Establishment of an indicator framework for the transmission risk of cutaneous leishmaniasis in Sri Lanka based on the Delphi-entropy weight method.

内容摘要

Background Cutaneous leishmaniasis (CL) is an emerging and rapidly escalating public health threat in Sri Lanka, where a complex interplay of environmental, vector-related, biological, and socio-economic factors governs transmission risk. Despite the rising case burden, no validated, country-specific framework exists to systematically quantify and prioritize these risk determinants. This study aimed to develop and validate a multi-level indicator framework for assessing CL transmission risk in Sri Lanka using a combined Delphi-entropy weight approach. Method A three-level hierarchical indicator framework was initially constructed through a systematic literature review of CL risk factors. A total of 65 domain experts engaged in leishmaniasis surveillance, clinical management, entomology, and epidemiological research in Sri Lanka were invited to participate. Seventeen experts provided informed consent and completed the survey. Expert consensus was elicited using two iterative Delphi rounds. An authority coefficient (Cr) was calculated for each expert by integrating familiarity (Cs) and judgment basis (Ca) scores to weight responses proportionally to expertise. Entropy weights were derived from the degree of dispersion in expert responses to provide objective, data-driven significance scores. Comprehensive indicator weights were obtained by integrating Delphi and entropy weights. Results The final framework comprised four primary indicators, 11 secondary indicators, and 46 tertiary indicators. Among the primary indicators, biological factors received the highest normalized Delphi weight (0.312), followed by environmental factors (0.229), interventions (0.200), and social factors (0.188). The top-ranked secondary indicators were climatic features (0.194), sand flies (0.152), geographic features (0.105), and dogs (0.095). Among tertiary indicators, the highest comprehensive weights were assigned to regular monitoring of sand fly density (0.118), annual average rainfall (0.113), indoor residual spraying (IRS) (0.096), sand fly density (0.067), and screening patients through mobile clinics (0.057). Notably, three of the five highest-weighted tertiary indicators were directly related to sand fly surveillance and control, highlighting the primacy of vector management in CL transmission risk reduction. A critical data gap was identified: the absence of systematic, national-level sand fly density monitoring, which constrains real-time risk assessment capacity. Patient screening through mobile clinics also emerged as a crucial measure, particularly for rural communities with limited healthcare access. Conclusion:The Delphi-entropy weight framework provides a validated, evidence-based tool for prioritizing CL transmission risk factors in Sri Lanka. The findings highlight the urgent need to establish a systematic national sand fly surveillance programme, analogous to existing dengue vector monitoring systems, and to reinstate targeted IRS in endemic areas. This framework can guide resource allocation and evidence-based policy decisions for CL prevention and control in Sri Lanka and may serve as a model for similar resource-limited, endemic settings.