The Potential Elimination of Plasmodium vivax Malaria by Relapse Treatment: Insights from a Transmission Model and Surveillance Data from NW India

Abstract

BackgroundWith over a hundred million annual infections and rising morbidity and mortality, Plasmodium vivax malaria remains largely a neglected disease. In particular, the dependence of this malaria species on relapses and the potential significance of the dormant stage as a therapeutic target, are poorly understood.Methodology/Principal FindingsTo quantify relapse parameters and assess the population-wide consequences of anti-relapse treatment, we formulated a transmission model for P. vivax suitable for parameter inference with a recently developed statistical method based on routine surveillance data. A low-endemic region in NW India, whose strong seasonality demarcates the transmission season, provides an opportunity to apply this modeling approach. Our model gives maximum likelihood estimates of 7.1 months for the mean latency and 31% for the relapse rate, in close agreement with regression estimates and clinical evaluation studies in the area. With a baseline of prevailing treatment practices, the model predicts that an effective anti-relapse treatment of 65% of those infected would result in elimination within a decade, and that periodic mass treatment would dramatically reduce the burden of the disease in a few years.Conclusion/SignificanceThe striking dependence of P. vivax on relapses for survival reinforces the urgency to develop more effective anti-relapse treatments to replace Primaquine (PQ), the only available drug for the last fifty years. Our methods can provide alternative and simple means to estimate latency times and relapse frequency using routine epidemiological data, and to evaluate the population-wide impact of relapse treatment in areas similar to our study area.

Dynamical malaria models reveal how immunity buffers effect of climate variability

“…We found highly significant correlation values between Ndiop cases and rainfall in the previous month (Pearson's r xy = 0.75, P value = 2.2e À 16), which suggests that rainfall plays an important role in Ndiop malaria dynamics, in agreement with the fact that local climate variability drives malaria outbreaks in low-transmission epidemic fringes (3,4,16). In the case of Dielmo, a high-transmission perennial site, the second peak is seen to be significantly modulated by rainfall in the previous month (Dielmo second peak: Pearson's r xy = 0.24, P value = 0.6e À 3) albeit to a lesser extent than in Ndiop.…”

“…Recent malaria models also predict a global net increase of the population at risk (13); however, others suggest a shift in spatial distribution rather than a large net increase in total malaria incidence worldwide (14,15). In epidemic fringes, variation in the incidence of disease is largely determined by the seasonal variation of the mosquito population's occurrence and density, which are essentially modulated by local rainfall [e.g., if water limited (3,16)] or temperature [e.g., if altitude limited (2,4,8)]. This is not the case in holoendemic transmission settings, where incidence of disease is determined not only by external forces, but also by the development of clinical and antiparasite immunity.…”

“…1, Upper) enable us to showcase the relative roles of internal and external factors in malaria epidemiology, assess the potential degree of predictability emanating from climatic variability, and generate estimates of key parameters in determining malaria population dynamics. To this end, we use a recently developed inference methodology for nonlinear stochastic dynamical systems, successfully applied to epidemic dynamics (3,16) but never applied to endemic settings. A general coupled mosquito-human compartment model that includes possible key mechanisms common to both villages serves our aim of disentangling differences related to immunity, infectivity, superinfection, and asymptomatic infections as well as to measure the relevance of local climate for each village.…”

The utility of genomic data forPlasmodium vivaxpopulation surveillance

“…For example, two critical parameters for P. vivax elimination are latency time and relapse frequency. 16 Geographic variation in these parameters is well documented, but it is still not known to what extent they are affected by genetic differences among parasites. 17 …”

Transmission dynamics of vivax malaria in the republic of Korea: Effectiveness of anti-malarial mass chemoprophylaxis

“…A total of 15,981 soldiers underwent chemoprophylaxis in the first year, and subsequently the number of subjects increased year by year reaching 90,000 in 2000. The effectiveness of chemoprophylaxis on preventing epidemic has been assessed in case-based studies in the past (Yeom et al, 2005;Roy et al, 2013). However, the incidence of vivax malaria in a year in Korea is strongly dependent on the incidence in the previous year due to the long-term incubation period, and thus, the full clarification of the population effectiveness of chemoprophylaxis requires us to explicitly account for the transmission dynamics.…”