Surveillance, Outbreak Response Management and Analysis System
New emerging diseases with the potential to lead to epidemic outbreaks, such as the recent 2014/15 West African Ebola Virus Disease (EVD) outbreak or 2016 Zika virus epidemic, pose new challenges for health infrastructures requiring rapid and adequate response. Research and development of new diagnostic tools and pharmaceutical interventions can be strongly supported with the application and deployment of novel infrastructures and mHealth tools. Information and data exchange can be rapidly processed, but also significant research conclusions can be drawn with the help of these tools. SORMAS (Surveillance, Outbreak Response Management and Analysis System) is developed as an open source mHealth tool in order to meet the specific technical and user requirements of West African countries for infection control and for real time transmission of epidemiological data. Hence, the aim of this project is to improve disease detection and control of outbreaks in low resource settings. The development is based on an agile software development concept. All source files are hosted on the GitHub repository, which is also used as platform for communication and issues tracking between researchers and software engineers. The whole development process is in close cooperation with African partners (AFENET, NCDC), who will support future users of SORMAS. SORMAS covers seven prone infectious diseases: EVD, Cholera, Measles, Avian flu, Lassa fever, Cerebrospinal Meningitis (CSM), and other viral haemorrhagic fevers (VHFs) such as Rift Valley fever. Users are assigned to specific roles (Informant, Rumor Officer, Surveillance Officer, Surveillance Supervisor, Laboratory Officer, Case Officer, Case Supervisor, Contact Officer, Contact Supervisor, and users from governmental levels), which either work with a web application or a mobile app. SORMAS also has a DHIS2 interface, providing interoperability with currently used systems in the field. The information process within SORMAS is bidirectional, supporting real time communication between all users. To simplify data entry of SORMAS the data items are designed in accordance to currently used paper-based standards, to show the users already used processes and to improve data quality with real time data quality feedback. Required system sustainability and flexibility is ensured in a long term perspective through the open source approach, challenging the technological community to continuously improve SORMAS for user needs and changing situations of diseases status. With all implemented features and its iterative quality assurance for the users, SORMAS might be used as a standard tool for in the West African setting. The pilot is planned in Nigeria, October 2017.
Partners involved in this project:
- Nigeria Center for Diseases Control (NCDC)
- Nigeria Field Epidemiology & Laboratory Training Program (NFELTP), Abuja, Nigeria
- African Field Epidemiology Network (AFENET)
- Federal Ministry of Health, Nigeria
- Bernhard-Nocht-Institut für Tropenmedizin (BNIT), Hamburg
- Robert Koch-Institut (RKI), Berlin
- Federal Ministry of Education and Research (BMBF)
- Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ)
- Symeda GmbH
Adeoye O, Tom-Aba D, Ameh C, Ojo O, Ilori E, Gidado S, Waziri E, Nguku P, Mall S, Denecke K, Lamshoeft M, et al. Implementing Surveillance and Outbreak Response Management and Analysis System (SORMAS) for Public Health in West Africa- Lessons Learnt and Future Direction. International Journal of TROPICAL DISEASE & Health. 2017;22(2):1-17.
Fähnrich C, Denecke K, Adeoye OO, Benzler J, Claus H, Kirchner G, Mall S, Richter R, Schapranow MP, Schwarz N, Tom-Aba D, et al. Surveillance and Outbreak Response Management System (SORMAS) to support the control of the Ebola virus disease outbreak in West Africa. Euro Surveill. 2015;20(12).
Moyer D, Tom-Aba D, Sharma S, Krause G. Taking Digital Innovation into the Field of Infectious Diseases: The Case of SORMAS®. In: Oswald GK, M., editor. Shaping the Digital Enterprise: Springer; 2016. p. 219-36.