Project

malaria; epidemiology; Plasmodium vivax; dynamics; Papua New Guinea

Lead
Lay summary
Four species of malaria parasites infect humans. Until recently, the focus has fallen largely on Plasmodium falciparum, which places a huge burden of disease across Africa. Attention is now also turning to Plasmodium vivax due to a growing awareness that it too can cause severe and fatal disease. P. vivax has the widest geographical spread, including Asia, the Middle East, Central and South America and the Western Pacific, totaling an estimated 70 million cases per year. Effective control strategies are urgently needed. Planners are hampered by the lack of information on the likely consequences of different interventions. Where data are lacking, mathematical models can be used to provide a 'best guess'. To provide valid predictions, the building blocks of the models must be correct. Basic measures of P. vivax infections are required, such as the duration of infections, relapse and clearance rates, the rate of new infections, infectivity to mosquitoes, and the relationship between clinical symptoms and parasite densities in the blood.P. vivax infection dynamics are difficult to study because people living in endemic areas may harbour several different infections at the same time, the density of parasites in the blood may transiently lie below the limit of detection, and because the parasites can lie dormant in liver cells for long periods and then relapse. Different infections can only be distinguished by high resolution genotyping which allows the characterization of the number of different infections and their diversity. Genotyping of samples from study participants taken repeatedly over time is underway for studies from Papua New Guinea. Statistical methods to analyse this data are not well developed. We propose to develop analyses, fitting models of the dynamics of infections to both the genotyping data and other sources, to estimate the above quantities. We expect that the estimates will be useful for both modelling and for P. vivax epidemiology.

Direct link to Lay Summary

Last update: 21.02.2013

Number	Title	Start	Funding scheme

BackgroundPlasmodium vivax is a protozoan parasite, one of four species that account for nearly all human malaria infections. Plasmodium vivax and Plasmodium falciparum together account for the vast majority of human malaria infections worldwide. Until recently, P. vivax has been the focus of relatively little research partly because it causes less severe disease than P. falciparum [2]. However it is increasingly recognized that P. vivax can cause severe and even fatal disease With growing awareness of the burden of P. vivax on affected populations, control of P. vivax infections and morbidity is once again seen as a priority for areas where the disease is endemic. The recent call from the Bill and Melinda Gates Foundation for malaria eradication has further highlighted the neglect of P. vivax since malaria eradication necessarily entails the elimination of both species.Mathematical models of Plasmodium vivax dynamics in humans are hampered by the lack of information on basic parameters describing infections and disease in endemic areas. Existing compartmental models of P. vivax population dynamics are unsuitable for predicting the impact of interventions.Aims and methods We have identified five processes that need to be quantified in any adequate general model of P. vivax dynamics, (i) the force of infection of the liver, (ii) the release of merozoites from the liver, (iii) the clearance of blood stage infections, (iv) pathogenesis, and (v) infectivity to Anopheles mosquitoes. We now propose a project to use both literature review and statistical analyses, (a) to obtain field-based estimates of the corresponding transition probabilites and rates; (b) to examine, where possible, what are the main factors modifying and determining these probabilities and rates; (c) to examine, in particular, how these rates and probabilities vary with age, and/or exposure to P. vivax.These analyses require longitudinal field studies to study infection dynamics over time. We will take advantage of such datasets from Papua New Guinea (PNG). P. vivax is endemic in PNG, and the north coast (Madang and East Sepik provinces) include some of the highest rates of P. vivax transmission in the world [3]. A number of intensive studies of P. vivax epidemiology are currently in progress and the data is made available via a strong existing collaboration between the Swiss Tropical Institute (STI) and the Papua New Guinea Institute of Medical Research (PNGIMR). The research proposed now is additional to the primary analyses covered by existing support of these field studies, but is covered by the existing research approvals and consent obtained for these studies. Infection dynamics of P. vivax in endemic areas are difficult to study because of the challenge of distinguishing persisting infections from new ones, because parasite densities are often transiently below the limit of detection and because of relapses. In high endemicity populations many hosts harbour multiple clones of P. vivax [1] and new or relapsing infections can only be distinguished from persisting ones by high resolution genotyping. Extensive genotyping (collected for characterising infection multiplicity and parasite diversity) is already planned for some of the PNG P. vivax studies. To estimate rates of infection, relapse, and clearance of blood stage infections in the PNG data we will therefore extend hidden Markov models and/or immigration-death models developed to analyse longitudinal genotyping data for P. falciparum [4;5]. Where necessary we will supplement these data with additional genotyping.Reference List1. Bruce MC, Galinski MR, Barnwell JW, Donnelly CA, Walmsley M, Alpers MP, Walliker D, Day KP: Genetic diversity and dynamics of plasmodium falciparum and P. vivax populations in multiply infected children with asymptomatic malaria infections in Papua New Guinea. Parasitology 121 ( Pt 3):257-272, 20002. Herrera S, Corradin G, Arevalo-Herrera M: A update on the search for a Plasmodium vivax vaccine. Trends Parasitol 23:122-128, 20073. Muller I, Bockarie M, Alpers MP, Smith T: The epidemiology of malaria in Papua New Guinea. Trends Parasitol 19:253-259, 20034. Sama W, Owusu-Agyei S, Felger I, Vounatsou P, Smith T: An immigration-death model to estimate the duration of malaria infection when detectability of the parasite is imperfect. Stat.Med. 24:3269-3288, 20055. Smith T, Vounatsou P: Estimation of infection and recovery rates for highly polymorphic parasites when detectability is imperfect, using hidden Markov models. Stat.Med. 22:1709-1724, 2003