Hysteresis in Simulations of Malaria Transmission

Title Hysteresis in Simulations of Malaria Transmission
Publication Type Manuscript
Year of Publication 2016
Authors Yamana, T. K., Qiu, X. & Eltahir, E. A. B.
Editor Graham C. Sander
Journal Advances in Water Resources
Start Page 1-7
Date Published 6 October 2016
Keywords Malaria; Hysteresis, Initial conditions, Immunity, Environmental drivers

https://www.sciencedirect.com/science/article/pii/S030917081630519X?via%3DihubMalaria transmission is a complex system and in many parts of the world is closely related to climate conditions. However, studies on environmental determinants of malaria generally consider only concurrent climate conditions and ignore the historical or initial conditions of the system. Here, we demonstrate the concept of hysteresis in malaria transmission, defined as non-uniqueness of the relationship between malaria prevalence and concurrent climate conditions. We show the dependence of simulated malaria transmission on initial prevalence and the initial level of human immunity in the population. Using realistic time series of environmental variables, we quantify the effect of hysteresis in a modeled population. In a set of numerical experiments using HYDREMATS, a field-tested mechanistic model of malaria transmission, the simulated maximum malaria prevalence depends on both the initial prevalence and the initial level of human immunity in the population. We found the effects of initial conditions to be of comparable magnitude to the effects of interannual variability in environmental conditions in determining malaria prevalence. The memory associated with this hysteresis effect is longer in high transmission settings than in low transmission settings. Our results show that efforts to simulate and forecast malaria transmission must consider the exposure history of a location as well as the concurrent environmental drivers.

URL http://www.sciencedirect.com/science/article/pii/S030917081630519X
DOI http://dx.doi.org/10.1016/j.advwatres.2016.10.003
Relevant Projects:
Early Warnings for Malaria Epidemics
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