# Economic Evaluation of Multi-Objective Schistosomiasis Control Through Systemic Causality: Theoretical Advances and Governance Implications

## TL;DR

This paper explores how to better control schistosomiasis by considering complex systems and economic factors across sectors.

## Contribution

The paper introduces a new framework for economic evaluation that integrates systemic modeling and multi-objective decision analysis for schistosomiasis control.

## Key findings

- Current economic evaluations of schistosomiasis control undervalue cross-sectoral investments like surveillance and environmental management.
- System dynamics and network models reveal rebound risks and feedback effects in schistosomiasis elimination strategies.
- Multi-criteria decision analysis is proposed to handle uncertainty and optimize long-term, cross-sectoral resource allocation.

## Abstract

Schistosomiasis elimination is increasingly constrained less by the technical efficacy of single interventions than by systemic dynamics in coupled human–animal–environment settings, including nonlinear feedback, spatial heterogeneity, and cross-sectoral govern frictions. We conducted a systematic methodological review (search date: 1 January 2026) across PubMed, Web of Science, Scopus, EconLit, and CNKI to identify studies that (i) addressed schistosomiasis control, (ii) used explicit system-based, causal, or network-oriented analytical structures, and (iii) incorporated economic evaluation with multi-domain outcomes. We synthesized modeling architectures, economic methods, and approaches to trade-offs and uncertainty, and applied an evidence-informed systemic causality framework to assess decision-analytic adequacy. The literature grouped into three related strands: transmission and system dynamics models that capture feedback processes and rebound risks; economic evaluations dominated by cost-effectiveness analyses; and cross-sectoral or surveillance-oriented decision models optimizing implementation under resource constraints. Across strands, elimination-stage investments such as surveillance, environmental management, and coordination exhibit strong externalities and quasi-public-good properties that are systematically undervalued in single-sector, single-metric frameworks. We argue that decision-relevant evaluation should be reframed as a multi-objective resource allocation problem that integrates systemic modeling with economic valuation, explicitly addresses uncertainty, and applies multi-criteria decision analysis to support long-horizon, cross-sectoral decision-making.