Fluctuations of psychological states on Twitter before and during COVID-19.

The COVID-19 pandemic has been repeatedly associated with poor mental health. Previous studies have mostly focused on short time frames such as around the first lockdown periods, and the majority of research is based on self-report questionnaires. Less is known about the fluctuations of psychological states over longer time frames across the pandemic. Twitter timelines of 4,735 users from London and New York were investigated to shed light on potential fluctuations of several psychological states and constructs related to the pandemic. Moving averages are presented for the years 2020 and 2019. Further, mixed negative binomial regression models were fitted to estimate monthly word counts for the time before and during the pandemic. Several psychological states and constructs fluctuated heavily on Twitter during 2020 but not during 2019. Substantial increases in levels of sadness, anxiety, anger, and concerns about home and health were observed around the first lockdown periods in both cities. The levels of most constructs decreased after the initial spike, but negative emotions such as sadness, anxiety, and anger remained elevated throughout 2020 compared to the year prior to the pandemic. Tweets from both cities showed remarkably similar temporal patterns, and there are similarities to reactions found on Twitter following other previous traumatic events.

NIH funding of COVID-19 research in 2020: a cross-sectional study.

OBJECTIVE: This study aims to characterise and evaluate the National Institutes of Health's (NIH's) grant allocation speed and pattern of COVID-19 research. DESIGN: Cross-sectional study. SETTING: COVID-19 NIH RePORTER Dataset was used to identify COVID-19 relevant grants. PARTICIPANTS: 1108 grants allocated to COVID-19 research. MAIN OUTCOMES AND MEASURES: The primary outcome was to determine the number of grants and funding amount the NIH allocated for COVID-19 by research type and clinical/scientific area. The secondary outcome was to calculate the time from the funding opportunity announcement to the award notice date. RESULTS: The NIH awarded a total of 56 169 grants in 2020, of which 2.0% (n=1108) wwas allocated for COVID-19 research. The NIH had a US$45.3 billion budget that year, of which 4.9% (US$2.2 billion) was allocated to COVID-19 research. The most common clinical/scientific areas were social determinants of health (n=278, 8.5% of COVID-19 funding), immunology (n=211, 25.8%) and pharmaceutical interventions research (n=208, 47.6%). There were 104 grants studying COVID-19 non-pharmaceutical interventions, of which 2 grants studied the efficacy of face masks and 6 studied the efficacy of social distancing. Of the 83 COVID-19 funded grants on transmission, 5 were awarded to study airborne transmission of COVID-19 and 2 grants on transmission of COVID-19 in schools. The average time from the funding opportunity announcement to the award notice date was 151 days (SD: ±57.9). CONCLUSION: In the first year of the pandemic, the NIH diverted a small fraction of its budget to COVID-19 research. Future health emergencies will require research funding to pivot in a timely fashion and funding levels to be proportional to the anticipated burden of disease in the population.