COVID-19 vaccination and changes in the menstrual cycle among vaccinated persons.

OBJECTIVE: To describe the characteristics of people who experience changes to their menstrual cycle after COVID-19 vaccination. DESIGN: Longitudinal study. PATIENT(S): We recruited a volunteer sample with and without a history of SARS-CoV-2 infection who enrolled in the Arizona COVID-19 Cohort (CoVHORT) study and participated in a reproductive sub-cohort who were pre-menopausal, not pregnant, and had received a COVID-19 vaccine in 2021 (n = 545). EXPOSURE(S): Demographic and reproductive characteristics were collected via self-reports. MAIN OUTCOME MEASURE(S): Information on self-reported changes in the menstrual cycle after COVID-19 vaccination was collected from May 2021 to December 2021. We looked at demographic and reproductive characteristics as predictors of menstrual cycle change. RESULT(S): The majority of our vaccinated sample received the Pfizer-BioNTech vaccine (58%), and were 26-35 years old (51%), non-Hispanic (84%), and White (88%). Approximately 25% of vaccinated participants reported a change in their menstrual cycle after vaccination; the majority reported changes after their second dose (56%) as compared with their first (18%) and third (14%) doses. The most commonly reported changes were irregular menstruation (43%), increased premenstrual symptoms (34%), increased menstrual pain or cramps (30%), and abnormally heavy or prolonged bleeding (31%). High self-reported perceived stress levels compared with low perceived stress (OR, 2.22; 95% CI 1.12-4.37) and greater body mass index (OR, 1.04; 95% CI 1.00-1.07) were associated with greater odds of experiencing the menstrual cycle changes after the vaccination. Participants having a history of SARS-CoV-2 infection were less likely to report changes in their menstrual cycle after vaccination compared with the participants with no history of SARS-CoV-2 infection (OR, 0.58; 95% CI 0.32-1.04). CONCLUSION(S): Among vaccinated participants, approximately 25% of them reported predominantly temporary changes in the menstrual cycle, however, we are unable to determine whether these changes are due to normal cycle variability. The COVID-19 vaccines are safe and effective for everyone, including pregnant people and people trying to conceive; hence, these findings should not discourage vaccination.

Consequences of COVID-19 on adolescents in Arizona: A longitudinal study protocol.

Introduction: The long-term impact of COVID-19 is unknown. We developed a 5-year prospective cohort study designed to generate actionable community-informed research about the consequences of COVID-19 on adolescents ages 12-17 years in Arizona. Methods: The study has two primary outcomes: 1) acute and long-term outcomes of COVID-19 illness and 2) symptoms of depression and anxiety. Data is collected using an online survey with plans to integrate qualitative data collection methods. The survey is administered at baseline, 4, and 8 months in year one, and annually in years two through five. This study is informed by Intersectionality Theory, which considers the diverse identities adolescents have that are self and socially defined and the influence they have collectively and simultaneously. To this end, a sample of variables collected is race/ethnicity, language usage, generational status, co-occurring health conditions, and gender. Additional measures capture experiences in social contexts such as home (parent employment, food, and housing security), school (remote learning, type of school), and society (racism). Results: Findings are not presented because the manuscript is a protocol designed to describe the procedure instead of report results. Discussion: The unique contributions of the study is its focus on COVID-19 the illness and COVID-19 the socially experienced pandemic and the impact of both on adolescents.

Pre-existing conditions associated with post-acute sequelae of COVID-19.

Post-acute sequelae of COVID-19 (PASC) are conditions that occur or remain at least 28 days after SARS-CoV-2 infection. While some risk factors for PASC have been identified, little is known about pre-existing conditions that render one susceptible to developing PASC. Data from participants (n = 1224) in a longitudinal COVID-19 cohort study in Arizona were used to investigate comorbid conditions associated with PASC. After adjustment of the models for age, BMI, gender, race, and smoking, the following pre-existing conditions were statistically significantly associated with the development of PASC: asthma (OR = 1.54; 95% CI = 1.10-2.15); chronic constipation (OR = 4.29; 95% CI = 1.15-16.00); reflux (OR = 1.54; 95% CI = 1.01-2.34); rheumatoid arthritis (OR = 3.69; 95%CI = 1.15-11.82); seasonal allergies (OR = 1.56; 95% CI = 1.22-1.98); and depression/anxiety (OR = 1.72; 95% CI = 1.17-2.52). When grouping conditions together, statistically significant associations with PASC were observed for respiratory (OR = 1.47; 95% CI = 1.06-2.14); gastrointestinal (OR = 1.62; 95% CI = 1.16-2.26), and autoimmune conditions (OR = 4.38; 95% CI = 1.59-12.06). After adjustment for severity of acute SARS-CoV-2 infection and depression/anxiety, seasonal allergies (OR = 1.48; 95% CI 1.15-1.91) and autoimmune disease (OR = 3.78; 95% CI - 1.31-10.91) remained significantly associated with risk for PASC. These findings indicate that numerous pre-existing conditions may be associated with an increased risk for the development of PASC. Patients with these conditions should consider taking extra steps to avoid infection.

Persisting gastrointestinal symptoms and post-infectious irritable bowel syndrome following SARS-CoV-2 infection: results from the Arizona CoVHORT.

In this study, we aimed to examine the association between gastrointestinal (GI) symptom presence during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and the prevalence of GI symptoms and the development of post-infectious irritable bowel syndrome (PI-IBS). We used data from a prospective cohort and logistic regression to examine the association between GI symptom status during confirmed SARS-CoV-2 infection and prevalence of persistent GI symptoms at ≥45 days. We also report the incidence of PI-IBS following SARS-CoV-2 infection. Of the 1475 participants in this study, 33.8% (n = 499) had GI symptoms during acute infection. Cases with acute GI symptoms had an odds of persisting GI symptoms 4 times higher than cases without acute GI symptoms (odds ratio (OR) 4.29, 95% confidence interval (CI) 2.45-7.53); symptoms lasted on average 8 months following infection. Of those with persisting GI symptoms, 67% sought care for their symptoms and incident PI-IBS occurred in 3.0% (n = 15) of participants. Those with acute GI symptoms after SARS-CoV-2 infection are likely to have similar persistent symptoms 45 days and greater. These data indicate that attention to a potential increase in related healthcare needs is warranted.

COVID-19 Infection, the COVID-19 Pandemic, and Changes in Sleep

The objective of this study was to investigate the differences in sleep patterns among individuals with and without laboratory-confirmed SARS-CoV-2 infection. Laboratory-confirmed SARS-CoV-2 test results and self-reported measures recalling sleep habits prior to and during the pandemic were collected from May 2020 to March 2021 among 1,848 individuals in The Arizona CoVHORT Study. We used linear and logistic regression to model the association between test status, presentation of symptoms, and time since test result with sleep duration and trouble sleeping, respectively. Mixed models were used to investigate change in sleep duration prior to the pandemic compared to during the pandemic. Overall, 16.2% of the sample were SARS-CoV-2 positive, 64.3% were SARS-CoV-2 negative, and 19.5% were untested for SARS-CoV-2. Independent of SARS-CoV-2 infection status, all participants slept longer during the pandemic compared to pre-pandemic (Δ SARS-CoV-2 positive: 77.7 min, 95% CI 67.9, 87.5;Δ SARS-CoV-2 negative: 13.4 min, 95% CI 8.4, 18.3). However, SARS-CoV-2 positive participants slept 60.9 min longer (95% CI 49.1, 72.8) than SARS-CoV-2 negative participants in multivariable-adjusted models and had greater odds of trouble sleeping three or more times per week since the start of the pandemic (OR: 1.34 95% CI 1.02, 1.77) This greater odds of trouble sleeping persisted for participants who reported sleep habits > 30 days after their positive SARS-CoV-2 (OR: 2.11 95% CI 1.47, 3.03). Sleep patterns among non-hospitalized individuals with COVID-19 were altered following infection, regardless of the presentation of symptoms and time since infection.

A Rasch analysis assessing the reliability and validity of the Arizona CoVHORT COVID-19 vaccine questionnaire.

BACKGROUND: Despite the widespread availability of COVID-19 vaccines in the United States, many that have chosen not to be vaccinated have done so because of vaccine hesitancy. This highlights the need for tools that accurately capture the knowledge, attitudes, and beliefs towards COVID-19 vaccines, and provide steps toward improving vaccine acceptance. METHODS: Participants of the Arizona CoVHORT (COVID-19 Cohort) received a one-time, electronic based cross-sectional questionnaire intended to capture underlying motivations regarding vaccination, as well as hesitations that may prevent people from getting vaccinated. Rasch analysis was conducted among 4703 CoVHORT participants who had completed the vaccine questionnaire to assess questionnaire reliability and validity. Response categories were grouped to optimize scale functioning and to ensure independent probabilities of participant endorsement. RESULTS: A total of 4703 CoVHORT participants completed the questionnaire, of whom 68% were female, and who had a mean age of 48 years. Participants were primarily White (90%), highly educated (63% with a college degree or above, with most respondents (45%) having an income of more than $75,000 per annum. The results indicated the questionnaire has good reliability and construct validity for assessing attitudes and beliefs about the COVID-19 vaccines. In-fit mean-squares for included items ranged from 0.61 to 1.72 and outfit mean-squares ranged from 0.56 to 1.75, and correlation coefficients ranged from 0.25 to 0.75. The person-item map indicated normal distribution of logit scores measuring perceptions about COVID-19 vaccinations. CONCLUSIONS: The CoVHORT vaccine questionnaire demonstrated satisfactory reliability and construct validity in assessing attitudes and beliefs about COVID-19 vaccines. Overall results provide a starting point for a reliable and valid tool to assess knowledge and perceptions about COVID-19 vaccination, ultimately providing public health professionals with an instrument to assess the factors that are associated with vaccine acceptance or hesitancy.

Elucidating symptoms of COVID-19 illness in the Arizona CoVHORT: a longitudinal cohort study.

OBJECTIVE: To elucidate the symptoms of laboratory-confirmed COVID-19 cases as compared with laboratory-confirmed negative individuals and to the untested general population among all participants who reported symptoms within a large prospective cohort study. SETTING AND DESIGN: This work was conducted within the framework of the Arizona CoVHORT, a longitudinal prospective cohort study conducted among Arizona residents. PARTICIPANTS: Eligible participants were any individual living in Arizona and were recruited from across Arizona via COVID-19 case investigations, participation in testing studies and a postcard mailing effort. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome measure was a comparison of the type and frequency of symptoms between COVID-19-positive cases, tested but negative individuals and the general untested population who reported experiencing symptoms consistent with COVID-19. RESULTS: Of the 1335 laboratory-confirmed COVID-19 cases, 180 (13.5%) reported having no symptoms. Of those that did report symptoms, the most commonly reported were fatigue (82.2%), headache (74.6%), aches, pains or sore muscles (66.3%), loss of taste or smell (62.8) and cough (61.9%). In adjusted logistic regression models, COVID-19-positive participants were more likely than negative participants to experience loss of taste and smell (OR 12.1; 95% CI 9.6 to 15.2), bone or nerve pain (OR 3.0; 95% CI 2.2 to 4.1), headache (OR 2.6; 95% CI 2.2 to 3.2), nausea (OR 2.4; 95% CI 1.9 to 3.1) or diarrhoea (OR 2.1; 95% CI 1.7 to 2.6). Fatigue (82.9) and headache (74.9) had the highest sensitivities among symptoms, while loss of taste or smell (87.2) and bone or nerve pain (92.9) had the high specificities among significant symptoms associated with COVID-19. CONCLUSION: When comparing confirmed COVID-19 cases with either confirmed negative or untested participants, the pattern of symptoms that discriminates SARS-CoV-2 infection from those arising from other potential circulating pathogens may differ from general reports of symptoms among cases alone.

Post-acute sequelae of COVID-19 in a non-hospitalized cohort: Results from the Arizona CoVHORT.

Clinical presentation, outcomes, and duration of COVID-19 has ranged dramatically. While some individuals recover quickly, others suffer from persistent symptoms, collectively known as long COVID, or post-acute sequelae of SARS-CoV-2 (PASC). Most PASC research has focused on hospitalized COVID-19 patients with moderate to severe disease. We used data from a diverse population-based cohort of Arizonans to estimate prevalence of PASC, defined as experiencing at least one symptom 30 days or longer, and prevalence of individual symptoms. There were 303 non-hospitalized individuals with a positive lab-confirmed COVID-19 test who were followed for a median of 61 days (range 30-250). COVID-19 positive participants were mostly female (70%), non-Hispanic white (68%), and on average 44 years old. Prevalence of PASC at 30 days post-infection was 68.7% (95% confidence interval: 63.4, 73.9). The most common symptoms were fatigue (37.5%), shortness-of-breath (37.5%), brain fog (30.8%), and stress/anxiety (30.8%). The median number of symptoms was 3 (range 1-20). Amongst 157 participants with longer follow-up (≥60 days), PASC prevalence was 77.1%.

COVID-19 containment on a college campus via wastewater-based epidemiology, targeted clinical testing and an intervention.

Wastewater-based epidemiology has potential as an early-warning tool for determining the presence of COVID-19 in a community. The University of Arizona (UArizona) utilized WBE paired with clinical testing as a surveillance tool to monitor the UArizona community for SARS-CoV-2 in near real-time, as students re-entered campus in the fall. Positive detection of virus RNA in wastewater lead to selected clinical testing, identification, and isolation of three infected individuals (one symptomatic and two asymptomatic) that averted potential disease transmission. This case study demonstrated the value of WBE as a tool to efficiently utilize resources for COVID-19 prevention and response. Thus, WBE coupled with targeted clinical testing was further conducted on 13 dorms during the course of the Fall semester (Table 3). In total, 91 wastewater samples resulted in positive detection of SARS-CoV-2 RNA that successfully provided an early-warning for at least a single new reported case of infection (positive clinical test) among the residents living in the dorm. Overall, WBE proved to be an accurate diagnostic for new cases of COVID-19 with an 82.0% positive predictive value and an 88.9% negative predictive value. Increases in positive wastewater samples and clinical tests were noted following holiday-related activities. However, shelter-in-place policies proved to be effective in reducing the number of daily reported positive wastewater and clinical tests. This case study provides evidence for WBE paired with clinical testing and public health interventions to effectively contain potential outbreaks of COVID-19 in defined communities.

Design of the Arizona CoVHORT: A Population-Based COVID-19 Cohort.

This study is a prospective, population-based cohort of individuals with a history of SARS-CoV-2 infection and those without past infection through multiple recruitment sources. The main study goal is to track health status over time, within the diverse populations of Arizona and to identify the long-term consequences of COVID-19 on health and well-being. A total of 2,881 study participants (16.2% with a confirmed SARS-CoV-2 infection) have been enrolled as of December 22, 2020, with a target enrollment of 10,000 participants and a planned follow-up of at least 2 years. This manuscript describes a scalable study design that utilizes a wide range of recruitment sources, leveraging electronic data collection to capture and link longitudinal participant data on the current and emerging issues associated with the COVID-19 pandemic. The cohort is built within a collaborative infrastructure that includes new and established partnerships with multiple stakeholders, including the state's public universities, local health departments, tribes, and tribal organizations. Challenges remain for ensuring recruitment of diverse participants and participant retention, although the electronic data management system and timing of participant contact can help to mitigate these problems.

Training and Incorporating Students in SARS-CoV-2 Case Investigations and Contact Tracing.

OBJECTIVES: In June 2020, Arizona had the fastest-growing number of cases of coronavirus disease 2019 (COVID-19) worldwide. As part of the growing public health response, the University of Arizona Student Aid for Field Epidemiology Response (SAFER) team was able to modify and increase case investigation efforts to assist local health departments. We outline the recommended logistical and management steps to include students in a public health response of this scope. METHODS: From April 1 through September 1, 2020, the SAFER team identified key components of a successful student team response: volunteer training, management that allows more senior students to manage newer students, adoption of case-management software, and use of an online survey platform for students to conduct interviews consistently and allow for data quality control and management. RESULTS: From April 1 through September 1, 2020, SAFER worked with 3 local health departments to complete 1910 COVID-19 case investigations through a virtual call center. A total of 233 volunteers and 46 hourly student workers and staff members were involved. As of September 2020, students were completing >150 interviews per week, including contact-tracing efforts. PRACTICE IMPLICATIONS: Developing relationships between applied public health and academic programs can relieve the burden of low-risk, high-volume case investigations at local and state health departments. Furthermore, by establishing a virtual call center, health sciences faculty and students can volunteer remotely during a pandemic with no additional risk of infection.