Disruptions in Health Care among Mwccs Participants during the Covid-19 Pandemic

Background: The COVID-19 pandemic resulted in disruptions to health care services. Vulnerable populations, including people living with HIV (PLHIV), may have experienced unique challenges when accessing medical care. The objective of this study was to evaluate the impact of social disruptions on health care visits among Multicenter AIDS Cohort Study/Women's Interagency HIV Study Combined Cohort Study (MWCCS) participants. Method(s): A survey collecting data on missed health care visits and social disruptions (i.e., disruptions in employment, childcare, financial support, housing, and health insurance) during the pandemic was administered via telephone to MWCCS participants 1-3 times from March and September 2020. Logistic regression models adjusted for sociodemographics and HIV-status were used to test the association between social disruptions and three medical care interruption outcomes (i.e., missed healthcare appointment, interruption of mental health care, and interruption of substance use care). Result(s): Surveys (n=10,076) were conducted among 2238 PLHIV (61% women) and 1427 people living without HIV (PLWoH) (41% women). Overall, 42% of participants reported disruptions in health care with no significant difference by HIV status. Among participants receiving mental health care services and substance use treatment, 52% and 36% reported interruptions of care, respectively. Participants reporting >= 2 social disruptions were more likely to report missed health care appointments (adjusted odds ratio [aOR]: 1.81, 95% confidence interval [CI]: 1.54-2.13), and interruptions in mental health care [aOR: 2.42, 95%CI: 1.85-3.17) or substance use treatment (aOR: 1.97, 95%CI: 1.26-3.09), compared to those reporting no disruptions. Participants who were unemployed were more likely to miss health care appointments (aOR:1.46, 95% CI: 1.25-1.71) and report disruptions in mental health care (aOR: 2.02, 95% CI: 1.54-2.66) compared to those who were employed. PLHIV reporting >= 2 social disruptions were at increased risk for missed health care appointments (aOR 1.92, 95%CI: 1.56-2.36) and disruptions in mental health care (aOR: 2.54, 95%CI: 1.83-3.53 (Table 1). Conclusion(s): Social disruptions as a result of the COVID-19 pandemic have adversely impacted the receipt of health care among PLHIV and PLWoH, including the receipt of treatment for mental health and substance abuse. Providing childcare, financial support, housing, and health insurance may reduce disruptions in care and improve health outcomes.

What Proportion of Infectious Diseases Physicians Have Buprenorphine Waivers to Treat Opioid Use Disorder in the United States?

Background. Since the onset of the COVID-19 pandemic, opioid-related overdose deaths have increased. Buprenorphine, a medication for opioid use disorder (OUD), is safe and effective but is underutilized and requires qualifying physicians to obtain a waiver. Infectious diseases (ID) physicians are uniquely positioned to treat OUD, as persons with OUD may present with infectious complications from injection drug use. We sought to understand the proportion and distribution of ID physicians with waivers in the United States (US). Methods. This was a cross-sectional study merging data from the Centers for Medicare & Medicaid Services and the Drug Enforcement Agency Substance Abuse and Mental Health Services Agency. Our primary outcome was proportion of ID physicians who possess buprenorphine waivers. We used multivariable regression models to identify individual and county-level characteristics associated with buprenorphine waiver possession. We used geospatial analysis to describe county-level distribution of buprenorphine-waivered ID physicians. Results. Among 6439 ID physicians in the US, 170 (2.6%) possessed buprenorphine waivers. Overall, 57.2% of ID physicians were male with a median 23 (IQR 15-33) years since medical school. Most (97.3%) practiced in metropolitan counties. In multivariable analysis, medical school graduation beyond 20 years was associated with lower odds of waiver possession compared to those graduating within 20 years (OR 0.59, 95% CI 0.43-0.80). ID physicians practicing in counties with median income > 50,000/year and in counties with higher proportion of uninsured residents also had lower odds of having a waiver (OR 0.58, 95% CI 0.35-0.97;OR 0.93, 95% CI 0.90-0.97). Among counties with at least one ID physician (n=519), 86.6% had no buprenorphine-waivered ID physicians (Figure 1). Figure 1 County-Level Distribution of Infectious Diseases Physicians with Buprenorphine Waivers Conclusion. Fewer than 3% of ID physicians in the US have obtained waivers to prescribe buprenorphine, highlighting missed opportunities to treat individuals with OUD, especially in rural America. Education on OUD management should be integrated into ID continuing medical education, and policies are urgently needed to expand buprenorphine access to persons without insurance.

"Who can help me?": Knowledge Infused Matching of Support Seekers and Support Providers during COVID-19 on Reddit

During the ongoing COVID-19 crisis, subreddits on Reddit, such as r/Coronavirus saw a rapid growth in user's requests for help (support seekers - SSs) including individuals with varying professions and experiences with diverse perspectives on care (support providers - SPs). Currently, knowledgeable human moderators match an SS with a user with relevant experience, i.e, an SP on these subreddits. This unscalable process defers timely care. We present a medical knowledge-infused approach to efficient matching of SS and SPs validated by experts for the users affected by anxiety and depression, in the context of with COVID-19. After matching, each SP to an SS labeled as either supportive, informative, or similar (sharing experiences) using the principles of natural language inference. Evaluation by 21 domain experts indicates the efficacy of incorporated knowledge and shows the efficacy the matching system.

Impact of COVID-19 Mitigation Measures on PrEP Care at a Safety Net Health System in Atlanta

Background. The Grady Health System pre-exposure prophylaxis (PrEP) program modified its care practices to accommodate COVID-19 mitigation measures. Changes enacted included: transition to telemedicine visits, medication mail delivery, and flexible timing of quarterly laboratory testing. These were implemented in March 2020 and remain in place presently. This study aimed to evaluate patients' long-term acceptability of these modifications and to assess their impact on PrEP care. Methods. This was a cross-sectional study in a convenience sample of PrEP patients, ages 18 and older, at an urban clinic in Atlanta. They were invited to complete a survey between December 2020 and April 2021. The survey assessed the impact of mitigation measures on overall PrEP care, follow up visits, medication access, and ability to complete laboratory testing. It also evaluated the usability, quality, satisfaction, and concerns with telemedicine. Data were examined using median and interquartile ranges, and proportions. Results. Of 145 patients contacted, 61 completed the survey (median age 33 years, 72% Black, 75% cisgender men, 15% transgender women). Most participants did not report interruptions in their PrEP care (72%) or follow up visits (74%). Most found it easy to access medications (82%), as participants' report of medication mail delivery usage increased from 57% (pre-pandemic) to 73% (in-pandemic period). Interruptions in completing quarterly labs were more frequently reported, as only 62% found this to be easy. Overall, 89% reported using telemedicine;telephone call was the most used method (78%). Telemedicine users' ratings for quality, usability, and satisfaction of telemedicine was high (median score: 6/7) and nearly all users (97%) reported no concerns about its continued use for PrEP care. A few participants (5%) raised concerns about loss of telephone services due to financial issues, impacting their ability to complete telemedicine visits. Conclusion. PrEP care at an urban clinic was well- maintained despite COVID-19 mitigation measures. Telemedicine was found to be acceptable and usable by surveyed participants. Future research on widescale implementation of telemedicine for PrEP care is needed.

Disaster management in India's construction industry during the Covid-19 pandemic

A biological disaster such as Covid-19 is unique in that, unlike other natural disasters, it does not engage the civil engineering community directly. Gaps in managing the pandemic exposed the lack of an institutional memory of handling pandemics, plus a lack of risk perception of 'fat tail' events. The impact on the construction sector was significant across the world, but different sections of the sector were affected differently. This paper documents and analyses these issues and concludes with a case study of how small and medium engineering practices endured the pandemic. © 2022 ICE Publishing: All rights reserved.

COVID-19 in Spain and India: Comparing policy implications by analyzing epidemiological and social media data

The COVID-19 pandemic has forced public health experts to develop contingent policies to stem the spread of infection, including measures such as partial/complete lockdowns. The effectiveness of these policies has varied with geography, population distribution, and effectiveness in implementation. Consequently, some nations (e.g., Taiwan, Haiti) have been more successful than others (e.g., United States) in curbing the outbreak. A data-driven investigation into effective public health policies of a country would allow public health experts in other nations to decide future courses of action to control the outbreaks of disease and epidemics. We chose Spain and India to present our analysis on regions that were similar in terms of certain factors: (1) population density, (2) unemployment rate, (3) tourism, and (4) quality of living. We posit that citizen ideology obtainable from twitter conversations can provide insights into conformity to policy and suitably reflect on future case predictions. A milestone when the curves show the number of new cases diverging from each other is used to define a time period to extract policy-related tweets while the concepts from a causality network of policy-dependent sub-events are used to generate concept clouds. The number of new cases is predicted using sentiment scores in a regression model. We see that the new case predictions reflects twitter sentiment, meaningfully tied to a trigger sub-event that enables policy-related findings for Spain and India to be effectively compared. Copyright © 2020 for this paper by its authors.

Comorbidity burden is associated with hospitalization for COVID-19 among PWH

Background: The contributions of non-AIDS comorbidities and HIV-related factors to coronavirus disease 2019 (COVID-19) outcomes among persons with HIV (PWH) remain unclear. We aimed to identify risk factors for COVID-19 hospitalization among PWH. Methods: We evaluated all adult (≥18 years) PWH with a positive SARS-CoV-2 PCR evaluated in a public safety-net hospital system, a Ryan White-funded HIV clinic and a Veterans Affairs medical center in Atlanta, GA between March 1, 2020 and November 15, 2020. Demographic and clinical characteristics and COVID-19 disease outcomes were ascertained by medical record abstraction. We performed multivariable logistic regression to determine associations with COVID-19 hospitalization. Results: 180 patients (mean age 49 years, 78% male, 78% Black, 14% Latinx) were included. 97% were on antiretroviral therapy (ART), 91% had HIV-1 RNA <200 copies/ml, and mean CD4 count was 527 cells/mm3. 60 patients (33%) were hospitalized, 28 (47%) required supplemental oxygen. Overall mortality rate among PWH was 1.63%;mortality among hospitalized PWH was 5%. 130 patients (72%) had at least 1 non-AIDS comorbidity;22% had >4 comorbidities (hypertension, dyslipidemia, obesity and diabetes were most prevalent). In univariable models, age, hypertension, dyslipidemia, diabetes, heart disease, and chronic kidney disease were associated with hospitalization. HIV characteristics including CD4 count, viral load, and ART use were not associated with hospitalization. After adjusting for those baseline characteristicsassociated with hospitalization, only age [aOR(95%CI) 1.073 (1.036-1.110), p<0.0001] and diabetes mellitus [aOR(95%CI) 2.653 (1.027-6.853), p=0.0439] were associated with hospitalization. In a multivariable model adjusting only for age, comorbidity count was associated with a 25% increased risk for hospitalization [aOR(95% CI) 1.245 (1.013-1.531), p=0.0375];and having ≥4 comorbidities was associated with a 2.8-fold increased risk of hospitalization compared with 0-1 comorbidities [aOR(95% CI) 2.848 (1.174-6.910), p=0.0240] (Figure). In age-adjusted analyses restricted to CD4 <200 cells/mm3 or HIV-1 RNA >200 copies/mL, HIV-related factors were not associated with hospitalization. Conclusion: In a cohort of PWH with well-controlled HIV and COVID-19, age and non-AIDS comorbidities, but not HIV-related factors, were associated with hospitalization for COVID-19. Further research into causes of severe COVID-19 among PWH is warranted. (Figure Presented).

Knowledge infused policy gradients for adaptive pandemic control

COVID-19 has impacted nations differently based on their policy implementations. The effective policy requires taking into account public information and adaptability to new knowledge. Epidemiological models built to understand COVID-19 seldom provide the policymaker with the capability for adaptive pandemic control (APC). Among the core challenges to be overcome include (a) inability to handle a high degree of non-homogeneity in different contributing features across the pandemic timeline, (b) lack of an approach that enables adaptive incorporation of public health expert knowledge, and (c) transparent models that enable understanding of the decision-making process in suggesting policy. In this work, we take the early steps to address these challenges using Knowledge Infused Policy Gradient (KIPG) methods. Prior work on knowledge infusion does not handle soft and hard imposition of varying forms of knowledge in disease information and guidelines to necessarily comply with. Furthermore, the models do not attend to non-homogeneity in feature counts, manifesting as partial observability in informing the policy. Additionally, interpretable structures are extracted post-learning instead of learning an interpretable model required for APC. To this end, we introduce a mathematical framework for KIPG methods that can (a) induce relevant feature counts over multi-relational features of the world, (b) handle latent non-homogeneous counts as hidden variables that are linear combinations of kernelized aggregates over the features, and (b) infuse knowledge as functional constraints in a principled manner. The study establishes a theory for imposing hard and soft constraints and simulates it through experiments. In comparison with knowledge-intensive baselines, we show quick sample efficient adaptation to new knowledge and interpretability in the learned policy, especially in a pandemic context. © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). CEUR Workshop Proceedings (CEUR-WS.org)