Impact of climate variability on the transmission risk of malaria in northern Côte d'Ivoire

Abstract

Since the 1970s, the northern part of Côte d'Ivoire has experienced considerable fluctuation in its meteorology including a general decrease of rainfall and increase of temperature from 1970 to 2000, a slight increase of rainfall since 2000, a severe drought in 2004-2005 and flooding in 2006-2007. Such changing climate patterns might affect the transmission of malaria. The purpose of this study was to analyze climate and environmental parameters associated with malaria transmission in Korhogo, a city in northern Côte d'Ivoire. All data were collected over a 10-year period (2004-2013). Rainfall, temperature and Normalized Difference Vegetation Index (NDVI) were the climate and environmental variables considered. Association between these variables and clinical malaria data was determined, using negative binomial regression models. From 2004 to 2013, there was an increase in the annual average precipitation (1100.3-1376.5 mm) and the average temperature (27.2°C-27.5°C). The NDVI decreased from 0.42 to 0.40. We observed a strong seasonality in these climatic variables, which resembled the seasonality in clinical malaria. An incremental increase of 10 mm of monthly precipitation was, on average, associated with a 1% (95% Confidence interval (CI): 0.7 to 1.2%) and a 1.2% (95% CI: 0.9 to 1.5%) increase in the number of clinical malaria episodes one and two months later respectively. A 1°C increase in average monthly temperature was, on average, associated with a decline of a 3.5% (95% CI: 0.1 to 6.7%) in clinical malaria episodes. A 0.1 unit increase in monthly NDVI was associated with a 7.3% (95% CI: 0.8 to 14.1%) increase in the monthly malaria count. There was a similar increase for the preceding-month lag (6.7% (95% CI: 2.3% to 11.2%)). The study results can be used to establish a malaria early warning system in Korhogo to prepare for outbreaks of malaria, which would increase community resilience no matter the magnitude and pattern of climate change.

Fig 1. Time series of monthly reported malaria cases from 2004 to 2013.

The dots represent monthly counts of malaria cases attending the four facilities while the line has been obtained using a lowess smoother with a bandwith of 0.05.

Fig 2. Time series of monthly reported malaria cases per health centre.

a) centre 1 = CSI AN NOUR, b) centre 2 = HB TORGO, c) centre 3 = IP SOBA, d) centre 4 = IP TENEMANGA. The dots represent monthly counts of malaria cases attending the respective facility while the lines were obtained using a lowess smoother with a bandwith of 0.05.

Fig 3. Distribution of monthly malaria counts across the years 2004–2013 in Korhogo.

Fig 4

Time series of annual (Fig 4A) and average monthly (Fig 4B) rainfall and malaria cases over the period 2004–2013.

Fig 5

Time series of average annual (Fig 5A) and monthly (Fig 5B) temperature and malaria cases over the period 2004–2013.

Fig 6. Annual means of NDVI and malaria cases over 2004–2013.