1. Ecology
  2. Epidemiology and Global Health
Download icon

Mapping residual transmission for malaria elimination

  1. Robert C Reiner Jr  Is a corresponding author
  2. Arnaud Le Menach
  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. Indiana University School of Public Health, United States
  3. Clinton Health Access Initiative, United States
  4. National Malaria Control Program, Swaziland
  5. University of Texas Southwestern Medical Center, United States
  6. University of California, San Francisco, United States
  7. University of California, San Francisco Benioff Children’s Hospital, United States
  8. University of Notre Dame, United States
  9. University of Southampton, United Kingdom
  10. University of Oxford, United Kingdom
  11. University of Washington, United States
  12. Sanaria Institute for Global Health and Tropical Medicine, United States
Research Article
Cite this article as: eLife 2015;4:e09520 doi: 10.7554/eLife.09520
7 figures and 2 tables

Figures

Consensus network plot of causal links.

Panel A: Swaziland imported and local malaria cases (green squares and orange diamonds, respectively) are plotted spatially. Local case pairs identified as putative orphaned chains are indicated by red diamonds. A solitary local case also identified as an orphan is identified as a red diamond within a circle. Panel B: Swaziland imported (green line) and local (orange line) malaria cases are plotted in time, aggregated by month. Panel C: The final consensus network plot is displayed. Local cases are plotted as diamonds and imported cases as green circles. The color of each link corresponds to the “strength” of the connection as measured by the number of parameter sets where that link was identified as optimal. Imported cases that were not found to be the “most likely” parent of a local case are not displayed.

https://doi.org/10.7554/eLife.09520.003
Vulnerability, receptivity and malariogenic potential.

Panel A: Extrapolated Rc values for Swaziland using a zero-inflated negative binomial regression. Areas in orange to red indicate locations where Rc is greater than unity. The legend doubles as a histogram indicating the number of individuals (on a log10 scale) that live within each range of Rc values. Panel B: Extrapolated importation probabilities for Swaziland using a logistic regression. Panel C: Malariogenic potential for Swaziland calculated as the product of Rc and the probability of importation.

https://doi.org/10.7554/eLife.09520.004
Vulnerability, receptivity and malariogenic potential (2010-6/2012). 

Panel A: Extrapolated Rc values for Swaziland using a zero-inflated negative binomial regression. Areas in orange to red indicate locations where Rc is greater than unity. The legend doubles as a histogram indicating the number of individuals (on a log10 scale) that live within each range of Rc values. Panel B: Extrapolated importation probabilities for Swaziland using a logistic regression. Panel C: Malariogenic potential for Swaziland calculated as the product of Rc and the probability of importation.

https://doi.org/10.7554/eLife.09520.005
Vulnerability, receptivity and malariogenic potential (7/2012-2014).

Panel A: Extrapolated Rc values for Swaziland using a zero-inflated negative binomial regression. Areas in orange to red indicate locations where Rc is greater than unity. The legend doubles as a histogram indicating the number of individuals (on a log10 scale) that live within each range of Rc values. Panel B: Extrapolated importation probabilities for Swaziland using a logistic regression. Panel C: Malariogenic potential for Swaziland calculated as the product of Rc and the probability of importation.

https://doi.org/10.7554/eLife.09520.006
Timing of ‘orphan’ cases.

The average number of cases per month and total occurrence of looped (or ‘orphaned’ cases) are plotted against month.

https://doi.org/10.7554/eLife.09520.007
Spatial covariates for malaria receptivity regression.

The four significant covariates for the malaria receptivity regression were (A) distance from paved roads, (B) distance from unpaved roads, (C) distance from feeder roads, and (D) distance from Mozambique. All distances were in meters.

https://doi.org/10.7554/eLife.09520.008
Spatial covariates for malaria importation regression.

The ten significant covariates for the malaria importation regression were (A) elevation, (B) population, (C) annual mean temperature (bio1 - http://www.worldclim.org/bioclim), (D) maximum temperature of the warmest month (bio5 - http://www.worldclim.org/bioclim), (E) minimum temperature of coldest month (bio6 - http://www.worldclim.org/bioclim), (F) precipitation of the wettest month (bio13 - http://www.worldclim.org/bioclim), (G) precipitation of driest month (bio14 - http://www.worldclim.org/bioclim), (H) TWI, (I) normalized difference vegetation index, and (J) enhanced vegetation index.

https://doi.org/10.7554/eLife.09520.010

Tables

Table 1

Zero-inflated negative binomial regression summary.

https://doi.org/10.7554/eLife.09520.009
Factor (source)Count model coefficientZero-inflated coefficient
Intercept7.6864071642.7199
Elevation (m) (http://www.worldclim.org/bioclim)−0.0026−0.65197
Population (http://www.worldpop.org.uk/)−0.017571−0.01190
Annual Mean Temperature (0.1°C) (http://www.worldclim.org/bioclim)0.14197930.70232
Max Temperature of Warmest Month (0.1°C) (http://www.worldclim.org/bioclim)−0.113297−23.66837
Min Temperature of Coldest Month (0.1°C)−0.029091−10.04161
Precipitation of Wettest Month (mm) (http://www.worldclim.org/bioclim)0.0080320.50592
Precipitation of Driest Month (mm) (http://www.worldclim.org/bioclim)−0.10876712.04175
TWI−0.024820−4.02392
NDVI (https://landsat.usgs.gov/)2.461314−159.39390
EVI (https://landsat.usgs.gov/)−3.73279582.72595
Log(theta)−0.613861NA
Table 2

GAM logistic regression summary.

https://doi.org/10.7554/eLife.09520.011
FactoredfChi.sqp-value
Population (http://www.worldpop.org.uk/)6.729688.01<2e-16
Paved roads (source: country)5.909172.49<2e-16
Unpaved roads1.00215.886.88e-5
Feeders roads6.49950.373e-8
Distance to Mozambique (http://www.fao.org/geonetwork/srv/en/main.home)7.51675.271.04e-12

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)