scholarly journals Self-Cognizant Bionic Liquid Sensor for Pathogen Diagnosis

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
B. Fong
Keyword(s):  
Infectious Disease ◽  
Ionic Liquids ◽  
Disease Surveillance ◽  
Pathogen Detection ◽  
Rapid Diagnosis ◽  
Swine Flu ◽  
Fluid Sample ◽  
Public Areas ◽  
Liquid Sensing ◽  
Pathogen Diagnosis

As observed in the outbreaks of SARS and swine flu, as well as many other infectious diseases, the huge volume of human traffic across numerous enclosed public venues has posed immense challenges to preventing the spread of communicable diseases. There is an urgent need for effective disease surveillance management in public areas under pandemic outbreaks. The physicochemical properties associated with ionic liquids make them particularly suited for molecular communications in sensing networks where low throughput is quite adequate for pathogen detection. This paper presents a self-cognizant system for rapid diagnosis of infectious disease using a bionic sensor such that testing can be supported without collecting a fluid sample from a subject through any invasive methods. The system is implemented for testing the performance of the proposed bionic liquid sensing network.

scholarly journals Data science approaches to infectious disease surveillance

2021 ◽  
Vol 380 (2214) ◽  
Author(s):  
Qingpeng Zhang
Keyword(s):  
Public Health ◽  
Infectious Disease ◽  
Infectious Diseases ◽  
Disease Surveillance ◽  
Data Science ◽  
Swine Flu ◽  
Human Beings ◽  
Theme Issue ◽  
Infectious Disease Surveillance ◽  
Introductory Article

Novel data science approaches are needed to confront large-scale infectious disease epidemics such as COVID-19, human immunodeficiency viruses, African swine flu and Ebola. Human beings are now equipped with richer data and more advanced data analytics methodologies, many of which have become available only in the last decade. The theme issue Data Science Approaches to Infectious Diseases Surveillance reports the latest interdisciplinary research on developing novel data science methodologies to capitalize on the rich ‘big data’ of human behaviours to confront infectious diseases, with a particular focus on combating the ongoing COVID-19 pandemic. Compared to conventional public health research, articles in this issue present innovative data science approaches that were not possible without the growing human behaviour data and the recent advances in information and communications technology. This issue has 12 research papers and one review paper from a strong lineup of contributors from multiple disciplines, including data science, computer science, computational social sciences, applied maths, statistics, physics and public health. This introductory article provides a brief overview of the issue and discusses the future of this emerging field. This article is part of the theme issue ‘Data science approaches to infectious disease surveillance’.

scholarly journals Assessment of the core and support functions of the integrated disease surveillance and response system in Zanzibar, Tanzania

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Fatma Saleh ◽  
Jovin Kitau ◽  
Flemming Konradsen ◽  
Leonard E. G. Mboera ◽  
Karin L. Schiøler
Keyword(s):  
Infectious Disease ◽  
Early Detection ◽  
Disease Surveillance ◽  
Health Facilities ◽  
Outbreak Detection ◽  
World Health ◽  
Support Functions ◽  
The Core ◽  
Surveillance And Response ◽  
Facility Level

Abstract Background Disease surveillance is a cornerstone of outbreak detection and control. Evaluation of a disease surveillance system is important to ensure its performance over time. The aim of this study was to assess the performance of the core and support functions of the Zanzibar integrated disease surveillance and response (IDSR) system to determine its capacity for early detection of and response to infectious disease outbreaks. Methods This cross-sectional descriptive study involved 10 districts of Zanzibar and 45 public and private health facilities. A mixed-methods approach was used to collect data. This included document review, observations and interviews with surveillance personnel using a modified World Health Organization generic questionnaire for assessing national disease surveillance systems. Results The performance of the IDSR system in Zanzibar was suboptimal particularly with respect to early detection of epidemics. Weak laboratory capacity at all levels greatly hampered detection and confirmation of cases and outbreaks. None of the health facilities or laboratories could confirm all priority infectious diseases outlined in the Zanzibar IDSR guidelines. Data reporting was weakest at facility level, while data analysis was inadequate at all levels (facility, district and national). The performance of epidemic preparedness and response was generally unsatisfactory despite availability of rapid response teams and budget lines for epidemics in each district. The support functions (supervision, training, laboratory, communication and coordination, human resources, logistic support) were inadequate particularly at the facility level. Conclusions The IDSR system in Zanzibar is weak and inadequate for early detection and response to infectious disease epidemics. The performance of both core and support functions are hampered by several factors including inadequate human and material resources as well as lack of motivation for IDSR implementation within the healthcare delivery system. In the face of emerging epidemics, strengthening of the IDSR system, including allocation of adequate resources, should be a priority in order to safeguard human health and economic stability across the archipelago of Zanzibar.

scholarly journals The Southern African Centre for Infectious Disease Surveillance: A One Health Consortium

2013 ◽  
Vol 6 (1) ◽  
pp. 19958 ◽  
Author(s):  
Mark M. Rweyemamu ◽  
Peter Mmbuji ◽  
Esron Karimuribo ◽  
Janusz Paweska ◽  
Dominic Kambarage ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Disease Surveillance ◽  
One Health ◽  
Infectious Disease Surveillance

scholarly journals Applications of Robotics, AI, and Digital Technologies During COVID-19: A Review

2021 ◽  
pp. 1-23
Author(s):  
Zhuo Zhao ◽  
Yangmyung Ma ◽  
Adeel Mushtaq ◽  
Abdul M. Azam Rajper ◽  
Mahmoud Shehab ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Technology Adoption ◽  
Digital Technology ◽  
Digital Technologies ◽  
Rapid Diagnosis ◽  
Quick Response ◽  
Virus Spread ◽  
Future Directions ◽  
Public Areas ◽  
Potential Impact

Abstract Many countries have enacted a quick response to the unexpected COVID-19 pandemic by utilizing existing technologies. For example, robotics, artificial intelligence, and digital technology have been deployed in hospitals and public areas for maintaining social distancing, reducing person-to-person contact, enabling rapid diagnosis, tracking virus spread, and providing sanitation. In this paper, 163 news articles and scientific reports on COVID-19-related technology adoption were screened, shortlisted, categorized by application scenario, and reviewed for functionality. Technologies related to robots, artificial intelligence, and digital technology were selected from the pool of candidates, yielding a total of 50 applications for review. Each case was analyzed for its engineering characteristics and potential impact on the COVID-19 pandemic. Finally, challenges and future directions regarding the response to this pandemic and future pandemics were summarized and discussed.

Infectious disease surveillance in animal movement networks: An approach based on the friendship paradox

2015 ◽  
Vol 121 (3-4) ◽  
pp. 306-313 ◽  
Author(s):  
Marcos Amaku ◽  
José Henrique de Hildebrand Grisi-Filho ◽  
Rísia Lopes Negreiros ◽  
Ricardo Augusto Dias ◽  
Fernando Ferreira ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Disease Surveillance ◽  
Animal Movement ◽  
Infectious Disease Surveillance
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