Associations between COVID-19 mobility restrictions and economic, mental health, and suicide-related concerns in the US using cellular phone GPS and Google search volume data.

During the COVID-19 pandemic, US populations have experienced elevated rates of financial and psychological distress that could lead to increases in suicide rates. Rapid ongoing mental health monitoring is critical for early intervention, especially in regions most affected by the pandemic, yet traditional surveillance data are available only after long lags. Novel information on real-time population isolation and concerns stemming from the pandemic's social and economic impacts, via cellular mobility tracking and online search data, are potentially important interim surveillance resources. Using these measures, we employed transfer function model time-series analyses to estimate associations between daily mobility indicators (proportion of cellular devices completely at home and time spent at home) and Google Health Trends search volumes for terms pertaining to economic stress, mental health, and suicide during 2020 and 2021 both nationally and in New York City. During the first pandemic wave in early-spring 2020, over 50% of devices remained completely at home and searches for economic stressors exceeded 60,000 per 10 million. We found large concurrent associations across analyses between declining mobility and increasing searches for economic stressor terms (national proportion of devices at home: cross-correlation coefficient (CC) = 0.6 (p-value <0.001)). Nationally, we also found strong associations between declining mobility and increasing mental health and suicide-related searches (time at home: mood/anxiety CC = 0.53 (<0.001), social stressor CC = 0.51 (<0.001), suicide seeking CC = 0.37 (0.006)). Our findings suggest that pandemic-related isolation coincided with acute economic distress and may be a risk factor for poor mental health and suicidal behavior. These emergent relationships warrant ongoing attention and causal assessment given the potential for long-term psychological impact and suicide death. As US populations continue to face stress, Google search data can be used to identify possible warning signs from real-time changes in distributions of population thought patterns.

Burden and characteristics of COVID-19 in the United States during 2020.

The COVID-19 pandemic disrupted health systems and economies throughout the world during 2020 and was particularly devastating for the United States, which experienced the highest numbers of reported cases and deaths during 20201-3. Many of the epidemiological features responsible for observed rates of morbidity and mortality have been reported4-8; however, the overall burden and characteristics of COVID-19 in the United States have not been comprehensively quantified. Here we use a data-driven model-inference approach to simulate the pandemic at county-scale in the United States during 2020 and estimate critical, time-varying epidemiological properties underpinning the dynamics of the virus. The pandemic in the United States during 2020 was characterized by national ascertainment rates that increased from 11.3% (95% credible interval (CI): 8.3-15.9%) in March to 24.5% (18.6-32.3%) during December. Population susceptibility at the end of the year was 69.0% (63.6-75.4%), indicating that about one third of the US population had been infected. Community infectious rates, the percentage of people harbouring a contagious infection, increased above 0.8% (0.6-1.0%) before the end of the year, and were as high as 2.4% in some major metropolitan areas. By contrast, the infection fatality rate fell to 0.3% by year's end.

A Spatiotemporal Tool to Project Hospital Critical Care Capacity and Mortality From COVID-19 in US Counties.

Objectives. To create a tool to rapidly determine where pandemic demand for critical care overwhelms county-level surge capacity and to compare public health and medical responses.Methods. In March 2020, COVID-19 cases requiring critical care were estimated using an adaptive metapopulation SEIR (susceptible‒exposed‒infectious‒recovered) model for all 3142 US counties for future 21-day and 42-day periods from April 2, 2020, to May 13, 2020, in 4 reactive patterns of contact reduction-0%, 20%, 30%, and 40%-and 4 surge response scenarios-very low, low, medium, and high.Results. In areas with increased demand, surge response measures could avert 104 120 additional deaths-55% through high clearance of critical care beds and 45% through measures such as greater ventilator access. The percentages of lives saved from high levels of contact reduction were 1.9 to 4.2 times greater than high levels of hospital surge response. Differences in projected versus actual COVID-19 demands were reasonably small over time.Conclusions. Nonpharmaceutical public health interventions had greater impact in minimizing preventable deaths during the pandemic than did hospital critical care surge response. Ready-to-go spatiotemporal supply and demand data visualization and analytics tools should be advanced for future preparedness and all-hazards disaster response.

Rotavirus Gastroenteritis Infection Among Children Vaccinated and Unvaccinated With Rotavirus Vaccine in Southern China: A Population-Based Assessment.

Importance: Since 2000, the Lanzhou lamb rotavirus vaccine has been exclusively licensed in China for voluntary rotavirus gastroenteritis (RV-GE) prevention. Objective: To evaluate the association of the Lanzhou lamb rotavirus vaccination with RV-GE among children in southern China. Design, Setting, and Participants: This cross-sectional, ecological study was set in Guangzhou, China. Participants were infants possibly vaccinated (aged 2 months to 3 years) and the children ineligible for vaccination (aged ≥4 years). The study was conducted from May 1, 2007, to April 30, 2016, and the data analysis was conducted in July 2016. Main Outcomes and Measures: Annual median age at onset of RV-GE and seasonal distribution of incidence. Cases of RV-GE in Guangzhou, China, diagnosed from May 1, 2007, to April 30, 2016, and reported to the National Information System for Disease Control and Prevention were examined. Poisson regression models were fitted among 32 452 children younger than 4 years and among 450 children who had been ineligible for vaccination, while controlling for secular trends, socioeconomic status, and meteorological factors. Logistic regression was used to assess the indirect effects provided by the vaccinated infants from 2009 to 2011 on unvaccinated infants aged 2 to 35 months based on a separate case-control data set. Results: During 9 seasons, 119 705 patients with gastroenteritis were reported; 33 407 were confirmed for RV-GE (21 202 [63.5%] male, 32 022 [95.8%] aged <4 years, and 31 306 [93.8%] residing in urban districts). The median age at onset for all patients with RV-GE increased from 11 months during the 2007 season to 15 months during the 2015 season, and the onset, peak, and cessation of incidence were delayed. When citywide vaccination coverage in the prior 12 months was classified into high and low groups (≥8.36% vs <8.36%), the incidence rate ratio for the high coverage group decreased by 32.4% among children younger than 4 years (incidence rate ratio, 0.676; 95% CI, 0.659-0.693; P < .001). Among the children ineligible for vaccination, the incidence rate ratio in higher coverage periods was 0.790 (95% CI, 0.351-0.915; P < .001) compared with the lower coverage. Compared with districts with 14% or less vaccination coverage, the adjusted odds ratio for RV-GE among unvaccinated children younger than 3 years was 0.85 (95% CI, 0.73-0.99; P = .03) for districts with 15% to 19% of coverage, and 0.79 (95% CI, 0.67-0.93; P = .004) for districts with more than 20% of coverage. Conclusions and Relevance: This study provides evidence of the population health benefits of the Lanzhou lamb rotavirus vaccination in preventing RV-GE among children in China younger than 4 years, including herd effects.