Updated on May 13, 2024


Created on December 6, 2022

SORMAS (Surveillance Outbreak Response Management & Analysis System)

SORMAS is a free solution to improve prevention and control of communicable diseases in resource-poor settings.

Developed By Unknown
Content Partners


Product Description

SORMAS (Surveillance Outbreak Response Management & Analysis System) is the digital solution for Mobile Health (mHealth) and e-Healthcare (eHealth) surveillance for epidemics worldwide. It covers infectious diseases from COVID-19 to Ebola and provides digital infrastructure for timely management and control measures to verify disease cases.

Target SDGs

SDG 3: Good Health and Well-Being

SDG 10: Reduced Inequalities

Target Users (Target Impact Group)


Distributors / Implementing Organizations

Vitasystems, Netzlink, Scigraphix, Crowdcode, Mirabilia, Elektro- & Datentechnik.

Manufacturing/Building Method

Open-source software created as a code by software developers.

Intellectural Property Type

Select Type

User Provision Model

By contacting the team directly for procurement; direct download for demo version.

Distributions to Date Status

In 2016, SORMAS was migrated into an open-source software application. This fulfills the objective to ensure a sustainable software product independent from IT companies but that can be used within the software community to develop the health sector goals. The following are some use cases to date: Ghana Health Services and Ghana Community Network decided to deploy SORMAS as a test pilot in a few districts in Ghana in 2019. The HZI team traveled to Ghana to help set up and train future SORMAS users. During the SARS-CoV-2-pandemic in early 2020, the team quickly implemented a COVID19 into SORMAS which lead to a wide spread use of SORMAS in France, Switzerland and Germany. Addtionally, Fiji, Nepal, Burkina Faso and Ivory Coast are planning implementation in the near future. In November the German Chancellor and regional bosses decided that SORMAS should be used by 90% of all health departments in Germany.

Design Specifications

SORMAS has been developed on VAADIN framework, JAVA EE Server Payara, PostgreSQL Database, REST-API, VAADIN web client application. SORMAS can be used on desktop computers, tablets and mobile phones, both online and offline. It offers 10 different menus, including one for cases, contacts, tasks or a dashboard. Different user roles ensure data protection of cases and contacts and the connection between different public health institutes such as hospitals, labs and surveillance officers. The following are some design specifications:

  • Detection phase - Community Informant notifies the Hospital Informant about any disease that has been detected. Similarly, Citizens Hotlines can inform the Epidemic Intelligence Officer about detection of a disease.
  • Investigate phase - The inputs from Hospital Informant, Epidemic Intelligence Officer and Port of Entry Officer flows to the Surveillance Officer who notifies his/her Surveillance Supervisor, who further enters the information into the SORMAS system. The Surveillance Officer is also supplied with information by the Laboratory Officers who get their data from Hospital Informants.
  • Control phase - Laboratory Officers and Surveillance Supervisors inform the Case Supervisor and Contact Supervisor who take necessary steps by delegating further work to Case Officer and Contact Officer respectively to control an epidemic.

Product Schematics

Technical Support

Through direct contact with manufacturer.

Replacement Components




Manufacturer Specified Performance Parameters


Vetted Performance Status

Successfully tested in 84 private and public hospitals in Nigeria. SORMAS prototype was distributed in 84 private and public health institutions in two states of Nigeria. In July 2015, data was collected and entered about cholera, measles and highly pathogenic avian influenza. In addition, a simulation of a complex Ebola outbreak was performed.



Complementary Technical Systems


Academic Research and References

Silenou, B. C., Nyirenda, J. L. Z., Zaghloul, A., Lange, B., Doerrbecker, J., Schenkel, K., & Krause, G., 2021, “Availability and Suitability of Digital Health Tools in Africa for Pandemic Control: Scoping Review and Cluster Analysis”, JMIR Public Health Surveill, 7(12), e30106. doi:10.2196/30106

Tom-Aba, D., Silenou, B. C., Doerrbecker, J., Fourie, C., Leitner, C., Wahnschaffe, M., . . . Krause, G., 2020, “The Surveillance Outbreak Response Management and Analysis System (SORMAS): Digital Health Global Goods Maturity Assessment”, JMIR Public Health Surveill, 6(2), e15860. doi:10.2196/15860

Silenou, B. C., Tom-Aba, D., Adeoye, O., Arinze, C. C., Oyiri, F., Suleman, A. K., . . . Krause, G., 2020, “Use of Surveillance Outbreak Response Management and Analysis System for Human Monkeypox Outbreak, Nigeria, 2017-2019”, Emerg Infect Dis, 26(2), 345-349. doi:10.3201/eid2602.191139

Yavlinsky A, Lule SA, Burns R et al., 2020, “Mobile-based and open-source case detection and infectious disease outbreak management systems: a review”, Wellcome Open Res 2020, 5:37

Kassim I., Arinze C., Tom-Aba D., Adeoye O., Ihekweazu C., McHugh T D., Abubakar I., Krause G., Mwakasungula S., Masanja H., and Aldridge R W., 2020, “Mobile-based and open-source infectious disease surveillance and outbreak management in Tanzania”, European Journal of Public Health, Volume 30, Issue Supplement_5, ckaa166.1347

Yinka-Ogunleye, A., Aruna, O., Dalhat, M., Ogoina, D., Krause, G., Disu, Y., . . . Team, C. D. C. M. O., 2019, “Outbreak of human monkeypox in Nigeria in 2017-18: a clinical and epidemiological report”, Lancet Infect Dis, 19(8), 872-879. doi:10.1016/S1473-3099(19)30294-4

Tom-Aba, D., Nguku, P. M., Arinze, C. C., & Krause, G., 2018, “Assessing the Concepts and Designs of 58 Mobile Apps for the Management of the 2014-2015 West Africa Ebola Outbreak: Systematic Review”, JMIR Public Health Surveill, 4(4), e68. doi:10.2196/publichealth.9015

Tom-Aba, D., Toikkanen, S. E., Glockner, S., Adeoye, O., Mall, S., Fahnrich, C., . . . Krause, G., 2018., “User Evaluation Indicates High Quality of the Surveillance Outbreak Response Management and Analysis System (SORMAS); After Field Deployment in Nigeria in 2015 and 2018”, Stud Health Technol Inform, 253, 233-237. doi:10.3233/978-1-61499-896-9-233

Toikkanen, S. E., Adeoye, O., Ameh, C., Glöckner, S., Poggensee, G., & Krause, G., 2017, “Piloting SORMAS (Surveillance Outbreak Response Management and Analysis System): Association between task execution time and user feedback”, Das Gesundheitswesen, 79(08/09), 656-804. doi:10.1055/s-0037-1605995

Fähnrich C, Denecke K, Adeoye O O, Benzler J, Claus H, Kirchner G, Mall S, Richter R, Schapranow M P, Schwarz NG, Tom-Aba D, Uflacker M, Poggensee G, Krause G., 2015, “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):pii=21071

Compliance with regulations

SORMAS adheres to international data standards (e.g. HL7 FHIR) and enhances technical and contextual interoperability with LIMS, NCDC, dhis2, eIDSR, Africa CDC, WHO etc.  Public health agency running SORMAS is in charge of data security and data protection and has to ensure compliance with national data protection and data security regulations in their respective jurisdiction. 

Evaluation methods

Direct testing in 84 public and private hospitals in Nigeria.  

Other Information

Covers acute flaccid paralysis, anthrax, COVID-19, cholera, congenital rubella, dengue fever, Ebola virus disease, guinea worm, human rabies, influenza, lassa, malaria, measles, meningitis (CSM), monkey pox, plague, poliomyelitis, unspecified VHF, yellow fever.

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