scholarly journals Delayed Interventions, Low Compliance, and Health Disparities Amplified the Early Spread of COVID-19

2020 ◽  
Author(s):  
Aliea M. Jalali ◽  
Sumaia G. Khoury ◽  
JongWon See ◽  
Alexis M. Gulsvig ◽  
Brent M. Peterson ◽  
...  
Keyword(s):  
Public Health ◽  
Health Disparities ◽  
State Level ◽  
The United States ◽  
Health Interventions ◽  
Systematic Evaluation ◽  
Public Health Interventions ◽  
Multivariate Statistical ◽  
The Us ◽  
At Home

AbstractThe United States (US) public health interventions were rigorous and rapid, yet failed to arrest the spread of the Coronavirus Disease 2019 (COVID-19) pandemic as infections spread throughout the US. Many factors have contributed to the spread of COVID-19, and the success of public health interventions depends on the level of community adherence to preventative measures. Public health professionals must also understand regional demographic variation in health disparities and determinants to target interventions more effectively. In this study, a systematic evaluation of three significant interventions employed in the US, and their effectiveness in slowing the early spread of COVID-19 was conducted. Next, community-level compliance with a state-level stay at home orders was assessed to determine COVID-19 spread behavior. Finally, health disparities that may have contributed to the disproportionate acceleration of early COVID-19 spread between certain counties were characterized. The contribution of these factors for the disproportionate spread of the disease was analyzed using both univariate and multivariate statistical analyses. Results of this investigation show that delayed implementation of public health interventions, a low level of compliance with the stay at home orders, in conjunction with health disparities, significantly contributed to the early spread of the COVID-19 pandemic.

scholarly journals Early COVID-19 Interventions Failed to Replicate 1918 St. Louis vs. Philadelphia Outcomes in the United States

2020 ◽  
Author(s):  
Aliea M. Jalali ◽  
Brent M. Peterson ◽  
Thushara Galbadage
Keyword(s):  
Public Health ◽  
United States ◽  
State Level ◽  
The United States ◽  
The State ◽  
Health Interventions ◽  
Public Health Interventions ◽  
Public Health Response ◽  
Health Response ◽  
The Us

The Coronavirus disease 2019 (COVID-19) pandemic has elicited an abrupt pause in the United States in multiple sectors of commerce and social activity. As the US faces this health crisis, the magnitude, and rigor of their initial public health response was unprecedented. As a response, the entire nation shutdown at the state-level for the duration of approximately one to three months. These public health interventions, however, were not arbitrarily decided, but rather, implemented as a result of evidence-based practices. These practices were a result of lessons learned during the 1918 influenza pandemic and the city-level non-pharmaceutical interventions (NPIs) taken across the US. During the 1918 pandemic, two model cities, St. Louis, MO, and Philadelphia, PA, carried out two different approaches to address the spreading disease, which resulted in two distinctly different outcomes. Our group has evaluated the state-level public health response adopted by states across the US, with a focus on New York, California, Florida, and Texas, and compared the effectiveness of reducing the spread of COVID-19. Our assessments show that while the states mentioned above benefited from the implementations of early preventative measures, they inadequately replicated the desired outcomes observed in St. Louis during the 1918 crisis. Our study indicates that there are other factors, including health disparities that may influence the effectiveness of public health interventions applied. Identifying more specific health determinants may help implement targeted interventions aimed at preventing the spread of COVID-19 and improving health equity.

scholarly journals Differential impact of non-pharmaceutical public health interventions on COVID-19 epidemics in the United States

2020 ◽  
Author(s):  
Xiaoshuang Liu ◽  
Xiao Xu ◽  
Guanqiao Li ◽  
Xian Xu ◽  
Yuyao Sun ◽  
...  
Keyword(s):  
Public Health ◽  
United States ◽  
Decision Making ◽  
The United States ◽  
School Closure ◽  
Health Interventions ◽  
Public Health Interventions ◽  
Health Crisis ◽  
The Us ◽  
Individualized Decision

Abstract Background: The widespread pandemic of novel coronavirus disease 2019 (COVID-19) poses an unprecedented global health crisis. In the United States (US), different state governments have adopted various combinations of non-pharmaceutical public health interventions (NPIs), such as non-essential business closures and gathering bans, to mitigate the epidemic from February to April, 2020. Quantitative assessment on the effectiveness of NPIs is greatly needed to assist in guiding individualized decision making for adjustment of interventions in the US and around the world. However, the impacts of these approaches remain uncertain.Methods: Based on the reported cases, the effective reproduction number (Rt) of COVID-19 epidemic for 50 states in the US was estimated. Measurements on the effectiveness of nine different NPIs were conducted by assessing risk ratios (RRs) between R t and NPIs through a generalized linear model (GLM). Results: Different NPIs were found to have led to different levels of reduction in Rt. Stay-at-home contributed approximately 51% (95% CI 46%-57%), wearing (face) masks 29% (15%-42%), gathering ban (more than 10 people) 19% (14%-24%), non-essential business closure 16% (10%-21%), declaration of emergency 13% (8%-17%), interstate travel restriction 11% (5%-16%), school closure 10% (7%-14%), initial business closure 10% (6%-14%), and gathering ban (more than 50 people) 7% (2%-11%).Conclusions: This retrospective assessment of NPIs on Rt has shown that NPIs played critical roles on epidemic control in the US in the past several months. The quantitative results could guide individualized decision making for future adjustment of NPIs in the US and other countries for COVID-19 and other similar infectious diseases.

scholarly journals Differential impact of non-pharmaceutical public health interventions on COVID-19 epidemics in the United States

2020 ◽  
Author(s):  
Xiaoshuang Liu ◽  
Xiao Xu ◽  
Guanqiao Li ◽  
Xian Xu ◽  
Yuyao Sun ◽  
...  
Keyword(s):  
Public Health ◽  
United States ◽  
Decision Making ◽  
The United States ◽  
School Closure ◽  
Health Interventions ◽  
Public Health Interventions ◽  
The Us ◽  
The Impact ◽  
Individualized Decision

Abstract The widespread pandemic of novel coronavirus disease 2019 (COVID-19) poses an unprecedented global health crisis. In the United States (US), different state governments have adopted various combinations of non-pharmaceutical public health interventions (NPIs) to mitigate the epidemic from February to April, 2020. Quantitative assessment on the effectiveness of NPIs is in great need to assist in guiding the individualized decision making for adjustment of interventions in the US and around the world. However, the impact of these approaches remain uncertain. Based on the reported cases, the effective reproduction number of COVID-19 epidemic for 50 states in the US was estimated. The measurement on the effectiveness of eight different NPIs was conducted by assessing risk ratios (RRs) between and NPIs through a generalized linear model (GLM). Different NPIs were found to have led to different levels of reduction in. Stay-at-home contributed approximately 51% (95% CI 46%-57%), gathering ban (more than 10 people) 19% (14%-24%), non-essential business closure 16% (10%-21%), declaration of emergency 13% (8%-17%), interstate travel restriction 11% (5%-16%), school closure 10% (7%-13%), initial business closure 10% (6%-14%), and gathering ban (more than 50 people) 6% (2%-11%). This retrospective assessment of NPIs on has shown that NPIs played critical roles on epidemic control in the US in the past several months. The quantitative results could guide individualized decision making for future adjustment of NPIs in the US and other countries for COVID-19 and other similar infectious diseases.

scholarly journals Differential impact of non-pharmaceutical public health interventions on COVID-19 epidemics in the United States

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xiaoshuang Liu ◽  
Xiao Xu ◽  
Guanqiao Li ◽  
Xian Xu ◽  
Yuyao Sun ◽  
...  
Keyword(s):  
Public Health ◽  
United States ◽  
Decision Making ◽  
The United States ◽  
School Closure ◽  
Health Interventions ◽  
Public Health Interventions ◽  
Health Crisis ◽  
The Us ◽  
Individualized Decision

Abstract Background The widespread pandemic of novel coronavirus disease 2019 (COVID-19) poses an unprecedented global health crisis. In the United States (US), different state governments have adopted various combinations of non-pharmaceutical public health interventions (NPIs), such as non-essential business closures and gathering bans, to mitigate the epidemic from February to April, 2020. Quantitative assessment on the effectiveness of NPIs is greatly needed to assist in guiding individualized decision making for adjustment of interventions in the US and around the world. However, the impacts of these approaches remain uncertain. Methods Based on the reported cases, the effective reproduction number (Rt) of COVID-19 epidemic for 50 states in the US was estimated. Measurements on the effectiveness of nine different NPIs were conducted by assessing risk ratios (RRs) between Rt and NPIs through a generalized linear model (GLM). Results Different NPIs were found to have led to different levels of reduction in Rt. Stay-at-home contributed approximately 51% (95% CI 46–57%), wearing (face) masks 29% (15–42%), gathering ban (more than 10 people) 19% (14–24%), non-essential business closure 16% (10–21%), declaration of emergency 13% (8–17%), interstate travel restriction 11% (5–16%), school closure 10% (7–14%), initial business closure 10% (6–14%), and gathering ban (more than 50 people) 7% (2–11%). Conclusions This retrospective assessment of NPIs on Rt has shown that NPIs played critical roles on epidemic control in the US in the past several months. The quantitative results could guide individualized decision making for future adjustment of NPIs in the US and other countries for COVID-19 and other similar infectious diseases.

scholarly journals Differential impact of non-pharmaceutical public health interventions on COVID-19 epidemics in the United States

2020 ◽  
Author(s):  
Xiaoshuang Liu ◽  
Xiao Xu ◽  
Guanqiao Li ◽  
Xian Xu ◽  
Yuyao Sun ◽  
...  
Keyword(s):  
Public Health ◽  
United States ◽  
Decision Making ◽  
The United States ◽  
School Closure ◽  
Health Interventions ◽  
Public Health Interventions ◽  
Health Crisis ◽  
The Us ◽  
Individualized Decision

Abstract Background: The widespread pandemic of novel coronavirus disease 2019 (COVID-19) poses an unprecedented global health crisis. In the United States (US), different state governments have adopted various combinations of non-pharmaceutical public health interventions (NPIs), such as non-essential business closures and gathering bans, to mitigate the epidemic from February to April, 2020. Quantitative assessment on the effectiveness of NPIs is greatly needed to assist in guiding individualized decision making for adjustment of interventions in the US and around the world. However, the impacts of these approaches remain uncertain. Methods: Based on the reported cases, the effective reproduction number (B) of COVID-19 epidemic for 50 states in the US was estimated. Measurements on the effectiveness of nine different NPIs were conducted by assessing risk ratios (RRs) between a and NPIs through a generalized linear model (GLM). Results: Different NPIs were found to have led to different levels of reduction in c. Stay-at-home contributed approximately 51% (95% CI 46%-57%), wearing (face) masks 29% (15%-42%), gathering ban (more than 10 people) 19% (14%-24%), non-essential business closure 16% (10%-21%), declaration of emergency 13% (8%-17%), interstate travel restriction 11% (5%-16%), school closure 10% (7%-14%), initial business closure 10% (6%-14%), and gathering ban (more than 50 people) 7% (2%-11%). Conclusions: This retrospective assessment of NPIs on k has shown that NPIs played critical roles on epidemic control in the US in the past several months. The quantitative results could guide individualized decision making for future adjustment of NPIs in the US and other countries for COVID-19 and other similar infectious diseases.

Recent Attitudes toward ADHD in the Broader Community: A Systematic Review

2021 ◽  
pp. 108705472110036
Author(s):  
Matthew Bisset ◽  
Leanne Winter ◽  
Christel M. Middeldorp ◽  
David Coghill ◽  
Nardia Zendarski ◽  
...  
Keyword(s):  
Public Health ◽  
Mental Health ◽  
Social Distance ◽  
Mental Health Literacy ◽  
The United States ◽  
Health Interventions ◽  
Public Health Interventions ◽  
Negative Attitudes ◽  
Community Attitudes ◽  
Standardized Protocol

Objective: This review aimed to understand the broader community’s attitudes toward ADHD, which could facilitate public health interventions to improve outcomes for individuals with ADHD. Methods: A standardized protocol identified peer-reviewed studies focusing on attitudes of broader community samples, published from January 2014 to February 2020 (inclusive). Results: A total of 1,318 articles were screened and 10 studies were included, examining attitudes of broader community samples from Australia, Sweden, Germany, Finland, Korea, Indonesia, and the United States. Findings revealed that broader community samples displayed varying degrees of ADHD-related knowledge, negative attitudes (that ADHD is over-diagnosed; that pharmacological treatment is not acceptable; that those with ADHD are more likely to exhibit poor behavior), and a desire for maintaining social distance from individuals with ADHD. Conclusion: Findings suggest that community attitudes are generally negative toward those with ADHD. Targeted mental health literacy could provide an important avenue for improving the broader community’s attitudes toward those with ADHD.

Syphilis epidemiology and public health interventions in Western Australia from 1991 to 2009

Sexual Health ◽  
2012 ◽  
Vol 9 (3) ◽  
pp. 272 ◽  
Author(s):  
Kellie S. H. Kwan ◽  
Carolien M. Giele ◽  
Heath S. Greville ◽  
Carole A. Reeve ◽  
P. Heather Lyttle ◽  
...  
Keyword(s):  
Public Health ◽  
Western Australia ◽  
Aboriginal People ◽  
Congenital Syphilis ◽  
The United States ◽  
Health Interventions ◽  
Public Health Interventions ◽  
Sex With Men ◽  
Notification Data ◽  
The Impact

Objectives To describe the epidemiology of congenital and infectious syphilis during 1991–2009, examine the impact of public health interventions and discuss the feasibility of syphilis elimination among Aboriginal people in Western Australia (WA). Methods: WA congenital and infectious syphilis notification data in 1991–2009 and national infectious syphilis notification data in 2005–2009 were analysed by Aboriginality, region of residence, and demographic and behavioural characteristics. Syphilis public health interventions in WA from 1991–2009 were also reviewed. Results: During 1991–2009, there were six notifications of congenital syphilis (50% Aboriginal) and 1441 infectious syphilis notifications (61% Aboriginal). During 1991–2005, 88% of notifications were Aboriginal, with several outbreaks identified in remote WA. During 2006–2009, 62% of notifications were non-Aboriginal, with an outbreak in metropolitan men who have sex with men. The Aboriginal : non-Aboriginal rate ratio decreased from 173 : 1 (1991–2005) to 15 : 1 (2006–2009). Conclusions: These data demonstrate that although the epidemiology of syphilis in WA has changed over time, the infection has remained endemic among Aboriginal people in non-metropolitan areas. Given the continued public health interventions targeted at this population, the limited success in eliminating syphilis in the United States and the unique geographical and socioeconomic features of WA, the elimination of syphilis seems unlikely in this state.

scholarly journals Accurate spatiotemporal mapping of drug overdose deaths by machine learning of drug-related web-searches

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0243622
Author(s):  
David S. Campo ◽  
Joseph W. Gussler ◽  
Amanda Sue ◽  
Pavel Skums ◽  
Yury Khudyakov
Keyword(s):  
Public Health ◽  
Machine Learning ◽  
Strong Association ◽  
The United States ◽  
Health Interventions ◽  
Morbidity And Mortality ◽  
Public Health Interventions ◽  
Mortality Trends ◽  
Spatiotemporal Mapping ◽  
Increased Risk

Persons who inject drugs (PWID) are at increased risk for overdose death (ODD), infections with HIV, hepatitis B (HBV) and hepatitis C virus (HCV), and noninfectious health conditions. Spatiotemporal identification of PWID communities is essential for developing efficient and cost-effective public health interventions for reducing morbidity and mortality associated with injection-drug use (IDU). Reported ODDs are a strong indicator of the extent of IDU in different geographic regions. However, ODD quantification can take time, with delays in ODD reporting occurring due to a range of factors including death investigation and drug testing. This delayed ODD reporting may affect efficient early interventions for infectious diseases. We present a novel model, Dynamic Overdose Vulnerability Estimator (DOVE), for assessment and spatiotemporal mapping of ODDs in different U.S. jurisdictions. Using Google® Web-search volumes (i.e., the fraction of all searches that include certain words), we identified a strong association between the reported ODD rates and drug-related search terms for 2004–2017. A machine learning model (Extremely Random Forest) was developed to produce yearly ODD estimates at state and county levels, as well as monthly estimates at state level. Regarding the total number of ODDs per year, DOVE’s error was only 3.52% (Median Absolute Error, MAE) in the United States for 2005–2017. DOVE estimated 66,463 ODDs out of the reported 70,237 (94.48%) during 2017. For that year, the MAE of the individual ODD rates was 4.43%, 7.34%, and 12.75% among yearly estimates for states, yearly estimates for counties, and monthly estimates for states, respectively. These results indicate suitability of the DOVE ODD estimates for dynamic IDU assessment in most states, which may alert for possible increased morbidity and mortality associated with IDU. ODD estimates produced by DOVE offer an opportunity for a spatiotemporal ODD mapping. Timely identification of potential mortality trends among PWID might assist in developing efficient ODD prevention and HBV, HCV, and HIV infection elimination programs by targeting public health interventions to the most vulnerable PWID communities.

scholarly journals Public Health Interventions’ Effect on Hospital Use in Patients With COVID-19: Comparative Study (Preprint)

2020 ◽  
Author(s):  
Xiaofeng Wang ◽  
Rui Ren ◽  
Michael W Kattan ◽  
Lara Jehi ◽  
Zhenshun Cheng ◽  
...  
Keyword(s):  
Public Health ◽  
United States ◽  
New York ◽  
New York State ◽  
The United States ◽  
Health Interventions ◽  
Public Health Interventions ◽  
Social Distancing ◽  
Transmission Rates ◽  
Hospital Use

BACKGROUND Different states in the United States had different nonpharmaceutical public health interventions during the COVID-19 pandemic. The effects of those interventions on hospital use have not been systematically evaluated. The investigation could provide data-driven evidence to potentially improve the implementation of public health interventions in the future. OBJECTIVE We aim to study two representative areas in the United States and one area in China (New York State, Ohio State, and Hubei Province), and investigate the effects of their public health interventions by time periods according to key interventions. METHODS This observational study evaluated the numbers of infected, hospitalized, and death cases in New York and Ohio from March 16 through September 14, 2020, and Hubei from January 26 to March 31, 2020. We developed novel Bayesian generalized compartmental models. The clinical stages of COVID-19 were stratified in the models, and the effects of public health interventions were modeled through piecewise exponential functions. Time-dependent transmission rates and effective reproduction numbers were estimated. The associations of interventions and the numbers of required hospital and intensive care unit beds were studied. RESULTS The interventions of social distancing, home confinement, and wearing masks significantly decreased (in a Bayesian sense) the case incidence and reduced the demand for beds in all areas. Ohio’s transmission rates declined before the state’s “stay at home” order, which provided evidence that early intervention is important. Wearing masks was significantly associated with reducing the transmission rates after reopening, when comparing New York and Ohio. The centralized quarantine intervention in Hubei played a significant role in further preventing and controlling the disease in that area. The estimated rates that cured patients become susceptible in all areas were small (<0.0001), which indicates that they have little chance to get the infection again. CONCLUSIONS The series of public health interventions in three areas were temporally associated with the burden of COVID-19–attributed hospital use. Social distancing and the use of face masks should continue to prevent the next peak of the pandemic.

scholarly journals Spread of COVID-19 through Georgia, USA. Near-term projections and impacts of social distancing via a metapopulation model

2020 ◽  
Author(s):  
Stephen J Beckett ◽  
Marian Dominguez-Mirazo ◽  
Seolha Lee ◽  
Clio Andris ◽  
Joshua S Weitz
Keyword(s):  
Public Health ◽  
Disease Risk ◽  
State Level ◽  
Health Interventions ◽  
County Level ◽  
Public Health Interventions ◽  
Social Distancing ◽  
Viral Spread ◽  
Near Term ◽  
Premature Removal

Epidemiological forecasts of COVID-19 spread at the country and/or state level have helped shape public health interventions. However, such models leave a scale-gap between the spatial resolution of actionable information (i.e. the county or city level) and that of modeled viral spread. States and nations are not spatially homogeneous and different areas may vary in disease risk and severity. For example, COVID-19 has age-stratified risk. Similarly, ICU units, PPE and other vital equipment are not equally distributed within states. Here, we implement a county-level epidemiological framework to assess and forecast COVID-19 spread through Georgia, where 1,933 people have died from COVID-19 and 44,638 cases have been documented as of May 27, 2020. We find that county-level forecasts trained on heterogeneity due to clustered events can continue to predict epidemic spread over multi-week periods, potentially serving efforts to prepare medical resources, manage supply chains, and develop targeted public health interventions. We find that the premature removal of physical (social) distancing could lead to rapid increases in cases or the emergence of sustained plateaus of elevated fatalities.

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