Enhancing vaccine distribution efficiency in sri lanka's cold chain through unmanned aerial systems: a district-based approach

Background: With their high speed and low response time, unmanned aerial vehicles (UAVs) have been suggested as a solution to overcome the systematic inefficiencies in the current vaccine cold chain of Sri Lanka. The implementation of unmanned aerial systems (UASs) at the district level is recommended to maintain the end -to -end effectiveness of the program. Under the suggested distribution network, vaccines are transported directly from the Regional Medical Supplies Division (RMSD) warehouse to the respective health facilities, bypassing the Medical Officer of Health (MOH) unit warehouse. However, the use of UAVs is not appropriate in every RMSD due to the high fixed cost of a UAS. Methods: To determine an appropriate division, a suitability analysis was conducted by intersecting eight factors with their weights of importance. Suitable factors were determined using previous literature and weights of importance were calculated by an expert survey. Results: From the analysis, it was determined that the Kurunegala division is the most appropriate for UAV implementation. Therefore, Kurunegala is recommended as a starting point for the implementation of the proposed UAVinclusive delivery system in Sri Lanka to realize its potential benefits and practical implications. Furthermore, it was found that a uniform solution involving only UAVs offers greater advantages compared to a mixed solution involving both trucks and UAVs. Nonetheless, owing to limited technological expertise and resistance to change in low-income nations, it is advisable to begin with a mixed approach and gradually transition to a uniform strategy in the coming years. Conclusions: The newly developed random search algorithm for the cyclic delivery synchronization problem gives results that are close to those obtained with mixed -integer programming. The main advantage of the algorithm is the reduction in computing time, which is relevant to the utilization of this method in practice, especially for larger problems.