Impact of seasonal variations in Plasmodium falciparum malaria transmission on the surveillance of pfhrp2 gene deletions
- Imperial College London, United Kingdom
- World Health Organisation, Switzerland
- University of Kinshasa, Democratic Republic of the Congo
- University of North Carolina, United States
Abstract
Ten countries have reported pfhrp2/pfhrp3 gene deletions since the first observation of pfhrp2-deleted parasites in 2012. In a previous study (Watson et al., 2017) we characterised the drivers selecting for pfhrp2/3 deletions, and mapped the regions in Africa with the greatest selection pressure. In February 2018, the World Health Organization issued guidance on investigating suspected false-negative rapid diagnostic tests (RDTs) due to pfhrp2/3 deletions. However, no guidance is provided regarding the timing of investigations. Failure to consider seasonal variation could cause premature decisions to switch to alternative RDTs. In response, we have extended our methods and predict that the prevalence of false-negative RDTs due to pfhrp2/3 deletions is highest when sampling from younger individuals during the beginning of the rainy season. We conclude by producing a map of the regions impacted by seasonal fluctuations in pfhrp2/3 deletions and a database identifying optimum sampling intervals to support malaria control programmes.
Data availability
All data generated are provided within the online database, hosted through a shiny application at https://ojwatson.shinyapps.io/seasonal_hrp2/. The raw data for the application is available within the github repository at https://github.com/OJWatson/hrp2malaRia.
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PfPR2-10 in Africa 2000-2015Malaria Atlas Project, http://www. map.ox.ac.uk/.
Article and author information
Author details
Oliver John Watson
Funding
Wellcome (109312/Z/15/Z)
- Oliver John Watson
Medical Research Council (MR/N01507X/1)
- Robert Verity
Department for International Development
- Azra C Ghani
Medical Research Council
- Tini Garske
National Institute of Allergy and Infectious Diseases (R01AI132547)
- Steven R Meshnick
- Jonathan B Parr
American Society for Tropical Medicine and Hygiene-Burroughs Wellcome Fund
- Jonathan B Parr
Imperial College London
- Hannah C Slater
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Ben Cooper, Mahidol Oxford Tropical Medicine Research Unit, Thailand
Version history
- Received: July 25, 2018
- Accepted: April 29, 2019
- Accepted Manuscript published: May 2, 2019 (version 1)
- Version of Record published: May 23, 2019 (version 2)
Copyright
© 2019, Watson et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Impact of seasonal variations in Plasmodium falciparum malaria transmission on the surveillance of pfhrp2 gene deletions
eLife 8:e40339.
https://doi.org/10.7554/eLife.40339
Further reading
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- Cancer Biology
- Epidemiology and Global Health
Background:
Age is the most important risk factor for cancer, but aging rates are heterogeneous across individuals. We explored a new measure of aging-Phenotypic Age (PhenoAge)-in the risk prediction of site-specific and overall cancer.
Methods:
Using Cox regression models, we examined the association of Phenotypic Age Acceleration (PhenoAgeAccel) with cancer incidence by genetic risk group among 374,463 participants from the UK Biobank. We generated PhenoAge using chronological age and nine biomarkers, PhenoAgeAccel after subtracting the effect of chronological age by regression residual, and an incidence-weighted overall cancer polygenic risk score (CPRS) based on 20 cancer site-specific polygenic risk scores (PRSs).
Results:
Compared with biologically younger participants, those older had a significantly higher risk of overall cancer, with hazard ratios (HRs) of 1.22 (95% confidence interval, 1.18–1.27) in men, and 1.26 (1.22–1.31) in women, respectively. A joint effect of genetic risk and PhenoAgeAccel was observed on overall cancer risk, with HRs of 2.29 (2.10–2.51) for men and 1.94 (1.78–2.11) for women with high genetic risk and older PhenoAge compared with those with low genetic risk and younger PhenoAge. PhenoAgeAccel was negatively associated with the number of healthy lifestyle factors (Beta = –1.01 in men, p<0.001; Beta = –0.98 in women, p<0.001).
Conclusions:
Within and across genetic risk groups, older PhenoAge was consistently related to an increased risk of incident cancer with adjustment for chronological age and the aging process could be retarded by adherence to a healthy lifestyle.
Funding:
This work was supported by the National Natural Science Foundation of China (82230110, 82125033, 82388102 to GJ; 82273714 to MZ); and the Excellent Youth Foundation of Jiangsu Province (BK20220100 to MZ).
