Characterizing, controlling and eliminating residual malaria transmission

Abstract

Long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) interventions can reduce malaria transmission by targeting mosquitoes when they feed upon sleeping humans and/or rest inside houses, livestock shelters or other man-made structures. However, many malaria vector species can maintain robust transmission, despite high coverage of LLINs/IRS containing insecticides to which they are physiologically fully susceptible, because they exhibit one or more behaviours that define the biological limits of achievable impact with these interventions: (1) Natural or insecticide-induced avoidance of contact with treated surfaces within houses and early exit from them, thus minimizing exposure hazard of vectors which feed indoors upon humans; (2) Feeding upon humans when they are active and unprotected outdoors, thereby attenuating personal protection and any consequent community-wide suppression of transmission; (3) Feeding upon animals, thus minimizing contact with insecticides targeted at humans or houses; (4) Resting outdoors, away from insecticide-treated surfaces of nets, walls and roofs. Residual malaria transmission is, therefore, defined as all forms of transmission that can persist after achieving full universal coverage with effective LLINs and/or IRS containing active ingredients to which local vector populations are fully susceptible. Residual transmission is sufficiently intense across most of the tropics to render malaria elimination infeasible without new or improved vector control methods. Many novel or improved vector control strategies to address residual transmission are emerging that either: (1) Enhance control of adult vectors that enter houses to feed and/or rest by killing, repelling or excluding them; (2) Kill or repel adult mosquitoes when they attack people outdoors; (3) Kill adult mosquitoes when they attack livestock; (4) Kill adult mosquitoes when they feed upon sugar or; (5) Kill immature mosquitoes in aquatic habitats. To date, none of these options has sufficient supporting evidence to justify full-scale programmatic implementation. Concerted investment in their rigorous selection, development and evaluation is required over the coming decade to enable control and, ultimately, elimination of residual malaria transmission. In the meantime, national programmes may assess options for addressing residual transmission under programmatic conditions through pilot studies with strong monitoring, evaluation and operational research components, similar to the Onchocerciasis Control Programme.

Figures

Figure 1

The importance of feeding upon humans as a determinant of malaria transmission and vector control impact. A and B: Simulated relationship between malaria transmission intensity mediated by an Anopheles mosquito population and the proportion of blood meals that these vectors obtain from humans, in the presence and absence of long-lasting insecticidal nets (LLINs) with a mean nightly usage rate of 80%, presented with a linear (A) and logarithmic (B) vertical axis (Adapted from reference 11). C: Frequency distribution for the mean proportion of blood meals obtained from humans for the 33 most important locally dominant malaria vectors worldwide as reviewed in reference [7].

Figure 2

Global map of the highest human blood index among nationally important vectors, as extracted from reference 7 and kindly drafted by Fredros Okumu and Alex Limwagu.

Figure 3

Progressive dramatic reduction of mosquito survival and infection probability as an increasing proportion of available blood meals are covered with LLINs or IRS. The probability curves presented represent the outputs of simulations implemented exactly as previously described [14] at 0, 20, 40 and 60% biological coverage of all available blood resources [10, 13] with LLINs that kill 60% of all mosquitoes encountering them.

Figure 4

A schematic illustration of the differing trajectories of impact of an intervention upon malaria transmission by a vector population under the distinctive scenarios of either (A) Stable limitation of sustained impact arising from expression of pre-existing behavioural traits within a resilient vector population, or (B) Failure of impact and resurgence of malaria transmission when, either intervention programme implementation quality and coverage weakens, or selected behavioural or physiological traits emerge within an increasingly resistant, rebounding vector population[31].

Figure 5

A schematic illustration of how mosquitoes may survive despite high coverage of long-lasting insecticidal nets or indoor residual spraying by entering, but then rapidly leaving houses protected with LLINs or IRS without exposing themselves to lethal doses of the active ingredients, and then continuing to forage until an unprotected blood host is found[–41].

Figure 6

Frequency distribution of the preferred biting times for 25 separate populations of 11 Latin AmericanAnophelesspecies, which were classified as either: 1) potent primary vectors; 2) weak, incidental or secondary vectors; or 3) non-vectors (Adapted from reference[19]).

Figure 7

Estimates of the proportion of human exposure to African malaria vector populations that occurs indoors for both unprotected residents (πh,i) and users of long-lasting insecticidal nets (πh,i,n), from field sites across eastern, southern and western Africa[16], as previously calculated [71, 72] and presented in summary form [29]. Original data kindly provided by Bernadette Huho, Olivier Briët, Aklilu Seyoum, Chadwick Sikaala, Nabie Bayoh, John Gimnig, Fredros Okumu, Diadier Diallo, Salim Abdulla and Tom Smith.

Figure 8

Historical estimates of the proportion of human exposure to Latin American malaria vector populations in Colombia that would have occured indoors for both unprotected residents (πh,i) and users of modern long-lasting insecticidal nets (πh,i,n), calculated as originally described[19, 20], except for the breakdown of indoor exposure into the fractions that would and would not be prevented by net use[71, 72].

Figure 9

Estimates of the proportion of human exposure to Asian malaria vector populations that occurs indoors for both unprotected residents (πh,i) and users of long-lasting insecticidal nets (πh,i,n), from the Solomon Islands [75], Laos [76], Iran [17] and Myanmar [77, 78], calculated as previously described [71, 72], except that in the Iranian examples, indoor and outdoor biting densities were assumed to be equal because they were not reported separately [17]. Original data from the Solomon Islands and Myanmar were kindly provided by Hugo Bugoro, Tanya Russell, Frank Smithuis and Nick White.

Figure 10

A graphic illustration of the estimated maximum achievable biological coverage of all blood resources (Cv,max) utilized by the vector species described in Figures1,2,7,8and9, for which estimates of both the proportion of blood meals obtained from humans (Qh) and the proportion of human blood meals obtained indoors (πh,i) were available. The width of the grey rectangles relative to that of the white squares represents the limit of personal protection and derived community-wide reduction of mutual human-vector exposure, while their relative area represents the achievable limit of biological coverage of all blood resources that determines the extent to which the density and survival of the vector population can be controlled [8, 10, 11, 13].

Figure 11

A schematic representation of the sequential layers of interventions required to eliminate malaria from the most staunchly endemic regions of Africa, adapted from references [64] and [29]. White arrows crudely illustrate the impacts of intervention strategies for which reasonable experience and understanding already exists (suppression of high transmission with LLINs or IRS and elimination of sparse residual human parasite reservoirs with drugs). Dark arrows illustrate the potential impact of interventions that urgently need to be developed and evaluated to either maximize impact of existing control measures (adequate and sustainable financing, long-term resistance management) or make more meaningful progress towards elimination (programmatic-scale interruption of residual transmission by behaviourally resilient and/or resistant mosquitoes using novel vector control tools, possibly supplemented with vaccines or chemoprophylaxis).

Figure 12

A schematic summary of how specific behaviours enable mosquito populations to survive and mediate residual malaria transmission despite high coverage of long-lasting insecticidal nets and/or indoor residual sprays, and how these might be tackled with new or improved vector control strategies[27, 84, 85].

Figure 13

A schematic representation of how various alternative strategies for targeting vector mosquitoes when they utilize specific resources can suppress (Green) or redistribute, stabilize and even increase (Red) malaria transmission, depending on values for measurable behavioural parameters of the mosquito population and its interaction with interventions [, , , –15, 80]. Red and green ovals indicate effects upon malaria transmission, with the magnitude of their impact indicated by their size. The relative magnitude of persisting transmission after intervention (ψ) is expressed as a function of: (1) the utilization rate (α) or probability (Q) of targetable subsets (x) of a defined resource (R, which may be specified as blood (v), resting sites (r), sugar (s) or aquatic larval habitat (a)); (2) the coverage of that resource subset (Rx) achieved ; (3) the mortality probability (μ) of mosquitoes utilizing covered forms of that resource subset; where human blood is the targeted resource, (4) the personal protection (ρ) afforded as a result of repellence, irritance or physical deterrence (Δ) combined with fast-acting toxicity that occurs before the mosquito can feed (μpre); and (5) the proportion of exposure that would otherwise occur when that intervention is used . For all parameters described, values approaching or exceeding one are considered high and values approaching zero are considered low. The subscripts h, l and i refer to the subsets human, livestock and indoors.