The development, implementation, and evaluation of an optimal model for the case detection, referral, and case management of Neglected Tropical Diseases

Abstract

Background People affected by Neglected Tropical Diseases (NTDs), specifically leprosy, Buruli ulcer (BU), yaws, and lymphatic filariasis, experience significant delays in accessing health services, often leading to catastrophic physical, psychosocial, and economic consequences. Global health actors have recognized that Sustainable Development Goal 3:3 is only achievable through an integrated inter and intra-sectoral response. This study evaluated existing case detection and referral approaches in Liberia, utilizing the findings to develop and test an Optimal Model for integrated community-based case detection, referral, and confirmation. We evaluate the efficacy of implementing the Optimal Model in improving the early diagnosis of NTDs, thus minimizing access delays and reducing disease burden. Methods We used a participatory action research approach to develop, implement, and evaluate an Optimal Model for the case detection, referral, and management of case management NTDs in Liberia. We utilized qualitative and quantitative methods throughout the cycle and implemented the model for 12 months. Results During the implementation of our optimal model, the annual number of cases detected increased compared to the previous year. Cases were detected at an earlier stage of disease progression, however; gendered dynamics in communities shape the case identification process for some individuals. Qualitative data showed increased knowledge of the transmission, signs, symptoms, and management options among community health workers (CHW). Conclusion The results provide evidence of the benefits of an integrated approach and the programmatic challenges to improve access to health services for persons affected by NTDs. The effectiveness of an integrated approach depends on a high level of collaboration, joint planning, and implementation embedded within existing health systems infrastructure.