P058 Experiences of New Visitors Seeking Emergency Food Assistance Due to the COVID-19 Pandemic

During the COVID-19 pandemic, food insecurity rates doubled, even tripled among households with children. In May 2020, Feeding America reported an average increase of charitable food use by 59% compared to the previous year across 98% of their network food banks. At that time, an estimated 38% of visitors were new to charitable food assistance. To explore food insecure, first-time visitors' experiences seeking food assistance during COVID-19. A qualitative study design. Adults (ages 18-64) seeking food assistance at emergency food distribution sites in West Central Florida were recruited to participate in the study between November 2020 and July 2021. Individuals that were food insecure and first-time visitors due to COVID-19 participated in in-depth interviews (N = 18). Using food security as a multidimensional concept, the interview guide explored the impact of emergency food assistance on food availability, access, utilization, and stability. Interviews were recorded, transcribed verbatim, and analyzed on ATLAS.ti 22. Applied thematic analysis was conducted to identify emergent themes. Participants were predominantly White (55.6%), female (72.2%), and between 40 and 59 years old (55.6%). There were seven salient themes including (1) crisis, added burdens, and barriers to pandemic assistance caused the need to seek food assistance, (2) fear of COVID-19 exposure and reducing risks, (3) new food purchasing behaviors to reduce spending, (4) pantry environments impact clients' feelings, (5) pantry foods – hit or miss, (6) mixed quality of pantry foods, and (7) gaining firsthand insight on hunger as a societal problem and appreciation for services. These themes describe how emergency food assistance increased participants' food availability and access during COVID-19, however, there were challenges in being able to use the pantry foods. Seeking food assistance made a difference in the way participants felt and impacted how they viewed hunger. Study findings suggest that emergency food providers can support clients by helping navigate pandemic recovery as they experience food insecurity as a temporary situation. University of South Florida College of Public Health;Feeding Tampa Bay

Unmasking partisanship: Polarization undermines public response to collective risk

Political polarization may undermine public policy response to collective risk, especially in periods of crisis when political actors have incentives to manipulate public perceptions. We study these dynamics in the U.S., focusing on how partisanship has influenced the use of face masks to stem the spread of COVID-19. Using a variety of approaches, we find partisanship is the single most important predictor of mask use and local policy interventions do not offset this relationship.

Lessons learned from the first 50 COVID-19 critical care transfer missions conducted by a civilian UK Helicopter Emergency Medical Service (preprint)

Background: The COVID-19 pandemic has placed exceptional demand on Intensive Care Units, necessitating the critical care transfer of patients on a regional and national scale. Performing these transfers required specialist expertise and involved moving patients over significant distances. Air Ambulance Kent Surrey Sussex (AAKSS) created a designed critical care transfer team and was one of the first civilian air ambulances in the United Kingdom to move ventilated COVID-19 patients by air. We describe the practical set up of such a service and the key lessons learned from the first 50 transfers. Methods Retrospective review of air critical care transfer service set up and case review of first 50 transfers. Results We describe key elements of the critical care transfer service, including coordination and activation; case interrogation; workforce; training; equipment; aircraft modifications; human factors and clinical governance. A total of 50 missions are described between 18 December 2020 and 1 February 2021. The mean age of these patients was 58 years (29–83). 30 (60%) were male and 20 (40%) were female. The mean total mission cycle (time of referral until the time team declared free at receiving hospital) was 264 minutes (range 149–440 min). The mean time spent at the referring hospital prior to leaving for the receiving unit was 72 minutes (31–158). The mean transfer transit time between referring and receiving units was 72 minutes (9–182). Conclusion Critically ill COVID-19 patients have highly complex medical needs during transport. Critical care transfer of COVID-19-positive patients by civilian HEMS services, including air-transfer, can be achieved safely with specific planning, protocols and pre-cautions. Regional planning of COVID-19 critical care transfers is required to optimise the time available of critical care transfer teams.

Effect of losartan on hospitalized patients with COVID-19-induced lung injury: A randomized clinical trial (preprint)

Background SARS-CoV-2 viral entry may disrupt angiotensin II (Ang II) homeostasis in part via ACE2 downregulation, potentially contributing to COVID-19 induced lung injury. Preclinical models of viral pneumonias that utilize ACE2 demonstrate Ang II type 1 receptor (AT1R) blockade mitigates lung injury, though observational COVID-19 data addressing the effect of AT1R blockade remain mixed. Methods Multicenter, blinded, placebo-controlled randomized trial of losartan (50 mg PO twice daily for 10 days) versus placebo. Hospitalized patients with COVID-19 and a respiratory sequential organ failure assessment score of at least 1 and not already taking a renin-angiotensin-aldosterone system (RAAS) inhibitor were eligible. The primary outcome was the imputed partial pressure of oxygen to fraction of inspired oxygen (PaO 2 /FiO 2 ) ratio at 7 days. Secondary outcomes included ordinal COVID-19 severity, oxygen, ventilator, and vasopressor-free days, and mortality. Losartan pharmacokinetics (PK) and RAAS components [Ang II, angiotensin-(1–7) (Ang-(1–7)), ACE, ACE2] were measured in a subgroup of participants. Findings From April 2020 - February 2021, 205 participants were randomized, 101 to losartan and 104 to placebo. Compared to placebo, losartan did not significantly affect PaO 2 /FiO 2 ratio at 7 days [difference of -24.8 (95% -55.6 to 6.1; p=0.12)]. Losartan did not improve any secondary clinical outcome, but worsened vasopressor-free days. PK data were consistent with appropriate steady-state concentrations, but we observed no significant effect of losartan on RAAS components. Interpretation Initiation of orally administered losartan to hospitalized patients with COVID-19 and acute lung injury does not improve PaO 2 / FiO 2 ratio at 7 days. These data may have implications for ongoing clinical trials. Trial Registration Losartan for Patients With COVID-19 Requiring Hospitalization ( NCT04312009 ), https://clinicaltrials.gov/ct2/show/NCT04312009

Statistical Issues and Recommendations for Clinical Trials Conducted During the COVID-19 Pandemic (preprint)

The COVID-19 pandemic has had and continues to have major impacts on planned and ongoing clinical trials. Its effects on trial data create multiple potential statistical issues. The scale of impact is unprecedented, but when viewed individually, many of the issues are well defined and feasible to address. A number of strategies and recommendations are put forward to assess and address issues related to estimands, missing data, validity and modifications of statistical analysis methods, need for additional analyses, ability to meet objectives and overall trial interpretability.

AutoTriage - An Open Source Edge Computing Raspberry Pi-based Clinical Screening System (preprint)

With the recent COVID-19 pandemic, healthcare systems all over the world are struggling to manage the massive increase in emergency department (ED) visits. This has put an enormous demand on medical professionals. Increased wait times in the ED increases the risk of infection transmission. In this work we present an open-source, low cost, off-body system to assist in the automatic triage of patients in the ED based on widely available hardware. The system initially focuses on two symptoms of the infection fever and cyanosis. The use of visible and far-infrared cameras allows for rapid assessment at a 1m distance, thus reducing the load on medical staff and lowering the risk of spreading the infection within hospitals. Its utility can be extended to a general clinical setting in non-emergency times as well to reduce wait time, channel the time and effort of healthcare professionals to more critical tasks and also prioritize severe cases. Our system consists of a Raspberry Pi 4, a Google Coral USB accelerator, a Raspberry Pi Camera v2 and a FLIR Lepton 3.5 Radiometry Long-Wave Infrared Camera with an associated IO module. Algorithms running in real-time detect the presence and body parts of individual(s) in view, and segments out the forehead and lip regions using PoseNet. The temperature of the forehead-eye area is estimated from the infrared camera image and cyanosis is assessed from the image of the lips in the visible spectrum. In our preliminary experiments, an accuracy of 97% was achieved for detecting fever and 77% for the detection of cyanosis, with a sensitivity of 91% and area under the receiver operating characteristic curve of 0.91. Heart rate and respiratory effort are also estimated from the visible camera. Although preliminary results are promising, we note that the entire system needs to be optimized before use and assessed for efficacy. The use of low-cost instrumentation will not produce temperature readings and identification of cyanosis that is acceptable in many situations. For this reason, we are releasing the full code stack and system design to allow others to rapidly iterate and improve the system. This may be of particular benefit in low-resource settings, and low-to-middle income countries in particular, which are just beginning to be affected by COVID-19.