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Relapse or reinfection: Classification of malaria infection using transition likelihoods.

ABSTRACT: In patients with Plasmodium vivax malaria treated with effective blood-stage therapy, the recurrent illness may occur due to relapse from latent liver-stage infection or reinfection from a new mosquito bite. Classification of the recurrent infection as either relapse or reinfection is critical when evaluating the efficacy of an anti-relapse treatment. Although one can use whether a shared genetic variant exists between baseline and recurrence genotypes to classify the outcome, little has been suggested to use both sharing and nonsharing variants to improve the classification accuracy. In this paper, we develop a novel classification criterion that utilizes transition likelihoods to distinguish relapse from reinfection. When tested in extensive simulation experiments with known outcomes, our classifier has superior operating characteristics. A real data set from 78 Cambodian P. vivax malaria patients was analyzed to demonstrate the practical use of our proposed method.

SUBMITTER: Lin FC

PROVIDER: S-EPMC8711853 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Relapse or reinfection: Classification of malaria infection using transition likelihoods.

Lin Feng-Chang FC Li Quefeng Q Lin Jessica T JT

Biometrics 20200303 4

In patients with Plasmodium vivax malaria treated with effective blood-stage therapy, the recurrent illness may occur due to relapse from latent liver-stage infection or reinfection from a new mosquito bite. Classification of the recurrent infection as either relapse or reinfection is critical when evaluating the efficacy of an anti-relapse treatment. Although one can use whether a shared genetic variant exists between baseline and recurrence genotypes to classify the outcome, little has been su ...[more]

PMID: 32022247

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Project description:Our study sought to compare the strain types of Clostridium difficile causing initial and recurrent episodes of C. difficile infection (CDI) in adult patients with a first episode of CDI or 1 prior episode of CDI within the previous 90 days. Strains originated from patients who had been entered into two phase 3 randomized clinical trials of fidaxomicin versus vancomycin. Isolates of C. difficile from the initial and recurrent episodes within 28 (± 2) days of cure of CDI were compared using restriction endonuclease analysis (REA) typing. Paired isolates were available from 90 of 194 (46%) patients with recurrent CDI. Patients with isolates available were significantly younger (P = .008) and more likely to be from Canadian sites (P = .0001), compared with patients without isolates. In 75 of 90 subjects (83.3%), the identical REA type strain was identified at recurrence and the initial episode (putative relapse). Early recurrences (0-14 days after treatment completion) were relapses in 86.7% and a new strain (reinfection) in 13.3%. Later recurrences (15-31 days after treatment) were relapses in 76.7% and reinfections in 23.3%. Mean time (± standard deviation) to recurrence was 12.2 (± 6.4) days for relapses and 14.7 (± 6.8) days for reinfections (P = .177). The most common BI/NAP1/027 group and the previous US epidemic REA group J/NAP2/001 had a significantly higher combined rate of recurrence with the same strain (relapse), compared with the other REA groups (39 of 42 [93%] vs 36 of 48 [75%], respectively; P = .023). We found a higher than historic rate of recurrent CDI caused by the same isolate as the original episode, a finding that may be related to the relatively short observation period in this study and the high frequency of isolation of epidemic strains, such as groups BI and J, for which relapse rates may be higher than for other REA groups. Caution in generalizing these observations is required, because the patients studied were younger and more likely to be from Canadian sites than were patients with recurrence who did not provide isolates.

Project description:In the present study, we propose and analyze an epidemic mathematical model for malaria dynamics, considering multiple recurrent phenomena: relapse, reinfection, and recrudescence. A limitation in hospital bed capacity, which can affect the treatment rate, is modeled using a saturated treatment function. The qualitative behavior of the model, covering the existence and stability criteria of the endemic equilibrium, is investigated rigorously. The concept of the basic reproduction number of the proposed model is obtained using the concept of the next-generation matrix. We find that the malaria-free equilibrium point is locally asymptotically stable if the basic reproduction number is less than one and unstable if it is larger than one. Our observation on the malaria-endemic equilibrium of the proposed model shows possible multiple endemic equilibria when the basic reproduction number is larger or smaller than one. Hence, we conclude that a condition of a basic reproduction number less than one is not sufficient to guarantee the extinction of malaria from the population. To test our model in a real-life situation, we fit our model parameters using the monthly incidence data from districts in Central Sumba, Indonesia called Wee Luri, which were collected from the Wee Luri Health Center. Using the first twenty months' data from Wee Luri district, we show that our model can fit the data with a confidence interval of 95%. Both analytical and numerical experiments show that a limitation in hospital bed capacity and reinfection can trigger a more substantial possibility of the appearance of backward bifurcation. On the other hand, we find that an increase in relapse can reduce the chance of the appearance of backward bifurcation. A non-trivial result appears in that a higher probability of recrudescence (treatment failure) does not always result in the appearance of backward bifurcation. From the global sensitivity analysis using a combination of Latin hypercube sampling and partial rank correlation coefficient, we found that the initial infection rate in humans and the mosquito infection rate are the most influential parameters in determining the increase in total new human infections. We expand our model as an optimal control problem by including three types of malaria interventions, namely the use of bed net, hospitalization, and fumigation as a time-dependent variable. Using the Pontryagin maximum principle, we characterize our optimal control problem. Results from our cost-effectiveness analysis suggest that hospitalization only is the most cost-effective strategy required to control malaria disease.

Dataset Information

Relapse or reinfection: Classification of malaria infection using transition likelihoods.

Publications

Relapse or reinfection: Classification of malaria infection using transition likelihoods.

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