Modeling the synergistic interplay between malaria dynamics and economic growth

Calistus N Ngonghala; Hope Enright; Olivia Prosper; Ruijun Zhao

doi:10.1016/j.mbs.2024.109189

Modeling the synergistic interplay between malaria dynamics and economic growth

Math Biosci. 2024 Apr 3:372:109189. doi: 10.1016/j.mbs.2024.109189. Online ahead of print.

Authors

Calistus N Ngonghala¹, Hope Enright², Olivia Prosper³, Ruijun Zhao²

Affiliations

¹ Department of Mathematics, University of Florida, Gainesville, FL 32611, USA; Emerging Pathogens Institute, University of Florida, Gainesville, FL 32610, USA. Electronic address: calistusnn@ufl.edu.
² Department of Mathematics and Statistics, Minnesota State University, Mankato, MN 56001, USA.
³ Department of Mathematics, University of Tennessee, Knoxville, TN 37916, USA.

PMID: 38580079
DOI: 10.1016/j.mbs.2024.109189

Abstract

The mosquito-borne disease (malaria) imposes significant challenges on human health, healthcare systems, and economic growth/productivity in many countries. This study develops and analyzes a model to understand the interplay between malaria dynamics, economic growth, and transient events. It uncovers varied effects of malaria and economic parameters on model outcomes, highlighting the interdependence of the reproduction number (R₀) on both malaria and economic factors, and a reciprocal relationship where malaria diminishes economic productivity, while higher economic output is associated with reduced malaria prevalence. This emphasizes the intricate interplay between malaria dynamics and socio-economic factors. The study offers insights into malaria control and underscores the significance of optimizing external aid allocation, especially favoring an even distribution strategy, with the most significant reduction observed in an equal monthly distribution strategy compared to longer distribution intervals. Furthermore, the study shows that controlling malaria in high mosquito biting areas with limited aid, low technology, inadequate treatment, or low economic investment is challenging. The model exhibits a backward bifurcation implying that sustainability of control and mitigation measures is essential even when R₀ is slightly less than one. Additionally, there is a parameter regime for which long transients are feasible. Long transients are critical for predicting the behavior of dynamic systems and identifying factors influencing transitions; they reveal reservoirs of infection, vital for disease control. Policy recommendations for effective malaria control from the study include prioritizing sustained control measures, optimizing external aid allocation, and reducing mosquito biting.

Keywords: Backward bifurcation; Coupled malaria-economic growth model; External aid allocation; Long transients; Per capita capital; Reproduction number.