COVID-19 vaccination dynamics in the US: coverage velocity and carrying capacity based on socio-demographic vulnerability indices in California's pediatric population.

Introduction: COVID-19 vaccine inequities have been widespread across California, the United States, and globally. As COVID-19 vaccine inequities have not been fully understood in the youth population, it is vital to determine possible factors that drive inequities to enable actionable change that promotes vaccine equity among vulnerable minor populations. Methods: The present study used the social vulnerability index (SVI) and daily vaccination numbers within the age groups of 12-17, 5-11, and under 5 years old across all 58 California counties to model the growth velocity and the anticipated maximum proportion of population vaccinated. Results: Overall, highly vulnerable counties, when compared to low and moderately vulnerable counties, experienced a lower vaccination rate in the 12-17 and 5-11 year-old age groups. For age groups 5-11 and under 5 years old, highly vulnerable counties are expected to achieve a lower overall total proportion of residents vaccinated. In highly vulnerable counties in terms of socioeconomic status and household composition and disability, the 12-17 and 5-11 year-old age groups experienced lower vaccination rates. Additionally, in the 12-17 age group, high vulnerability counties are expected to achieve a higher proportion of residents vaccinated compared to less vulnerable counterparts. Discussion: These findings elucidate shortcomings in vaccine uptake in certain pediatric populations across California and may help guide health policies and future allocation of vaccines, with special emphasis placed on vulnerable populations, especially with respect to socioeconomic status and household composition and disability.

COVID-19 Vaccination Dynamics in the US: Coverage Velocity and Carrying Capacity Based on Socio-demographic Vulnerability Indices in California.

Coronavirus disease 2019 (COVID-19) disparities among vulnerable populations are of paramount concern that extend to vaccine administration. With recent uptick in infection rates, dominance of the delta variant, and authorization of a third booster shot, understanding the population-level vaccine coverage dynamics and underlying sociodemographic factors is critical for achieving equity in public health outcomes. This study aimed to characterize the scope of vaccine inequity in California counties through modeling the trends of vaccination using the Social Vulnerability Index (SVI). Overall SVI, its four themes, and 9228 data points of daily vaccination numbers from December 15, 2020, to May 23, 2021, across all 58 California counties were used to model the growth velocity and anticipated maximum proportion of population vaccinated, defined as having received at least one dose of vaccine. Based on the overall SVI, the vaccination coverage velocity was lower in counties in the high vulnerability category (v = 0.0346, 95% CI 0.0334, 0.0358) compared to moderate (v = 0.0396, 95% CI 0.0385, 0.0408) and low (v = 0.0414, 95% CI 0.0403, 0.0425) vulnerability categories. SVI Theme 3 (minority status and language) yielded the largest disparity in coverage velocity between low and high-vulnerable counties (v = 0.0423 versus v = 0.035, P < 0.001). Based on the current trajectory, while counties in low-vulnerability category of overall SVI are estimated to achieve a higher proportion of vaccinated individuals, our models yielded a higher asymptotic maximum for highly vulnerable counties of Theme 3 (K = 0.544, 95% CI 0.527, 0.561) compared to low-vulnerability counterparts (K = 0.441, 95% CI 0.432, 0.450). The largest disparity in asymptotic proportion vaccinated between the low and high-vulnerability categories was observed in Theme 2 describing the household composition and disability (K = 0.602, 95% CI 0.592, 0.612; versus K = 0.425, 95% CI 0.413, 0.436). Overall, the large initial disparities in vaccination rates by SVI status attenuated over time, particularly based on Theme 3 status which yielded a large decrease in cumulative vaccination rate ratio of low to high-vulnerability categories from 1.42 to 0.95 (P = 0.002). This study provides insight into the problem of COVID-19 vaccine disparity across California which can help promote equity during the current pandemic and guide the allocation of future vaccines such as COVID-19 booster shots.

Changes in social support of pregnant and postnatal mothers during the COVID-19 pandemic.

OBJECTIVE: Our objectives were to assess in perinatal women: the most effective methods used to meet social support needs during COVID-19, the impact of COVID-19 on self-reported social support levels, and how perceived change in social support related to distress, depression, and mental health. DESIGN: One-time survey administered from April to August 2020 SETTING: Online PARTICIPANTS: Pregnant and postpartum women with infants less than 6 months of age MEASUREMENT AND FINDINGS: Participants indicated the methods they used to meet social support needs during COVID-19. They self-rated their social support level pre- and during pandemic and their distress, depressive symptoms, and mental health changes on a Likert scale. Out of 1142 participants, the most effective methods for obtaining social support during the pandemic were virtual means (e.g. video call) and interaction with friends. There was a significant difference in distribution of self-reported levels of social support before and during the pandemic, with more respondents reporting a decrease in support. Decreases in social support were associated with higher distress levels, higher levels of depressive symptoms, and poorer mental health. KEY CONCLUSIONS: Perinatal women reported decreased social support during the COVID-19 pandemic which was associated with poorer mental health. Using virtual means of social support and support provided by friends had the largest positive effect on perceived social support levels. IMPLICATIONS FOR PRACTICE: Interventions using virtual support means from friends may be helpful to improve social support and mental health in this population.

Coronavirus Disease 2019 (COVID-19): A Modeling Study of Factors Driving Variation in Case Fatality Rate by Country.

Background: The novel Severe Acute Respiratory Syndrome Coronavirus-2 has led to a global pandemic in which case fatality rate (CFR) has varied from country to country. This study aims to identify factors that may explain the variation in CFR across countries. Methods: We identified 24 potential risk factors affecting CFR. For all countries with over 5000 reported COVID-19 cases, we used country-specific datasets from the WHO, the OECD, and the United Nations to quantify each of these factors. We examined univariable relationships of each variable with CFR, as well as correlations among predictors and potential interaction terms. Our final multivariable negative binomial model included univariable predictors of significance and all significant interaction terms. Results: Across the 39 countries under consideration, our model shows COVID-19 case fatality rate was best predicted by time to implementation of social distancing measures, hospital beds per 1000 individuals, percent population over 70 years, CT scanners per 1 million individuals, and (in countries with high population density) smoking prevalence. Conclusion: Our model predicted an increased CFR for countries that waited over 14 days to implement social distancing interventions after the 100th reported case. Smoking prevalence and percentage population over the age of 70 years were also associated with higher CFR. Hospital beds per 1000 and CT scanners per million were identified as possible protective factors associated with decreased CFR.