Availability of published evidence on coverage, cost components, and funding support for digitalisation of infectious disease surveillance in Africa, 2003-2022: a systematic review.

BACKGROUND: The implementation of digital disease surveillance systems at national levels in Africa have been challenged by many factors. These include user applicability, utility of IT features but also stable financial support. Funding closely intertwines with implementations in terms of geographical reach, disease focus, and sustainability. However, the practice of evidence sharing on geographical and disease coverage, costs, and funding sources for improving the implementation of these systems on the continent is unclear. OBJECTIVES: To analyse the key characteristics and availability of evidence for implementing digital infectious disease surveillance systems in Africa namely their disease focus, geographical reach, cost reporting, and external funding support. METHODS: We conducted a systematic review of peer-reviewed and grey literature for the period 2003 to 2022 (PROSPERO registration number: CRD42022300849). We searched five databases (PubMed, MEDLINE over Ovid, EMBASE, Web of Science, and Google Scholar) and websites of WHO, Africa CDC, and public health institutes of African countries. We mapped the distribution of projects by country; identified reported implementation cost components; categorised the availability of data on cost components; and identified supporting funding institutions outside Africa. RESULTS: A total of 29 reports from 2,033 search results were eligible for analysis. We identified 27 projects implemented in 13 countries, across 32 sites. Of these, 24 (75%) were pilot projects with a median duration of 16 months, (IQR: 5-40). Of the 27 projects, 5 (19%) were implemented for HIV/AIDs and tuberculosis, 4 (15%) for malaria, 4 (15%) for all notifiable diseases, and 4 (15%) for One Health. We identified 17 cost components across the 29 reports. Of these, 11 (38%) reported quantified costs for start-up capital, 10 (34%) for health personnel compensation, 9 (31%) for training and capacity building, 8 (28%) for software maintenance, and 7(24%) for surveillance data transmission. Of 65 counts of external funding sources, 35 (54%) were governmental agencies, 15 (23%) foundations, and 7 (11%) UN agencies. CONCLUSIONS: The evidence on costing data for the digitalisation of surveillance and outbreak response in the published literature is sparse in quantity, limited in detail, and without a standardised reporting format. Most initial direct project costs are substantially donor dependent, short lived, and thus unsustainable.

Introduction and acceptability of the Surveillance Outbreak Response Management and Analysis System (SORMAS) during the COVID-19 pandemic in Côte d'Ivoire.

BACKGROUND: The Surveillance Outbreak Response Management and Analysis System (SORMAS) has been implemented for various infectious diseases since 2015. 2020, at the beginning of the COVID-19 pandemic, SORMAS was adapted to SARS-CoV2. METHODS: We assessed the acceptability and usability of SORMAS and accompanied its implementation in two pilot regions of Côte d'Ivoire (Abidjan 2 and Gbêkê) from July/August 2021 to March 2022. We conducted 136 semi-structured interviews to cover knowledge on COVID-19, information on conventional surveillance systems for disease monitoring including COVID-19, acceptability of SORMAS, and impact of SORMAS on epidemic preparedness and surveillance. Scores before and 6-8 months after implementation were compared. RESULTS: SORMAS was implemented in two pilot regions in Côte d'Ivoire. The conventional software for the surveillance of the COVID-19 pandemic by the company MAGPI was maintained in parallel; the additional time needs to enter and manage the data in SORMAS were the main concern. SORMAS acceptance and satisfaction scores were high after the user training, which was prior to implementation, and after 6-8 months of use. The ability of SORMAS to improve COVID-19 preparedness and early detection of cases and contacts was widely acknowledged. To keep the understanding and skills of users up-to-date, regular refresher trainings were requested. The expectation to be able to make decisions based on data produced by SORMAS was high at baseline and the perceived experience after several months of use of the software was very positive. Unfortunately, the link with the laboratories could not be established in the pilot regions, but it is an existing feature of SORMAS that many users were asking for. Following the positive experience using SORMAS for COVID-19, the pilot regions expanded its use for monitoring and management of measles, yellow fever, meningitis, and cholera. CONCLUSION: SORMAS was very well accepted by users and decision makers in the two pilot regions of Côte d'Ivoire and its ability to improve epidemic preparedness and surveillance was acknowledged. If the hurdles of maintenance (tablets, server, and maintaining user skills) are handled sustainably, it can serve as a valid tool to identify, surveil and manage future outbreaks of various infectious diseases in Côte d'Ivoire.