Examining the association between vaccine reactogenicity and antibody titer dynamics after the third dose of BNT162b2 vaccine using a mixed-effects model

Background: To mitigate the COVID-19 pandemic, many countries have recommended the use of booster vaccinations. The relationship between the degree of adverse vaccine reactions and elevated antibody titers is of interest;however, no studies have investigated the temporal changes in antibody titers based on repeated measurements after a third dose of the BNT162b2 vaccine. Methods: This prospective longitudinal cohort study was conducted with 62 healthcare workers who received a third dose of the BNT162b2 at Okayama University Hospital, Japan. Venous blood draw and fingertip whole blood test sample collection were conducted at the early (3–13 days) and 1-month time points;only FWT sample collection was conducted at the 2-month time point. Information on adverse reactions within 1 week after vaccination was also obtained. The association between fever of 37.5 °C or higher and antibody titers after the third dose of BNT162b2 was examined using a mixed-effects model and Poisson regression with robust variance. Results: A trend toward higher antibody titers in the early period after vaccination was observed in the febrile individuals, but the differences were not significant at 1 and 2 months post-vaccination (the partial regression coefficient for fever was 8094.3 [-1910.2, 18,098.8] at 1 month after vaccination, and 1764.1 [-4133.9, 7662.1] at 2 months after vaccination in the adjusted models). Conclusion: The findings suggest that the presence of fever after the third vaccine does not predict a sustained elevation in serum antibody titers. © 2022 Japanese Society of Chemotherapy and The Japanese Association for Infectious Diseases

Asthma-Related Emergency Department Visits in Texas: Associations with Viruses and Allergenic Pollen

Rationale: Asthma exacerbations cause many emergency department visits but much remains unknown about the role of seasonal environmental triggers including viruses and allergenic pollen. A better understanding of these triggers and the role of regionally-important pollen types such as ‘mountain cedar' (in the Cupressaceae family) in Texas could help prioritize public health interventions. Methods: We acquired data on all emergency department visits in Texas from 2015–2020 where asthma was the primary ICD diagnosis code. Emergency department visit rates were compared to concentrations of several pollen types (Cupressaceae, trees, and other plants), and to test positivity of viruses (rhinovirus, coronavirus, RSV, and influenza) among populations living near eight pollen monitoring stations. We analyzed these relationships with age-stratified Poisson regression analyses in a distributed lag framework. Results: Young children had high asthma-related emergency department rates (22.4 visits/1,000,000 person-days), which were explained by viruses (70.4±2.6%), Cupressaceae pollen (0.4±0.1%), and tree pollen (0.9±0.4%). School-aged children also had high rates (19.7 visits/1,000,000 person-days), which were attributed to viruses (61±2%), Cupressaceae pollen (0.5±%) and tree pollen (1.5±0.1%). Adults had lower rates (7.6 visits/1,000,000 people/day) which were attributed to viruses (38±2%), Cupressaceae pollen (0.5±0.1%) and tree pollen (2.5±0.2%). Rates attributed to pollen exhibited spatio-temporal patterns;for example, Cupressaceae accounted for 7% of adult cases in January in Austin, but <1% in Houston. Similarly, for adults in Houston tree pollen accounted for 2% of cases annually but 19% in March. Conclusions: These findings demonstrate the consequences of regionally important allergenic plants to respiratory health and spatio-temporal patterns of emergency department visits.

136. Telemedicine for Adolescent and Young Adult Long-acting Reversible Contraception Initial Follow-up Visit: Outcomes Over 1 Year

Purpose: Telemedicine for adolescent and young adult (AYA) care, including long-acting reversible contraception (LARC) care, was quickly implemented in response to the COVID-19 pandemic. Therefore, outcomes of telemedicine LARC care is understudied. We compare outcomes of AYAs receiving LARC follow-up care via telemedicine and in-person over 1 year. Methods: This cohort study includes patients who had LARC, intrauterine device (IUD) or implant, inserted between 4/1/20-3/31/21 and attended an initial LARC follow-up visit at 4 US Adolescent Medicine clinics. Initial LARC follow-up visit was defined as the first visit within 12 weeks of insertion. Eligible patients were 13-26 years old, had LARC inserted without sedation, and had LARC in place for at least 12 weeks. We compared outcomes over 1 year between patients attending the initial follow-up visit via telemedicine (telemedicine attendees) to those who completed the visit in-person (in-person attendees). Outcomes included patient-reported side effects, medical menstrual management, acne management, IUD malposition or expulsion, sexually transmitted infection (STI) testing and results, and LARC removal. Descriptive statistics described the sample and compared groups. Adjusted Poisson regression examined factors associated with number of visits and adjusted logistic regression models examined the association between initial visit modality and initiation of medical menstrual management. Site-specific institutional review board approvals were obtained. Results: Our study included 194 AYAs, ages 13.9-25.7 years (mean 18.7 years, SD = 2.3) who attended an initial follow-up visit. Most AYAs (n = 168, 86.6%) attended only one visit in the 12 weeks post-insertion. Telemedicine attendees comprised 40.2% of the sample. Telemedicine and in-person attendees were similar with regards to site of LARC insertion (p =.43), age (p =.17), race/ethnicity (p =.25), prior pregnancy (p =.95), complex medical diagnoses (p =.32), menstrual diagnoses (p =.11), and reason for LARC (p =.82). In-person attendees were more likely to have the IUD than telemedicine attendees (p =.003). Bivariate analyses showed similar frequency of patient-reported symptoms over 1 year between groups. Outcomes of menstrual management (OR = 1.02, CI: 0.40-2.60), number of visits attended (RR = 1.08, CI: 0.99-1.19), acne management (p =.28), IUD expulsion (p =.13), IUD malposition (p =.51), and LARC removal (p =.95) were similar between groups. In-person attendees were more likely to have STI testing done (p =.001) than telemedicine attendees. However, no positive STI tests were captured in either group. Conclusions: Roughly two-fifths of patients presenting to an initial LARC follow-up visit did so via telemedicine. Type of LARC may influence modality of follow-up visit. Except for STI testing, outcomes over 1 year were similar regardless of the first visit modality. Reassuringly, no positive STI tests were detected in either group over 1 year of follow-up. More research is needed to determine if the decrease in STI testing for patients seeking care via telemedicine is clinically significant. Telemedicine may play an important role in AYA LARC follow-up care, and more research is needed in this area. Sources of Support: N/a.

Sharp Rise in New Onset Pediatric Diabetes During the Covid-19 Pandemic

Objectives This study aims to determine the incidence of new onset pediatric diabetes pre-pandemic vs during the pandemic. A second aim is to analyze the presentation based on age, severity, HbA1c, BMI, and Covid testing. Methods This retrospective cohort study includes pediatric patients with newly diagnosed diabetes (Type 1 and 2) admitted to the American Family Children's Hospital (Madison, WI) from 2018 to 2021. Data includes age at diagnosis, body mass index, hemoglobin A1c % and pH at presentation, presence of autoimmune pancreatic antibodies, and Covid-19 PCR results at admission in pre-pandemic (Jan 2018-March 2020) versus pandemic periods (March 2020 onwards). Diabetes was diagnosed as Type 1 when 1 or more pancreatic antibodies were positive, Type 2 when all 4 antibodies were negative and BMI >85th percentile. Statistical analysis was performed using SAS software with the incidence rates analyzed using univariate and multivariate Poisson regression analyses. Results During the pandemic, the incidence of both T1DM and T2DM increased (72% and 257% respectively, Table 1 and Figure 1), and a higher percent of T1DM patients presented in DKA (diabetic ketoacidosis), i.e., pH <7.3 (61.5% vs 48% pre-pandemic). Rates of severe DKA (pH <7.1) increased from 16% in 2018-2019 to 26% in 2020, with a decrease to 22% in 2021. T1DM patients with a BMI >95th percentile increased from fewer than 10% to above 15%. There were no significant differences observed in HbA1c between the two periods. Almost all patients were Covid-19 PCR negative at the time of diagnosis (97% in 2020 and 94.8% in 2021). Conclusions We and others have shown an increased number and severity of newly diagnosed pediatric diabetes cases with the pandemic. The increase in the incidence of pediatric diabetes at our center was not explained by factors such as changes in referral patterns or insurance coverage. Societal factors such as changes in the functionality and accessibility of the healthcare system and parental fears over contracting Covid may have contributed to increased severity at time of presentation. A possible direct diabetogenic effect of Covid-19 remains unknown.

Information Seeking and COVID-19 Preventive Behaviors: A Comparison Between Immigrants and the Host Population in Japan

Little is known about information seeking and its influence on preventive behaviors among immigrants in Japan, despite their vulnerabilities during the coronavirus disease 2019 (COVID-19) pandemic. This study investigated information seeking about COVID-19, and examined differences with compliance with preventive measures between immigrants and the host population in Japan based on an Internet survey conducted in October 2021. We used chi-squared tests to determine the difference in information seeking and preventive behaviors between the two groups, and Poisson regression with robust standard errors to examine the association between information seeking and compliance with preventive measures. Our results show that, although the overall tendencies of information seeking and the preventive behaviors of immigrants were similar to those of the Japanese, significant differences were identified in some behavior: immigrants were more likely to acquire COVID-19 information from social networking services (SNS) and official websites in Japan, and maintain physical distance and ventilation than Japanese locals. Furthermore, immigrants' sources of information diversified according to their sociodemographic characteristics (e.g., educational level, Japanese language skills, length of residence in Japan, and country or region of origin). Additionally, the effects of information seeking on preventive actions against COVID-19 differed according to the information sources;some information sources (e.g., SNS) had different impacts on preventive behaviors between immigrants and Japanese locals. Obtaining information from traditional media and Japanese official websites increases engagement with all five preventive measures among immigrants and four measures among the Japanese. The study highlights the importance of customized health policies for immigrants according to their behavioral tendencies. © Fuji Technology Press Ltd.

Pulmonary embolism on ventilation/perfusion scintigraphy during the COVID-19 pandemic

Aim/Introduction: In March 2020, the World Health Organization (WHO) declared the coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) a pandemic. One complication associated with COVID-19 disease is a thrombotic event, including pulmonary embolism. The most commonly used imaging modality in nuclear medicine for diagnosing pulmonary embolism is ventilation/perfusion singlephoton emission computed tomography (V/Q-SPECT), especially in patients who are contraindicated to iodinated contrast agents and are not suitable for computed tomographic pulmonary angiography (CTPA). However, the true impact of these increased thromboembolic events on pulmonary scintigraphy results has not yet been investigated. Therefore, we investigated the value of ventilation/perfusion scintigraphy for diagnosing pulmonary embolism during the COVID-19 pandemic. Material(s) and Method(s): We retrospectively reviewed medical records of patients examined with 81mKr or 133Xe ventilation/ 99mTc-MAA perfusion scintigraphy between January 2019 and May 2021. Patients only examined with perfusions scintigraphy were excluded. The lung scintigraphy findings before (January 01, 2019 to March 15, 2020) and during (March 16, 2020 to May 31, 2021) the pandemic were compared. The number of examinations performed in the two periods were compared using Poisson regression, whereas Pearson's chisquare test was used for severity parameters. Result(s): The study population contained 1.127 patients, 538 before and 589 during the COVID-19 pandemic. The mean age was 68 years (standard deviation 17, range 17-99 years). No difference in the prevalence of positive lung scintigraphy was found before [144 (27 %)] and during the pandemic [179 (29%)] (p=0.433). During the pandemic the percentage of patients exhibiting central or segmental pulmonary embolisms slightly increased [3 (0.6%) vs. 9 (1.5%) and 21 (3.9%) vs. 29 (4.9%)] compared to before, whereas. subsegmental pulmonary embolisms were equally frequent [120 (22%) vs. 132 (22%)] (overall p=0.345). The number of multiple (>4) emboli was increased [32 (5.9%) vs. 45 (7.6%), p=0.314]. Conclusion(s): During the COVID-19 pandemic, pulmonary ventilation/perfusion scintigraphy is also a reliable examination method for detecting pulmonary emboli. Although increased thromboembolic events were described with COVID-19 infections, no significant increase in the number or severity of detected pulmonary emboli could be observed in our population.

Quantifying the impact of COVID-19 on essential health services: a comparison of interrupted time series analysis using Prophet and Poisson regression models.

BACKGROUND: Coronavirus disease 2019 (COVID-19) altered healthcare utilization patterns. However, there is a dearth of literature comparing methods for quantifying the extent to which the pandemic disrupted healthcare service provision in sub-Saharan African countries. OBJECTIVE: To compare interrupted time series analysis using Prophet and Poisson regression models in evaluating the impact of COVID-19 on essential health services. METHODS: We used reported data from Uganda's Health Management Information System from February 2018 to December 2020. We compared Prophet and Poisson models in evaluating the impact of COVID-19 on new clinic visits, diabetes clinic visits, and in-hospital deliveries between March 2020 to December 2020 and across the Central, Eastern, Northern, and Western regions of Uganda. RESULTS: The models generated similar estimates of the impact of COVID-19 in 10 of the 12 outcome-region pairs evaluated. Both models estimated declines in new clinic visits in the Central, Northern, and Western regions, and an increase in the Eastern Region. Both models estimated declines in diabetes clinic visits in the Central and Western regions, with no significant changes in the Eastern and Northern regions. For in-hospital deliveries, the models estimated a decline in the Western Region, no changes in the Central Region, and had different estimates in the Eastern and Northern regions. CONCLUSIONS: The Prophet and Poisson models are useful in quantifying the impact of interruptions on essential health services during pandemics but may result in different measures of effect. Rigor and multimethod triangulation are necessary to study the true effect of pandemics on essential health services.

Has the COVID-19 pandemic affected the incidence of type 1 diabetes in Italy? Analysis on population-based registries over a 33-year period

Introduction: It is currently not well known if the incidence of type 1 diabetes (T1D) changed during COVID-19 pandemic. Objective(s): Basing on two population-based registries collecting data of new cases in Italy since 1989, we analyzed changes on incidence in a long and short period. Method(s): All new cases of T1D in children aged between 0.5 and 14, recruited by the Piedmont and Marche registries during 1989- 2021, were considered. Poisson regression was used to estimate the incidence trend, adjusted for age and sex, for the period 1989-2019 and to predict the incidence in the years 2020 and 2021. The observed rates in the years of the pandemic were compared with those predicted by the model and with those of the three-year prepandemic period 2017-2019. Result(s): Between 1989 and 2021, 4009 children diagnosed with T1D were observed, 2144 males (53.5%). The standardized incidence for the entire period was 16.9 (95%CI 14.4-17.5) per 100,000 personyears, 17.6 and 16.2 for males and females respectively. The incidence over time increased from 12.0 (95% CI 9.6-14.4) in 1989 to 20.9 (95% CI 17.5-24.9) in 2019, with an annual increasing trend of 1.9% (95% CI 1.5-2.2). The observed incidence rates in 2020 and 2021 were 21.6 (95% CI: 18.3-25.3) and 26.7 (95% CI 23.0-30.9) respectively, not significantly different from the ones predicted by the model, 21.6 (95%CI 20.3-23.0;p = 0.995) and 22.0 (95%CI 20.5- 26.6;p = 0.074). The mean incidence rate of T1D in the pre-pandemic 3 years, equal to 20.5 (95%CI 18.6-22.5), was not different from that of 2020, but significantly lower than that observed in 2021 (<0.001). Conclusion(s): The incidence of T1D < 15 years continues to increase over time. During 2020-2021, the observed incidence was in line with the expected trend 1989-2019. However, narrowing the analysis to 2017-2021, there was a higher incidence in 2021. Continuous observation of T1D in children is critical to better understanding the role of COVID-19 in influencing the disease.

Corneal collagen cross-linking in Australia, before and during the COVID-19 pandemic

Purpose: Corneal collagen cross-linking (CCXL) is a minimally invasive treatment for progressive corneal ectatic disorders, recently introduced on the Australian Medicare Benefits Schedule in May 2018. We aim to explore CCXL service rates over time in Australia and investigate potential changes during the COVID-19 pandemic. Method(s): Retrospective analysis of CCXL services in Australia between 2018 and 2021, as recorded by Medicare. We used Poisson regression to explore changes in service rates with time, and to compare differences in distribution by age, sex and state/territory. Result(s): A total of 8009 CCXL services were performed during the study period, with the majority for males (66.5%), those aged 15-24 years (40.5%) and in Victoria (27.7%). CCXL rates tended to increase annually, rising from 7.55 (in 2018) to 9.15 (in 2021) services per 100 000 people. While CCXL rates increased by 14% between 2019 and 2020 (service rate ratio [RR] 1.14, 95% confidence interval [CI] 1.07-1.20), there was a 35% reduction between March and April 2020 when the COVID-19 pandemic began (RR 0.65, 95% CI 0.52-0.82). CCXL rates subsequently increased by 99% between April and August 2020 (RR 1.99, 95% CI 1.60-2.48). Conclusion(s): CCXL service rates increased annually in Australia from 2018. This could be attributable to increased access to treatment for progressive corneal ectasia, and/or an increasing burden of disease. CCXL rates decreased transiently early in 2020, likely due to lockdowns and elective surgery restrictions during the initial COVID-19 pandemic.

Riders on the Storm: Exploring Meteorological and Temporal Impacts on Shared E-Scooters (SES) in Munich, Germany

This paper analyzes the meteorological and temporal impacts on shared e-scooters (SES) over 27 months of service in Munich. The objective is to explore the factors associated with SES utilization (hourly usage counts, median ride distances, and booking durations), focusing on time-variant variables (weather, holiday, time of the year, week, and day). This study employs the negative binomial (NB) and Consul's generalized Poisson (GP-1) regressions for modeling SES hourly demand. The Poisson regression is used for hourly medians of SES ride distances and booking durations. Random forest models evaluate the relative importance of meteorological and temporal variables for SES usage. In Munich, the popularity of SES grew over time. The peak booking numbers were on Fridays, Saturdays, and afternoons. Longer rides were on the weekends and holidays than on working days. The most extended trips were around midnight, posing the issue of riders' visibility. The COVID-19 lockdown negatively impacted SES bookings. Compared to winter, more and longer rides were between July and November. The weather impacted e-scooter usage with fewer bookings and shorter rides when raining and humid and more and longer trips when warm. Negative weather impacts for e-scooters may be partially due to a reduction in recreational use as weather discourages many outside activities. © 2022 IEEE.

Bayesian Inference for the Negative Binomial-Quasi Lindley Model for Time Series Count Data on the COVID-19 Pandemic

In statistical models, the generalized linear model (GLMs) plays a role in studying to describe a response variable as a function of 1 or more predictor variables. Computational methods and mixed distributions are frequently used to build predictive models to perform time-to-event data analysis. To develop a statistical model so that the model can make predictions appropriately and accurately, it starts with developing a suitable distribution for the nature of the actual data. This paper proposes a new mixed negative binomial distribution for count data with over-dispersion, the so-called negative binomial-quasi Lindley (NB-QL) distribution. A new GLMs framework for the NB-QL model to build the time series count data model is introduced, and its application is carried out based on the actual data sets of the COVID-19 epidemic in Thailand. The models are related to GLMs as they are linear relationships between outcome variables and covariates. Where the response variable was in the form of time series count data under the exponential family distribution function, with the random components and link functions. In this study, we study the factors that affect the number of COVID-19 death cases in Thailand and provide the predictive modeling of the number of the COVID-19 death cases from 1 January 2020 to 31 December 2020, for which this data set has the observed sample of 366 days. In contrast, a model with an NB-QL distribution and NB has approached the uniform. Based on the deviance, DIC, pD and the probability integral transform histogram, we can see that the proposed model is also suitable for forecasting the number of the COVID-19 death cases daily in Thailand, indicating that the NB-QL time series model was another efficient alternative to modeling count data that has an over-dispersion problem. According to the NB-QL time series model about the number of the COVID-19 death cases daily in Thailand, it is indicated that the average number of daily COVID-19 deaths is influenced by the number of the COVID-19 death cases in the previous 3 days. The average number of COVID-19 death cases in Thailand is also influenced by the previous 2 days. At the same time, the number of infected cases daily in Thailand is influenced by the number of the COVID-19 death cases daily. In addition, there are also the components interventions of internal covariate effects due to the data, as there was a surge in the number of the COVID-19 death cases daily in Thailand at the time between 73 143 and t ≥ 352. ≤t ≤. © 2022, Walailak University. All rights reserved.

Association between meteorological indicators and COVID-19 pandemic in Pakistan.

This study was designed to investigate the impact of meteorological indicators (temperature, rainfall, and humidity) on total COVID-19 cases in Pakistan, its provinces, and administrative units from March 10, 2020, to August 25, 2020. The correlation analysis showed that COVID-19 cases and temperature showed a positive correlation. It implies that the increase in COVID-19 cases was reported due to an increase in the temperature in Pakistan, its provinces, and administrative units. The generalized Poisson regression showed that the rise in the expected log count of COVID-19 cases was 0.024 times for a 1 °C rise in the average temperature in Pakistan. Second, the correlation between rainfall and COVID-19 cases was negative in Pakistan. However, the regression coefficient between the expected log count of COVID-19 cases and rainfall was insignificant in Pakistan. Third, the correlation between humidity and the total COVID-19 cases was negative, which implies that the increase in humidity is beneficial to stop the transmission of COVID-19 in Pakistan, its provinces, and administrative units. The reduction in the expected log count of COVID-19 cases was 0.008 times for a 1% increase in the humidity per day in Pakistan. However, humidity and COVID-19 cases were positively correlated in Sindh province. It is required to create awareness among the general population, and the government should include the causes, symptoms, and precautions in the educational syllabus. Moreover, people should adopt the habit of hand wash, social distancing, personal hygiene, mask-wearing, and the use of hand sanitizers to control the COVID-19.

COVID-19 transmission in Africa: estimating the role of meteorological factors.

Climate variables play a critical role in COVID-19's spread. Therefore, this research aims to analyze the effect of average temperature and relative humidity on the propagation of COVID-19 in Africa's first four affected countries (South Africa, Morocco, Tunisia, and Ethiopia). As a result, policymakers should develop effective COVID-19 spread control strategies. For each country, using daily data of confirmed cases and weather variables from May 1, 2020, to April 30, 2021, generalized linear models (Poisson regression) and general linear models were estimated. According to the findings, the rising average temperature causes COVID-19 daily new cases to increase in South Africa and Ethiopia while decreasing in Morocco and Tunisia. However, in Tunisia, the relative humidity and daily new cases of COVID-19 are positively correlated, while in the other three countries, they are negatively associated.

Spatiotemporal Bayesian estimation of the number of under-reported COVID-19 cases in Victoria Australia.

Having an estimate of the number of under-reported cases is crucial in determining the true burden of a disease. In the COVID-19 pandemic, there is a great need to quantify the true disease burden by capturing the true incidence rate to establish appropriate measures and strategies to combat the disease. This study investigates the under-reporting of COVID-19 cases in Victoria, Australia, during the third wave of the pandemic as a result of variation in geographic area and time. It is aimed to determine potential under-reported areas and generate the true picture of the disease in terms of the number of cases. A two-tiered Bayesian hierarchical model approach is employed to estimate the true incidence and detection rates through Bayesian model averaging. The proposed model goes beyond testing inequality across areas by looking into other covariates such as weather, vaccination rates, and access to vaccination and testing centres, including interactions and variations between space and time. This model aims for parsimony yet allows a broader range of scope to capture the underlying dynamic of the reported COVID-19 cases. Moreover, it is a data-driven, flexible, and generalisable model to a global context such as cross-country estimation and across time points under strict pandemic conditions.

Effects of climate variables on the COVID-19 mortality in Bangladesh.

Infectious diseases such as severe acute respiratory syndrome (SARS) and influenza are influenced by weather conditions. Climate variables, for example, temperature and humidity, are two important factors in the severity of COVID-19's impact on the human respiratory system. This study aims to examine the effects of these climate variables on COVID-19 mortality. The data are collected from March 08, 2020, to April 30, 2022. The parametric regression under GAM and semiparametric regression under GAMLSS frameworks are used to analyze the daily number of death due to COVID-19. Our findings revealed that temperature and relative humidity are commencing to daily deaths due to COVID-19. A positive association with COVID-19 daily death counts was observed for temperature range and a positive association for humidity. In addition, one-unit increase in daily temperature range was only associated with a 1.08% (95% CI: 1.06%, 1.10%), and humidity range was only associated with a 1.03% (95% CI: 1.02%, 1.03%) decrease in COVID-19 deaths. A flexible regression model within the framework of Generalized Additive Models for Location Scale and Shape is used to analyze the data by adjusting the time effect. We used two adaptable predictor models, such as (i) the Fractional polynomial model and (ii) the B-spline smoothing model, to estimate the systematic component of the GAMLSS model. According to both models, high humidity and temperature significantly (and drastically) lessened the severity of COVID-19 death. The findings on the epidemiological trends of the COVID-19 pandemic and weather changes may interest policymakers and health officials.

Impact of the Second Year COVID-19 Pandemic on the U.S. Kidney Transplantation: Interrupted Time Series Analysis

Purpose: The number of kidney transplant (KT) was decreased since the COVID-19 pandemic;however, the magnitude of the pandemic on the number of U.S. KT is unclear. We aim to examine KT access in the United States over the past 2 years of the COVID-19 pandemic. Method(s): The number of U.S. kidney transplant recipients from 1988 to 11/28/21 among 48 States performing KT and confirmed COVID-19 cases and deaths were retrieved from OPTN/SRTR and CDC, respectively. The association of COVID-19 cases and deaths in 2020 and 2021 with the change in the number of KT were examined by linear regression. Interrupted time series defining the beginning of the pandemic in late 2019 as the time reflecting event change and Poisson regression were used to test the magnitude of KT decline since the beginning of pandemic. Result(s): The number of KT had generally trended up from 1988 until 2019 when it has trended down (23,401, 22,817, and 20,736 in 2019, 2020, and 2021, respectively). The number of COVID-19 cases increased from 19,759,635 in 2020 to 27,284,847 in 2021 and mean COVID-19 death rate increased (227 and 340 deaths/10,000 COVID- 19 cases;p 0.592). Compared to 2020, every 10,000 increased in COVID-19 cases in 2021 was associated with significant decrease in 18 KT;however, there was no significant association between the changes in COVID-19 deaths and KT between 2020 and 2021 (betacases 0.00018, p 0.005, 95%CI 0.00006, 0.00030 (Figure 1A) and betadeaths 0.00014, p 0.805, 95%CI -0.00098, 0.00126 (Figure 1B)). The number of KT after the COVID-19 pandemic is 1.43% lower than those before the pandemic (IRR 0.985, p 0.010, 95%CI 0.975, 0.997;Figure 2). Conclusion(s): Although ongoing COVID-19 pandemic over the past 2 years leads to increasing number of COVID-19 cases and deaths, only the number of COVID-19 cases, but not deaths, has significantly affected the number of KT in the United States.

SARS-CoV-2 Antibody Response by mRNA Vaccine Platform in Incrementally Immunosuppressed Patients

Purpose: This study compares SARS-CoV-2 antibody responses between the twodose mRNA-1273 and BNT162b2 vaccine series across groups of incrementally immunosuppressed patients. Method(s): Semiquantitative testing for antibodies against the receptor binding domain (RBD) of the SARS-CoV-2 spike protein was performed using the Roche Elecsys anti-SARS-CoV-2 S enzyme immunoassay (EIA), 15-45 days after the second vaccine dose for SARS-CoV-2 naive patients with rheumatic and musculoskeletal disease (RMD), and solid organ transplant recipients (SOTRs) from an observational cohort. Anti-RBD titers were divided into categories of >=50, >=100 and >=250 U/mL based on levels associated with plasma neutralizing capacity in COVID-19 convalescent patients. Participants were stratified by increasing intensity of immunosuppression: RMD not on immunosuppression, RMD on immunosuppression, SOTR not on mycophenolate (MMF), and SOTR on MMF. Response rates between mRNA-1273 and BNT162b2 recipients were compared using modified Poisson regression weighted for age, time since vaccination, and number of immunosuppressive medications. This analysis was repeated for several thresholds of positive response: 50, 100, and 250 U/mL. Result(s): Of 1868 participants, 55.8% of RMD and 52.7% of SOTRs received BNT162b2;the remainder received mRNA-1273. Demographics, diagnoses, and immunosuppressive regimens were similar across vaccine groups. Among RMD participants not on immunosuppression, the chance of anti-RBD >=250U/ml was comparable among BNT162b2 and mRNA-1273 recipients (IRR= 0.91 1.03 1.16 p= 0.67). mRNA-1273 recipients had a higher chance than BNT162b2 recipients to achieve anti-RBD >=250U/ml among RMD participants on immunosuppression (IRR = 1.15 1.241.34, p<0.001);SOTRs not on MMF (IRR = 1.24 1.561.96, p <0.001);and SOTRs on MMF (IRR=1.28 2.625.37, p= 0.01). Similar trends were observed with titer cutoffs of >=100 and >=50 U/mL (Table 1). Conclusion(s): The two-dose mRNA-1273 vaccine series was more likely to induce stronger humoral immunogenicity compared to BNT162b2 in immunosuppressed patients;this effect was more pronounced with greater immunosuppression. These findings suggest importance in the choice of mRNA vaccine platform in optimizing immune responses to SARS-CoV-2 vaccination and can help inform vaccination strategies for booster doses in high-risk, immunosuppressed populations.

Kinetics and Durability of a Third Dose of SARS-CoV-2 Vaccination Among Solid Organ Transplant Recipients

Purpose: Understanding the dynamics of antibody response to a third dose (D3) of anti-SARS-CoV-2 vaccine in solid organ transplant recipients (SOTRs) is important to inform booster strategies. Method(s): We studied the the dynamics of anti-RBD (Roche, <0.8 to >2500 U/dL) and anti-S (Euroimmun, 0.1 to >8.9 AU) antibody levels in a cohort of SOTRs at 2 weeks, 1 month and 3 months after D3. We compared the proportion of seroconversion at 1 month or 3 months after D3 between mRNA and Ad.26.COV2.S D3 recipients, using Poisson regression with robust standard error, adjusting for age and numbers of immunosuppressants. Result(s): Among 928 SOTRs with 2-week (n=655), 1-month (n=651) or 3-month (n=404) post-D3 titer, 78%, 82% and 86% tested positive for antibodies. The median (IQR) anti-RBD at the three timepoints were >2500 (73, >2500), 2494 (49, >2500) and 1234 (59, >2500) U/mL (Figure 1A, blue), and there were 61% (n=436), 60% (n=491) and 53% (n=313) with anti-RBD> 1000 u/mL, respectively. The median (IQR) anti-S at the three timepoints were 3.2 (0.3, 8.4), 8 (2, >8.9) and 7.4 (2, >8.9) AU (Figure 1B, blue), and there were 47% (n=218), 61% (n=161) and 64% (n=91) who developed anti-S>4 AU. Among patients with no or minimal immune response at 2 weeks post-D3 (n=102), 3/41 (7%) had increased anti-RBD by 1 month while 11/18 (61%) had increased anti-S (Fisher exact p<0.001). 6/29 (21%) had increased anti-RBD by 3 months while 12/20 (60%) had increased anti-S (p<0.01) (Figure 1A&B, yellow). 27/102 (27%) of them seroconverted at 1 or 3 months after D3. Having received Ad.26.COV2.S as D3 is associated with 3.9X increased proportion of seroconversion at 1 month or 3 months among patients with no or minimal immune response at 2 weeks after D3 (aIRR=2.223.926.92, p<0.001). Conclusion(s): Among SOTRs who received a booster anti-SARS-CoV-2 vaccination, dynamics of Anti-RBD and Anti-S antibodies differed substantially. Anti-RBD titers on average declined only slightly after 14 days post-D3, while anti-S increased up through 30-60 days post-D3. After the peak, average titer values for both antibodies declined slightly through three months post-D3.

Effect of Mycophenolate Mofetil Dosing on Antibody Response to SARS-CoV-2 Vaccination in Heart and Lung Transplant Recipients

Purpose: Mycophenolate mofetil (MMF) use is associated with decreased antibody response to the SARS-CoV-2 mRNA vaccine series in heart and lung transplant recipients (HLTRs). Higher MMF doses have been associated with poor immunogenicity in kidney transplant recipients, but limited data exist on HLTRs. We evaluated the relationship between daily MMF dose and vaccine-induced antibody response in HLTRs. Method(s): HLTRs (n= 212) from an observational cohort were categorized by daily MMF doses (None, Low: <1000mg, Moderate: 1000-2000mg, High: >=2000mg). Semi-quantitative antibody testing was performed at 1, 3, and 6-months post-dose 2 (D2) using the Roche Elecsys anti-SARS-CoV-2 S enzyme immunoassay (EIA), testing for antibodies to SARSCoV2 spike protein receptor binding domain, and the EUROIMMUN EIA, testing for S1 domain of SARS-CoV-2 spike protein. Multivariable Poisson regression was used to estimate the risk of a negative antibody response with increasing MMF dose. Result(s): At the time of vaccination, 94 (44.3%) HLTRs reported receiving no MMF, 33 (15.6%) reported a low dose, 54 (25.7%) reported a moderate dose, and 31 (14.8%) reported a high dose regimen. There were statistically significant differences in the number of participants on mTOR inhibitors and Triple immunosuppression among the groups but the participants in all 4 dose categories were otherwise comparable (Table 1) The risk ratio of a negative post-D2 titer with low, moderate and high dose regimens compared to no MMF was 0.65 1.15 2.05 (p=0.63), 1.34 2.043.10 (p=0.001) and 1.83 2.77 4.21 (p<0.001) after adjusting for age, sex, vaccine type, time since transplant, and corticosteroid use. Conclusion(s): HLTRs taking MMF >1000mg/day are at higher risk of remaining seronegative after mRNA vaccination, with evidence of a dose-nonresponse effect. The findings support the exploration of whether targeted MMF reduction strategies in HLTRs increase SARS-CoV-2 vaccine immunogenicity. (Table Presented).

Better Antibody Response After a Dose of Ad.26.cov2.s vs MRNA Vaccines in Seronegative Transplant Recipients After 2-Dose MRNA Vaccination

Purpose: To compare antibody response to a third dose (D3) of SARS-CoV-2 vaccine in solid organ transplant recipients (SOTRs) with negative or low-positive antibody levels after 2-dose mRNA vaccination across D3 platforms. Method(s): From our observational study, 532 SOTRs who developed suboptimal antibody responses to 2-dose mRNA vaccination (Roche<50 U/mL or EUROIMMUN <1.1 AU) were selected. Belatacept recipients and persons with any COVID-19 diagnosis were excluded. We compared post-D3 antibody levels among SOTRs who received an mRNA vaccine for D3 (n=487) versus Ad.26.COV2.S for D3 (n=45). Poisson regression with robust standard error was used to study the association between vaccine platform and seroconversion, adjusting for immunosuppression, age, time since transplant, and liver transplant status. Result(s): Pre-D3, 342 SOTRs (64%) were seronegative, of whom 107 (31%) developed high-positive antibody levels post-D3. In contrast, of the 190 (36%) with low-positive pre-D3 antibody levels, 172 (91%) were high-positive post-D3 (Figure 1). Among SOTRs seronegative pre-D3, 1.8x more Ad.26.COV2.S D3 recipients seroconverted compared to mRNA D3 recipients (49.7% vs 27.8%, Fisher's exact=0.014) (Figure 2). Among the pre-D3 seronegative group, there was a 2x higher chance of developing high-positive post-D3 levels with Ad.26.COV2.S compared to mRNA D3 (IRR =1.42.02.9, p<0.001). This was despite the Ad.26. COV2.S D3 group having fewer younger patients and liver transplant recipients, factors that are associated with higher odds of positive antibody response. 165 SOTRs (31%) remained seronegative after D3 (22% of Ad.26.COV2.S recipients vs 32% of mRNA recipients). Conclusion(s): Heterologous boosting with Ad.26.COV2.S may be a promising vaccination option for SOTRs with poor response to the 2-dose mRNA series, particularly among those who are seronegative. (Table Presented).