Early Warning of Malaria Epidemics in African Highlands Using <I>Anopheles</I> (Diptera: Culicidae) Indoor Resting Density

Abstract

Several highland regions of Africa recently have suffered malaria epidemics. Because malaria transmission is unstable and the population has little or no immunity, these highlands are prone to explosive outbreaks when densities of Anopheles exceed critical levels and conditions favor transmission. If an incipient epidemic can be detected early enough, control efforts may reduce morbidity, mortality, and transmission. Here we present three methods (direct, minimum sample size, and sequential sampling approaches) that could be used to determine whether the household indoor resting density of Anopheles gambiae s.I. has exceeded critical levels associated with epidemic transmission. Data on Anopheles density before, during, and after a malaria epidemic (December 1997-July 1998) in the highlands of southwestern Uganda were evaluated to demonstrate the application of these three approaches. During this epidemic, a density of 0.25 Anopheles mosquitoes per house was associated with epidemic transmission, whereas 0.05 mosquitoes per house was chosen as a normal level expected during nonepidemic months. The direct approach to calculating mean Anopheles density with an allowable error of 20-50% of the mean would require the sampling of 102-16 houses, respectively. In contrast, with only seven houses, the minimum sample size approach could be used to determine whether Anopheles density had exceeded the critical level. This method, however, would result in an overestimation of the risk of an epidemic at low Anopheles density. Finally, a sequential sampling plan could require as many as 50 houses to conclude that risk of an epidemic existed, but this disadvantage is offset by the ability to preset the probabilities of concluding that risk of an epidemic exists at both the critical and normal Anopheles densities. Our study illustrated that it is feasible, and probably expedient, to include monitoring of Anopheles density in highland malaria epidemic early warning systems.

Community awareness about malaria, its treatment and mosquito vector in rural highlands of central Ethiopia

“…Highland malaria epidemic has repeatedly become one of the serious public health problems in many east African countries like Ethiopia, Kenya, Uganda and Tanzania particularly since the late 1980s mainly due to climatic change (1) and other factors related to changes in land use, drug resistance, migration of non-immune people, inadequate health facilities (2,3). In Ethiopia, malaria was previously considered a major public health threat to people living in lowland areas of the country (4).…”

Malaria risk in the highlands of western Kenya: an entomological perspective

“…Temperature and vector density have been used to develop early warning systems based on data from past epidemics (Githeko and Ndegwa 2001;Lindblade, Walker and Wilson 2000). Our results demonstrate that monitoring the larval stages may provide an additional means to assess the likelihood of outbreaks of malaria.…”

Rapid assessment of malaria risk using entomological techniques: taking an epidemiological snapshot

“…Another measure that may prove useful is to estimate the probability of finding a mosquito within a certain sampling effort. For the low mosquito numbers sampled by Lindblade, Walker and Wilson (2000), there was a 95% probability of finding a female An. gambiae in every seven houses sampled.…”

“…If several houses are sampled fruitlessly for mosquitoes, how is it possible to estimate risk? Lindblade, Walker and Wilson (2000) have addressed this question by comparing different sampling approaches and subsequent analyses to obtain estimates of risk of a malaria epidemic. If one uses a statistical approach driven by confidence intervals, then clearly the reliability of the data increases with sampling effort (20% error in risk estimation for 102 houses sampled increasing to 50% error for 16 houses).…”

“…Trapping effort and outcome for malaria. The amount of effort that must be put into sampling has been modelled (Lindblade, Walker and Wilson 2000). The effort required is a combination of the required decision and the population densities of mosquitoes.…”