Model development of Malaria control and elimination by community participation in the Thai-Myanmar border area, Ranong Province

Abstract

     This study aimed to develop a service model for malaria management in the Thailand-Myanmar border area of Ranong Province through community participation. Using participatory action research methodology, the study was conducted in 12 sub-districts across three districts: Mueang Ranong, Kapoe, and Kraburi in Ranong Province, with 360 participants over an 6-month period.

     The study revealed complex malaria transmission patterns in the Thailand-Myanmar border area, with an incidence rate of 183.45 per 100,000 population in Kraburi District, significantly higher than the national average. Key challenges identified included unequal access to services, delayed surveillance systems, shortage of specialized personnel, and language and cultural barriers.

     The developed service model comprised five core components: participatory surveillance and case detection system, community-based diagnosis and treatment system, integrated prevention and control system, data management and communication system, and participatory management system. Twelve malaria posts were established, and 62 malaria volunteers were trained and developed.

     Effectiveness evaluation demonstrated significant improvements across all indicator levels. Malaria incidence decreased from 183.45 to 98.76 per 100,000 population, representing a 46.18% reduction. Patient reporting time decreased from 2.85 to 1.12 days, Implementation of the 1-3-7 strategy showed remarkable improvement, with patient reporting within one day increasing from 67.40% to 94.80%.

     Community participation increased significantly, with overall scores rising from 7.19 to 10.42 points. Participants expressed high satisfaction with the development process (Mean = 4.16). Sustainability assessment six months post-project completion showed high-level results (34.01 out of 40 points), with strengths in community acceptance, volunteer system robustness, and local government support.