disease research
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2022 ◽  
Vol 72 ◽  
pp. 48-54
Jon J. Brudvig ◽  
Jill M. Weimer

2022 ◽  
Vol 9 ◽  
Adrianna Perryman ◽  
Gebremedhin Beedemariam Gebretekle ◽  
Adeteju Ogunbameru ◽  
Joanna M. Bielecki ◽  
Beate Sander

Introduction: Evidence on authorship trends of health research conducted about or in Africa shows that there is a lack of local researchers in the first and last authorship positions, with high income country collaborations taking up these positions. The differences in authorship calls into question power imbalances in global health research and who benefits from the production of new discoveries and innovations. Health studies may further go on to inform policy and clinical practice within the region having an impact on public health. This paper aims to compare the differences in authorship between COVID-19 and relevant infectious diseases in Africa.Materials and Methods: We will conduct a bibliometric analysis comparing authorship for COVID-19 research during a public health emergency with authorship for four other infectious diseases of relevance to Africa namely: Ebola, Zika Virus (ZIKV), Tuberculosis (TB) and Influenza. Our scoping review will follow the framework developed by Arksey and O'Malley and reviewed by Levac et al. We will search MEDLINE (Ovid), African Index Medicus (AIM), Eastern Mediterranean Region (IMEMR) Index Medicus, Embase (Ovid), and Web of Science (Clarivate). We will compare the different trends of disease research between the selected diseases. This study is registered with OSF registries and is licensed with the Academic Free License version 3.0. The open science registration number is 10.17605/OSF.IO/5ZPGN.

2022 ◽  
Vol 9 (1) ◽  
pp. 205395172110707
Richard Milne ◽  
Alessia Costa ◽  
Natassia Brenman

In this paper, we examine the practice and promises of digital phenotyping. We build on work on the ‘data self’ to focus on a medical domain in which the value and nature of knowledge and relations with data have been played out with particular persistence, that of Alzheimer's disease research. Drawing on research with researchers and developers, we consider the intersection of hopes and concerns related to both digital tools and Alzheimer's disease using the metaphor of the ‘data shadow’. We suggest that as a tool for engaging with the nature of the data self, the shadow is usefully able to capture both the dynamic and distorted nature of data representations, and the unease and concern associated with encounters between individuals or groups and data about them. We then consider what the data shadow ‘is’ in relation to ageing data subjects, and the nature of the representation of the individual's cognitive state and dementia risk that is produced by digital tools. Second, we consider what the data shadow ‘does’, through researchers and practitioners’ discussions of digital phenotyping practices in the dementia field as alternately empowering, enabling and threatening.

2021 ◽  
Pablo Cárdenas ◽  
Mauricio Santos-Vega

Genomics is fundamentally changing epidemiological research. However, exploring hypotheses about pathogen evolution in different epidemiological contexts poses new challenges. Models intertwining pathogen epidemiology and genomic evolution can help understand processes such as the emergence of novel pathogen genotypes with higher transmission or resistance to treatment. In this work, we present Opqua, a computational framework for flexible simulation of pathogen epidemiology and evolution. We use Opqua to study determinants of evolution across fitness valleys. We confirm that competition can limit evolution in high transmission environments and find that low transmission, host mobility, and complex pathogen life cycles facilitate reaching new adaptive peaks through population bottlenecks and decoupling selective pressures. The results show the potential of genomic epidemiological modeling as a tool in infectious disease research.

2021 ◽  
pp. 1-11
Debra S. Regier ◽  
Jennifer A. Weaver ◽  
Nancy Cheng ◽  
Mark L. Batshaw ◽  
Mary Ottolini ◽  

Rare disease clinician investigators are essential to ensure appropriate diagnosis, care, and treatment for the rapidly growing rare disease population. As these researchers are spread across many specialties, learning the unique skill set for rare disease research (RDR) can be a hurdle and may hinder progress in the field. The need for an RDR focused training program for investigators in many specialties and backgrounds was identified in a needs assessment of trainees in the NIH funded Rare Diseases Clinical Research Network. Based on this information, the Rare Disease Research Scholars Program (RDRSP) was developed. We describe the needs assessment, curriculum creation, scholar recruitment, and outcome evaluation based on four years of programmatic data (2015–2019). This one year-long RDRSP uses a blended approach that includes in-person, web-based, synchronous and asynchronous learning. We evaluated the RDRSP using quantitative and qualitative approaches. Quantitative measures included pre and post questionnaires about knowledge, self-efficacy, and intent to remain in RDR. Data were analyzed using descriptive statistics and a paired t-test. Qualitative semi-structured interviews explored the RDR scholars’ perceptions of the RDRSP; thematic analysis examined the textual data. Quantitative pre- and post-measures were statistically significant in the following areas: 1) improved knowledge content in RDR, 2) enhanced self-efficacy in clinical research, and 3) intent to remain in the field of RDR. Qualitative data analysis found the program supported the development of the scholar’s research skills as well as ‘soft-skills’. By combining training of skills unique to RDR with the more general topics of leadership, mentorship and collaboration among participants in diverse specialties, we created a program that supports the development of the next generation of rare disease clinician investigators and serves as a model for training in other niche research areas.

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