A Novel Framework to Forecast COVID-19 Incidence Based on Google Trends Search Data

The global outbreak of coronavirus disease 2019 (COVID-19) has spread to more than 200 countries worldwide, leading to severe health and socioeconomic consequences. As such, the topic of monitoring and predicting epidemics has been attracting a lot of interest. Previous work reported search volumes from Google Trends are beneficial in decoding influenza dynamics, implying its potential for COVID-19 prediction. Therefore, a predictive model using the Wiener methods was built based on epidemic-related search queries from Google Trends, along with climate variables, aiming to forecast the dynamics of the weekly COVID-19 incidence in Washington, DC, USA. The Wiener model, which shares the merits of interpretability, low computation costs, and adaptation to nonlinear fluctuations, was used in this study. Models with multiple sets of features were constructed and further optimized by the highest weight selecting strategy. Furthermore, comparisons to the other two commonly used prediction models based on the autoregressive integrated moving average (ARIMA) and long short-term memory (LSTM) were also performed. Our results showed the predicted COVID-19 trends significantly correlated with the actual (rho <inline-formula> <tex-math notation="LaTeX">$=$</tex-math> </inline-formula> 0.88, <inline-formula> <tex-math notation="LaTeX">$p $</tex-math> </inline-formula> <inline-formula> <tex-math notation="LaTeX">$<$</tex-math> </inline-formula> 0.0001), outperforming those with ARIMA and LSTM approaches, indicating Google Trends data as a useful tool in terms of COVID-19 prediction. Also, the model using 20 search queries with the highest weighting outperformed all other models, supporting the highest weight feature selection as a feasible criterion. Google Trends search query data can be used to forecast the outbreak of COVID-19, which might assist health policymakers to allocate health care resources and taking preventive strategies. IEEE

Yoga at Every Size: A Preliminary Evaluation of a Brief Online Size-Inclusive Yoga and Body Gratitude Journaling Intervention to Enhance Positive Embodiment in Higher Weight College Women.

The present pilot randomized controlled trial (RCT) evaluated the feasibility, acceptability, and preliminary efficacy of a 4-week online yoga and body gratitude journaling intervention for strengthening positive embodiment among racially-diverse higher weight college women. Seventy-five participants were initially randomized to either the yoga condition (n = 36) or to a wait-list control (n = 39). Participants completed measures of positive and negative body image, weight bias internalization, self-compassion, drive for leanness, and physical activity acceptance at both baseline and post. Preliminary results among the 42 analyzed completers (mean age = 20.9, SD = 2.4; 30% Black or African American) revealed acceptable feasibility given the low-intensity nature of the intervention reflected in a 36% attrition rate. Self-reported adherence was strong for the yoga component with 81% of participants indicating that they practiced with the videos ≥3-4 times per week as suggested. Although 71% reported completing the body gratitude journal ≥1-2 times per week, daily adherence was minimal. Acceptability was also high among participants randomized to the yoga condition as indicated by 86% expressing at least moderate levels of satisfaction with the overall program. Qualitative feedback from participants further supported the acceptability of the program and pointed to important areas in further refining the protocol in the future. Preliminary efficacy was supported by significant reductions in internal body shame and gains in body appreciation, functional body appreciation, functional body satisfaction, functional body awareness, and behavioral commitment to physical activity engagement among the yoga vs. wait-list control participants. These promising findings once replicated in larger, higher-powered trials may have important implications for extending the reach and accessibility of mind-body wellness practices like yoga to benefit racially-/ethnically-diverse college women of higher weight. This research is further responsive to the growing need for efficacious remotely-delivered, and scalable behavioral health interventions in the ongoing era of the COVID-19 pandemic. However, additional research is warranted to explore ways of enhancing engagement of participants with lower levels of positive embodiment and to further incentivize the journaling component of the intervention.

Equity in Vaccine Trials for Higher Weight People? A Rapid Review of Weight-Related Inclusion and Exclusion Criteria for COVID-19 Clinical Trials.

Higher weight status, defined as body mass index (BMI) ≥ 30 kg/m2, is frequently described as a risk factor for severity and susceptibility to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease (known as COVID-19). Therefore, study groups in COVID-19 vaccine trials should be representative of the weight spectrum across the global population. Appropriate subgroup analysis should be conducted to ensure equitable vaccine outcomes for higher weight people. In this study, inclusion and exclusion criteria of registered clinical trial protocols were reviewed to determine the proportion of trials including higher weight people, and the proportion of trials conducting subgroup analyses of efficacy by BMI. Eligibility criteria of 249 trial protocols (phase I, II, III and IV) were analysed; 51 protocols (20.5%) specified inclusion of BMI > 30, 73 (29.3%) specified exclusion of BMI > 30, and 125 (50.2%) did not specify whether BMI was an inclusion or exclusion criterion, or if BMI was included in any 'health' screenings or physical examinations during recruitment. Of the 58 protocols for trials in phase III and IV, only 2 (3.4%) indicated an intention to report subgroup analysis of vaccine efficacy by weight status. Higher weight people appear to be significantly under-represented in the majority of vaccine trials. This may result in reduced efficacy and acceptance of COVID-19 vaccines for higher weight people and exacerbation of health inequities within this population group. Explicit inclusion of higher weight people in COVID-19 vaccine trials is required to reduce health inequities.