Data-Driven Decision Making and Proactive Citizen–Scientist Communication: A Cross-Sectional Study on COVID-19 Vaccination Adherence

Syundyukov, Emil; Mednis, Martins; Zaharenko, Linda; Pildegovica, E.; Danovska, Ieva; Kistkins, Svjatoslavs; Benis, Arriel; Pīrāgs, Valdis; Tzivian, Lilian

doi:10.3390/vaccines9121384

Cited by 3 publications

(2 citation statements)

References 32 publications

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“…During pregnancy, many dynamic changes occur to prevent adverse immune reactions to the fetus and to protect both the mother and fetus from infections, but it is still unclear how these immune responses contribute to changes in infection risk [ 5 , 6 , 7 , 8 ]. It was hypothesized that the physiological immune modulation that occurs during pregnancy might make pregnant females more susceptible to viral infections with possible, in certain circumstances, serious consequences such as embryo/fetus loss [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

The Risk of Spontaneous Abortion Does Not Increase Following First Trimester mRNA COVID-19 Vaccination

Citu

Cîtu

Gorun

et al. 2022

JCM

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Clinical trials for COVID-19 vaccines initially excluded pregnant women due to safety concerns, and when the vaccines were authorized for emergency use, they were not recommended for this population. However, observational studies discovered that pregnant women infected with COVID-19 have higher risks of negative pregnancy and delivery outcomes compared to non-pregnant women, raising the question of the risks–benefits of administering COVID-19 vaccines to pregnant women. By mid-2021, there was general consensus on the relative safety of COVID-19 vaccination during pregnancy; therefore, it is critical to investigate the safety issues related to these vaccines, considering the increasing acceptance among pregnant women. To address these concerns, we developed a research project to study the short-term effects and outcomes of COVID-19 vaccination during the first trimester of pregnancy. Our research followed an observational retrospective design for 12 months from the beginning of the vaccination campaign, and included 124 cases of spontaneous abortions and 927 ongoing pregnancies. The odds of spontaneous abortion were non-significant for both versions of the mRNA vaccine (Pfizer BNT162b2 AOR = 1.04, CI = 0.91–1.12; Moderna mRNA-1273 AOR = 1.02, CI = 0.89–1.08). Overall, our data indicated that the risk of spontaneous abortion after mRNA COVID-19 immunization during the first trimester of pregnancy is commensurate with the predicted risk in non-vaccinated pregnant women. These findings contribute to the growing body of information regarding the safety of mRNA COVID-19 vaccination during pregnancy.

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Section: Introductionmentioning

confidence: 99%

The Risk of Spontaneous Abortion Does Not Increase Following First Trimester mRNA COVID-19 Vaccination

Citu

Cîtu

Gorun

et al. 2022

JCM

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“…Such aspects of emergency management demand a continuous follow-up of humans’, animals’, and surrounding environments’ health care in a P5 medicine approach [ 85 - 88 ] that combines (1) prediction, acquiring data and building relevant models supporting emergency and disaster preparedness [ 8 ]; (2) prevention, detecting (weak) signals of abnormalities and treating them before strong deviations (eg, preventive confinement to avoid an epidemic); (3) participation, involving the handling of human, animal, or environmental issues (eg, engaging in vaccination campaigns [ 89 - 91 ]); (4) personalization, proposing the use of the adapted solutions to a detected issue (a drug-based treatment for a human or an animal or the development of a repopulation program for a hurt vegetable ecosystem); and (5) precision, delivering the right intervention at the right time (as much as possible in real time) by the right individual on the right ecosystem components to get to, for example, efficient and dedicated evacuation plans [ 92 , 93 ].…”

Section: Discussionmentioning

confidence: 99%

One Digital Health Intervention for Monitoring Human and Animal Welfare in Smart Cities: Viewpoint and Use Case

Benis¹,

Haghi²,

Deserno³

et al. 2023

JMIR Med Inform

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Smart cities and digital public health are closely related. Managing digital transformation in urbanization and living spaces is challenging. It is critical to prioritize the emotional and physical health and well-being of humans and their animals in the dynamic and ever-changing environment they share. Human-animal bonds are continuous as they live together or share urban spaces and have a mutual impact on each other’s health as well as the surrounding environment. In addition, sensors embedded in the Internet of Things are everywhere in smart cities. They monitor events and provide appropriate responses. In this regard, accident and emergency informatics (A&EI) offers tools to identify and manage overtime hazards and disruptive events. Such manifold focuses fit with One Digital Health (ODH), which aims to transform health ecosystems with digital technology by proposing a comprehensive framework to manage data and support health-oriented policies. We showed and discussed how, by developing the concept of ODH intervention, the ODH framework can support the comprehensive monitoring and analysis of daily life events of humans and animals in technologically integrated environments such as smart homes and smart cities. We developed an ODH intervention use case in which A&EI mechanisms run in the background. The ODH framework structures the related data collection and analysis to enhance the understanding of human, animal, and environment interactions and associated outcomes. The use case looks at the daily journey of Tracy, a healthy woman aged 27 years, and her dog Mego. Using medical Internet of Things, their activities are continuously monitored and analyzed to prevent or manage any kind of health-related abnormality. We reported and commented on an ODH intervention as an example of a real-life ODH implementation. We gave the reader examples of a “how-to” analysis of Tracy and Mego’s daily life activities as part of a timely implementation of the ODH framework. For each activity, relationships to the ODH dimensions were scored, and relevant technical fields were evaluated in light of the Findable, Accessible, Interoperable, and Reusable principles. This “how-to” can be used as a template for further analyses. An ODH intervention is based on Findable, Accessible, Interoperable, and Reusable data and real-time processing for global health monitoring, emergency management, and research. The data should be collected and analyzed continuously in a spatial-temporal domain to detect changes in behavior, trends, and emergencies. The information periodically gathered should serve human, animal, and environmental health interventions by providing professionals and caregivers with inputs and “how-to's” to improve health, welfare, and risk prevention at the individual and population levels. Thus, ODH complementarily combined with A&EI is meant to enhance policies and systems and modernize emergency management.

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One Digital Health Intervention for Monitoring Human and Animal Welfare in Smart Cities: Viewpoint and Use Case (Preprint)

Benis,

Haghi,

Deserno

et al. 2022

Preprint

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UNSTRUCTURED Smart cities and digital public health are closely related. Managing digital transformation in urbanization and living spaces is challenging. It is critical to prioritize the emotional and physical health and well-being of humans and their animals in the dynamic and ever-changing environment they share. Human-animal bonds are continuous as they live together or share urban spaces and have a mutual impact on each other’s health as well as the surrounding environment. In addition, sensors embedded in the Internet of Things are everywhere in smart cities. They monitor events and provide appropriate responses. In this regard, accident and emergency informatics (A&EI) offers tools to identify and manage overtime hazards and disruptive events. Such manifold focuses fit with One Digital Health (ODH), which aims to transform health ecosystems with digital technology by proposing a comprehensive framework to manage data and support health-oriented policies. We showed and discussed how, by developing the concept of ODH intervention, the ODH framework can support the comprehensive monitoring and analysis of daily life events of humans and animals in technologically integrated environments such as smart homes and smart cities. We developed an ODH intervention use case in which A&EI mechanisms run in the background. The ODH framework structures the related data collection and analysis to enhance the understanding of human, animal, and environment interactions and associated outcomes. The use case looks at the daily journey of Tracy, a healthy woman aged 27 years, and her dog Mego. Using medical Internet of Things, their activities are continuously monitored and analyzed to prevent or manage any kind of health-related abnormality. We reported and commented on an ODH intervention as an example of a real-life ODH implementation. We gave the reader examples of a “how-to” analysis of Tracy and Mego’s daily life activities as part of a timely implementation of the ODH framework. For each activity, relationships to the ODH dimensions were scored, and relevant technical fields were evaluated in light of the Findable, Accessible, Interoperable, and Reusable principles. This “how-to” can be used as a template for further analyses. An ODH intervention is based on Findable, Accessible, Interoperable, and Reusable data and real-time processing for global health monitoring, emergency management, and research. The data should be collected and analyzed continuously in a spatial-temporal domain to detect changes in behavior, trends, and emergencies. The information periodically gathered should serve human, animal, and environmental health interventions by providing professionals and caregivers with inputs and “how-to's” to improve health, welfare, and risk prevention at the individual and population levels. Thus, ODH complementarily combined with A&EI is meant to enhance policies and systems and modernize emergency management.

show abstract

Data-Driven Decision Making and Proactive Citizen–Scientist Communication: A Cross-Sectional Study on COVID-19 Vaccination Adherence

Cited by 3 publications

References 32 publications

The Risk of Spontaneous Abortion Does Not Increase Following First Trimester mRNA COVID-19 Vaccination

The Risk of Spontaneous Abortion Does Not Increase Following First Trimester mRNA COVID-19 Vaccination

One Digital Health Intervention for Monitoring Human and Animal Welfare in Smart Cities: Viewpoint and Use Case

One Digital Health Intervention for Monitoring Human and Animal Welfare in Smart Cities: Viewpoint and Use Case (Preprint)

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