scholarly journals Higher COVID-19 vaccination rates are linked to decreased county-level COVID-19 incidence across USA

2021 ◽  
Author(s):  
Arjun Puranik ◽  
AJ Venkatakrishnan ◽  
Colin Pawlowski ◽  
Bharathwaj Raghunathan ◽  
Eshwan Ramudu ◽  
...  
Keyword(s):  
Incidence Rate ◽  
Vaccine Efficacy ◽  
Vaccine Dose ◽  
The United States ◽  
Vaccination Rate ◽  
Incidence Rates ◽  
P Value ◽  
County Level ◽  
Vaccination Rates ◽  
The Impact

Real world evidence studies of mass vaccination across health systems have reaffirmed the safety1 and efficacy2,3 of the FDA-authorized mRNA vaccines for COVID-19. However, the impact of vaccination on community transmission remains to be characterized. Here, we compare the cumulative county-level vaccination rates with the corresponding COVID-19 incidence rates among 87 million individuals from 580 counties in the United States, including 12 million individuals who have received at least one vaccine dose. We find that cumulative county-level vaccination rate through March 1, 2021 is significantly associated with a concomitant decline in COVID-19 incidence (Spearman correlation ρ = −0.22, p-value = 8.3e-8), with stronger negative correlations in the Midwestern counties (ρ = −0.37, p-value = 1.3e-7) and Southern counties (ρ = −0.33, p-value = 4.5e-5) studied. Additionally, all examined US regions demonstrate significant negative correlations between cumulative COVID-19 incidence rate prior to the vaccine rollout and the decline in the COVID-19 incidence rate between December 1, 2020 and March 1, 2021, with the US western region being particularly striking (ρ = −0.66, p-value = 5.3e-37). However, the cumulative vaccination rate and cumulative incidence rate are noted to be statistically independent variables, emphasizing the need to continue the ongoing vaccination roll out at scale. Given confounders such as different coronavirus restrictions and mask mandates, varying population densities, and distinct levels of diagnostic testing and vaccine availabilities across US counties, we are advancing a public health resource to amplify transparency in vaccine efficacy monitoring (https://public.nferx.com/covid-monitor-lab/vaccinationcheck). Application of this resource highlights outliers like Dimmit county (Texas), where infection rates have increased significantly despite higher vaccination rates, ostensibly owing to amplified travel as a “vaccination hub”; as well as Henry county (Ohio) which encountered shipping delays leading to postponement of the vaccine clinics. This study underscores the importance of tying the ongoing vaccine rollout to a real-time monitor of spatio-temporal vaccine efficacy to help turn the tide of the COVID-19 pandemic.

scholarly journals Counties with Lower Insurance Coverage and Housing Problems Are Associated with Both Slower Vaccine Rollout and Higher COVID-19 Incidence

Vaccines ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 973
Author(s):  
Gregory Donadio ◽  
Mayank Choudhary ◽  
Emily Lindemer ◽  
Colin Pawlowski ◽  
Venky Soundararajan
Keyword(s):  
Socioeconomic Factors ◽  
Insurance Coverage ◽  
Vaccination Rate ◽  
Incidence Rates ◽  
P Value ◽  
Strongly Correlated ◽  
Marginalized Communities ◽  
Vaccination Rates ◽  
Using Data ◽  
The Impact

Equitable vaccination distribution is a priority for outcompeting the transmission of COVID-19. Here, the impact of demographic, socioeconomic, and environmental factors on county-level vaccination rates and COVID-19 incidence changes is assessed. In particular, using data from 3142 US counties with over 328 million individuals, correlations were computed between cumulative vaccination rate and change in COVID-19 incidence from 1 December 2020 to 6 June 2021, with 44 different demographic, environmental, and socioeconomic factors. This correlation analysis was also performed using multivariate linear regression to adjust for age as a potential confounding variable. These correlation analyses demonstrated that counties with high levels of uninsured individuals have significantly lower COVID-19 vaccination rates (Spearman correlation: −0.460, p-value: <0.001). In addition, severe housing problems and high housing costs were strongly correlated with increased COVID-19 incidence (Spearman correlations: 0.335, 0.314, p-values: <0.001, <0.001). This study shows that socioeconomic factors are strongly correlated to both COVID-19 vaccination rates and incidence rates, underscoring the need to improve COVID-19 vaccination campaigns in marginalized communities.

scholarly journals Counties with lower insurance coverage are associated with both slower vaccine rollout and higher COVID-19 incidence across the United States

2021 ◽  
Author(s):  
Emily Lindemer ◽  
Mayank Choudhary ◽  
Gregory Donadio ◽  
Colin Pawlowski ◽  
Venky Soundararajan
Keyword(s):  
Health Insurance ◽  
Insurance Coverage ◽  
Health Insurance Coverage ◽  
The United States ◽  
Vaccination Rate ◽  
Incidence Rates ◽  
P Value ◽  
Spearman Correlation ◽  
Vaccination Rates ◽  
Vaccination Period

Efficient and equitable vaccination distribution is a priority for effectively outcompeting the transmission of COVID-19 globally. A recent study from the Centers for Disease Control and Prevention (CDC) identified that US counties with high social vulnerability according to metrics such as poverty, unemployment, low income, and no high school diploma, have significantly lower rates of vaccination compared to the national average1. Here, we build upon this analysis to consider associations between county-level vaccination rates and 68 different demographic, socioeconomic, and environmental factors for 1,510 American counties with over 228 million individuals for which vaccination data was also available. Our analysis reveals that counties with high levels of uninsured individuals have significantly lower COVID-19 vaccination rates (Spearman correlation: -0.264), despite the fact that the CDC has mandated that all COVID-19 vaccines are free and cannot be denied to anyone based upon health insurance coverage or immigration status. Furthermore, we find that the counties with high levels of uninsured individuals tend to have the highest COVID-19 incidence rates in March 2021 relative to December 2020 (Spearman correlation: 0.388). Among the 68 factors analyzed, insurance coverage is the only factor which is highly correlated with both vaccination rate and change in COVID-19 incidence during the vaccination period (|Spearman correlation| > 0.25). We also find that counties with higher percentages of Black and Hispanic individuals have significantly lower vaccination rates (Spearman correlations: -0.128, -0.136) and lesser declines of COVID-incidence rates (Spearman correlations: 0.334, 0.330) during the vaccination period. Surprisingly however, after controlling for race, we find that the association between lack of insurance coverage and vaccination rate as well as COVID-19 incidence rates is largely driven by counties with a majority white population. Among the counties with high proportions of white residents (top 10% decile), the association between insurance coverage and vaccination rate is significant (Spearman correlation: -0.210, p-value: 0.002), but among counties with low proportions of white residents (bottom 10% decile) this association is not significant (Spearman correlation: 0.072, p-value: 0.088). Taken together, this study highlights the fact that intricate socioeconomic factors are correlated not just to COVID-19 vaccination rates, but also to COVID-19 incidence fluctuations, underscoring the need to improve COVID-19 vaccination campaigns in marginalized communities. The strong positive correlation between low levels of health insurance coverage and low vaccination rates is particularly concerning, and calls for improved public health messaging to emphasize the fact that health insurance is not required to be eligible for any of the FDA-authorized COVID-19 vaccines in the United States.

scholarly journals The Effect of Vaccination Rates on the Infection of COVID-19 under the Vaccination Rate below the Herd Immunity Threshold

2021 ◽  
Vol 18 (14) ◽  
pp. 7491
Author(s):  
Yi-Tui Chen
Keyword(s):  
Infection Rate ◽  
Herd Immunity ◽  
The United States ◽  
Vaccination Rate ◽  
Infection Rates ◽  
Vaccination Rates ◽  
The United Kingdom ◽  
The World ◽  
Almost All ◽  
The Impact

Although vaccination is carried out worldwide, the vaccination rate varies greatly. As of 24 May 2021, in some countries, the proportion of the population fully vaccinated against COVID-19 has exceeded 50%, but in many countries, this proportion is still very low, less than 1%. This article aims to explore the impact of vaccination on the spread of the COVID-19 pandemic. As the herd immunity of almost all countries in the world has not been reached, several countries were selected as sample cases by employing the following criteria: more than 60 vaccine doses per 100 people and a population of more than one million people. In the end, a total of eight countries/regions were selected, including Israel, the UAE, Chile, the United Kingdom, the United States, Hungary, and Qatar. The results find that vaccination has a major impact on reducing infection rates in all countries. However, the infection rate after vaccination showed two trends. One is an inverted U-shaped trend, and the other is an L-shaped trend. For those countries with an inverted U-shaped trend, the infection rate begins to decline when the vaccination rate reaches 1.46–50.91 doses per 100 people.

scholarly journals The Impact of Healthcare Worker Influenza Vaccination on Nosocomial Influenza in a Tertiary Hospital: An Ecological Study

2020 ◽  
Author(s):  
Wycliffe Enli Wei ◽  
Stephanie Fook-Chong ◽  
Wen Kai Chen ◽  
Maciej Piotr Chlebicki ◽  
Wee Hoe Gan
Keyword(s):  
Protective Effect ◽  
Influenza Vaccination ◽  
Healthcare Worker ◽  
Healthcare Workers ◽  
Ecological Study ◽  
Tertiary Hospital ◽  
Vaccination Rate ◽  
Incidence Rates ◽  
Vaccination Rates ◽  
The Impact

Abstract Background: To protect hospitalized patients who are more susceptible to complications of influenza, seasonal influenza vaccination of healthcare workers (HCW) has been recommended internationally. However, its effectiveness is still being debated. To assess the effectiveness of HCW influenza vaccination, we performed an ecological study to evaluate the association between healthcare worker influenza vaccination and the incidence of nosocomial influenza in a tertiary hospital within Singapore between 2013-2018. Methods: Nosocomial influenza was defined by influenza among inpatients diagnosed 7 days or more post-admission by laboratory testing, while healthcare worker influenza vaccination rate was defined as the proportion of healthcare workers that was vaccinated at the end of each annual seasonal vaccination exercise. A modified Poisson regression was performed to assess the association between the HCW vaccination rates and monthly nosocomial influenza incidence rates. Results: Nosocomial influenza incidence rates followed the trend of non-nosocomial influenza, showing a predominant mid-year peak. Across 2,480,010 patient-days, there were 256 nosocomial influenza cases (1.03 per 10,000 patient-days). Controlling for background influenza activity and the number of influenza tests performed, no statistically significant association was observed between vaccination coverage and nosocomial influenza incidence rate although a protective effect was suggested (IRR 0.89, 95%CI:0.69-1.15, p =0.37). Conclusion: No significant association was observed between influenza vaccination rates and nosocomial influenza incidence rates, although a protective effect was suggested. Aligning local HCW vaccine timing and formulation to that of the Southern Hemisphere may improve effectiveness. HCW vaccination remains important but demonstrating its effectiveness in preventing nosocomial influenza is challenging.

scholarly journals The Impact of Healthcare Worker Influenza Vaccination on Nosocomial Influenza in a Tertiary Hospital: An Ecological Study

2020 ◽  
Author(s):  
Wycliffe Enli Wei ◽  
Stephanie Fook-Chong ◽  
Wen Kai Chen ◽  
Maciej Piotr Chlebicki ◽  
Wee Hoe Gan
Keyword(s):  
Protective Effect ◽  
Influenza Vaccination ◽  
Healthcare Worker ◽  
Healthcare Workers ◽  
Ecological Study ◽  
Tertiary Hospital ◽  
Vaccination Rate ◽  
Incidence Rates ◽  
Vaccination Rates ◽  
The Impact

Abstract Background: To protect hospitalized patients who are more susceptible to complications of influenza, seasonal influenza vaccination of healthcare workers (HCW) has been recommended internationally. However, its effectiveness is still being debated. To assess the effectiveness of HCW influenza vaccination, we performed an ecological study to evaluate the association between healthcare worker influenza vaccination and the incidence of nosocomial influenza in a tertiary hospital within Singapore between 2013-2018. Methods: Nosocomial influenza was defined by influenza among inpatients diagnosed 7 days or more post-admission by laboratory testing, while healthcare worker influenza vaccination rate was defined as the proportion of healthcare workers that was vaccinated at the end of each annual seasonal vaccination exercise. A modified Poisson regression was performed to assess the association between the HCW vaccination rates and monthly nosocomial influenza incidence rates.Results: Nosocomial influenza incidence rates followed the trend of non-nosocomial influenza, showing a predominant mid-year peak. Across 2,480,010 patient-days, there were 256 nosocomial influenza cases (1.03 per 10,000 patient-days). Controlling for background influenza activity and the number of influenza tests performed, no statistically significant association was observed between vaccination coverage and nosocomial influenza incidence rate although a protective effect was suggested (IRR 0.89, 95%CI:0.69-1.15, p=0.37). Conclusion: No significant association was observed between influenza vaccination rates and nosocomial influenza incidence rates, although a protective effect was suggested. Aligning local HCW vaccine timing and formulation to that of the Southern Hemisphere may improve effectiveness. HCW vaccination remains important but demonstrating its effectiveness in preventing nosocomial influenza is challenging.

scholarly journals Lifestyle Effects on the Risk of Transmission of COVID-19 in the United States: Evaluation of Market Segmentation Systems

2021 ◽  
Vol 18 (9) ◽  
pp. 4826
Author(s):  
Esra Ozdenerol ◽  
Jacob Seboly
Keyword(s):  
United States ◽  
The United States ◽  
Mortality Rates ◽  
Incidence Rates ◽  
Statistical Testing ◽  
Average Risk ◽  
County Level ◽  
Household Level ◽  
The Impact ◽  
The U.S

The aim of this study was to associate lifestyle characteristics with COVID-19 infection and mortality rates at the U.S. county level and sequentially map the impact of COVID-19 on different lifestyle segments. We used analysis of variance (ANOVA) statistical testing to determine whether there is any correlation between COVID-19 infection and mortality rates and lifestyles. We used ESRI Tapestry LifeModes data that are collected at the U.S. household level through geodemographic segmentation typically used for marketing purposes to identify consumers’ lifestyles and preferences. According to the ANOVA analysis, a significant association between COVID-19 deaths and LifeModes emerged on 1 April 2020 and was sustained until 30 June 2020. Analysis of means (ANOM) was also performed to determine which LifeModes have incidence rates that are significantly above/below the overall mean incidence rate. We sequentially mapped and graphically illustrated when and where each LifeMode had above/below average risk for COVID-19 infection/death on specific dates. A strong northwest-to-south and northeast-to-south gradient of COVID-19 incidence was identified, facilitating an empirical classification of the United States into several epidemic subregions based on household lifestyle characteristics. Our approach correlating lifestyle characteristics to COVID-19 infection and mortality rate at the U.S. county level provided unique insights into where and when COVID-19 impacted different households. The results suggest that prevention and control policies can be implemented to those specific households exhibiting spatial and temporal pattern of high risk.

scholarly journals Prostate Cancer in Lebanon: Incidence, Temporal Trends, and Comparison to Countries From Different Regions in the World

2021 ◽  
Vol 28 ◽  
pp. 107327482110552
Author(s):  
Najla A. Lakkis ◽  
Mona H. Osman
Keyword(s):  
Prostate Cancer ◽  
Incidence Rate ◽  
Task Force ◽  
Public Awareness ◽  
Temporal Trends ◽  
The United States ◽  
Incidence Rates ◽  
P Value ◽  
The World ◽  
Slow Growing

Background Prostate cancer is the most common malignancy in men globally. This study aims at investigating the incidence rates and trends of prostate cancer in Lebanon, and to compare them to those of countries from different regions in the world. Methods Data on prostate cancer were obtained from the Lebanese national cancer registry for the years 2005 to 2016. The calculated age-standardized incidence and age-specific rates were expressed as per 100 000 population. Results In Lebanon, prostate cancer is ranked as the most common cancer in men. The age-standardized incidence rate of prostate cancer has increased from 29.1 per 100 000 in 2005 to 37.3 per 100 000 in 2016; the highest rate was in 2012, surpassing the global average incidence rate for that year. The age-specific incidence rate of prostate cancer has increased exponentially starting at the age of 50 years to reach its peak in men aged 75 years or more. Two trends were identified in the age-standardized incidence rate of prostate cancer; an average significant increase of 7.28% per year for the period 2005–2009 ( P-value < .05), followed by a non-significant decrease of around .99% for the period between 2009 and 2016 ( P-value > .05). The age-standardized incidence rate in Lebanon was higher than most countries in the Middle East and North Africa region and Asia, but lower than the rates reported in Australia, America, and different European countries. Conclusion Prostate cancer is the leading cancer among men in Lebanon. Screening practices, changes in population age structure, and prevalence of genetic and risky lifestyle factors may explain the increased incidence rates of prostate cancer. Given the controversy of screening recommendations and the slow growing nature of prostate cancer, increasing public awareness on ways of prevention, and implementing the latest screening recommendation of the United States Preventive Services Task Force are the suggested way forward.

scholarly journals The Impact of Healthcare Worker Influenza Vaccination on Nosocomial Influenza in a Tertiary Hospital: An Ecological Study

2019 ◽  
Author(s):  
Wycliffe Enli Wei ◽  
Stephanie Fook-Chong ◽  
Wen Kai Chen ◽  
Maciej Piotr Chlebicki ◽  
Wee Hoe Gan
Keyword(s):  
Influenza Vaccination ◽  
Healthcare Worker ◽  
Healthcare Workers ◽  
Ecological Study ◽  
Statistical Significance ◽  
Tertiary Hospital ◽  
Vaccination Rate ◽  
Incidence Rates ◽  
Vaccination Rates ◽  
The Impact

Abstract Background To protect hospitalized patients who are more susceptible to complications of influenza, seasonal influenza vaccination of healthcare workers (HCW) has been recommended internationally. However, its effectiveness is still being debated. To assess the effectiveness of HCW influenza vaccination, we performed an ecological study to evaluate the association between healthcare worker influenza vaccination and the incidence of nosocomial influenza in a tertiary hospital within Singapore between 2013-2018.Methods Nosocomial influenza was defined by influenza among inpatients diagnosed 7 days or more post-admission by laboratory testing, while healthcare worker influenza vaccination rate was defined as the proportion of healthcare workers that was vaccinated at the end of each annual seasonal vaccination exercise. A modified Poisson regression was performed to assess the association between the HCW vaccination rates and monthly nosocomial influenza incidence rates.Results Nosocomial influenza incidence rates followed the trend of non-nosocomial influenza, showing a predominant mid-year peak. Across 2,480,010 patient-days, there were 256 nosocomial influenza cases (1.03 per 10,000 patient-days). Controlling for background influenza activity and the number of influenza tests performed, 10% increase in vaccination coverage corresponded to 11% decrease in nosocomial influenza incidence rate (IRR 0.89, 95%CI:0.69-1.15, p =0.37).Conclusion We observed a negative association between influenza vaccination rates and nosocomial influenza incidence rates, although statistical significance was not reached. Aligning local HCW vaccine timing and formulation to that of the Southern Hemisphere may improve effectiveness. HCW vaccination remains important but demonstrating its effectiveness in preventing nosocomial influenza is challenging.

scholarly journals COVID-19 and Historic Influenza Vaccinations in the United States: A Comparative Analysis

Vaccines ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1284
Author(s):  
Pranav Mirpuri ◽  
Richard A. Rovin
Keyword(s):  
Influenza Vaccination ◽  
The United States ◽  
Vaccination Rate ◽  
Primary Objective ◽  
Vaccine Uptake ◽  
Vaccine Hesitancy ◽  
County Level ◽  
Vaccination Rates ◽  
Global Challenge ◽  
Us Counties

The COVID-19 vaccination effort is a monumental global challenge. Recognizing and addressing the causes of vaccine hesitancy will improve vaccine uptake. The primary objective of this study was to compare the COVID-19 vaccination rates in US counties to historical vaccination rates for influenza in persons aged 65 and older. The secondary objective was to identify county-level demographic, socioeconomic, and political factors that influence vaccination rates. County level data were obtained from publicly available databases for comparison and to create predictive models. Overall, in US counties the COVID-19 vaccination rate exceeded influenza vaccination rates amongst those aged 65 or older (69.4.0% vs. 44%, p < 0.0001). 2690 (83.4%) of 3224 counties had vaccinated 50% or more of their 65 and older residents in the first seven months of the COVID-19 vaccination roll out. There were 467 (14.5%) of 3223 counties in which the influenza vaccination rate exceeded the COVID-19 vaccination rate. Most of these counties were in the Southern region, were considered politically “red” and had a significantly higher non-Hispanic Black resident population (14.4% vs. 8.2%, p < 0.0001). Interventions intended to improve uptake should account for nuances in vaccine access, confidence, and consider factual social media messaging, especially in vulnerable counties.

scholarly journals Whites’ County-Level Racial Bias, COVID-19 Rates, and Racial Inequities in the United States

2020 ◽  
Vol 17 (22) ◽  
pp. 8695
Author(s):  
Marilyn D. Thomas ◽  
Eli K. Michaels ◽  
Sean Darling-Hammond ◽  
Thu T. Nguyen ◽  
M. Maria Glymour ◽  
...  
Keyword(s):  
United States ◽  
Standard Deviation ◽  
Incidence Rate ◽  
Racial Bias ◽  
The United States ◽  
Mortality Rates ◽  
Incidence Rates ◽  
County Level ◽  
Explicit Bias ◽  
Implicit And Explicit

Mounting evidence reveals considerable racial inequities in coronavirus disease 2019 (COVID-19) outcomes in the United States (US). Area-level racial bias has been associated with multiple adverse health outcomes, but its association with COVID-19 is yet unexplored. Combining county-level data from Project Implicit on implicit and explicit anti-Black bias among non-Hispanic Whites, Johns Hopkins Coronavirus Resource Center, and The New York Times, we used adjusted linear regressions to estimate overall COVID-19 incidence and mortality rates through 01 July 2020, Black and White incidence rates through 28 May 2020, and Black–White incidence rate gaps on average area-level implicit and explicit racial bias. Across 2994 counties, the average COVID-19 mortality rate (standard deviation) was 1.7/10,000 people (3.3) and average cumulative COVID-19 incidence rate was 52.1/10,000 (77.2). Higher racial bias was associated with higher overall mortality rates (per 1 standard deviation higher implicit bias b = 0.65/10,000 (95% confidence interval: 0.39, 0.91); explicit bias b = 0.49/10,000 (0.27, 0.70)) and higher overall incidence (implicit bias b = 8.42/10,000 (4.64, 12.20); explicit bias b = 8.83/10,000 (5.32, 12.35)). In 957 counties with race-specific data, higher racial bias predicted higher White and Black incidence rates, and larger Black–White incidence rate gaps. Anti-Black bias among Whites predicts worse COVID-19 outcomes and greater inequities. Area-level interventions may ameliorate health inequities.

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