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Volume 17, Number 11—November 2011

Research

Dynamics of Cholera Outbreaks in Great Lakes Region of Africa, 1978–2008

Didier Bompangue Nkoko, Patrick Giraudoux, Pierre-Denis Plisnier, Annie Mutombo Tinda, Martine Piarroux, Bertrand Sudre, Stephanie Horion, Jean-Jacques Muyembe Tamfum, Benoît Kebela Ilunga, and Renaud PiarrouxComments to Author 
Author affiliations: Université de Franche-Comté, Besançon, France (D. Bompangue Nkoko, P. Giraudoux, M. Piarroux, B. Sudre); Ministère de la Santé Publique, Kinshasa, Democratic Republic of Congo (D. Bompangue Nkoko, A. Mutombo Tinda, J.-J. Muyembe Tamfum, B. Kebela Ilunga); Royal Museum for Central Africa, Tervuren, Belgium (P.-D. Plisnier); Joint Research Centre of the European Commission, Ispra, Italy (S. Horion); Université de Kinshasa, Kinshasha (J.-J. Muyembe Tamfum); Université de la Méditerranée, Marseille, France (R. Piarroux); University Hospital La Timone, Marseille (R. Piarroux)

Main Article

Figure 4

Seasonal patterns/components of cholera outbreaks for 5 hotspots in the African Great Lakes region, 2002–2008. Hotspots are Goma (A), Bukavu (B), Uvira (C), Kalemie (D), and Upper Congo Basin (E). Blue indicates the weekly average precipitation (in mm); red indicates the seasonal component of the total number of patients after the time series was decomposed into a trend and seasonal and residual components by using a seasonal-trend decomposition procedure based on loess regression. Horizontal gr

Figure 4. Seasonal patterns/components of cholera outbreaks for 5 hotspots in the African Great Lakes region, 2002–2008. Hotspots are Goma (A), Bukavu (B), Uvira (C), Kalemie (D), and Upper Congo Basin (E). Blue indicates the weekly average precipitation (in mm); red indicates the seasonal component of the total number of patients after the time series was decomposed into a trend and seasonal and residual components by using a seasonal-trend decomposition procedure based on loess regression. Horizontal gray lines indicate seasonal component = 0.

Main Article

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