COVID-19 is currently the third leading cause of death in the United States, and unvaccinated people continue to die in high numbers. Vaccine hesitancy and vaccine refusal are fueled by COVID-19 misinformation and disinformation on social media platforms. This online COVID-19 infodemic has deadly consequences. In this editorial, the authors examine the roles that social media companies play in the COVID-19 infodemic and their obligations to end it. They describe how fake news about the virus developed on social media and acknowledge the initially muted response by the scientific community to counteract misinformation. The authors then challenge social media companies to better mitigate the COVID-19 infodemic, describing legal and ethical imperatives to do so. They close with recommendations for better partnerships with community influencers and implementation scientists, and they provide the next steps for all readers to consider. This guest editorial accompanies the Journal of Medical Internet Research special theme issue, “Social Media, Ethics, and COVID-19 Misinformation.”

Coronavirus disease 2019 (COVID-19) is a novel human respiratory disease caused by the SARS-CoV-2 virus. Asymptomatic carriers of the virus display no clinical symptoms but are known to be contagious. Recent evidence reveals that this sub-population, as well as persons with mild disease, are a major contributor in the propagation of COVID-19. The asymptomatic sub-population frequently escapes detection by public health surveillance systems. Because of this, the currently accepted estimates of the basic reproduction number (R 0 ) of the disease are inaccurate. It is unlikely that a pathogen can blanket the planet in three months with an R 0 in the 1 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)

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Many believe that shelter-in-place or stay-at-home policies might cause an increase in so-called deaths of despair. While increases in psychiatric stressors during the COVID-19 pandemic are anticipated, whether suicide rates changed during stay-at-home periods has not been described. This was an observational cohort study that assembled suicide death data for persons aged 10 years or older from the Massachusetts Department of Health Registry of Vital Records and Statistics from January 2015 through May 2020. Using autoregressive integrated moving average (ARIMA) and seasonal ARIMA to analyze suicide deaths in Massachusetts, we compared the observed number of suicide deaths in Massachusetts during the stay-at-home period (March through May, 2020) in Massachusetts to the projected number of expected deaths. To be conservative, we also accounted for the deaths still pending final cause determination The incident rate for suicide deaths in Massachusetts was 0.67 per 100,000 person-month (95% CI 0.56-0.79) versus 0.81 per 100,000 person-month (95% CI 0.69-0.94) during the 2019 corresponding period (incident rate ratio of 0.83; 95% CI 0.66-1.03). The addition of the 57 deaths pending cause determination occurring from March through May 2020 and the 33 cases still pending determination from the 2019 corresponding period did not change these findings. The observed number of suicide deaths during the stay-at-home period did not deviate from ARIMA projected expectations using either preliminary data or an alternate scenario in which deaths pending investigation (exceeding the average remaining number of deaths still pending investigation which occurred during the corresponding 2015-2019 period) were ascribed to suicide. Decedent age and sex demographics were unchanged during the pandemic period compared to 2015-2019. The stable rates of suicide deaths during the stay-at-home advisory in Massachusetts parallel findings following ecological disasters. As the pandemic persists, uncertainty about its scope and economic impact may increase. However, our data are reassuring that an increase in suicide deaths in Massachusetts during the stay-at-home advisory period did not occur.

Background Infection fatality rate and infection hospitalization rate, defined as the proportion of deaths and hospitalizations, respectively, of the total infected individuals, can estimate the actual toll of COVID-19 on a community as the denominator is ideally based on a representative sample of a population, which captures the full spectrum of illness, including asymptomatic and untested individuals. Objective To determine the COVID-19 infection hospitalization rate and infection fatality rate among the non-congregate population in Connecticut between March 1 and June 1, 2020. Methods The infection hospitalization rate and infection fatality rate were calculated for adults residing in non-congregate settings in Connecticut before June 2020. Individuals with SARS-CoV-2 antibodies were estimated using the seroprevalence estimates from the recently conducted Post-Infection Prevalence study. Information on total hospitalizations and deaths was obtained from the Connecticut Hospital Association and the Connecticut Department of Public Health. Results Before June 1, 2020, nearly 113,515 (90% CI 56,758–170,273) individuals were estimated to have SARS-CoV-2 antibodies and there were 7792 hospitalizations and 1079 deaths among the non-congregate population. The overall COVID-19 infection hospitalization rate and infection fatality rate was 6.86% (90% CI, 4.58%–13.72%) and 0.95% (90% CI, 0.63%–1.90%) and there was variation in these rate estimates across subgroups; older individuals, men, non-Hispanic Black individuals, and those belonging to 2 of the counties had a higher burden of adverse outcomes, though the differences between most subgroups were not statistically significant. Conclusions Using representative seroprevalence estimates, the overall COVID-19 infection hospitalization rate and infection fatality rate were estimated to be 6.86% and 0.95%, respectively, among community residents in Connecticut.

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ImportanceAmid efforts in the US to promote health equity, there is a need to assess recent progress in reducing excess deaths and years of potential life lost among the Black population compared with the White population.ObjectiveTo evaluate trends in excess mortality and years of potential life lost among the Black population compared with the White population.Design, setting, and participantsSerial cross-sectional study using US national data from the Centers for Disease Control and Prevention from 1999 through 2020. We included data from non-Hispanic White and non-Hispanic Black populations across all age groups.ExposuresRace as documented in the death certificates.Main outcomes and measuresExcess age-adjusted all-cause mortality, cause-specific mortality, age-specific mortality, and years of potential life lost rates (per 100 000 individuals) among the Black population compared with the White population.ResultsFrom 1999 to 2011, the age-adjusted excess mortality rate declined from 404 to 211 excess deaths per 100 000 individuals among Black males (P for trend <.001). However, the rate plateaued from 2011 through 2019 (P for trend = .98) and increased in 2020 to 395—rates not seen since 2000. Among Black females, the rate declined from 224 excess deaths per 100 000 individuals in 1999 to 87 in 2015 (P for trend <.001). There was no significant change between 2016 and 2019 (P for trend = .71) and in 2020 rates increased to 192—levels not seen since 2005. The trends in rates of excess years of potential life lost followed a similar pattern. From 1999 to 2020, the disproportionately higher mortality rates in Black males and females resulted in 997 623 and 628 464 excess deaths, respectively, representing a loss of more than 80 million years of life. Heart disease had the highest excess mortality rates, and the excess years of potential life lost rates were largest among infants and middle-aged adults.Conclusions and relevanceOver a recent 22-year period, the Black population in the US experienced more than 1.63 million excess deaths and more than 80 million excess years of life lost when compared with the White population. After a period of progress in reducing disparities, improvements stalled, and differences between the Black population and the White population worsened in 2020.