China
Africa
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A Way Forward
Published in Rae-Ellen W. Kavey, Allison B. Kavey, Viral Pandemics, 2020
Rae-Ellen W. Kavey, Allison B. Kavey
Participatory disease surveillance supports sharing of health information among community members, enhancing early detection of human and animal diseases while simultaneously empowering communities to take ownership and control of surveillance practices. The widening use of mobile phones in sub-Saharan Africa, where the penetration rate has reached 67%, offers the opportunity to use mobile technology solutions for real-time event reporting. The Southern African Centre for Infectious Disease Surveillance used a participatory surveillance system to enhance early detection, timely reporting, and prompt response to health events in human and animal populations at multiple sites. Community health reporters (CHRs) and facility and district officials were trained to use a mobile phone reporting app. Between 2010 and 2016, the project trained and empowered 82 frontline CHRs and almost 100 support team members in Tanzania, Zambia, Burundi, and Kenya. The health data and associated geographical coordinates collected by CHRs were submitted to a centralized server system that created a spatial distribution of disease events from the latitude and longitude coordinates projected onto the map using the World Geodetic System. Smartphone data from trained citizens has been contributing to improved community engagement and disease surveillance in both human and animal populations in East and Southern African regions since 2010.51
Role of mass gathering surveillance
Published in David L. Blazes, Sheri H. Lewis, Disease Surveillance, 2016
Participatory surveillance is rooted in crowdsourcing methods that produce information and feed back that information to society in the form of collective knowledge. With the spread of digital social networks and knowledge platforms such as wiki style and web forums, the participation of users adding information led to a very favorable ecosystem for adopting a social control model of information. Data mining on social networks could be considered a type of participatory monitoring if the content published has data relevant to health. The big difference between this and participatory surveillance is the conscious user action in wanting to join a community, reporting symptoms in several cases that will compose the epidemiological scenarios.
Progress towards precision medicine for lupus: the role of genetic biomarkers
Published in Expert Review of Precision Medicine and Drug Development, 2018
Juan-Manuel Anaya, Kelly J. Leon, Manuel Rojas, Yhojan Rodriguez, Yovana Pacheco, Yeny Acosta-Ampudia, Diana M. Monsalve, Carolina Ramirez-Santana
In the near future, national inception cohorts are expected to be created and a translational program for the control of ADs such as SLE and their comorbidity to be put into practice (Figure 5). Interdisciplinary research using epidemiology, immunology, genetics, cell biology, nanotechnology, statistics, bioinformatics, and tools for health economics will contribute to the implementation of such a program and to the discovery of new mechanisms and taxonomy of ADs. The translational model should also involve educational and training programs together with digital participatory surveillance systems in order to significantly strengthen the prevention measures and allow the sustainability of the program [214]. In summary, healthcare’s one-size-fits-all approach to treating patients will be replaced with a personalized/precision approach to medicine that focuses on individuals and the unique needs of each family member.