An Investigation of the Factors influencing the Adoption of E-Health Services: A Case for Selected Hospitals in Lagos state, Nigeria

Research has identified a need for the improvement of the health situation in Nigeria. EHealth services are expected to make healthcare service delivery quicker and easier, covering a wider range of people. This research investigates the adoption level of e-Health in Nigerian health institutions, with focus on the use of the Electronic Medical Record (EMR). The SPSS (version 16.0) software was used to measure the variables with respect to the theories proposed and their individual items. For the purpose of this research, the theories adopted include the Technology Acceptance Model (TAM), Theory of Planned Behavior (TPB) and the Innovation Diffusion Theory. Using the elements of these theories, the research model developed postulated that Perceived Ease of Use (PEU), Perceived Social Influence (PSI) and Relative Advantage (RA) of the technology are what would determine the perceived usefulness (PU) which would in turn determine the intention to use (INT) the technology. Keywords: Adoption, E-Health, Nigeria, TAM

Geospatial Artificial Intelligence (GeoAI): Applications in Health Care

GeoAI is a new emerging research area that refers to set of technologies that integrate AI technology with a diversity of GIS (Geographic Information System) techniques. The present study observed that GeoAI goes beyond current GIS expectations and into the domain of possibility in the not-too-distant future. This emerging interdisciplinary science will lead us to sustainable decisions and explore the most suitable solutions to the existing problems. GeoAI has the potential to transform current geography and geomatics programs by incorporating a GeoAI dimension into modern GIS curricula. In this review, we have studied the application GeoAI in various healthcare fields. GeoAI has the potential to revolutionize healthcare, public health, infectious disease control, disaster aid, and the achievements of Sustainable Development Goals (SDG). in healthcare, GeoAI can help with disease diagnosis, treatment planning, and resource allocation. In public health, it can aid in disease surveillance, emergency response planning, and identifying health disparities. In infectious disease control, GeoAI can help predict and track disease outbreaks and support vaccination campaigns. In disaster aid, GeoAI can provide real time data on environmental hazards and their impact on public health. In achieving Sustainable Development Goals, it can support in land use planning, urban development, and resource allocation to promote health and environmental sustainability. Overall GeoAI has the potential to transform multiple sectors and improve the well-being of populations worldwide

Data-Centric Epidemic Forecasting: A Survey

The COVID-19 pandemic has brought forth the importance of epidemic forecasting for decision makers in multiple domains, ranging from public health to the economy as a whole. While forecasting epidemic progression is frequently conceptualized as being analogous to weather forecasting, however it has some key differences and remains a non-trivial task. The spread of diseases is subject to multiple confounding factors spanning human behavior, pathogen dynamics, weather and environmental conditions. Research interest has been fueled by the increased availability of rich data sources capturing previously unobservable facets and also due to initiatives from government public health and funding agencies. This has resulted, in particular, in a spate of work on 'data-centered' solutions which have shown potential in enhancing our forecasting capabilities by leveraging non-traditional data sources as well as recent innovations in AI and machine learning. This survey delves into various data-driven methodological and practical advancements and introduces a conceptual framework to navigate through them. First, we enumerate the large number of epidemiological datasets and novel data streams that are relevant to epidemic forecasting, capturing various factors like symptomatic online surveys, retail and commerce, mobility, genomics data and more. Next, we discuss methods and modeling paradigms focusing on the recent data-driven statistical and deep-learning based methods as well as on the novel class of hybrid models that combine domain knowledge of mechanistic models with the effectiveness and flexibility of statistical approaches. We also discuss experiences and challenges that arise in real-world deployment of these forecasting systems including decision-making informed by forecasts. Finally, we highlight some challenges and open problems found across the forecasting pipeline.Comment: 67 pages, 12 figure

International Society for Disease Surveillance Conference 2011: Building the Future of Public Health Surveillance: Building the Future of Public Health Surveillance

Daniel Reidpath - ORCID: 0000-0002-8796-0420 https://orcid.org/0000-0002-8796-04204pubpub1117

Grand Celebration: 10th Anniversary of the Human Genome Project

In 1990, scientists began working together on one of the largest biological research projects ever proposed. The project proposed to sequence the three billion nucleotides in the human genome. The Human Genome Project took 13 years and was completed in April 2003, at a cost of approximately three billion dollars. It was a major scientific achievement that forever changed the understanding of our own nature. The sequencing of the human genome was in many ways a triumph for technology as much as it was for science. From the Human Genome Project, powerful technologies have been developed (e.g., microarrays and next generation sequencing) and new branches of science have emerged (e.g., functional genomics and pharmacogenomics), paving new ways for advancing genomic research and medical applications of genomics in the 21st century. The investigations have provided new tests and drug targets, as well as insights into the basis of human development and diagnosis/treatment of cancer and several mysterious humans diseases. This genomic revolution is prompting a new era in medicine, which brings both challenges and opportunities. Parallel to the promising advances over the last decade, the study of the human genome has also revealed how complicated human biology is, and how much remains to be understood. The legacy of the understanding of our genome has just begun. To celebrate the 10th anniversary of the essential completion of the Human Genome Project, in April 2013 Genes launched this Special Issue, which highlights the recent scientific breakthroughs in human genomics, with a collection of papers written by authors who are leading experts in the field

An Investigation of the Public Health Informatics Research and Practice in the Past Fifteen Years from 2000 to 2014: A Scoping Review in MEDLINE

Objective: To examine the extent and nature of existing Public Health Informatics (PHI) studies in the past 15 years on MEDLINE. Methods: This thesis adopted the scientific scoping review methodology recommended by Arksey and O’Malley in 2005. It proceeded with the five main stages, which were: Stage I - identifying the research question; Stage II - identifying relevant studies; Stage III - study selection; Stage IV - charting the data; and Stage V - collating, summarizing, and reporting the results. Each methodological stage was carried out with the joint collaboration with the academic supervisor and a final result and conclusion were set forth. Results: The results of this study captured a total number of 486 articles in MEDLINE focused in PHI. Out of them, a majority belonged to the USA followed by the UK, Australia and Canada. Only about one fifth of the articles were from the rest of the world. Further, About 60% of the articles represented infectious disease monitoring, outbreak detection, and bio-terrorism surveillance. Furthermore, about 10% belonged to chronic disease monitoring; whereas public health policy system and research represented 40% of the total articles. The most frequently used information technology were electronic registry, website, and GIS. In contrast, mass media and mobile phones were among the least used technologies. Conclusion: Despite multiple research and discussions conducted in the past 15 years (starting from 2000), the PHI system requires further improvements in the application of modern PHT such as wireless devices, wearable devices, remote sensors, remote/ cloud computing etc. on various domains of PH, which were scarcely discussed or used in the available literature