1. Medicine
  2. Epidemiology and Global Health
Download icon

Mapping residual transmission for malaria elimination

  1. Robert C Reiner  Is a corresponding author
  2. Arnaud Le Manach
  3. Simon Kunene
  4. Nyasatu Ntshalintshali
  5. Michelle S Hsiang
  6. T Alex Perkins
  7. Bryan Greenhouse
  8. Andrew J Tatem
  9. Justin M Cohen
  10. David L Smith
  1. National Institutes of Health, United States
  2. Clinton Health Access Initiative, United States
  3. National Malaria Control Program, Swaziland
  4. University of Texas Southwestern Medical Center, United States
  5. University of California, San Francisco, United States
Research Article
  • Cited 38
  • Views 2,795
  • Annotations
Cite this article as: eLife 2015;4:e09520 doi: 10.7554/eLife.09520

Abstract

Eliminating malaria from a defined region involves draining the endemic parasite reservoir and minimizing local malaria transmission around imported malaria infections1. In the last phases of malaria elimination, as universal interventions reap diminishing marginal returns, national resources must become increasingly devoted to identifying where residual transmission is occurring. The needs for accurate measures of progress and practical advice about how to allocate scarce resources require new analytical methods to quantify fine-grained heterogeneity in malaria risk. Using routine national surveillance data from Swaziland (a sub-Saharan country on the verge of elimination), we estimated individual reproductive numbers. Fine-grained maps of reproductive numbers and local malaria importation rates were combined to show `malariogenic potential,' a first for malaria elimination. As countries approach elimination, these individual-based measures of transmission risk provide meaningful metrics for planning programmatic responses and prioritizing areas where interventions will contribute most to malaria elimination.

Article and author information

Author details

  1. Robert C Reiner

    Fogarty International Center, National Institutes of Health, Bethesda, United States
    For correspondence
    rcreiner@indiana.edu
    Competing interests
    The authors declare that no competing interests exist.
  2. Arnaud Le Manach

    Clinton Health Access Initiative, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Simon Kunene

    National Malaria Control Program, Manzini, Swaziland
    Competing interests
    The authors declare that no competing interests exist.
  4. Nyasatu Ntshalintshali

    Clinton Health Access Initiative, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Michelle S Hsiang

    Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. T Alex Perkins

    Fogarty International Center, National Institutes of Health, Bethesda, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Bryan Greenhouse

    Department of Medicine, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Andrew J Tatem

    Fogarty International Center, National Institutes of Health, Bethesda, United States
    Competing interests
    The authors declare that no competing interests exist.
  9. Justin M Cohen

    Clinton Health Access Initiative, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  10. David L Smith

    Fogarty International Center, National Institutes of Health, Bethesda, United States
    Competing interests
    The authors declare that no competing interests exist.

Reviewing Editor

  1. Mark Jit, London School of Hygiene & Tropical Medicine, and Public Health England, United Kingdom

Publication history

  1. Received: June 18, 2015
  2. Accepted: November 26, 2015
  3. Accepted Manuscript published: December 29, 2015 (version 1)
  4. Version of Record published: January 27, 2016 (version 2)

Copyright

© 2015, Reiner 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.

Metrics

  • 2,795
    Page views
  • 666
    Downloads
  • 38
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Download citations (links to download the citations from this article in formats compatible with various reference manager tools)

Open citations (links to open the citations from this article in various online reference manager services)

Further reading

    1. Genetics and Genomics
    2. Medicine
    Emanuela Abiusi et al.
    Research Article

    Background:

    Spinal muscular atrophy (SMA) is a neuromuscular disorder characterized by the degeneration of the second motor-neuron. The phenotype ranges from very severe to very mild forms. All patients have the homozygous loss of the SMN1 gene and a variable number of SMN2 (generally two-to-four copies), inversely related with the severity. The amazing results of the available treatments have made compelling the need of prognostic biomarkers to predict the progression trajectories of patients. Beside the SMN2 products, few other biomarkers have been evaluated so far, including some miRs.

    Methods:

    We performed whole miRNome analysis of muscle samples of patients and controls (14 biopsies and 9 cultures). The levels of muscle differentially expressed miRs were evaluated in serum samples (51 patients and 37 controls) and integrated with SMN2 copies, SMN2-full length transcript levels in blood and age (SMA-score).

    Results:

    Over 100 miRs were differentially expressed in SMA muscle; three of them (HSA-miR-181a-5p, -324-5p, -451a; SMA-miRs) were significantly up-regulated in serum of patients. The severity predicted by the SMA-score was related with that of the clinical classification at a correlation coefficient of 0.87 (p<10-5).

    Conclusions:

    miRNome analyses suggest the primary involvement of skeletal muscle in SMA pathogenesis; the SMA-miRs are likely actively released in the blood flow, even if their function and target cells require to be elucidated. The accuracy of the SMA-score needs to be verified in replicative studies: if confirmed, its use could be crucial for the routine prognostic assessment, also in pre-symptomatic patients.

    Funding:

    Telethon Italia (grant # GGP12116).

    1. Medicine
    Mieradilijiang Abudupataer et al.
    Research Article Updated

    Background:

    Bicuspid aortic valve (BAV) is the most common congenital cardiovascular disease in general population and is frequently associated with the development of thoracic aortic aneurysm (TAA). There is no effective strategy to intervene with TAA progression due to an incomplete understanding of the pathogenesis. Insufficiency of NOTCH1 expression is highly related to BAV-TAA, but the underlying mechanism remains to be clarified.

    Methods:

    A comparative proteomics analysis was used to explore the biological differences between non-diseased and BAV-TAA aortic tissues. A microfluidics-based aorta smooth muscle-on-a-chip model was constructed to evaluate the effect of NOTCH1 deficiency on contractile phenotype and mitochondrial dynamics of human aortic smooth muscle cells (HAoSMCs).

    Results:

    Protein analyses of human aortic tissues showed the insufficient expression of NOTCH1 and impaired mitochondrial dynamics in BAV-TAA. HAoSMCs with NOTCH1-knockdown exhibited reduced contractile phenotype and were accompanied by attenuated mitochondrial fusion. Furthermore, we identified that mitochondrial fusion activators (leflunomide and teriflunomide) or mitochondrial fission inhibitor (Mdivi-1) partially rescued the disorders of mitochondrial dynamics in HAoSMCs derived from BAV-TAA patients.

    Conclusions:

    The aorta smooth muscle-on-a-chip model simulates the human pathophysiological parameters of aorta biomechanics and provides a platform for molecular mechanism studies of aortic disease and related drug screening. This aorta smooth muscle-on-a-chip model and human tissue proteomic analysis revealed that impaired mitochondrial dynamics could be a potential therapeutic target for BAV-TAA.

    Funding:

    National Key R and D Program of China, National Natural Science Foundation of China, Shanghai Municipal Science and Technology Major Project, Shanghai Science and Technology Commission, and Shanghai Municipal Education Commission.