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Evaluating the Performance of Malaria Genetics for Inferring Changes in Transmission Intensity Using Transmission Modeling
Evaluating the Performance of Malaria Genetics for Inferring Changes in Transmission Intensity Using Transmission Modeling
- Source :
- Molecular Biology and Evolution
- Publication Year :
- 2020
- Publisher :
- Oxford University Press (OUP), 2020.
-
Abstract
- Substantial progress has been made globally to control malaria, however there is a growing need for innovative new tools to ensure continued progress. One approach is to harness genetic sequencing and accompanying methodological approaches as have been used in the control of other infectious diseases. However, to utilize these methodologies for malaria, we first need to extend the methods to capture the complex interactions between parasites, human and vector hosts, and environment, which all impact the level of genetic diversity and relatedness of malaria parasites. We develop an individual-based transmission model to simulate malaria parasite genetics parameterized using estimated relationships between complexity of infection and age from five regions in Uganda and Kenya. We predict that cotransmission and superinfection contribute equally to within-host parasite genetic diversity at 11.5% PCR prevalence, above which superinfections dominate. Finally, we characterize the predictive power of six metrics of parasite genetics for detecting changes in transmission intensity, before grouping them in an ensemble statistical model. The model predicted malaria prevalence with a mean absolute error of 0.055. Different assumptions about the availability of sample metadata were considered, with the most accurate predictions of malaria prevalence made when the clinical status and age of sampled individuals is known. Parasite genetics may provide a novel surveillance tool for estimating the prevalence of malaria in areas in which prevalence surveys are not feasible. However, the findings presented here reinforce the need for patient metadata to be recorded and made available within all future attempts to use parasite genetics for surveillance.
- Subjects :
- Plasmodium
Adolescent
030231 tropical medicine
malaria
Sample (statistics)
Mosquito Vectors
Biology
0601 Biochemistry and Cell Biology
AcademicSubjects/SCI01180
law.invention
03 medical and health sciences
0302 clinical medicine
0603 Evolutionary Biology
law
parasitic diseases
Prevalence
Genetics
medicine
Humans
Uganda
Transmission intensity
Child
Molecular Biology
Discoveries
Ecology, Evolution, Behavior and Systematics
030304 developmental biology
Evolutionary Biology
0604 Genetics
0303 health sciences
Genetic diversity
Models, Statistical
AcademicSubjects/SCI01130
Genetic Variation
modeling
Statistical model
medicine.disease
Kenya
Transmission (mechanics)
Child, Preschool
Superinfection
Vector (epidemiology)
surveillance
Predictive power
Malaria
Subjects
Details
- ISSN :
- 15371719 and 07374038
- Volume :
- 38
- Database :
- OpenAIRE
- Journal :
- Molecular Biology and Evolution
- Accession number :
- edsair.doi.dedup.....23e0328d718177d89fea30dfab9a052f
- Full Text :
- https://doi.org/10.1093/molbev/msaa225