# The properties of a Leontief production technology for Health System Modeling: the Thanzi la Onse model for Malawi

**Authors:** Martin Chalkley, Sakshi Mohan, Margherita Molaro, Bingling She, Wiktoria Tafesse

arXiv: 2508.21699 · 2025-09-01

## TL;DR

This paper explores the use of Leontief technology in health system modeling, demonstrating its flexibility and suitability for analyzing healthcare production and investment returns in Malawi.

## Contribution

It introduces a Leontief-based production approach within an agent-based health model, challenging its perceived restrictiveness and showing its applicability in health system analysis.

## Key findings

- Leontief technology can be integrated into complex health models.
- The model reveals non-restrictive properties of Leontief technology in healthcare.
- The approach aids in examining returns on health system investments.

## Abstract

As health system modeling (HSM) advances to include more complete descriptions of the production of healthcare, it is important to establish a robust conceptual characterisation of the production process. For the Thanzi La Onse model in Malawi we have incorporated an approach to production that is based on a form of Leontief technology -- fixed input proportions. At first sight, this form of technology appears restrictive relative to the general conception of a production function employed in economics. In particular, the Leontief technology is associated with constant returns to scale, and level sets that are piecewise linear, both of which are highly restrictive properties. In this article we demonstrate that once incorporated into an all disease, agent-based model these properties are no longer present and the Leontief framework becomes a rich structure for describing healthcare production, and hence for examining the returns to health systems investments.

## Full text

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## Figures

15 figures with captions in the complete paper: https://tomesphere.com/paper/2508.21699/full.md

## References

7 references — full list in the complete paper: https://tomesphere.com/paper/2508.21699/full.md

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Source: https://tomesphere.com/paper/2508.21699