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In Africa, malaria is predominantly a rural disease where agriculture forms the backbone of the economy.
V
arious agro-ecosystems and crop production systems have an impact on mosquito productivity, and hence malaria
transmission intensity. This study was carried out to determine spatial and temporal variations in anopheline mosquito
population and malaria transmission intensity in five villages, representing different agro-ecosystems in Mvomero dis-
trict, Tanzania, so as to provide baseline information for malaria interventions. The agro-ecosystems consisted of irri-
gated sugarcane, flooding rice irrigation, non-flooding rice irrigation, wet savannah and dry savannah. In each setting,
adult mosquitoes were sampled monthly using Centers for Disease Control and Prevention (CDC) light traps from
August 2004 to July 2005. A total of 35,702 female mosquitoes were collected.
Anopheles gambiae
sensu lato was the
most abundant (58.9%) mosquito species.
An. funestus
accounted for 12.0% of the mosquitoes collected. There was a
substantial village to village variation and seasonality in the density of Anopheles mosquito population, with peaks in
May towards the end of the warm and rainy season. Significantly larger numbers of
anophelines
were collected from tra-
ditional flooding rice irrigation ecosystem (70.7%) than in non-flooding rice irrigation (8.6%), sugarcane (7.0%), wet
savannah (7.3%) and dry savannah (6.4%). The overall sporozoite rates for
An. gambiae
and
An. funestus
were 3.4%
and 2.3%, respectively. The combined overall sporozoite rate (
An. gambiae
+
An. funestus
) was 3.2%. The mean annual
entomological inoculation rate (EIR) for
An. gambiae
s.l. was 728 infective bites per person per year and this was sig-
nificantly higher in traditional flooding rice irrigation (1351) than in other agro-ecosystems. The highest EIRs for
An.
gambiae
s.l. and
An. funestus
were observed during May 2005 (long rainy season) and December 2004 (short rainy sea-
son), respectively. The findings support the evidence that malaria transmission risk varies even between neighbouring vil-
lages and is influenced by agro-ecosystems. This study therefore, demonstrates the need to generate spatial and tempo-
ral data on transmission intensity on smaller scales taking into consideration agro-ecosystems that will identify area-spe-
cific transmission intensity to guide targeted control of malaria operations. |
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