scholarly journals Adapting serosurveys for the SARS-CoV-2 vaccine era

2021 ◽  
Author(s):  
Nathan Duarte ◽  
Mercedes Yanes-Lane ◽  
Rahul K Arora ◽  
Niklas Bobrovitz ◽  
Michael Liu ◽  
...  
Keyword(s):  
Vaccine Coverage ◽  
Immune Surveillance ◽  
Population Level ◽  
Public Health Decision ◽  
Humoral Immune ◽  
Health Decision Making ◽  
Humoral Immune Responses ◽  
Crucial Component ◽  
Health Decision ◽  
Vaccine Distribution

Abstract Population-level immune surveillance, which includes monitoring exposure and assessing vaccine-induced immunity, is a crucial component of public health decision-making during a pandemic. Serosurveys estimating the prevalence of SARS-CoV-2 antibodies in the population played a key role in characterizing SARS-CoV-2 epidemiology during the early phases of the pandemic. Existing serosurveys provide infrastructure to continue immune surveillance, but must be adapted to remain relevant in the SARS-CoV-2 vaccine era. Here, we delineate how SARS-CoV-2 serosurveys should be designed to distinguish infection- and vaccine-induced humoral immune responses to efficiently monitor the evolution of the pandemic. We discuss how serosurvey results can inform vaccine distribution to improve allocation efficiency in countries with scarce vaccine supplies and help assess the need for booster doses in countries with substantial vaccine coverage.

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. 

scholarly journals Prediction of vaccine efficacy of the Delta variant

2021 ◽  
Author(s):  
Xinhua Chen ◽  
Andrew S. Azman ◽  
Wanying Lu ◽  
Ruijia Sun ◽  
Nan Zheng ◽  
...  
Keyword(s):  
Vaccine Efficacy ◽  
Protective Efficacy ◽  
Adenovirus Vector ◽  
Neutralizing Antibody ◽  
Effective Vaccine ◽  
Public Health Decision ◽  
Additional Tool ◽  
Health Decision Making ◽  
Health Decision ◽  
Antibody Titers

AbstractThe emergence of SARS-CoV-2 variants have raised concerns over the protective efficacy of the current generation of vaccines, and it remains unclear to what extent, if any, different variants impact the efficacy and effectiveness of various SARS-CoV-2 vaccines. We systematically searched for studies of SARS-CoV-2 vaccine efficacy and effectiveness, as well as neutralization data for variants, and used a previously published statistical model to predict vaccine efficacy against variants. Overall, we estimate the efficacy of mRNA-1273 and ChAdOx1 nCoV-19 against infection caused by the Delta variant to be 25-50% lower than that of prototype strains. The predicted efficacy against symptomatic illness of the mRNA vaccines BNT162b2 and mRNA-1273 are 95.1% (UI: 88.4-98.1%) and 80.8% (60.7-92.3%), respectively, which are higher than that of adenovirus-vector vaccines Ad26.COV2.S (44.8%, UI: 29.8-60.1%) and ChAdOx1 nCoV-19 (41.1%, 19.8-62.8%). Taken together, these results suggest that the development of more effective vaccine strategies against the Delta variant may be needed. Finally, the use of neutralizing antibody titers to predict efficacy against variants provides an additional tool for public health decision making, as new variants continue to emerge.

Public Health Decision Making and Risk Perception

2010 ◽  
pp. 729-750 ◽  
Author(s):  
Julie S. Downs ◽  
Wändi Bruine de Bruin ◽  
Baruch Fischhoff ◽  
Elizabeth A. Walker
Keyword(s):  
Public Health ◽  
Decision Making ◽  
Risk Perception ◽  
Public Health Decision ◽  
Health Decision Making ◽  
Health Decision

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.

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