Toxic Exposures Among Young Children One Year into the COVID-19 Pandemic: A Retrospective Review of Three San Francisco Bay Area Emergency Departments.

BACKGROUND: Daycare and school closures prompted by shelter-in-place orders may have increased opportunities for unintentional ingestions among young children. OBJECTIVES: We examined emergency department (ED) presentations for toxic exposures among young children during the COVID-19 pandemic in the San Francisco Bay Area, which had some of the strictest and most prolonged shelter-in-place policies in the United States. METHODS: We performed a retrospective cross-sectional study of children 0 to 5 years of age who presented with an ED International Statistical Classification of Diseases and Related Health Problems, Tenth Revision diagnosis code of toxic exposure within a tertiary care hospital system between March 16, 2016 and March 15, 2021. We considered the period after March 16, 2020 to represent the pandemic. RESULTS: During the pandemic, the absolute number of poisonings among young children remained stable. Overall, ED encounters within this cohort decreased by 55%, which doubled the relative toxic exposure rate per 1000 ED encounters from 4.99 (95% confidence interval [CI] 3.19-5.90) to 9.79 (95% CI 8.09-11.49). Rates of admission, severe medical complications, operating room case requests, and length of stay were not significantly different. Shelter-in-place was associated with significantly higher odds of cannabis ingestion (odds ratio = 2.70, 95% CI 1.60-4.49). CONCLUSION: Despite dramatic decreases in overall ED patient volumes, the absolute number and severity of toxic exposures were similar during the pandemic compared with previous years. © 2022 Elsevier Inc.

Use of the Improvement Index to Evaluate Equitable COVID-19 Vaccine Allocation in the San Francisco Bay Area.

Introduction: A social determinants of health index score or Vaccine Equity Metric was used to prioritize resources and address geographic disparities in California's vaccination coverage. We calculated the improvement index or percentage of the vaccination disparity gap closed to evaluate the impacts of this vaccination strategy in the San Francisco Bay Area during the SARS-CoV-2 Delta variant surge. Methods: We conducted a cross-sectional study on San Francisco Bay Area ZIP codes during the Delta surge (July 6-October 5, 2021). Data came from the California Immunization Registry and the 2019 5-year American Community Survey. We used Spearman correlations to examine the relationships between Vaccine Equity Metric category and vaccine coverage and Kruskal-Wallis tests to compare vaccination improvement index across Vaccine Equity Metric categories. Results: We studied 248 ZIP codes in the San Francisco Bay Area. Those with the lowest resources (Vaccine Equity Metric Level 1) had the highest absolute increase in vaccination coverage (14.3 vs 5.4 percentage points in Vaccine Equity Metric Level 4), although a contribution was higher starting vaccination rates in Level 4 ZIP codes with the greatest resources. The ratio of vaccination coverage between the lowest- and highest-resourced ZIP codes increased from 0.79 to 0.9, suggesting reduced disparity. However, it is difficult to interpret given wide differences in n (Level 1 n=8 vs Level 4 n=151). In contrast, the vaccination improvement index accounts for each Vaccine Equity Metric category's baseline vaccination; all were statistically similar (grand mean=41.5%, p=0.367), implying comparable improvement across all ZIP codes. Conclusions: Using a Vaccine Equity Metric to identify and prioritize resources to vulnerable communities contributed to equitable vaccine allocation in the San Francisco Bay Area. Our study shows an example of the improvement index's advantages over conventional health equity metrics, such as absolute differences and relative effect measures, which can overestimate an intervention's impact.

COVID-19 lockdown introduces human mobility pattern changes for both Guangdong-Hong Kong-Macao greater bay area and the San Francisco bay area.

In response to the coronavirus disease 2019 (COVID-19) pandemic, various countries have sought to control COVID-19 transmission by introducing non-pharmaceutical interventions. Restricting population mobility, by introducing social distancing, is one of the most widely used non-pharmaceutical interventions. Although similar population mobility restriction interventions were introduced, their impacts on COVID-19 transmission are often inconsistent across different regions and different time periods. These differences may provide critical information for tailoring COVID-19 control strategies. In this paper, anonymized high spatiotemporal resolution mobile-phone location data were employed to empirically analyze and quantify the impact of lockdowns on population mobility. Both the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) in China and the San Francisco Bay Area (SBA) in the United States were studied. In response to the lockdowns, a general reduction in population mobility was observed, but the structural changes in mobility are very different between the two bays: 1) GBA mobility decreased by approximately 74.0-80.1% while the decrease of SBA was about 25.0-42.1%; 2) compared to SBA, the GBA had smoother volatility in daily volume during the lockdown. The volatility change indexes for GBA and SBA were 2.55% and 7.52%, respectively; 3) the effect of lockdown on short- to long-distance mobility was similar in GBA while the medium- and long-distance impact was more pronounced in SBA.

Impacts of the San Francisco Bay Area shelter-in-place during the COVID-19 pandemic on urban heat fluxes.

The purpose of this study was to make quantitative connections between changes in social and economic activities in northern California urban areas and related Earth system environmental responses to the COVID-19 pandemic in 2020. We tested the hypothesis that the absence of worker activities during Shelter-in-Place in the San Francisco Bay Area detectably altered the infrared heat flux from parking lots, highways, and large building rooftops, caused primarily by quantitative changes in the reflective properties in these different classes of urban surfaces. The Landsat satellite's thermal infrared (TIR) sensor imagery for surface temperature (ST) was quantified for all the large urban features in the Bay Area that have flat (impervious) surfaces, such parking lots, wide roadways, and rooftops. These large impervious surface features in the five-county Bay Area were first delineated and classified using sub-meter aerial imagery from the National Agriculture Imagery Program (NAIP). We then compared Landsat ST data acquired on (or near) the same dates from the three previous years (2017-2019) for all these contiguous impervious surfaces. Results showed that all the large parking lots, roadway corridors, and industrial/commercial rooftops across the entire Bay Area urban landscape were detected by Landsat ST time series as significantly cooler (by 5o C to 8o C) during the unprecedented Shelter-in-Place period of mid-March to late-May of 2020, compared to same months of the three previous years. The explanation for this region-wide cooling pattern in 2020 that was best supported by both remote sensing and ground-based data sets was that relatively low atmospheric aerosol lower (PM2.5) concentrations from mid-March to late May of 2020 resulted in weaker temperature inversions over the Bay Area, higher diurnal surface mixing, and lowered urban surface temperatures, compared to the three previous years.

Retrospective Screening for SARS-CoV-2 RNA in California, USA, Late 2019.

To investigate the possibility of earlier cases of severe acute respiratory syndrome coronavirus 2 infection than previously recognized, we retrospectively tested pooled samples from 1,700 persons with respiratory signs/symptoms seen at Stanford Health Care, Palo Alto, California, USA, during the last 2 months of 2019. We found no evidence of earlier infection.