scholarly journals Mask adherence and rate of COVID-19 across the United States

Author(s):  
Charlie B. Fischer ◽  
Nedghie Adrien ◽  
Jeremiah J. Silguero ◽  
Julianne J. Hopper ◽  
Abir I. Chowdhury ◽  
...  

AbstractMask wearing has been advocated by public health officials as a way to reduce the spread of COVID-19. In the United States, policies on mask wearing have varied from state to state over the course of the pandemic. Even as more and more government leaders encourage or even mandate mask wearing, many citizens still resist the notion. Our research examines mask wearing policy and adherence in association with COVID-19 case rates. We used state-level data on mask wearing policy for the general public and on proportion of residents who stated they always wear masks in public. For all 50 states and the District of Columbia (DC), these data were abstracted by month for April ⍰ September 2020 to measure their impact on COVID-19 rates in the subsequent month (May ⍰ October 2020). Monthly COVID-19 case rates (number of cases per capita over two weeks) >200 per 100,000 residents were considered high. Fourteen of the 15 states with no mask wearing policy for the general public through September reported a high COVID-19 rate. Of the 8 states with at least 75% mask adherence, none reported a high COVID-19 rate. States with the lowest levels of mask adherence were most likely to have high COVID-19 rates in the subsequent month, independent of mask policy or demographic factors. Mean COVID-19 rates for states with at least 75% mask adherence in the preceding month was 109.26 per 100,000 compared to 249.99 per 100,000 for those with less adherence. Our analysis suggests high adherence to mask wearing could be a key factor in reducing the spread of COVID-19. This association between high mask adherence and reduced COVID-19 rates should influence policy makers and public health officials to focus on ways to improve mask adherence across the population in order to mitigate the spread of COVID-19.

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0249891
Author(s):  
Charlie B. Fischer ◽  
Nedghie Adrien ◽  
Jeremiah J. Silguero ◽  
Julianne J. Hopper ◽  
Abir I. Chowdhury ◽  
...  

Mask wearing has been advocated by public health officials as a way to reduce the spread of COVID-19. In the United States, policies on mask wearing have varied from state to state over the course of the pandemic. Even as more and more states encourage or even mandate mask wearing, many citizens still resist the notion. Our research examines mask wearing policy and adherence in association with COVID-19 case rates. We used state-level data on mask wearing policy for the general public and on proportion of residents who stated they always wear masks in public. For all 50 states and the District of Columbia (DC), these data were abstracted by month for April ─ September 2020 to measure their impact on COVID-19 rates in the subsequent month (May ─ October 2020). Monthly COVID-19 case rates (number of cases per capita over two weeks) >200 per 100,000 residents were considered high. Fourteen of the 15 states with no mask wearing policy for the general public through September reported a high COVID-19 rate. Of the 8 states with at least 75% mask adherence, none reported a high COVID-19 rate. States with the lowest levels of mask adherence were most likely to have high COVID-19 rates in the subsequent month, independent of mask policy or demographic factors. Mean COVID-19 rates for states with at least 75% mask adherence in the preceding month was 109.26 per 100,000 compared to 249.99 per 100,000 for those with less adherence. Our analysis suggests high adherence to mask wearing could be a key factor in reducing the spread of COVID-19. This association between high mask adherence and reduced COVID-19 rates should influence policy makers and public health officials to focus on ways to improve mask adherence across the population in order to mitigate the spread of COVID-19.


Author(s):  
Edward J. Cherian ◽  
Tom W. Ryan

Health Information Technology (HIT) has the potential to redefine the confines of traditional medicine. Yet, in over a decade, little has been shown in improvements from HIT investments. In order to understand the failures of health IT policy, this chapter examines the diverse priorities of stakeholders in the health system. Using kiviat diagrams as adaptations of the traditional iron-triangle of tradeoffs, the priorities of four stakeholder groups (patients, providers, pharmaceuticals, and payers) are mapped against the priorities of government and public health. The chapter finds that the priorities of these stakeholders within the United States healthcare system are incongruent and in conflict. To better understand the HIT needs of the future, policy makers and public health officials must understand these dichotomous priorities and work to bring them in line.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Gregory A. Wellenius ◽  
Swapnil Vispute ◽  
Valeria Espinosa ◽  
Alex Fabrikant ◽  
Thomas C. Tsai ◽  
...  

AbstractSocial distancing remains an important strategy to combat the COVID-19 pandemic in the United States. However, the impacts of specific state-level policies on mobility and subsequent COVID-19 case trajectories have not been completely quantified. Using anonymized and aggregated mobility data from opted-in Google users, we found that state-level emergency declarations resulted in a 9.9% reduction in time spent away from places of residence. Implementation of one or more social distancing policies resulted in an additional 24.5% reduction in mobility the following week, and subsequent shelter-in-place mandates yielded an additional 29.0% reduction. Decreases in mobility were associated with substantial reductions in case growth two to four weeks later. For example, a 10% reduction in mobility was associated with a 17.5% reduction in case growth two weeks later. Given the continued reliance on social distancing policies to limit the spread of COVID-19, these results may be helpful to public health officials trying to balance infection control with the economic and social consequences of these policies.


2020 ◽  
Author(s):  
Ruoyan Sun ◽  
Henna Budhwani

BACKGROUND Though public health systems are responding rapidly to the COVID-19 pandemic, outcomes from publicly available, crowd-sourced big data may assist in helping to identify hot spots, prioritize equipment allocation and staffing, while also informing health policy related to “shelter in place” and social distancing recommendations. OBJECTIVE To assess if the rising state-level prevalence of COVID-19 related posts on Twitter (tweets) is predictive of state-level cumulative COVID-19 incidence after controlling for socio-economic characteristics. METHODS We identified extracted COVID-19 related tweets from January 21st to March 7th (2020) across all 50 states (N = 7,427,057). Tweets were combined with state-level characteristics and confirmed COVID-19 cases to determine the association between public commentary and cumulative incidence. RESULTS The cumulative incidence of COVID-19 cases varied significantly across states. Ratio of tweet increase (p=0.03), number of physicians per 1,000 population (p=0.01), education attainment (p=0.006), income per capita (p = 0.002), and percentage of adult population (p=0.003) were positively associated with cumulative incidence. Ratio of tweet increase was significantly associated with the logarithmic of cumulative incidence (p=0.06) with a coefficient of 0.26. CONCLUSIONS An increase in the prevalence of state-level tweets was predictive of an increase in COVID-19 diagnoses, providing evidence that Twitter can be a valuable surveillance tool for public health.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Margaret M. Padek ◽  
Stephanie Mazzucca ◽  
Peg Allen ◽  
Emily Rodriguez Weno ◽  
Edward Tsai ◽  
...  

Abstract Background Much of the disease burden in the United States is preventable through application of existing knowledge. State-level public health practitioners are in ideal positions to affect programs and policies related to chronic disease, but the extent to which mis-implementation occurring with these programs is largely unknown. Mis-implementation refers to ending effective programs and policies prematurely or continuing ineffective ones. Methods A 2018 comprehensive survey assessing the extent of mis-implementation and multi-level influences on mis-implementation was reported by state health departments (SHDs). Questions were developed from previous literature. Surveys were emailed to randomly selected SHD employees across the Unites States. Spearman’s correlation and multinomial logistic regression were used to assess factors in mis-implementation. Results Half (50.7%) of respondents were chronic disease program managers or unit directors. Forty nine percent reported that programs their SHD oversees sometimes, often or always continued ineffective programs. Over 50% also reported that their SHD sometimes or often ended effective programs. The data suggest the strongest correlates and predictors of mis-implementation were at the organizational level. For example, the number of organizational layers impeded decision-making was significant for both continuing ineffective programs (OR=4.70; 95% CI=2.20, 10.04) and ending effective programs (OR=3.23; 95% CI=1.61, 7.40). Conclusion The data suggest that changing certain agency practices may help in minimizing the occurrence of mis-implementation. Further research should focus on adding context to these issues and helping agencies engage in appropriate decision-making. Greater attention to mis-implementation should lead to greater use of effective interventions and more efficient expenditure of resources, ultimately to improve health outcomes.


2021 ◽  
Author(s):  
Margaret Padek ◽  
Stephanie Mazzucca ◽  
Peg Allen ◽  
Emily Rodriguez Weno ◽  
Edward Tsai ◽  
...  

Abstract Background: Much of the disease burden in the United States is preventable through application of existing knowledge. State-level public health practitioners are in ideal positions to affect programs and policies related to chronic disease, but the extent to which mis-implementation occurring with these programs is largely unknown. Mis-implementation refers to ending effective programs and policies prematurely or continuing ineffective ones. Methods: A 2018 comprehensive survey assessing the extent of mis-implementation and multi-level influences on mis-implementation was reported by state health departments (SHDs). Questions were developed from previous literature. Surveys were emailed to randomly selected SHD employees across the Unites States. Spearman’s correlation and multinomial logistic regression were used to assess factors in mis-implementation. Results: Half (50.7%) of respondents were chronic disease program managers or unit directors. Forty nine percent reported that programs their SHD oversees sometimes, often or always continued ineffective programs. Over 50% also reported that their SHD sometimes or often ended effective programs. The data suggest the strongest correlates and predictors of mis-implementation were at the organizational level. For example, the number of organizational layers impeded decision-making was significant for both continuing ineffective programs (OR=4.70; 95% CI=2.20, 10.04) and ending effective programs (OR=3.23; 95% CI=1.61, 7.40). Conclusion: The data suggest that changing certain agency practices may help in minimizing the occurrence of mis-implementation. Further research should focus on adding context to these issues and helping agencies engage in appropriate decision-making. Greater attention to mis-implementation should lead to greater use of effective interventions and more efficient expenditure of resources, ultimately to improve health outcomes.


2018 ◽  
Author(s):  
Romain Garnier ◽  
Ana I. Bento ◽  
Pejman Rohani ◽  
Saad B. Omer ◽  
Shweta Bansal

AbstractThere is scientific consensus on the importance of breastfeeding for the present and future health of newborns, in high- and low-income settings alike. In the United States, improving breast milk access is a public health priority but analysis of secular trends are largely lacking. Here, we used data from the National Immunization Survey of the CDC, collected between 2003 and 2016, to illustrate the temporal trends and the spatial heterogeneity in breastfeeding. We also considered the effect sizes of two key determinants of breastfeeding rates. We show that, while access to breast milk both at birth and at 6 months old has steadily increased over the past decade, large spatial disparities still remain at the state level. We also find that, since 2009, the proportion of households below the poverty level has become the strongest predictor of breastfeeding rates. We argue that, because variations in breastfeeding rates are associated with socio-economic factors, public health policies advocating for breastfeeding are still needed in particular in underserved communities. This is key to reducing longer term health disparities in the U.S., and more generally in high-income countries.


2019 ◽  
Vol 14 (10) ◽  
pp. 491-496
Author(s):  
Tracy Perron ◽  
Heather Larovere ◽  
Victoria Guerra ◽  
Kathleen Kilfeather ◽  
Nicole Pare ◽  
...  

As measles cases continue to rise in the United States and elsewhere, public health officials, health care providers and elected officials alike are facing critical questions of how to protect the health of the public from current and future vaccine preventable disease outbreaks while still preserving the religious and personal autonomy of the populations they serve. As measles cases are being examined and carefully managed, public health officials are also tasked with revisiting vaccination policies and agendas to determine the best evidence-based interventions to control this epidemic. To determine the best course of action for the public's interest, research and current literature must be examined to protect and promote the health and wellbeing of those currently affected by the measles outbreak and those yet to be exposed.


2020 ◽  
Vol 8 (2) ◽  
pp. 240-267
Author(s):  
Luke Petach

Applying previously unused regional data to the problem of wage- versus profit-led growth, this paper estimates a demand-and-distribution system for a panel of US states for the years 1974 to 2014. Using variation in minimum-wage policy across states as an instrument for the labor share, I find that – at a regional level – the United States is strongly wage-led. In the absence of a satisfactory econometric identification strategy, I estimate the distributive curve non-parametrically. The results suggest the presence of significant non-linearities, with US states exhibiting profit-squeeze dynamics at low levels of capacity utilization and wage-squeeze dynamics at high levels. These results suggest difficulties for wage-led policy akin to a coordination failure.


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