scholarly journals Combining weather patterns and cycles of population susceptibility to forecast dengue fever epidemic years in Brazil: a dynamic, ensemble learning approach

2019 ◽  
Author(s):  
Sarah F. McGough ◽  
Cesar L. Clemente ◽  
J. Nathan Kutz ◽  
Mauricio Santillana
Keyword(s):  
Dengue Fever ◽  
Disease Outbreaks ◽  
Climatic Conditions ◽  
Mosquito Vector ◽  
Public Health Decision ◽  
Weather Patterns ◽  
Susceptibility To Infection ◽  
Dengue Outbreaks ◽  
Health Decision ◽  
Forecast Models

AbstractTransmission of dengue fever depends on a complex interplay of human, climate, and mosquito dynamics, which often change in time and space. It is well known that disease dynamics are highly influenced by a population’s susceptibility to infection and microclimates, small-area climatic conditions which create environments favorable for the breeding and survival of the mosquito vector. Here, we present a novel machine learning dengue forecasting approach, which, dynamically in time and adaptively in space, identifies local patterns in weather and population susceptibility to make epidemic predictions at the city-level in Brazil, months ahead of the occurrence of disease outbreaks. Weather-based predictions are improved when information on population susceptibility is incorporated, indicating that immunity is an important predictor neglected by most dengue forecast models. Given the generalizability of our methodology, it may prove valuable for public-health decision making aimed at mitigating the effects of seasonal dengue outbreaks in locations globally.

scholarly journals A dynamic, ensemble learning approach to forecast dengue fever epidemic years in Brazil using weather and population susceptibility cycles

2021 ◽  
Vol 18 (179) ◽  
pp. 20201006
Author(s):  
Sarah F. McGough ◽  
Leonardo Clemente ◽  
J. Nathan Kutz ◽  
Mauricio Santillana
Keyword(s):  
Dengue Fever ◽  
Disease Outbreaks ◽  
Climatic Conditions ◽  
Time And Space ◽  
Public Health Decision ◽  
Susceptibility To Infection ◽  
Dengue Outbreaks ◽  
Health Decision ◽  
Forecast Models ◽  
Local Patterns

Transmission of dengue fever depends on a complex interplay of human, climate and mosquito dynamics, which often change in time and space. It is well known that its disease dynamics are highly influenced by multiple factors including population susceptibility to infection as well as by microclimates: small-area climatic conditions which create environments favourable for the breeding and survival of mosquitoes. Here, we present a novel machine learning dengue forecasting approach, which, dynamically in time and space, identifies local patterns in weather and population susceptibility to make epidemic predictions at the city level in Brazil, months ahead of the occurrence of disease outbreaks. Weather-based predictions are improved when information on population susceptibility is incorporated, indicating that immunity is an important predictor neglected by most dengue forecast models. Given the generalizability of our methodology to any location or input data, it may prove valuable for public health decision-making aimed at mitigating the effects of seasonal dengue outbreaks in locations globally.

scholarly journals Rigorous surveillance is necessary for high confidence in end-of-outbreak declarations for Ebola and other infectious diseases

2019 ◽  
Vol 374 (1776) ◽  
pp. 20180431 ◽  
Author(s):  
Robin N. Thompson ◽  
Oliver W. Morgan ◽  
Katri Jalava
Keyword(s):  
Infectious Disease ◽  
Disease Outbreaks ◽  
Decision Makers ◽  
World Health ◽  
Theme Issue ◽  
Public Health Decision ◽  
Infectious Disease Outbreaks ◽  
Travel Restrictions ◽  
Health Decision ◽  
Health Organization

The World Health Organization considers an Ebola outbreak to have ended once 42 days have passed since the last possible exposure to a confirmed case. Benefits of a quick end-of-outbreak declaration, such as reductions in trade/travel restrictions, must be balanced against the chance of flare-ups from undetected residual cases. We show how epidemiological modelling can be used to estimate the surveillance level required for decision-makers to be confident that an outbreak is over. Results from a simple model characterizing an Ebola outbreak suggest that a surveillance sensitivity (i.e. case reporting percentage) of 79% is necessary for 95% confidence that an outbreak is over after 42 days without symptomatic cases. With weaker surveillance, unrecognized transmission may still occur: if the surveillance sensitivity is only 40%, then 62 days must be waited for 95% certainty. By quantifying the certainty in end-of-outbreak declarations, public health decision-makers can plan and communicate more effectively.This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’. This issue is linked with the earlier theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’.

scholarly journals ‘All In’: A Pragmatic Framework for COVID-19 Testing and Action on a Global Scale

2020 ◽  
Author(s):  
Syril D Pettit ◽  
Keith Jerome ◽  
David Rouquie ◽  
Susan Hester ◽  
Leah Wehmas ◽  
...  
Keyword(s):  
Public Health ◽  
Disease Outbreaks ◽  
Global Scale ◽  
Material Resource ◽  
Public Health Decision ◽  
The Public ◽  
Health Decision Making ◽  
Clinical Community ◽  
Health Decision ◽  
Broad Consensus

Current demand for SARS-CoV-2 testing is straining material resource and labor capacity around the globe. As a result, the public health and clinical community are hindered in their ability to monitor and contain the spread of COVID-19. Despite broad consensus that more testing is needed, pragmatic guidance towards realizing this objective has been limited. This paper addresses this limitation by proposing a novel and geographically agnostic framework (‘the 4Ps Framework) to guide multidisciplinary, scalable, resource-efficient, and achievable efforts towards enhanced testing capacity. The 4Ps (Prioritize, Propagate, Partition, and Provide) are described in terms of specific opportunities to enhance the volume, diversity, characterization, and implementation of SARS-CoV-2 testing to benefit public health. Coordinated deployment of the strategic and tactical recommendations described in this framework have the potential to rapidly expand available testing capacity, improve public health decision-making in response to the COVID-19 pandemic, and/or to be applied in future emergent disease outbreaks.

scholarly journals Using online data to track outbreaks and understand public responses during a pandemic: A rapid evidence review (Preprint)

2019 ◽  
Author(s):  
Dale Weston ◽  
Natasha L. Bloodworth ◽  
Richard Amlôt ◽  
G. James Rubin
Keyword(s):  
Large Scale ◽  
Disease Outbreaks ◽  
Health Behaviours ◽  
Outbreak Detection ◽  
Validity And Reliability ◽  
Online Data ◽  
Public Health Decision ◽  
Infectious Disease Outbreaks ◽  
Health Decision ◽  
Evidence Review

UNSTRUCTURED Established methods for collecting surveillance data and attitudinal or behaviour data during a pandemic are limited by issues including cost, timeliness and reliability. This paper presents the outcomes of a rapid evidence review exploring the potential utility of online data, and particularly social media data, for contributing to both outbreak detection and the assessment of influenza-related health behaviours and sentiments. Three literature reviews, including one systematised review, contributed to this rapid evidence review. The systematised review search was conducted on PubMed and Google Scholar. From an initial total of 787 papers found through the search, 54 relevant articles were identified and included in the synthesis. These papers were combined with our initial narrative reviews to form the rapid evidence review and subsequent literature synthesis. Overall, the literature suggests that online data do have a role to play in both surveillance and understanding public responses and concerns during large-scale infectious disease outbreaks. However, given the relative infancy of work in this area, more research is needed – particularly around evaluating the validity and reliability of these approaches – before complex online data can be used with confidence to inform public health decision-making.

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 High-Deductible Health Plans and Prevention

2019 ◽  
Vol 40 (1) ◽  
pp. 411-421 ◽  
Author(s):  
Olena Mazurenko ◽  
Melinda J.B. Buntin ◽  
Nir Menachemi
Keyword(s):  
Preventive Services ◽  
Current Evidence ◽  
Future Research ◽  
Health Plans ◽  
Public Health Decision ◽  
Traditional Health ◽  
Research Designs ◽  
Health Decision ◽  
The Impact ◽  
Care Costs

High-deductible health plans (HDHPs) are becoming more popular owing to their potential to curb rising health care costs. Relative to traditional health insurance plans, HDHPs involve higher out-of-pocket costs for consumers, which have been associated with lower utilization of health services. We focus specifically on the impact that HDHPs have on the use of preventive services. We critique the current evidence by discussing the benefits and drawbacks of the research designs used to examine this relationship. We also summarize the findings from the most methodologically sophisticated studies. We conclude that the balance of the evidence shows that HDHPs are reducing the use of some preventive service, especially screenings. However, it is not clear if HDHPs affect all preventive services. Additional research is needed to determine why variability in conclusions exists among studies. We describe an agenda for future research that can further inform public health decision makers on the impact of HDHPs on prevention.

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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