): A descriptive and cross-sectional study was conducted. A total of 25 nasopharyngeal swab samples including negative and positive samples for SARS-CoV-2 were analyzed, through the RT-LAMP method compared to the RT-qPCR assay. Result(s): LAMP method detected ~18 copies of the N gene, in 30 min, evidenced a detection limit similar to the standard method, in a shorter time and a concordance in RT-LAMP of 100% with the results. Conclusion(s): RT-LAMP is a sensitive, specific, and rapid method that can be used as a diagnostic aid of COVID-19 disease.Copyright © 2021. All Rights Reserved.
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In this work, we modified a dynamical system that addresses COVID-19 infection under a fractal-fractional-order derivative. The model investigates the psychological effects of the disease on humans. We establish global and local stability results for the model under the aforementioned derivative. Additionally, we compute the fundamental reproduction number, which helps predict the transmission of the disease in the community. Using the Carlos Castillo-Chavez method, we derive some adequate results about the bifurcation analysis of the proposed model. We also investigate sensitivity analysis to the given model using the criteria of Chitnis and his co-authors. Furthermore, we formulate the characterization of optimal control strategies by utilizing Pontryagin's maximum principle. We simulate the model for different fractal-fractional orders subject to various parameter values using Adam Bashforth's numerical method. All numerical findings are presented graphically. © 2023 by the authors.
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Globally, the COVID-19 pandemic's development has presented significant societal and economic challenges. The carriers of COVID-19 transmission have also been identified as asymptomatic infected people. Yet, most epidemic models do not consider their impact when accounting for the disease's indirect transmission. This study suggested and investigated a mathematical model replicating the spread of coronavirus disease among asymptomatic infected people. A study was conducted on every aspect of the system's solution. The equilibrium points and the basic reproduction number were computed. The endemic equilibrium point and the disease-free equilibrium point had both undergone local stability analyses. A geometric technique was used to look into the global dynamics of the endemic point, whereas the Castillo-Chavez theorem was used to look into the global stability of the disease-free point. The system's transcritical bifurcation at the disease-free point was discovered to exist. The system parameters were changed using the basic reproduction number's sensitivity technique. Ultimately, a numerical simulation was used to apply the model to the population of Iraq in order to validate the findings and define the factors that regulate illness breakout.
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In this paper, the mathematical model of the coronavirus pandemic with vaccination is formulated and analyzed to show the impact of severe acute respiratory syndrome coronavirus 2 pathogens in the environmental reservoir. In the model analysis, the vaccination-induced reproduction number which helps us in establishing the local and global stability of COVID-19-free and endemic equilibrium points was derived. The local stability of the COVID-19-free equilibrium is established via the Jacobian matrix and Routh-Hurwitz criteria. In contrast, the global stability of the endemic equilibrium is proved by using an appropriate Lyapunov function. Sensitivity indices are also discussed. The proposed model is extended into the optimal control problem by incorporating three control variables: preventive, medical care, and surface disinfection. Then, the necessary conditions for the optimal control of the disease were analyzed by applying Pontryagin minimum principle. Finally, the numerical simulations indicated that a combination of medical care and surface disinfection strategies is effective in controlling the disease epidemic. [ FROM AUTHOR] Copyright of Journal of Mathematical Sciences is the property of Springer Nature 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.)
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Bulgaria has the lowest COVID-19 vaccination rate in the European Union and the second-highest COVID-19 mortality rate in the world. That is why we think it is important better to understand the reason for this situation and to analyse the development of the disease over time. In this paper, an extended time-dependent SEIRS model SEIRS-VB is used to investigate the long-term behaviour of the COVID-19 epidemic. This model includes vaccination and vital dynamics. To apply the SEIRS-VB model some numerical simulation tools have been developed and for this reason a family of time-discrete variants are introduced. Suitable inverse problems for the identification of parameters in discrete models are solved. A methodology is proposed for selecting a discrete model from the constructed family, which has the closest parameter values to these in the differential SEIRS-VB model. To validate the studied models, Bulgarian COVID-19 data are used. To obtain all these results for the discrete models a mathematical analysis is carried out to illustrate some biological properties of the differential model SEIRS-VB, such as the non-negativity, boundedness, existence, and uniqueness. Using the next-generation method, the basic reproduction number associated with the model in the autonomous case is defined. The local stability of the disease-free equilibrium point is studied. Finally, a sensitivity analysis of the basic reproduction number is performed.
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Objectives: The United Kingdom (UK) implemented an autumn 2022 booster programme that allowed those at higher risk from COVID-19, including those >= 50 years, to receive a booster to increase protection against infection and subsequent severe outcomes. As the UK transitions out of the pandemic, future booster campaigns may be required to maintain protection against such outcomes. The objective of this analysis was to estimate the value-based price (VBP) for a bivalent COVID-19 vaccine used in a future autumn 2023 campaign in the UK to protect people aged >= 50 years. Method(s): A Susceptible-Exposed-Infected-Recovered (SEIR) model was used to predict infections across a 1-year time horizon starting September 2023 with and without an autumn booster campaign. Initial effectiveness was predicted to be 89% and 97% against infection and hospitalization respectively based on BA.4/BA.5 antibody titers and correlates of protection. A monthly decline in protection of 1.4% and 4.8%, respectively, was assumed based on monovalent vaccine data. A decision tree was used to predict the quality-adjusted life-years (QALY) lost and costs associated with infections. Result(s): Considering a willingness-to-pay (WTP) threshold of 20,000/QALY, the VBP associated with an autumn 2023 booster campaign is 343/dose. Considering a WTP threshold of 30,000, the VBP increases to 476. In sensitivity analyses, excluding the post-infection costs (e.g., long COVID), reduces the VBP by 11%. Varying the hospitalization rates by +/-25% changes the VBP by +/- 6%. Varying hospitalization unit costs only impacts the VBP by 1%. Doubling the rate of waning for booster effectiveness increases the VBP by 54% because the effectiveness provided from past campaigns falls faster and an autumn 2023 booster becomes more valuable. Conclusion(s): While the trajectory of COVID-19 incidence is highly uncertain, pricing the bivalent booster lower than the VBP is expected to result in a cost-effective strategy for the UK.Copyright © 2023
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Medical waste has been excessively generated in various medical facilities due to COVID-19, and its treatment has become an important concern. Previously, an optimized medical waste sterilization and shredding system was developed for hospital scale but due to increased demand, it is necessary to scale such a system for different facilities. Therefore, in this paper, a sensitivity analysis for the design variables of the shredding system has been conducted and a surrogate model is developed for stress estimation. The surrogate model was generated using LHS (Latin hypercube sampling), which can represent the overall information of the design domain with a limited number of samples. The surrogate model was then used to increase the number of samples for sensitivity analysis which helped in reducing the computational time for finite element analysis. The sensitive variables for the shredder system were then estimated using sensitivity analysis. Consequently, an efficient design framework for various capacities of medical waste shredder was suggested using sensitivity analysis and a data-driven surrogate model.
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209 Figure 1Kaplan-Meier curves displaying cumulative all-cause mortality[Figure omitted. See PDF]Conflict of InterestNo conflicts of interest
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When it comes to supplying oxygen, current standard hospitals in Iran have proven inadequate in the face of the COVID-19 pandemic, particularly during infection peaks. Power disruptions drastically reduce the oxygen pressure in hospitals, putting patients' health at risk. The present study is the first to attempt to power an oxygen concentrator with a solar-energy-based system. The HOMER 2.81 package was used for technical–economic–environmental–energy analysis. The most notable aspects of this work include evaluating different available solar trackers, using up-to-date equipment price data and up-to-date inflation rate, considering the temperature effects on solar cell performance, sensitivity analysis for the best scenario, considering pollution penalties, and using a three-time tariff system with price incentives for renewable power. The study has been carried out at Hajar Hospital, Shahrekord, Chaharmahal and Bakhtiari Province, Iran. The study showed that, by supplying 60% of the power demand, the dual-axis solar tracking system offered the highest annual power output (47,478 kWh). Furthermore, generating power at—$0.008/kWh due to selling power to the grid, the vertical-axis tracker was found to be the most economical design. Comparing the configuration with a vertical-axis tracker with the conventional scenario (relying on the power distribution grid), the investment is estimated to be recovered in three years with $234,300 in savings by the end of the 25th year. In the best economic scenario, 6137 kg CO2 is produced, and the analysis revealed the negative impact of a temperature rise on the performance and solar power output.
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The COVID-19 has placed pandemic modeling at the forefront of the whole world's public policymaking. Nonetheless, forecasting and modeling the COVID-19 medical waste with a detoxification center of the COVID-19 medical wastes remains a challenge. This work presents a Fuzzy Inference System to forecast the COVID-19 medical wastes. Then, people are divided into five categories are divided according to the symptoms of the disease into healthy people, suspicious, suspected of mild COVID-19, and suspicious of intense COVID-19. In this regard, a new fuzzy sustainable model for COVID-19 medical waste supply chain network for location and allocation decisions considering waste management is developed for the first time. The main purpose of this paper is to minimize supply chain costs, the environmental impact of medical waste, and to establish detoxification centers and control the social responsibility centers in the COVID-19 outbreak. To show the performance of the suggested model, sensitivity analysis is performed on important parameters. A real case study in Iran/Tehran is suggested to validate the proposed model. Classifying people into different groups, considering sustainability in COVID 19 medical waste supply chain network and examining new artificial intelligence methods based on TS and GOA algorithms are among the contributions of this paper. Results show that the decision-makers should use an FIS to forecast COVID-19 medical waste and employ a detoxification center of the COVID-19 medical wastes to reduce outbreaks of this pandemic. © 2023, Crown.
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Objectives: Various interventions were used to control the COVID-19 pandemic and protect population health, including vaccination, medication and nonpharmaceutical interventions (NPIs). This study aims to examine the cost-effectiveness of different combinations of NPIs (including social distancing, mask wearing, tracing-testing-isolation, mass testing, and lockdown), oral medicine (Paxlovid), and vaccination (including two-dose and three-dose vaccination) under the Delta and Omicron pandemic in China. Method(s): We constructed a Markov model using a SIRI structure with a one-week cycle length over one-year time horizon to estimate the cost-effectiveness of different combinations in China from societal perspective. Effectiveness of interventions, disease transition probabilities and costs were from published data, quality-adjusted life years (QALYs) gained and incremental cost-effectiveness ratios (ICER) and net monetary benefits were calculated for one-year time horizon. One-way and probabilistic sensitivity analyses were performed to test the robustness of the model. Scenario analysis was developed to examine different situations under the Omicron pandemic. Result(s): Under the Delta pandemic, implementing the combination of social distancing, mask wearing, mass testing and three-dose vaccination was the optimal strategy, with cost at $11165635.33 and utility of 94309.94 QALYs, and had 60% probability of being cost-effective compared with other strategies. Three-dose vaccination combinations were better than two-dose combinations. Under the Omicron pandemic, antigen testing was better than nucleic testing by avoiding cross infections;second, adding Paxlovid or lockdown to the combined intervention strategies could increase limited health outcomes at huge cost and thus were not cost-effective;last, encouraging patients to stay at home can save societal costs compared with concentrated quarantine at hospitals. Conclusion(s): Three-dose vaccination and self-quarantine of asymptomatic and mild cases can save total costs. Under the Omicron pandemic outbreak, antigen testing is a better way to control the pandemic, and adding Paxlovid or lockdown to intervention combinations is not cost-effective.Copyright © 2023
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Since the outbreak of the Middle East Respiratory Syndrome Coronavirus (MERS-CoV) in 2012 in the Middle East, we have proposed a deterministic theoretical model to understand its transmission between individuals and MERS-CoV reservoirs such as camels. We aim to calculate the basic reproduction number (R0) of the model to examine its airborne transmission. By applying stability theory, we can analyze and visualize the local and global features of the model to determine its stability. We also study the sensitivity of R0 to determine the impact of each parameter on the transmission of the disease. Our model is designed with optimal control in mind to minimize the number of infected individuals while keeping intervention costs low. The model includes time -dependent control variables such as supportive care, the use of surgical masks, government campaigns promoting the importance of masks, and treatment. To support our analytical work, we present numerical simulation results for the proposed model.
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In the context of the present global health crisis, we examine the design and valuation of a pandemic emergency financing facility (PEFF) akin to a catastrophe (CAT) bond. While a CAT bond typically enables fund generation to the insurers and re-insurers after a disaster happens, a PEFF or pandemic bond's payout is linked to random thresholds that keep evolving as the pandemic continues to unfold. The subtle difference in the timing and structure of the funding payout between the usual CAT bond and PEFF complicates the valuation of the latter. We address this complication, and our analysis identifies certain aspects in the PEFF's design that must be simplified and strengthened so that this financial instrument is able to serve the intent of its original creation. An extension of the compartmentalized deterministic epidemic model-which describes the random number of people in three classes: susceptible (S), infected (I), and removed (R) or SIR for short-to its stochastic analog is put forward. At time t, S(t), I(t), and R (t) satisfy a system of interacting stochastic differential equations in our extended framework. The payout is triggered when the number of infected people exceeds a predetermined threshold. A CAT-bond pricing setup is developed with the Vasicek-based financial risk factor correlated with the SIR dynamics for the PEFF valuation. The probability of a pandemic occurrence during the bond's term to maturity is calculated via a Poisson process. Our sensitivity analyses reveal that the SIR's disease transmission and recovery rates, as well as the interest rate's mean-reverting level, have a substantial effect on the bond price. Our proposed synthesized model was tested and validated using a Canadian COVID-19 dataset during the early development of the pandemic. We illustrate that the PEFF's payout could occur as early as seven weeks after the official declaration of the pandemic, and the deficiencies of the most recent PEFF sold by an international financial institution could be readily rectified.
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Objectives: Meta-analyses have investigated associations between race and ethnicity and COVID-19 outcomes. However, there is uncertainty about these associations' existence, magnitude, and level of evidence. We, therefore, aimed to synthesize, quantify, and grade the strength of evidence of race and ethnicity and COVID-19 outcomes in the US. Method(s): In this umbrella review, we searched four databases (Pubmed, Embase, the Cochrane Database of Systematic Reviews, and Epistemonikos) from database inception to April 2022. The methodological quality of each meta-analysis was assessed using the Assessment of Multiple Systematic Reviews, version 2 (AMSTAR-2). The strength of evidence of the associations between race and ethnicity with outcomes was ranked according to established criteria as convincing, highly suggestive, suggestive, weak, or non-significant. The study protocol was registered with PROSPERO, CRD42022336805 Results: Of 880 records screened, we selected seven meta-analyses for evidence synthesis, with 42 associations examined. Overall, 10 of 42 associations were statistically significant (p <= 0.05). Two associations were highly suggestive, two were suggestive, and two were weak, whereas the remaining 32 associations were non-significant. The risk of COVID-19 infection was higher in Black individuals compared to White individuals (risk ratio, 2.08, 95% Confidence Interval (CI), 1.60-2.71), which was supported by highly suggestive evidence;with the conservative estimates from the sensitivity analyses, this association remained suggestive. Among those infected with COVID-19, Hispanic individuals had a higher risk of COVID-19 hospitalization than non-Hispanic White individuals (odds ratio, 2.08, 95% CI, 1.60-2.70) with highly suggestive evidence which remained after sensitivity analyses. Conclusion(s): Individuals of Black and Hispanic groups had a higher risk of COVID-19 infection and hospitalization. These associations of race and ethnicity and COVID-19 outcomes existed more obviously in the pre-hospitalization stage. More consideration should be given in this stage for addressing health inequity.Copyright © 2023
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Beside the unexpected toll of mortality and morbidity caused by COVID-19 worldwide, low- and middle-income countries are more suffering from the devastating issues on economic and social life. This disease has fostered mathematical modelling. In this paper, a SEIAR mathematical model is presented to illustrate how policymakers may apply efficient strategies to end or at least to control the devastating wide spread of COVID-19. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Objectives: Pertussis, a highly contagious respiratory disease caused by Bordetella pertussis, is endemic in Brazil, but is underdiagnosed in adults due to atypical symptomatology and limited diagnosis time window. Brazil's Ministry of Health recommends decennial boosters in adults against diphtheria and tetanus, but not pertussis. After the COVID-19 pandemic, infectious diseases surged worldwide due to lack of natural exposure and reduced immunization coverage. Asthma and COPD populations are at increased risk of pertussis infection. This study assessed the cost-utility of decennial pertussis vaccination with Tdap vaccine versus no pertussis vaccination in Brazil's adult asthma and COPD populations in a high-incidence context. Method(s): A static cross-sectional population-based cost-utility model of decennial Tdap boosters in asthma patients >=50 years and COPD patients >=40 years was developed from the payer's perspective. Pertussis incidence from Sao Paulo's state surveillance system in the peak year 2014 was adjusted for underdiagnosis and relative risk of pertussis in asthma and COPD populations. Vaccine efficacy and coverage, and costs and outcomes discounted at 5%, were obtained from the literature and public databases. Deterministic and probabilistic sensitivity analyses, and scenario analyses were run, including alternative annual incidence. Result(s): In the asthma population, Tdap boosters would incur 7,065,788 Brazilian reais (BRL) direct costs and save 32.85 Life Years (LYs) and 262.13 Quality-Adjusted LYs (QALYs). In the COPD population, Tdap boosters would incur 41,102,844 BRL direct costs and save 157.47 LYs and 1,078.26 QALYs. Discounted incremental cost-utility ratios were 26,956 and 38,120 BRL/QALY in asthma and COPD populations, respectively. At a cost-effectiveness threshold of 1 Gross Domestic Product (GDP)/capita, 85.8% and 49.7% of simulations were cost-effective in asthma and COPD populations, respectively, while all simulations were cost-effective at a threshold of 3 GDP/capita. Conclusion(s): Implementing decennial Tdap boosters for adult asthma and COPD patients should be considered, given the favorable cost-utility profile in peak-incidence years.Copyright © 2023
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Problem: Despite being over 3 years into the pandemic, infants remain highly undervaccinated and at a high risk for hospitalization due to COVID-19. Further investigation as to how maternal health decisions for immunization can reduce morbidity from infant COVID-19 by providing passive immunity is necessary. The objective of this study was to describe the rates of SARS-CoV-2 variant antibody transfer from mother to infant cord blood by trimester ofmaternal vaccination. Methods of study: This is an observational cohort study including mother-infant dyads receiving primary or subsequent booster COVID- 19 vaccines during pregnancy.Unvaccinated, but SARS-CoV-2 infected dyads with were included as a comparison group. We quantified median titer and interquartile range (IQR) for SARS-CoV-2 receptor binding domain (RBD) IgG in infant cord blood samples at delivery using the mesoscale discovery platform (electrochemiluminescence). Primary outcome was infant cord IgG titer by trimester of vaccination for the WA1/2022 RBD IgG and current circulating, immune evasive XBB RBD IgG. Secondary outcome is the percent detectable IgG for each variant. Sensitivity analysis was performed based on known SARS-CoV-2 infection. Result(s): Eighty-three mother-infant dyads were included in this analysis. Seven were vaccinated in the first trimester, 37 in the second trimester, 33 in the third trimester, and 6 were unvaccinated and infected. Twenty-three (30%) of the vaccinated group had known SARS-CoV-2 infection. Most received monovalent mRNA COVID-19 vaccines during pregnancy, aside from two who received the viralvectored Ad26.COV2.S, and two received the bivalent mRNA vaccine during pregnancy. The median cord blood WA1/2020 RBD IgG titer was 5370 (412-7296) for first, 1225 (589-3289) for second, 2623 (664-5809) for third trimester in individuals who received aCOVID-19 vaccine dose during pregnancy, and 45 (10-187) in those unvaccinated and infected. After excluding thosewith infection, the cord blood IgG was 514 (106-4182), 1070 (518-2317), and 2477 (664-4470) for first, second, and third trimester, respectively. The rate of detectable WA1/2020 RBD IgG was 100% for all three trimesters, even when excluding infected individuals. For theXBBvariant, cord bloodRBDIgG titer was 284 (43-1296) for first, 66 (32-227) for second, 173 (45-389) for third trimester, and 10 (10-11) in the unvaccinated/infected group. Excluding infections, the cord blood XBB RBD IgG was 54 (10-128), 44 (25-181), and 152 (45-360) for first, second, and third trimester vaccination, respectively. The rate of detectable XBB IgG in those who received a vaccine during pregnancy were 83%, 91%, and 90% for first, second, and third trimester respectively, compared to 17% in the unvaccinated/infected group. Excluding infections, the rate of XBB RBD IgG detection was 66%, 89%, and 95% for first, second, and third trimester vaccination, respectively. Conclusion(s): Vaccination during pregnancy leads to high rates of detectable cord blood IgG specific to SARS-CoV-2 WA1/2020 variant and current circulating variants (XBB), regardless of trimester of vaccination. Infection history leads to higher cord blood IgG in vaccinated;however, infection alone without vaccination leads to lower titer and greater rates of undetectable cord IgG at delivery.
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Objectives: Mucormycosis is a rare invasive fungal infection with high lethality, affecting mainly patients with hematological neoplasia, decompensated diabetes, and covid-19 infection. The aim was to perform a cost-effectiveness analysis of liposomal Amphotericin B (standard treatment) versus isavuconazole for treating mucormycosis in the consolidation phase from the perspective of the Brazilian Unified Health System. Method(s): A decision tree model was built. The analysis considered the costs of the treatment over a six-month time horizon. This included hospitalization during the entire course of treatment and the expenditures related to dialysis, complication occurring in 5% (3%-6%) of cases treated with the Amphotericin B. Appointments with specialists were included in the isavuconazole arm, and amphotericin B was used if the patient failed to respond to isavuconazole. The utility of the patient with mucormycosis, cured and with renal failure was estimated. Uncertainties were assessed through probabilistic and deterministic sensitivity analyses. Result(s): The average cost of amphotericin B and isavuconazole arm was R$1.054.874,39 and R$522.344,05, respectively. The utility was 0.479 with amphotericin B and 0.480 with isavuconazole. The ICER was R$ -684,494,237 (dominant). In deterministic sensitivity analysis, the probability of dialysis was the variable with the greatest impact. In probabilistic analysis, the ICER is distributed in the right and left lower quadrant, the acceptability curve for all the scenarios analyzed is favorable for isavuconazole. The budget impact suggests a potential savings of between R$ 350 million and R$ 415 million over five years. Conclusion(s): The treatment of mucormycosis during the consolidation phase with isavuconazole represents a lower cost, besides the convenience of oral treatment and reduced incidence of severe adverse events, with mortality similar to the Amphotericin B arm. In Brazil, the formulation of posaconazole approved is inadequate for treating mucormycosis during the consolidation phase, therefore isavuconazole is the single oral drug available.Copyright © 2023