scholarly journals Applying infectious disease forecasting to public health: a path forward using influenza forecasting examples

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Chelsea S. Lutz ◽  
Mimi P. Huynh ◽  
Monica Schroeder ◽  
Sophia Anyatonwu ◽  
F. Scott Dahlgren ◽  
...  
Keyword(s):  
Public Health ◽  
Infectious Disease ◽  
State Level ◽  
The United States ◽  
Federal State ◽  
Main Body ◽  
Disease Forecasting ◽  
Public Health Decision ◽  
Health Decision ◽  
State And Local

Abstract Background Infectious disease forecasting aims to predict characteristics of both seasonal epidemics and future pandemics. Accurate and timely infectious disease forecasts could aid public health responses by informing key preparation and mitigation efforts. Main body For forecasts to be fully integrated into public health decision-making, federal, state, and local officials must understand how forecasts were made, how to interpret forecasts, and how well the forecasts have performed in the past. Since the 2013–14 influenza season, the Influenza Division at the Centers for Disease Control and Prevention (CDC) has hosted collaborative challenges to forecast the timing, intensity, and short-term trajectory of influenza-like illness in the United States. Additional efforts to advance forecasting science have included influenza initiatives focused on state-level and hospitalization forecasts, as well as other infectious diseases. Using CDC influenza forecasting challenges as an example, this paper provides an overview of infectious disease forecasting; applications of forecasting to public health; and current work to develop best practices for forecast methodology, applications, and communication. Conclusions These efforts, along with other infectious disease forecasting initiatives, can foster the continued advancement of forecasting science.

Persons with Disabilities and Public Health Ethics

2019 ◽  
pp. 218-231
Author(s):  
Monika Mitra ◽  
Linda Long-Bellil ◽  
Robyn Powell
Keyword(s):  
Public Health ◽  
Health Policy ◽  
Public Health Policy ◽  
Ethical Issues ◽  
The United States ◽  
Policy And Practice ◽  
Persons With Disabilities ◽  
Public Health Decision ◽  
Health Decision ◽  
Health Policy And Practice

This chapter draws on medical, social, and legal perspectives to identify and highlight ethical issues pertaining to the treatment, representation, and inclusion of persons with disabilities in public health policy and practice. A brief history of disability in the United States is provided as a context for examining the key ethical issues related to public health policy and practice. Conceptual frameworks and approaches to disability are then described and applied. The chapter then discusses the imperativeness of expanding access to public health programs by persons with disabilities, the need to address implicit and structural biases, and the importance of including persons with disabilities in public health decision-making.

Challenges of Designing and Implementing High Consequence Infectious Disease Response

2018 ◽  
Vol 12 (5) ◽  
pp. 563-566 ◽  
Author(s):  
Joan M. King ◽  
Chetan Tiwari ◽  
Armin R. Mikler ◽  
Martin O’Neill
Keyword(s):  
Public Health ◽  
Infectious Disease ◽  
Health Care ◽  
Spatial Configuration ◽  
The United States ◽  
Health Care Facilities ◽  
Disease Response ◽  
Response Planning ◽  
Care Facilities ◽  
State And Local

AbstractEbola is a high consequence infectious disease—a disease with the potential to cause outbreaks, epidemics, or pandemics with deadly possibilities, highly infectious, pathogenic, and virulent. Ebola’s first reported cases in the United States in September 2014 led to the development of preparedness capabilities for the mitigation of possible rapid outbreaks, with the Centers for Disease Control and Prevention (CDC) providing guidelines to assist public health officials in infectious disease response planning. These guidelines include broad goals for state and local agencies and detailed information concerning the types of resources needed at health care facilities. However, the spatial configuration of populations and existing health care facilities is neglected. An incomplete understanding of the demand landscape may result in an inefficient and inequitable allocation of resources to populations. Hence, this paper examines challenges in implementing CDC’s guidance for Ebola preparedness and mitigation in the context of geospatial allocation of health resources and discusses possible strategies for addressing such challenges. (Disaster Med Public Health Preparedness. 2018;12:563–566)

scholarly journals A collaborative multiyear, multimodel assessment of seasonal influenza forecasting in the United States

2019 ◽  
Vol 116 (8) ◽  
pp. 3146-3154 ◽  
Author(s):  
Nicholas G. Reich ◽  
Logan C. Brooks ◽  
Spencer J. Fox ◽  
Sasikiran Kandula ◽  
Craig J. McGowan ◽  
...  
Keyword(s):  
Public Health ◽  
United States ◽  
Real Time ◽  
Forecast Accuracy ◽  
The United States ◽  
Public Health Response ◽  
Public Health Decision ◽  
Health Decision Making ◽  
Health Response ◽  
Health Decision

Influenza infects an estimated 9–35 million individuals each year in the United States and is a contributing cause for between 12,000 and 56,000 deaths annually. Seasonal outbreaks of influenza are common in temperate regions of the world, with highest incidence typically occurring in colder and drier months of the year. Real-time forecasts of influenza transmission can inform public health response to outbreaks. We present the results of a multiinstitution collaborative effort to standardize the collection and evaluation of forecasting models for influenza in the United States for the 2010/2011 through 2016/2017 influenza seasons. For these seven seasons, we assembled weekly real-time forecasts of seven targets of public health interest from 22 different models. We compared forecast accuracy of each model relative to a historical baseline seasonal average. Across all regions of the United States, over half of the models showed consistently better performance than the historical baseline when forecasting incidence of influenza-like illness 1 wk, 2 wk, and 3 wk ahead of available data and when forecasting the timing and magnitude of the seasonal peak. In some regions, delays in data reporting were strongly and negatively associated with forecast accuracy. More timely reporting and an improved overall accessibility to novel and traditional data sources are needed to improve forecasting accuracy and its integration with real-time public health decision making.

After September 11: Rethinking Public Health Federalism

2002 ◽  
Vol 30 (2) ◽  
pp. 201-211 ◽  
Author(s):  
Wendy E. Parmet
Keyword(s):  
Public Health ◽  
Public Health System ◽  
The United States ◽  
Federal State ◽  
The Public ◽  
Control And Prevention ◽  
Local Officials ◽  
State And Local ◽  
Effective Public Health ◽  
Suspicious Case

In the fall of 2001, the need for a vigorous and effective public health system became more apparent than it had been for many decades. With the advent of the first widescale bioterrorist attack on the United States, the government's obligation to respond and take steps to protect the public health became self-evident.Also obvious was the need for of an effective partnership between federal, state, and local officials. Local officials are almost always on the front lines of the struggle against bioterrorism. They are the first to recognize a suspicious case and to provide testing and treatment for the affected population. At the same time, state officials are needed to support and coordinate local efforts, providing an expertise that may be lacking in many communities, especially smaller ones.But few would doubt that the federal government has a key role to play. The Centers for Disease Control and Prevention (CDC) is expected to lead the epidemiological investigation and provide expertise on how to cope with diseases that remain unfamiliar to most physicians.

scholarly journals Use of electronic health records to support a public health response to the COVID-19 pandemic in the United States: a perspective from 15 academic medical centers

2020 ◽  
Author(s):  
Subha Madhavan ◽  
Lisa Bastarache ◽  
Jeffrey S Brown ◽  
Atul J Butte ◽  
David A Dorr ◽  
...  
Keyword(s):  
Public Health ◽  
Clinical Care ◽  
Population Level ◽  
The United States ◽  
Socioeconomic Indicators ◽  
Healthcare Organizations ◽  
Public Health Response ◽  
Public Health Decision ◽  
Health Decision ◽  
Electronic Health

Abstract Our goal is to summarize the collective experience of 15 organizations in dealing with uncoordinated efforts that result in unnecessary delays in understanding, predicting, preparing for, containing, and mitigating the COVID-19 pandemic in the US. Response efforts involve the collection and analysis of data corresponding to healthcare organizations, public health departments, socioeconomic indicators, as well as additional signals collected directly from individuals and communities. We focused on electronic health record (EHR) data, since EHRs can be leveraged and scaled to improve clinical care, research, and to inform public health decision-making. We outline the current challenges in the data ecosystem and the technology infrastructure that are relevant to COVID-19, as witnessed in our 15 institutions. The infrastructure includes registries and clinical data networks to support population-level analyses. We propose a specific set of strategic next steps to increase interoperability, overall organization, and efficiencies

The Public Health Workforce and Willingness to Respond to Emergencies: A 50-State Analysis of Potentially Influential Laws

2014 ◽  
Vol 42 (1) ◽  
pp. 64-71 ◽  
Author(s):  
Lainie Rutkow ◽  
Jon S. Vernick ◽  
Maxim Gakh ◽  
Jennifer Siegel ◽  
Carol B. Thompson ◽  
...  
Keyword(s):  
Public Health ◽  
Emergency Preparedness ◽  
Critical Role ◽  
Population Level ◽  
The United States ◽  
Public Health Emergency ◽  
Public Health Workforce ◽  
Federal State ◽  
State And Local ◽  
The Government

Law plays a critical role in all stages of a public health emergency, including planning, response, and recovery. Public health emergencies introduce health concerns at the population level through, for example, the emergence of a novel infectious disease. In the United States, at the federal, state, and local levels, laws provide an infrastructure for public health emergency preparedness and response efforts: they grant the government the ability to officially declare an emergency, authorize responders to act, and facilitate interjurisdictional coordination. Law is perhaps most visible during an emergency when the president or a state's governor issues a disaster declaration establishing the temporal and geographic parameters for the response and making financial and other resources available. This legal authority has increasingly been used during the last decade.

Youth Vaping and Tobacco Use in Context in the United States: Results From the 2018 National Youth Tobacco Survey

2020 ◽  
Author(s):  
Allison M Glasser ◽  
Amanda L Johnson ◽  
Raymond S Niaura ◽  
David B Abrams ◽  
Jennifer L Pearson
Keyword(s):  
Public Health ◽  
Tobacco Use ◽  
The United States ◽  
Tobacco Product ◽  
Decision Makers ◽  
Public Health Decision ◽  
Use Patterns ◽  
Product Use ◽  
Health Decision ◽  
Low Prevalence

Abstract Introduction According to the National Youth Tobacco Survey (NYTS), youth e-cigarette use (vaping) rose between 2017 and 2018. Frequency of vaping and concurrent past 30-day (p30d) use of e-cigarettes and tobacco products have not been reported. Methods We analyzed the 2018 NYTS (N = 20 189) for vaping among all students (middle and high school; 6–12th grades; 9–19 years old) by frequency of vaping, exclusive vaping, p30d poly-product use (vaping and use of one or more tobacco product), and any past tobacco product use. Results In 2018, 81.4% of students had not used any tobacco or vapor product in the p30d, and 86.2% had not vaped in the p30d. Among all students, of the 13.8% vaped in the p30d, just over half vaped on ≤5 days (7.0%), and roughly a quarter each vaped on 6–19 days (3.2%) and on 20+ days (3.6%). Almost three quarters of p30d vapers (9.9%) reported past or concurrent tobacco use and the remainder (3.9%) were tobacco naïve. 2.8% of students were tobacco naïve and vaped on ≤5 days; 0.7% were tobacco-naïve and vaped on 6–19 days, and 0.4% were tobacco-naïve and vaped on 20+ days. Conclusions Vaping increased among US youth in 2018 over 2017. The increases are characterized by patterns of low p30d vaping frequency and high poly-product use, and a low prevalence of vaping among more frequent but tobacco naïve vapers. Implications Results underscore the importance of including the full context of use patterns. The majority of vapers (60.0%–88.9% by use frequency) were concurrent p30d or ever tobacco users. About 4% of students were tobacco naïve and vaped in the p30d, but few (0.4%) vaped regularly on 20 or more days. Reporting youth vaping data with frequency and tobacco product co-use will give public health decision-makers the best possible information to protect public health.

scholarly journals Can auxiliary indicators improve COVID-19 forecasting and hotspot prediction?

2021 ◽  
Vol 118 (51) ◽  
pp. e2111453118 ◽  
Author(s):  
Daniel J. McDonald ◽  
Jacob Bien ◽  
Alden Green ◽  
Addison J. Hu ◽  
Nat DeFries ◽  
...  
Keyword(s):  
Public Health ◽  
Predictive Accuracy ◽  
The United States ◽  
Ar Model ◽  
Search Activity ◽  
Public Health Decision ◽  
Health Decision Making ◽  
Public Health Reporting ◽  
Health Decision ◽  
Google Search

Short-term forecasts of traditional streams from public health reporting (such as cases, hospitalizations, and deaths) are a key input to public health decision-making during a pandemic. Since early 2020, our research group has worked with data partners to collect, curate, and make publicly available numerous real-time COVID-19 indicators, providing multiple views of pandemic activity in the United States. This paper studies the utility of five such indicators—derived from deidentified medical insurance claims, self-reported symptoms from online surveys, and COVID-related Google search activity—from a forecasting perspective. For each indicator, we ask whether its inclusion in an autoregressive (AR) model leads to improved predictive accuracy relative to the same model excluding it. Such an AR model, without external features, is already competitive with many top COVID-19 forecasting models in use today. Our analysis reveals that 1) inclusion of each of these five indicators improves on the overall predictive accuracy of the AR model; 2) predictive gains are in general most pronounced during times in which COVID cases are trending in “flat” or “down” directions; and 3) one indicator, based on Google searches, seems to be particularly helpful during “up” trends.

scholarly journals Determinants of workplace perceptions among federal, state, and local public health staff in the US, 2014 to 2017

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jonathon P. Leider ◽  
Katie Sellers ◽  
Jessica Owens-Young ◽  
Grace Guerrero-Ramirez ◽  
Kyle Bogaert ◽  
...  
Keyword(s):  
Public Health ◽  
Intent To Leave ◽  
The United States ◽  
Public Health Workforce ◽  
Federal State ◽  
Health Staff ◽  
Local Health ◽  
The Us ◽  
Us Government ◽  
State And Local

Abstract Background The governmental public health workforce in the United States comprises almost 300,000 staff at federal, state, and local levels. The workforce is poised for generational change, experiencing significant levels of retirement. However, intent to leave for other reasons is also substantial, and diversity is lacking in the workforce. Methods Workforce perception data from 76,000 staff from Health and Human Services (HHS) including 14,000 from the Centers for Disease Control and Prevention were analyzed across 2014 and 2017. Additionally, data from 32,000 state and local health department staff in 46 agencies reporting in both years. Estimates were constructed accounting for survey design and non-response. Results In 2017, women made up 43% of the total US government workforce and 33% of supervisors or higher, compared to 73 and 68% generally in State Health Agencies (p < .0001); and 62% vs 52% in HHS (p < .0001). Among state staff, intent to leave increased from 22 to 31% (p < .0001), but fell in 2017 from 33 to 28% for HHS (p < .0001). Correlates of intent to leave included low job satisfaction, pay satisfaction, and agency type. Federal entities saw the highest proportion respondents that indicated they would recommend their organization as a good place to work. Conclusions While intent to leave fell at federal agencies from 2014 to 2017, it increased among staff in state and local health departments. Additionally, while public health is more diverse than the US government overall, significant underrepresentation is observed in supervisory positions for staff of color, especially women.

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