Objective: The COVID-19 pandemic presented a challenge to established seed grant funding mechanisms aimed at fostering collaboration in child health research between investigators at the University of Minnesota (UMN) and Children's Hospitals and Clinics of Minnesota (Children's MN). We created a "rapid response," small grant program to catalyze collaborations in child health COVID-19 research. In this paper, we describe the projects funded by this mechanism and metrics of their success.
Methods: Using seed funds from the UMN Clinical and Translational Science Institute, the UMN Medical School Department of Pediatrics, and the Children's Minnesota Research Institute, a rapid response request for applications (RFAs) was issued based on the stipulations that the proposal had to: 1) consist of a clear, synergistic partnership between co-PIs from the academic and community settings; and 2) that the proposal addressed an area of knowledge deficit relevant to child health engendered by the COVID-19 pandemic.
Results: Grant applications submitted in response to this RFA segregated into three categories: family fragility and disruption exacerbated by COVID-19; knowledge gaps about COVID-19 disease in children; and optimizing pediatric care in the setting of COVID-19 pandemic restrictions. A series of virtual workshops presented research results to the pediatric community. Several manuscripts and extramural funding awards underscored the success of the program.
Conclusions: A "rapid response" seed funding mechanism enabled nascent academic-community research partnerships during the COVID-19 pandemic. In the context of the rapidly evolving landscape of COVID-19, flexible seed grant programs can be useful in addressing unmet needs in pediatric health.
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http://dx.doi.org/10.1017/cts.2022.422 | DOI Listing |
Health Promot Pract
January 2025
University of Nebraska Medical Center, Omaha, NE, USA.
The meat processing industry was significantly impacted by the COVID-19 pandemic. Deemed essential, the meat processing workforce faced the risk of exposure to the SARS-CoV-2 virus. Along with other essential workforces, meat processing workers were prioritized in the national approach to receive COVID-19 vaccines by the Centers for Disease Control and Prevention Advisory Committee on Immunization Practices.
View Article and Find Full Text PDFIndian J Med Ethics
January 2025
Senior Resident, Department of Forensic Medicine and Toxicology, AIIMS Bilaspur, Himachal Pradesh 174037, INDIA.
Telemedicine technology plays a crucial role in addressing healthcare challenges, particularly in countries like India, by mitigating physician shortages, reducing patient burden and costs, and aiding in disease prevention. The term telemedicine, meaning "healing at a distance," was coined in 1970 [1]. It encompasses the use of electronic, communication, and information technologies to deliver healthcare services remotely.
View Article and Find Full Text PDFFront Child Adolesc Psychiatry
December 2022
Department of Community Medicine and Behavioral Sciences, Faculty of Medicine, Health Science Center, Kuwait University, Jabryia, Kuwait.
Background: COVID-19 is an infectious disease that was declared as a pandemic and public health emergency in late 2019 and has impacted children's mental health worldwide. This study aimed to assess the general and mental health status of children during different stages of COVID-19 pandemic, and to identify the associated factors.
Methods: A cross-sectional study conducted on children aging 3 to 12 years in Kuwait during three different stages of COVID19 pandemic (pre-total curfew, during total curfew, and post-total curfew).
Ann Transl Med
December 2024
Medical Direction, Rovereto Hospital, Provincial Agency for Social and Sanitary Services (APSS), Trento, Italy.
Sens Diagn
December 2024
Department of Bioengineering, Rice University Houston TX 77030 USA
CRISPR-Cas-based lateral flow assays (LFAs) have emerged as a promising diagnostic tool for ultrasensitive detection of nucleic acids, offering improved speed, simplicity and cost-effectiveness compared to polymerase chain reaction (PCR)-based assays. However, visual interpretation of CRISPR-Cas-based LFA test results is prone to human error, potentially leading to false-positive or false-negative outcomes when analyzing test/control lines. To address this limitation, we have developed two neural network models: one based on a fully convolutional neural network and the other on a lightweight mobile-optimized neural network for automated interpretation of CRISPR-Cas-based LFA test results.
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