Capacitated preventive health infrastructure planning with accessibility-based service equity

Abstract

Hard-to-access health infrastructure is likely to lead to increased morbidity and mortality. The optimal layout of health facilities is significant for disease control and prevention. This study aims to propose a method to provide equitable access to capacitated preventive health facilities, which captures the key features of the effect of congestion in a competitive choice environment. The problem is formulated as a bilevel nonlinear integer programming model. The upper level is a biobjective programming model subject to investment budget (B) constraint, and the lower level is a user equilibrium analogous model resulting from the users’ choice of facility location. An efficient and operable heuristic algorithm was designed according to the bilevel decision structure where a genetic algorithm (GA) with elite strategy is developed to solve the upper-level problem and the method of successive averages (MSA) is adopted to solve the lower-level problem. A case study is employed to validate the performance of the proposed method. The results show that the method is robust and could reach an equal service quality in a reasonable computation time. However, the sensitivity analysis indicated that the marginal benefit of the investment decreased. There is an optimal B beyond which further increments in investment would not offset the benefits. In addition, the proposed method could be beneficial for other congested public service facilities that users are free to choose from.