| Title |
Plasmodium vivax and Plasmodium falciparum infection dynamics: re-infections, recrudescences and relapses
|
|---|---|
| Published in |
Malaria Journal, April 2018
|
| DOI | 10.1186/s12936-018-2318-1 |
| Pubmed ID | |
| Authors |
Michael T. White, Stephan Karl, Cristian Koepfli, Rhea J. Longley, Natalie E. Hofmann, Rahel Wampfler, Ingrid Felger, Tom Smith, Wang Nguitragool, Jetsumon Sattabongkot, Leanne Robinson, Azra Ghani, Ivo Mueller |
| Abstract |
In malaria endemic populations, complex patterns of Plasmodium vivax and Plasmodium falciparum blood-stage infection dynamics may be observed. Genotyping samples from longitudinal cohort studies for merozoite surface protein (msp) variants increases the information available in the data, allowing multiple infecting parasite clones in a single individual to be identified. msp genotyped samples from two longitudinal cohorts in Papua New Guinea (PNG) and Thailand were analysed using a statistical model where the times of acquisition and clearance of each clone in every individual were estimated using a process of data augmentation. For the populations analysed, the duration of blood-stage P. falciparum infection was estimated as 36 (95% Credible Interval (CrI): 29, 44) days in PNG, and 135 (95% CrI 94, 191) days in Thailand. Experiments on simulated data indicated that it was not possible to accurately estimate the duration of blood-stage P. vivax infections due to the lack of identifiability between a single blood-stage infection and multiple, sequential blood-stage infections caused by relapses. Despite this limitation, the method and data point towards short duration of blood-stage P. vivax infection with a lower bound of 24 days in PNG, and 29 days in Thailand. On an individual level, P. vivax recurrences cannot be definitively classified into re-infections, recrudescences or relapses, but a probabilistic relapse phenotype can be assigned to each P. vivax sample, allowing investigation of the association between epidemiological covariates and the incidence of relapses. The statistical model developed here provides a useful new tool for in-depth analysis of malaria data from longitudinal cohort studies, and future application to data sets with multi-locus genotyping will allow more detailed investigation of infection dynamics. |
X Demographics
The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 10% |
| Belgium | 1 | 10% |
| Italy | 1 | 10% |
| Australia | 1 | 10% |
| Japan | 1 | 10% |
| Unknown | 5 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 40% |
| Scientists | 3 | 30% |
| Science communicators (journalists, bloggers, editors) | 2 | 20% |
| Practitioners (doctors, other healthcare professionals) | 1 | 10% |
Mendeley readers
The data shown below were compiled from readership statistics for 136 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 136 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 25 | 18% |
| Student > Master | 20 | 15% |
| Researcher | 19 | 14% |
| Student > Bachelor | 8 | 6% |
| Professor | 6 | 4% |
| Other | 21 | 15% |
| Unknown | 37 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 20 | 15% |
| Biochemistry, Genetics and Molecular Biology | 18 | 13% |
| Immunology and Microbiology | 11 | 8% |
| Agricultural and Biological Sciences | 9 | 7% |
| Mathematics | 6 | 4% |
| Other | 24 | 18% |
| Unknown | 48 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 16. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 December 2022.
All research outputs
#2,105,987
of 24,294,766 outputs
Outputs from Malaria Journal
#412
of 5,804 outputs
Outputs of similar age
#44,721
of 330,687 outputs
Outputs of similar age from Malaria Journal
#7
of 119 outputs
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We're also able to compare this research output to 119 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.