The distribution of incubation and relapse times in experimental human infections with the malaria parasite Plasmodium vivax

Abstract

BackgroundThe distributions of incubation and relapse periods are key components of infectious disease models for the malaria parasite Plasmodium vivax; however, detailed distributions based upon experimental data are lacking.MethodsUsing a range of historical, experimental mosquito-transmitted human infections, Bayesian estimation with non-informative priors was used to determine parametric distributions that can be readily implemented for the incubation period and time-to-first relapse in P. vivax infections, including global subregions by parasite source. These analyses were complemented with a pooled analysis of observational human infection data with infections that included malaria chemoprophylaxis and long-latencies. The epidemiological impact of these distributional assumptions was explored using stochastic epidemic simulations at a fixed reproductive number while varying the underlying distribution of incubation periods.ResultsUsing the Deviance Information Criteria to compare parameterizations, experimental incubation periods are most closely modeled with a shifted log-logistic distribution; a log-logistic mixture is the best fit for incubations in observational studies. The mixture Gompertz distribution was the best fit for experimental times-to-relapse among the tested parameterizations, with some variation by geographic subregions. Simulations suggest underlying distributional assumptions have critically important impacts on both the time-scale and total case counts within epidemics.ConclusionsThese results suggest that the exponential and gamma distributions commonly used for modeling incubation periods and relapse times inadequately capture the complexity in the distributions of event times in P. vivax malaria infections. In future models, log-logistic and Gompertz distributions should be utilized for general incubation periods and relapse times respectively, and region-specific distributions should be considered to accurately model and predict the epidemiology of this important human pathogen.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2334-14-539) contains supplementary material, which is available to authorized users.

Do hypnozoites cause relapse in malaria?

“…Recurrences aside, where do the parasites live that are responsible for long incubation periods, not only in P. falciparum and P. malariae malaria, but also in P. vivax (e.g., [31,45]) and P. ovale (e.g., [41,[46][47][48][49]) infections? Moreover, are the persisting parasites sporozoites, hypnozoites, merozoites, or more than one of these?…”

The utility of genomic data forPlasmodium vivaxpopulation surveillance

“…Relapse plays an important role in P. vivax transmission dynamics, 24 in initiating the transmission season in seasonal transmission settings (such as Southern Mexico 51 ), contributes to high levels of genetic diversity in populations, and is responsible for a high percentage of P. vivax cases, for example more than 50% in a cohort in Cambodia. 23 It also confounds monitoring for treatment failures due to resistance, as the reappearance of blood stage infection can also be due to the emergence of previously latent parasites.…”

A mathematical model for assessing the effectiveness of controlling relapse in Plasmodium vivax malaria endemic in the Republic of Korea

“…Activation of these hypnozoites makes future relapse possible even if blood-stage malaria is removed from primary infection. Hypnozoites are produced when the conditions for transmission of the parasite are less favorable, for instance, during short seasons of appropriate temperatures and vectors available at high latitudes [5]. The relapse rate caused by these hypnozoites is around 68% across the world, without any popular treatment for such relapses [6].…”