Federal Multi Criteria Decision Making Framework in Distribution of Anti-SARS-CoV-2 Monoclonal Antibody to Eligible High-Risk Patients as Case Study
The British University in Dubai (BUiD)
No specific treatment was available for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) when the epidemic firstly broke out. The urgent need to end this unusual situation has resulted in many attempts to deal with SARS-CoV-2. In addition to several types of vaccinations that have been created, anti-SARS-CoV-2 monoclonal antibodies (mAbs) have added a new dimension to preventative and treatment efforts. This therapy also helps prevent severe symptoms for those at a high risk. Therefore, it is a promising treatment for mild-to-moderate SARS-CoV-2 cases. However, the availability of anti-SARS-CoV-2 mAb therapy is limited and leads to two main challenges. The first is the privacy challenge of selecting eligible patients from the distribution hospital networking, which requires data sharing; the second is the prioritisation of all eligible patients amongst the distribution hospitals according to dose availability. To our knowledge, no research has combined the federated fundamental approach with multicriteria decision-making methods for the treatment of SARS-COV-2, which indicates a research gap. This thesis presents a unique sequence processing methodology that distributes anti-SARS-CoV-2 mAbs to eligible high-risk patients with SARS-CoV-2 according to medical requirements by using a novel federated decision-making distributor (FDMD). A novel FDMD of anti-SARS-CoV-2 mAbs is proposed for eligible high-risk patients. FDMD is implemented on augmented data of 49,152 cases of patients with SARS-CoV-2 with mild and moderate symptoms. For proof of concept, three hospitals with 16 patients each are enrolled. The proposed FDMD is constructed from the two sides of claim sequencing: central federated server (CFS) and local machine (LM). The CFS includes five sequential phases synchronised with the LMs, namely, the preliminary criteria setting phase that determines the high-risk criteria, calculates their weights using the newly formulated interval-valued spherical fuzzy and hesitant 2-tuple fuzzy-weighted zero-inconsistency (IVSH2-FWZIC) and allocates their values. The subsequent phases are federation, dose availability confirmation, global prioritisation of eligible patients and alerting the hospitals with the patients most eligible for receiving the anti-SARS-CoV-2 mAbs according to dose availability. The LM independently performs all local prioritisation processes without sharing patients’ data using the provided criteria settings and federated parameters from the CFS via the proposed federated TOPSIS (F-TOPSIS). The sequential processing steps are coherently performed at both sides. The results are presented as follows: (1) The proposed FDMD efficiently and independently identifies the high-risk patients who are most eligible for receiving anti-SARS-CoV-2 mAbs at each local distribution hospital. The final decision at the CFS relies on the indexed patients’ score and dose availability without sharing the patients’ data. (2) The IVSH2-FWZIC effectively weights the high-risk criteria of patients with SARS-CoV-2. (3) The local and global prioritisation ranks of the F-TOPSIS for eligible patients are subjected to a systematic ranking validated by high correlation results across nine scenarios by altering the weights of the criteria. (4) A comparative analysis of the experimental results with a prior study confirms the effectiveness of the proposed FDMD. The study of the proposed FDMD implies that it has the benefits of centrally distributing anti-SARS-CoV-2 mAbs to high-risk patients prioritised according to their eligibility and dose availability. It also simultaneously protects their privacy and offers an effective cure to prevent progression to severe SARS-CoV-2, hospitalisation or death.
federal multi criteria decision, Anti-SARS-CoV-2, respiratory syndrome, monoclonal antibodies (mAbs)