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El Ni?o and the shifting geography of cholera in Africa

  1. Justin Lesslera,1
  1. aDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205;
  2. bDepartment of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556;
  3. cEck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46556;
  4. dDepartment of Earth and Planetary Sciences, Johns Hopkins University, Baltimore, MD 21218;
  5. eDivision of Foodborne, Waterborne and Environmental Diseases, Centers for Disease Control and Prevention, Atlanta, GA 30329;
  6. fDepartment of Pandemic and Epidemic Diseases, World Health Organization, 1211, Geneva, Switzerland;
  7. gEpicentre, 75012 Paris, France;
  8. hDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205;
  9. iMédecins Sans Frontières, 75011 Paris, France
  1. Edited by Andrea Rinaldo, Laboratory of Ecohydrology (ECHO/IIE/ENAC), Ecole Polytechnique Federale Lausanne, and approved March 8, 2017 (received for review October 18, 2016)

  1. Fig. 2.

    Geographical distribution and incidence rates for El Ni?o-sensitive regions. (A) Regions with positive (red) and negative (blue) sensitivity to El Ni?o events in cholera incidence. Areas selected by smoothing the normalized difference in cholera incidence using a kernel smoothing algorithm with a bandwidth of 150 km, then clustering areas into areas where cholera incidence is positively sensitive (red), negatively sensitive (blue) and insensitive (white) to El Ni?o events. Callouts indicate major reported outbreaks of the 2015–16 cholera season (SI Appendix, 1. SI Materials and Methods). (B) Kernel density (violin) plot of cases per 10,000 in different El Ni?o-sensitive regions during El Ni?o and non-El Ni?o years. Black circles are grid cell-level medians ± 1 SD and blue diamonds are grid-cell level means. (C) Overlay of El Ni?o sensitive clusters from holding out each El Ni?o or non-El Ni?o pair of years with negatively sensitive clusters = ?1 (blue) and positively sensitive clusters = 1 (red).

  2. Fig. 3.

    Association between cholera and rainfall by river basin. (A and B) River basin-level rainfall anomalies (anomalies smaller than ±5% not shown) (A) and (log) cholera anomalies (B) between El Ni?o and non-El Ni?o years. (C) River basin-level cholera incidence anomalies by region and the strength of rainfall anomalies. Positive cholera anomalies are associated with negative rainfall anomalies (lowest quartile) in every region and positive rainfall anomalies (highest quartile) in East and Southern Africa. *The difference in log cholera incidence between El Ni?o and non-El Ni?o years for a given rainfall anomaly quartile and geographical region is significantly different from the difference in log incidence for areas within that region with rainfall anomalies that fall in the low to mid or mid to high ranges (second and third quartiles).

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