Person:

Ngonghala, Calistus N.

Buruli Ulcer is a devastating skin disease caused by the pathogen Mycobacterium ulcerans. Emergence and distribution of Buruli ulcer cases is clearly linked to aquatic ecosystems, but the specific route of transmission of M. ulcerans to humans remains unclear. Relying on the most detailed field data in space and time on M. ulcerans and Buruli ulcer available today, we assess the relative contribution of two potential transmission routes –environmental and water bug transmission– to the dynamics of Buruli ulcer in two endemic regions of Cameroon. The temporal dynamics of Buruli ulcer incidence are explained by estimating rates of different routes of transmission in mathematical models. Independently, we also estimate statistical models of the different transmission pathways on the spatial distribution of Buruli ulcer. The results of these two independent approaches are corroborative and suggest that environmental transmission pathways explain the temporal and spatial patterns of Buruli ulcer in our endemic areas better than the water bug transmission.

Understanding why some human populations remain persistently poor remains a significant challenge for both the social and natural sciences. The extremely poor are generally reliant on their immediate natural resource base for subsistence and suffer high rates of mortality due to parasitic and infectious diseases. Economists have developed a range of models to explain persistent poverty, often characterized as poverty traps, but these rarely account for complex biophysical processes. In this Essay, we argue that by coupling insights from ecology and economics, we can begin to model and understand the complex dynamics that underlie the generation and maintenance of poverty traps, which can then be used to inform analyses and possible intervention policies. To illustrate the utility of this approach, we present a simple coupled model of infectious diseases and economic growth, where poverty traps emerge from nonlinear relationships determined by the number of pathogens in the system. These nonlinearities are comparable to those often incorporated into poverty trap models in the economics literature, but, importantly, here the mechanism is anchored in core ecological principles. Coupled models of this sort could be usefully developed in many economically important biophysical systems—such as agriculture, fisheries, nutrition, and land use change—to serve as foundations for deeper explorations of how fundamental ecological processes influence structural poverty and economic development.