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 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.

scholarly journals Can Auxiliary Indicators Improve COVID-19 Forecasting and Hotspot Prediction?

2021 ◽  
Author(s):  
Daniel J McDonald ◽  
Jacob Bien ◽  
Alden Green ◽  
Addison J Hu ◽  
Nat DeFries ◽  
...  
Keyword(s):  
Public Health ◽  
Online Survey ◽  
Web Search ◽  
Predictive Accuracy ◽  
Probabilistic Forecasting ◽  
Public Health Decision ◽  
Public Health Reporting ◽  
Health Decision ◽  
Insurance Claims Data ◽  
Survey Responses

Reliable, short-term forecasts of traditional public health reporting streams (such as cases, hospitalizations, and deaths) are a key ingredient in effective public health decision-making during a pandemic. Since April 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. This paper studies the utility of these indicators from a forecasting perspective. We focus on five indicators, derived from medical insurance claims data, web search queries, and online survey responses. For each indicator, we ask whether its inclusion in a simple model leads to improved predictive accuracy relative to a similar model excluding it. We consider both probabilistic forecasting of confirmed COVID-19 case rates and binary prediction of case "hotspots". Since the values of indicators (and case rates) are commonly revised over time, we take special care to ensure that the data provided to a forecaster is the version that would have been available at the time the forecast was made. Our analysis shows that consistent but modest gains in predictive accuracy are obtained by using these indicators, and furthermore, these gains are related to periods in which the auxiliary indicators behave as "leading indicators" of case rates.

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.

scholarly journals The NCCMT’s dynamic model for evidence-informed public health

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
E Clark ◽  
S Neil-Sztramko ◽  
M Dobbins
Keyword(s):  
Public Health ◽  
Decision Making ◽  
Research Evidence ◽  
Decision Makers ◽  
Local Data ◽  
Public Health Decision ◽  
Health Decision Making ◽  
Political Preferences ◽  
Health Decision ◽  
Structured Approach

Abstract Issue It is well accepted that public health decision makers should use the best available research evidence in their decision-making process. However, research evidence alone is insufficient to inform public health decision making. Description of the problem As new challenges to public health emerge, there can be a paucity of high quality research evidence to inform decisions on new topics. Public health decision makers must combine various sources of evidence with their public health expertise to make evidence-informed decisions. The National Collaborating Centre for Methods and Tools (NCCMT) has developed a model which combines research evidence with other critical sources of evidence that can help guide decision makers in evidence-informed decision making. Results The NCCMT's model for evidence-informed public health combines findings from research evidence with local data and context, community and political preferences and actions and evidence on available resources. The model has been widely used across Canada and worldwide, and has been integrated into many public health organizations' decision-making processes. The model is also used for teaching an evidence-informed public health approach in Masters of Public Health programs around the globe. The model provides a structured approach to integrating evidence from several critical sources into public health decision making. Use of the model helps ensure that important research, contextual and preference information is sought and incorporated. Lessons Next steps for the model include development of a tool to facilitate synthesis of evidence across all four domains. Although Indigenous knowledges are relevant for public health decision making and should be considered as part of a complete assessment the current model does not capture Indigenous knowledges. Key messages Decision making in public health requires integrating the best available evidence, including research findings, local data and context, community and political preferences and available resources. The NCCMT’s model for evidence-informed public health provides a structured approach to integrating evidence from several critical sources into public health decision making.

scholarly journals Contributions in the field of Public Health for decision-making in health

2017 ◽  
Vol 27 (2) ◽  
pp. 128 ◽  
Author(s):  
Luiz Antônio Tavares Neves
Keyword(s):  
Public Health ◽  
Decision Making ◽  
Motor Development ◽  
Growth And Development ◽  
Human Growth ◽  
Public Health Decision ◽  
Health Decision Making ◽  
Scientific World ◽  
Health Decision ◽  
Human Growth And Development

  Brazil has made a wide development and contribution in the field of Public Health. These contributions have maximized public health decision-making, which is a factor of great importance for the maintenance of health of a given population, either in the prevention of disease, as is the case of immunizations or with actions in Health Promotion, improving the quality of life of the affected population. Thus, the Journal of Human Growth and Development has contributed enormously to the dissemination of knowledge, not only in Brazil but also in the world making a major effort with its publications in English which is the preferred language of the modern scientific world. It was evidenced the importance of research in the investigation of better ways to obtain the public health of a given community, bringing discussion of themes that involve aspects of human growth and development such as nutritional aspects, sexuality, motor development, covering situations and diseases as obesity, cerebral palsy, dyslexia and violence. The Journal of Human Growth and Development has maintained the tradition of approaching the different aspects that involve clinical practice for people and for Public Health. 

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