SORMAS in Nigeria: Adapting a Fully Integrated Surveillance System to Track COVID-19
|The Exemplars in Global Health program would like to thank Dr. Chikwe Ihekweazu and Lois Olajide from the Nigeria Centre for Disease Control and the SORMAS teams at the Helmholtz Centre for Disease Research and the German Agency for International Cooperation for their contributions and review of this report.|
In this case study, we describe the implementation story of SORMAS in Nigeria and its adaptation during COVID-19. At end, there is an assessment of performance against the MAPS framework.
During the 2014–2015 Ebola outbreak in West Africa, researchers and public health experts from Germany and Nigeria developed a digital early warning and disease management system: the Surveillance Outbreak Response Management and Analysis System (SORMAS). Since then, SORMAS has expanded to accommodate other diseases including monkeypox, Lassa fever, and now COVID-19.1
At its core, SORMAS receives inputs from those involved in surveillance (e.g., health care workers, surveillance officers) and presents this data to users throughout the health system to drive a comprehensive strategy and response. The tool is a comprehensive, customizable, user-friendly system that enables early detection of disease outbreaks and faster mobilization of resources for containment and treatment. In addition to tracking cases, SORMAS addresses all aspects of disease response, including rumor management and validation, and is linked to Nigeria’s existing data systems and strategies (e.g., District Health Information Software 2 and the regional Integrated Disease Surveillance and Response Strategy).2 Health officials can use SORMAS to visualize chains of transmission, analyze risk factors for infection, and change policies such as travel restrictions as pandemic outbreaks evolve over time. It can also provide workflow reminders to health care workers on the dashboard and via short message service (SMS or text message).2
SORMAS is modular, so it is quick to adapt and scale. Even before Nigeria reported its first case of COVID-19 in February 2020, SORMAS had begun to deploy a new COVID-19 module that would enable Nigerian authorities to track cases and contacts.3 The 2017 monkeypox outbreak prepared the Nigeria Centre for Disease Control (NCDC) for quick deployment during the COVID-19 outbreak.4 Because SORMAS was familiar to those working in 19 states where it was already in place, the new COVID-19 module required minimal training to scale up to the rest of the states. Partners at the Helmholtz Centre for Infection Research (HZI) in Germany designed a free additional module that works on mobile phones and serves as a digital hospital health record.3
What Does SORMAS Do?
SORMAS is an integrated surveillance system using open-source software designed to detect and manage disease outbreaks. It connects each level of the health system in real time, from individual informants who might identify a suspected case within a health facility up to national and regional bodies, such as the NCDC or West African Health Organization.5 SORMAS is available via desktop, tablets, and mobile phone applications and can be used offline on mobile devices.
Different users have access to tailored forms, dashboards, and other features based on their role in disease surveillance.6 The system includes 12 user types (personas) that are linked through shared data, with a set of workflows that push data and notifications as needed. For example:
- Surveillance officers receive notifications for diseases through their dashboard and are prompted to complete forms on the case, which may require further investigation. They can also see information and visualizations of reported cases and lab samples within their area and information on events or rumors that can aid in further investigation of the outbreak.7
- Surveillance supervisors can see visualizations, such as maps with case locations, and a dashboard that summarizes the epidemiological situation in their area. They can also assign tasks to other SORMAS users, for example, to follow up with a suspected case. 8
- Contact officers interview contacts of a case and track their status over time. Within SORMAS, they can create contacts and are prompted to follow up regularly with exposed individuals. Information collected from interviews and follow-ups are entered in SORMAS. If a contact becomes a suspected case, SORMAS automatically notifies contact and surveillance supervisors.9
How SORMAS operates
SORMAS Before COVID-19
During Nigeria’s 2014 Ebola outbreak, health care workers and officials encountered several project management challenges. Some health care providers used a tool called Open Data Kit to report their case numbers to the government, while others shared case data using Microsoft Excel, SMS, or even paper forms.2,10 This resulted in delayed transmission of the disaggregated data. In addition, unsubstantiated rumors of disease outbreaks and stigmatization of the disease made it difficult to prevent those exposed to the disease from traveling and ensure they received treatment.
To meet these challenges and improve the response to the next epidemic, a consortium of Nigerian and German academics and government stakeholders worked alongside HZI to devise a way to collect and share comprehensive, reliable health data. SORMAS was the result.
|Nigeria’s health system is decentralized across 36 states and the Federal Capital Territory and 774 local governmental areas. Its burgeoning digital health environment, however, enabled some aspects of the health system to be centralized. At least 24 information and communications technology and eHealth initiatives already had nationwide coverage, and the eHealth Strategy Toolkit developed by the World Health Organization and the International Telecommunication Union assessed the overall status of the country’s enabling environment as “developing and building up.” In 2013, Nigeria adopted DHIS2 as its national health management information system, although there were initial gaps in full integration with the other tools in use. In addition, Nigeria has more than 125 million mobile phone users, so much of the population was already somewhat familiar with mobile technology.11|
To ensure joint ownership and to maximize the usability of the final product, the SORMAS development process was collaborative, drawing in stakeholders from across the country during every phase of outbreak response. System requirements were shaped by input from stakeholders with prior experience analyzing, detecting, tracing, and containing Ebola and other disease outbreaks. Working in partnership with the Nigeria Field Epidemiology and Laboratory Training Program, researchers from HZI held six design workshops focusing in particular on the experiences of frontline workers and members of the Ebola Emergency Operations Center.10,12 They also spoke to people from Rivers and Lagos (the states most impacted by the Ebola outbreak), the NCDC, and officials responsible for port security and animal control.13,14
To gather feedback and test the usability of the system, developers piloted the first version of SORMAS on mobile phones in June 2015 in Kano and Oyo states. This pilot focused on nurses and doctors who submit information to local agencies and provided functionality across four diseases—Ebola, cholera, measles, and highly pathogenic avian influenza. If a case was identified, SORMAS would notify others within the surveillance network, such as contact officers or district surveillance officers.12
In 2016, the NCDC, African Field Epidemiology Network, and HZI signed a memorandum of understanding to implement SORMAS across Nigeria.15 That same year, at the request of the primary funder German Agency for International Cooperation, SORMAS developers turned the initial SAP-based proprietary platform into an open-source system2 to align SORMAS with recognized best practices for digital global goods and ensure that future development would be less expensive.16
Timeline of key events
Adapting to a New Challenge
Early pilot tests focused on specific places and user groups, but SORMAS scaled up quickly—especially in 2017 and 2018, as Nigeria experienced outbreaks of monkeypox, Lassa fever, and meningitis. The system’s adaptable design enabled its developers to quickly build and deploy new modules for tracking Lassa fever, monkeypox, dengue fever, yellow fever, meningitis, and plague.2 Dr. Chikwe Ihekweazu, head of the NCDC, explained some of the benefits of deploying this multimodal version of SORMAS:
|Dealing with one outbreak can be difficult. Dealing with four concurrent outbreaks in a large country such as Nigeria presents far greater challenges. The use of SORMAS during 2017–2018 enabled us to adopt a more coordinated approach to data collection, analysis, and presentation for decision making across all four diseases, reducing the need for multiple approaches in the context of limited resources.2|
The new modules increased the utility of SORMAS and helped boost support for its expansion throughout Nigeria. At the beginning of the COVID-19 pandemic, not every Nigerian state had access to SORMAS. It was more common in larger, more urban states such as Lagos and Kano. (Likewise, COVID-19 testing response and availability varied widely across the country’s decentralized health system.) Even before the World Health Organization declared COVID-19 a public health emergency of international concern at the end of January 2020, HZI had developed a COVID-19 module for SORMAS, and the pandemic further accelerated the scaling of the system across the country. By the end of 2020, SORMAS covered all 260 million people in Nigeria.
Nigeria’s rollout of SORMAS by state
Scaling up to the national level allowed Nigeria to publish daily situation reports and collect uniform data from states.4 (This data is fully owned by the government and stored on government-rented servers.) SORMAS is aligned with the electronic Infectious Disease Surveillance and Response system and Epi Info to allow public health experts at the World Health Organization and West African Health Organization to easily compile data at a regional level, and it enables compliance with the International Health Regulations.2
Technical and organizational interoperability of SORMAS
The Path to Scale and Sustainability
SORMAS has streamlined and expedited Nigeria’s response to COVID-19. Without it, health care workers would have a greater reliance on paper forms and multiple disconnected tools, causing delays in information reporting and larger gaps in data. The system has also supported contact tracing efforts by reducing friction from paper forms and by linking the tracing tools to the case database.
Despite the quick expansion, there have been some bumps in the road. For example, although SORMAS is now widely used in Nigeria, financing for its long-term survival has not yet been established. The main developer, HZI, subsidizes the development costs of the system and associated trainings but is funded by the German government through the German Agency for International Cooperation with support from various donors including the European Union, the Bill & Melinda Gates Foundation, and the US Centers for Disease Control and Prevention.17 Through the NCDC, the government of Nigeria has begun to commit funding for SORMAS use in the annual budget. Although this donor-supported model is working currently, especially with revived global focus on surveillance for COVID-19 response, the best practice is to incorporate the bulk of the costs into regular government budgeting, encouraging local ownership of the system and increasing the predictability of funding levels.18
Although SORMAS was designed with usability in mind, its recent expansion has resulted in approximately 1,000 first-time users to the system, without adequate time and resources to get the usual training that ensures a high-quality data feed. As a result, health administrators sometimes struggle to get essential data in real time. The NCDC has continued to train more state-level staff on using SORMAS, and has deployed officials to support states, which is supplemented by partner support staff.
Other countries have also implemented SORMAS as the COVID-19 pandemic stretches on, despite the bumps experienced with national scale-up of the pilot system in Nigeria. The second SORMAS pilot was launched in Ghana, which also rolled out the system nationwide within the first months of the pandemic.16 With support from HZI, Fiji was able to implement SORMAS in all jurisdictions within four weeks—before the first COVID-19 cases appeared. High-income countries including France, Switzerland, and Germany have also adopted the system. This new higher-income user context has partially shifted the development approach to include more up-front investment, especially related to novel service and server technology, federated data management approaches, complex interfaces, high-end data protection, and data safety requirements. These developments were previously on HZI’s road map, but the pressure to scale up during the pandemic has vastly accelerated development and implementation efforts—what would have typically taken 3 years was made available within 9 months. HZI expects these changes to benefit users in countries all over the world.
Throughout the pilot and development process, the SORMAS team conducted studies of usability for hospital informants. During the initial 2015 pilot, 74 percent of users found SORMAS useful, and this proportion increased to 94 percent after further development in a 2018 pilot. Both studies also showed that over 90 percent of users would recommend use of the system. A limitation was that both pilots were conducted with small numbers of one user type.19
An additional evaluation of SORMAS was conducted during the 2017–2019 monkeypox outbreak, when the government expanded use of the system to 120 additional local government areas in 2 months to deal with four concurrent outbreaks. The evaluation found multiple benefits to using SORMAS over the previous, paper-reliant system. For example, the time from which local government areas recorded a case to when the NCDC received word decreased from 2 days with mailed-in paper forms to 2 seconds, and the average time to update a case in the system decreased from 20 minutes to 5 minutes. Additional benefits included more comprehensive data collection in SORMAS and the availability of automatically updated dashboards and visualizations like cluster diagrams.19
As of spring 2021, there has not been an evaluation of performance during the COVID-19 pandemic, although the government expanded the scale of SORMAS nationwide (a milestone planned for the end of 2021 prior to the pandemic). NCDC representatives have reported its usefulness in several ways: identifying case clusters, reducing reliance in paper forms, and providing more actionable data for real-time decision making.3
What Were the Key Drivers of Scale?
- Partnerships — Joint development and full government ownership: SORMAS was developed jointly by HZI and the Nigerian government. Because in-country stakeholders were involved in the design and implementation at each step, from ideation to piloting, developers built a surveillance system that was responsive to the country’s needs and integrated with systems that were already in place. It was also easily adaptable — when new outbreaks occurred, SORMAS grew to accommodate them. This adaptability also encouraged uptake and widespread use. The system is managed by a central NCDC team of 13 people with input from stakeholders including the World Health Organization and state officials.
- Groundwork — Designed by users and subject-matter experts: Early in the development process, the SORMAS team interviewed multiple types of potential users (e.g., frontline workers, government surveillance officers) to inform pilot testing.10 As a result, SORMAS is designed for two-way data transmission and is tailored to health care workers at all levels of the surveillance system — it accommodates 12 personas with tailored workflows and dashboards.13 Trainings include multiple use cases, and SORMAS is available in several languages, with user-translatable elements to make it more accessible.
- Operations — Investment in capacity to use the system: The SORMAS team at NCDC provides several training opportunities, including running scenarios, videos for instruction, user guides in multiple languages, and user surveys. Different trainings are in place for different users, and the training program relies on a set of “master trainers” at both national and subnational levels.2,16 The system also includes tools for evaluation and supervision: for instance, each user action is logged, so supervisors can check to see that information is being updated regularly, and they can remind others in the system to follow up or take action.1 With limited per diem funding for trainings, getting health care workers to attend is sometimes a challenge — but during COVID, training has shifted to a remote model, and countries have established hotlines for answering questions.
What Implementation and Scaling Challenges Remain?
SORMAS has achieved remarkable scale in Nigeria, but challenges remain in sustainable financing and in consistent high-quality data collection, especially with continued use of paper forms and multiple systems.
- Financial Health — Cost transparency and sustainable funding: Much of the funding for SORMAS at the initial stages came from the German government. Since 2019, however, the Nigerian government contributes increasingly to the costs using its budgetary allocation and extra budgetary funds such as the Regional Disease Surveillance Systems Enhancement and the Basic Health Care Provision Fund.2 SORMAS operating costs are difficult to quantify, and there is not a clear path to understanding them at the level needed for line-item level budgeting. Despite this, costs have reduced over time as the system scaled up to the national level in Nigeria and beyond to other countries.
- Operations — Maintaining capacity to use tools when needed: In the aftermath of the Ebola outbreak, developers cataloged several lessons, including the importance of tracking rumors and challenges related to comprehensive contact tracing. However, not all lessons learned were implemented or maintained between 2015 and the current COVID-19 pandemic. Although SORMAS expanded to accommodate more diseases and functionality, the personnel needed to support the large-scale outbreak of COVID-19 in Nigeria has not. This is not unexpected, given the need for more contact tracers and surveillance officers as more cases are detected.
- Technology & Architecture — Obtaining high-quality data from dispersed sources: During the COVID-19 pandemic, the NCDC identified issues related to data quality. Consequently, partners — including the African Field Epidemiology Network and NCDC — developed a data-quality improvement plan to first understand the source of quality-related challenges, and then correct the issues starting with usability of the system itself before moving on to improve human resource and infrastructure issues.20
Nigeria’s quick national rollout of SORMAS allowed the government to reduce its reliance on paper forms, accelerate data-reporting times, and incorporate all disease-tracking data nationwide into SORMAS’s dashboards for cluster tracking. The system has also continued to adapt to the COVID-19 response, adding a feature to notify people of negative test results that was deployed in early 2021. As a result, they are better prepared for the next disease outbreak.
Assessment of SORMAS implementation in Nigeria across the MAPS framework
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SORMAS Surveillance officer video. Daniel Tom-Aba YouTube page. Published August 2, 2018. Accessed February 25, 2021. https://www.youtube.com/watch?v=nVJ1k-84d-0&feature=emb_logo
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United Nations Foundation. Assessing the Enabling Environment for ICTs in Nigeria: A Review of Policies. Washington, DC: United Nations Foundation; 2014. Accessed January 21, 2021. health.gov.ng/doc/nigeria-Health-ICT-policy-report.pdf
Tom-Aba D, Toikkanen SE, Glöckner S, et al. User evaluation indicates high quality of the Surveillance Outbreak Response Management and Analysis System (SORMAS) after field deployment in Nigeria in 2015 and 2018. In: Hübner U, Sax U, Prokosch H-U, eds. German Medical Data Sciences: A Learning Healthcare System. Amsterdam, Netherlands: IOS Press; 2018. Accessed January 21, 2021. http://ebooks.iospress.nl/publication/50064
Adeoye O, Tom-Aba D, Ameh C, et al. Implementing Surveillance and Outbreak Response Management and Analysis System (SORMAS) for public health in West Africa- lessons learnt and future direction. Int J Trop Dis Health. 2017;22(2):1–17. http://dx.doi.org/10.9734/IJTDH/2017/31584
Perscheid C, Benzler J, Hermann C, et al. Ebola outbreak containment: real-time task and resource coordination with SORMAS. Front ICT. 2018;5. https://doi.org/10.3389/fict.2018.00007
Principles for Digital Development website. Accessed February 4, 2021. https://digitalprinciples.org/
Disease surveillance and outbreak response technology in West Africa. European Commission website. Published April 24, 2020. Accessed January 21, 2021. https://ec.europa.eu/international-partnerships/stories/disease-surveillance-and-outbreak-response-technology-west-africa_en
World Health Organization (WHO). Digital Implementation Investment Guide (DIIG): Integrating Digital Interventions into Health Programmes. Geneva, WHO; 2020. Accessed January 28, 2021. https://www.who.int/publications/i/item/9789240010567
Silenou BC, Tom-Aba D, Adeoye O, et al. Use of surveillance outbreak response management and analysis system for human monkeypox outbreak, Nigeria, 2017–2019. Emerg Infect Dis. 2020;26(2):345–349. https://doi.org/10.3201/eid2602.191139
Nigeria COVID-19 Response: AFENET and other partners develop and implement data quality improvement plan (DQIP) for Improved Quality Data Collection [Internet]. Accessed January 21, 2021. http://afenet.net/index.php/news/news/751-nigeria-covid-19-response-afenet-and-other-partners-develop-and-implement-data-quality-improvement-plan-dqip-for-improved-quality-data-collection