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.

Design and implementation of a health messaging protocol employed for use within a COVID-19 health dissemination platform.

Introduction: AZCOVIDTXT, a bilingual, two-way information sharing platform was created in April of 2020 in response to rising COVID-19 cases in Arizona. The aim of this paper is to delineate the protocol and processes used to develop and disseminate health messaging to serve as guidance for other groups, universities, or public health programs in the implementation or enhancement of health communication services. Methods: Health messaging formats included website articles, published on the system's website (azcovidtxt.org), infographics posted on social media, and SMS. Social media and SMS infographics were intended to highlight and augment the topics covered in the weekly website articles, to create a seamless multimodal source of reliable COVID-19 information for AZCOVIDTXT enrollees and the broader public. All health messaging information, text message and social media content was planned and reviewed collaboratively by the AZCOVIDTXT team topic experts for accuracy, efficacy, and content consistency. Results: As of July 2021, AZCOVIDTXT provided weekly COVID-19-related health communication to 3,747 participating households located across 225 Arizona zip codes. AZCOVIDTXT has developed and sent 446 unique, bilingual SMS for a total of 271,977 contact points. The team has produced and published 179 website articles, which averaged a combined 7,000-page views per month, and 173 social media posts were made available to 268 followers across three platforms. Discussion: Several programmatic aspects were deemed essential to the success of AZCOVIDTXT. These included (1) addressing community specific needs, (2) creating timely and relevant content, (3) developing an adaptable system, and (4) prioritizing system automation where possible, (5) having an interdisciplinary team approach to identifying and crafting key messages.

State mask mandates and psychological reactance theory: The role of political partisanship and COVID-19 risk in mask adoption and resistance.

RATIONALE: Psychological reactance theory was applied to examine the implications of state-level mask mandates in the United States during the COVID-19 pandemic. We evaluated the role of political partisanship and COVID-19 risk on changes in self-reported mask wearing before and after the imposition and removal of state mask mandates. METHOD: Secondary data from several sources were aggregated about self-reported mask wearing behavior, state mandates, COVID-19 infection rates, and state-level political partisanship. Difference-in-differences tests were performed using logistic regression to evaluate whether change in mask wearing behavior following the imposition or removal of a mandate was greater in states based on state-level political partisanship and COVID-19 infection rates. RESULTS: Although mask adoption generally increased following mandates, the amount of increase was smaller in more Republican states compared to more Democratic states. Mask wearing generally decreased following the removal of mandates, with greater decreases when COVID-19 infection rates were lower. CONCLUSION: The results collectively offer insights about the nuanced role of contextual factors in the adoption and resistance to masks following state mask mandates. Partisanship was important in responses to the imposition of state mask mandates and COVID-19 risk played a critical role in responses to mandate removal.