COvid19 Network Technology based Responsive Action

The project "COVID-19 Network Technology-based Responsive Action" (CONTRA), June 2020 - March 2022, focused on supporting public health authorities with the delivery of a COVID-19 vaccine in a country, particularly in low- and middle-income countries. The goal was to develop an intuitive web-based decision support system (DSS) to help allocate COVID-19 vaccines to different locations and groups in a country within a short time frame. To achieve its objectives, the project followed five steps: (i) stakeholder analysis and definition of the COVID-19 supply chain; (ii) identify key performance indicators (KPIs) to assess the system, (iii) mathematical modelling, (iv) analyze different realistic scenarios using the model, and (v) present the set of best-in-class allocation options to public health authorities. The result of the project can be summarized as follows. Firstly, we studied the problem in close collaboration with health authorities from Norway and Belgium. It was found that the distribution of COVID-19 vaccine in a country could be examined at central and local allocation levels. While the problem at the central level can be generalized to many contexts (high-, middle-, and low-income countries), the problem at the local level was found to be significantly context-dependent. The central problem concerns the distribution of vaccines from central warehouses to the regional storage facilities in a country after vaccines have been received (and repackaged) at the main entry points (e.g. airports). The local problem involves receiving the vaccines at regional facilities and administering them in vaccine administration points to target groups. The CONTRA project had a focus on low- and middle-income countries, but researchers on the project could only get in touch with key decision-makers mainly in high- and upper-middle-income counties for a short time. Therefore, we targeted the central allocation problem. Second, we found that public health authorities tracked the achievement of five main goals in vaccine allocation in that problem at the central level. Despite limited vaccine supply, they focused on vaccinating as quickly as possible, vaccinating as many as possible, vaccinating in line with priority and other guidelines set by the responsible coordinating body (e.g. the Institute of Public Health), equitable access and public trust in vaccination. However, the public health authorities experienced several challenges in achieving these goals: extracting doses from vials, handling changed dose intervals, deciding whether to discard a vaccine or use it, establishing computer systems for calling in patients and distributing vaccines, and not at least, to balance the need for operational staff with the need for training. Our findings support identifying ways central government can promote a harmonious, coordinated national pandemic response, while allowing for distributed improvisation. Third, CONTRA developed a new mathematical model to support public health authorities in achieving the above objectives. The model focuses on equitable access to vaccines and it can produce allocation strategies within seconds. The model seeks a "fair level of coverage", which is calculated based on the size and importance of several regions and population target groups. The results of testing the model on different COVID-19 datasets from Turkey indicated that the factors used for prioritizing regions can result in significantly different allocation decisions. We also found that the limited capacity of facilities at municipal and regional level can significantly hamper the fairness of the entire vaccination system. It is therefore understood that a system must be developed that can incorporate several potential scenarios before or after the presentation of solution alternatives to public health authorities. Fourth, the CONTRA team developed a decision support system (DSS) that incorporated our mathematical model into an online user-friendly dashboard to support vaccine allocation. Several validation meetings were held with representatives of public health authorities from different countries where the system was tested with different scenarios and datasets. The validation result revealed that deciding on vaccine allocation is indeed a complicated task, but the authorities often do not have enough time, resources and knowledge to incorporate sophisticated decision support tools. As a result, allocation decisions have been criticised. Several tests of the developed dashboard at the CONTRA project showed that the need for intelligent systems to support the vaccine allocation problem in real operations was a realistic assumption. Based on the findings above, we have identified several future research directions that can be found in the project's reports no. 1-4.