Optimization-based strategic interventions for public health crises using Delphi and mathematical modeling

Global lockdowns brought about by the pandemic upset economies and created serious problems in a number of areas, most notably employment. Traditional qualitative research techniques like focus groups, community studies, and observations were rendered impractical by social distancing policies, which compelled a switch to internet platforms. To assure expert participation, preserve anonymity, and reduce biases, this study uses the Delphi technique in a fully virtual manner. Prior to their involvement, experts were made aware of the study's goals and procedures, and their formal e-consent was acquired. A scoping review that divided individual competency units into two clusters was the first step in the multi-round Delphi process. Despite regional variations and clinical prejudices, this iterative process made sure that a range of viewpoints were included and made reaching an agreement easier. A high consensus level of 99.775%, as determined by a Likert scale, backed the final choice that was made at the end of the process with few interruptions. Experts were able to analyze inputs at their convenience and contribute independently due to the asynchronous nature of online responses. A competency matrix was also created as a result of the process, which strengthened team-based decision-making. This study shows that the Delphi procedure is a useful tool for strategic intervention in public health emergencies when paired with optimization techniques.