Precision, Equity, and Public Health and Epidemiology Informatics – A Scoping Review

Buckeridge, David L.

doi:10.1055/s-0040-1701989

Cited by 12 publications

(5 citation statements)

References 48 publications

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“…What we present here is a case for precision public health that uses new technologies to improve local public health efforts by generating tailored and spatially targeted interventions. Our experiences and findings advocate not only for strong agency-academic collaborations but also for improved, granular population surveillance data sources on a national scale that can be leveraged to target interventions and deliver the correct intervention to the high-risk population in a timely manner [ 21 , 22 ].…”

Section: Discussionmentioning

confidence: 99%

Evaluation of a Targeted COVID-19 Community Outreach Intervention: Case Report for Precision Public Health

De La Cerda,

Bauer,

Zhang

et al. 2023

JMIR Public Health Surveill

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Background Cameron County, a low-income south Texas-Mexico border county marked by severe health disparities, was consistently among the top counties with the highest COVID-19 mortality in Texas at the onset of the pandemic. The disparity in COVID-19 burden within Texas counties revealed the need for effective interventions to address the specific needs of local health departments and their communities. Publicly available COVID-19 surveillance data were not sufficiently timely or granular to deliver such targeted interventions. An agency-academic collaboration in Cameron used novel geographic information science methods to produce granular COVID-19 surveillance data. These data were used to strategically target an educational outreach intervention named “Boots on the Ground” (BOG) in the City of Brownsville (COB). Objective This study aimed to evaluate the impact of a spatially targeted community intervention on daily COVID-19 test counts. Methods The agency-academic collaboration between the COB and UTHealth Houston led to the creation of weekly COVID-19 epidemiological reports at the census tract level. These reports guided the selection of census tracts to deliver targeted BOG between April 21 and June 8, 2020. Recordkeeping of the targeted BOG tracts and the intervention dates, along with COVID-19 daily testing counts per census tract, provided data for intervention evaluation. An interrupted time series design was used to evaluate the impact on COVID-19 test counts 2 weeks before and after targeted BOG. A piecewise Poisson regression analysis was used to quantify the slope (sustained) and intercept (immediate) change between pre- and post-BOG COVID-19 daily test count trends. Additional analysis of COB tracts that did not receive targeted BOG was conducted for comparison purposes. Results During the intervention period, 18 of the 48 COB census tracts received targeted BOG. Among these, a significant change in the slope between pre- and post-BOG daily test counts was observed in 5 tracts, 80% (n=4) of which had a positive slope change. A positive slope change implied a significant increase in daily COVID-19 test counts 2 weeks after targeted BOG compared to the testing trend observed 2 weeks before intervention. In an additional analysis of the 30 census tracts that did not receive targeted BOG, significant slope changes were observed in 10 tracts, of which positive slope changes were only observed in 20% (n=2). In summary, we found that BOG-targeted tracts had mostly positive daily COVID-19 test count slope changes, whereas untargeted tracts had mostly negative daily COVID-19 test count slope changes. Conclusions Evaluation of spatially targeted community interventions is necessary to strengthen the evidence base of this important approach for local emergency preparedness. This report highlights how an academic-agency collaboration established and evaluated the impact of a real-time, targeted intervention delivering precision public health to a small community.

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Section: Discussionmentioning

confidence: 99%

Evaluation of a Targeted COVID-19 Community Outreach Intervention: Case Report for Precision Public Health

De La Cerda,

Bauer,

Zhang

et al. 2023

JMIR Public Health Surveill

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“…Precision public health is defined as the use of data and evidence to tailor interventions to the characteristics of a single population [18]. It differs from precision medicine in terms of its focus on populations and limited use of human genomics data, although this is changing as progress is made in molecular epidemiology.…”

Section: Definitionsmentioning

confidence: 99%

Dietary Oncopharmacognosy as a Crosswalk between Precision Oncology and Precision Nutrition

et al. 2023

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While diet and nutrition are modifiable risk factors for many chronic and infectious diseases, their role in cancer prevention and control remains under investigation. The lack of clarity of some diet–cancer relationships reflects the ongoing debate about the relative contribution of genetic factors, environmental exposures, and replicative errors in stem cell division as determinate drivers of cancer risk. In addition, dietary guidance has often been based upon research assuming that the effects of diet and nutrition on carcinogenesis would be uniform across populations and for various tumor types arising in a specific organ, i.e., that one size fits all. Herein, we present a paradigm for investigating precision dietary patterns that leverages the approaches that led to successful small-molecule inhibitors in cancer treatment, namely understanding the pharmacokinetics and pharmacodynamics of small molecules for targeting carcinogenic mechanisms. We challenge the scientific community to refine the paradigm presented and to conduct proof-in-concept experiments that integrate existing knowledge (drug development, natural products, and the food metabolome) with developments in artificial intelligence to design and then test dietary patterns predicted to elicit drug-like effects on target tissues for cancer prevention and control. We refer to this precision approach as dietary oncopharmacognosy and envision it as the crosswalk between the currently defined fields of precision oncology and precision nutrition with the goal of reducing cancer deaths.

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“…Addressing socioeconomic dis-parities often improves health -for example, antipoverty programs were found to reduce psychopathologies in US-based youth [7]. Tackling social and economic determinants of health, and predicting differential responses to treatments, involves annotation of social and contextual information that is generally under-reported even in public health contexts [8] and particularly in clinical data.…”

Section: Ontologies For Social and Contextual Informationmentioning

confidence: 99%

Achieving Inclusivity by Design: Social and Contextual Information in Medical Knowledge

Hastings

2022

Yearb Med Inform

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Objectives: To select, present, and summarize the most relevant papers published in 2020 and 2021 in the field of Knowledge Representation and Knowledge Management, Medical Vocabularies and Ontologies, with a particular focus on health inclusivity and bias. Methods: A broad search of the medical literature indexed in PubMed was conducted. The search terms 'ontology'/'ontologies' or 'medical knowledge management' for the dates 2020-2021 (search conducted November 26, 2021) returned 9,608 records. These were pre-screened based on a review of the titles for relevance to health inclusivity, bias, social and contextual factors, and health behaviours. Among these, 109 papers were selected for in-depth reviewing based on full text, from which 22 were selected for inclusion in this survey. Results: Selected papers were grouped into three themes, each addressing one aspect of the overall challenge for medical knowledge management. The first theme addressed the development of ontologies for social and contextual factors broadening the scope of health information. The second theme addressed the need for synthesis and translation of knowledge across historical disciplinary boundaries to address inequities and bias. The third theme encompassed a growing interest in the semantics of datasets used to train medical artificial intelligence systems and on how to ensure they are free of bias. Conclusions: Medical knowledge management and semantic resources have much to offer efforts to tackle bias and enhance health inclusivity. Tackling inequities and biases requires relevant, semantically rich data, which needs to be captured and exchanged.

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Precision, Equity, and Public Health and Epidemiology Informatics – A Scoping Review

Cited by 12 publications

References 48 publications

Evaluation of a Targeted COVID-19 Community Outreach Intervention: Case Report for Precision Public Health

Evaluation of a Targeted COVID-19 Community Outreach Intervention: Case Report for Precision Public Health

Dietary Oncopharmacognosy as a Crosswalk between Precision Oncology and Precision Nutrition

Achieving Inclusivity by Design: Social and Contextual Information in Medical Knowledge

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