2021/05/25 by Ricardo Castillo-Neyra, Bhaswar Bhattacharya, Bhaswar B. Bhattacharya +15
Biochemistry, Genetics and Molecular Biology · Immunology and Microbiology · Medicine · #FOS: Biological sciences #Human-Animal Interaction Studies #Quantitative Methods (q-bio.QM) #Rabies epidemiology and control #Virology and Viral Diseases #q-bio.QM
paper · pdf · doi:10.48550/arxiv.2105.12163
21 pages, 2 tables, 5 figures
arxiv created 2021/05/25 · openalex publication_date 2021/05/25 · arxiv updated 2021/05/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The mainstay of canine rabies control is fixed point mass dog vaccination campaigns (MDVC). However, in some regions, ideal vaccination coverage in dogs is not obtained due to low participation in the MDVC. Travel distance to the vaccination sites has been identified as an important barrier to participation. We aim to increase MDVC participation by optimally placing fixed point vaccination locations to minimize walking distance to the nearest vaccination location. We quantified participation probability based on walking distance to the nearest vaccination point using a Poisson regression model. The regression was fit with survey data collected from 2016-2019. We then used a computational recursive interchange technique to solve the facility location problem to find a set of optimal placements of fixed point vaccination locations. Finally, we compared predicted participation of optimally placed vaccination sites to historical participation data from surveys collected from 2016-2019. We identified the p-median algorithm to solve the facility location problem as ideal for fixed point vaccination placement. We found a predicted increase in MDVC participation if vaccination locations are placed optimally. We also found a more even vaccination coverage with optimized vaccination sites; however, the workload in some optimized locations increased significantly. We developed a data-driven computational algorithm to combat an ongoing rabies epidemic by optimally using limited resources to maximize vaccination coverage. The main positive effects we expect if this algorithm is to be implemented would be increased overall vaccination coverage and increased spatial evenness of coverage. A potential negative effect could be the presence of long waiting lines as participation increases.