Research Article: Hitting Hotspots: Spatial Targeting of Malaria for Control and Elimination

Date Published: January 31, 2012

Publisher: Public Library of Science

Author(s): Teun Bousema, Jamie T. Griffin, Robert W. Sauerwein, David L. Smith, Thomas S. Churcher, Willem Takken, Azra Ghani, Chris Drakeley, Roly Gosling

Abstract: Teun Bousema and colleagues argue that targeting malaria “hotspots” is a highly efficient way to reduce malaria transmission at all levels of transmission intensity.

Partial Text: Current malaria elimination guidelines are based on the concept that malaria transmission becomes heterogeneous in the later phases of malaria elimination [1]. In the pre-elimination and elimination phases, interventions have to be targeted to entire villages or towns with higher malaria incidence until only individual episodes of malaria remain and become the centre of attention [1]. With increasing evidence of clustering of malaria episodes within villages, we argue that there is an intermediate step. Heterogeneity in malaria transmission within villages is present long before areas enter the pre-elimination phase, and identifying and targeting hotspots of malaria transmission should form the cornerstone of both successful malaria control and malaria elimination.

Variation in the risk of malaria between villages in endemic regions has long been recognized [2]–[4]. This variation is common for many infectious and parasitic diseases where a small number of human hosts are most frequently or most heavily infected while the majority of a local population carry few or no infections [5]–[8]. In malaria, this is exemplified by a study in Dielmo, Senegal, where children were monitored daily during their first 2 years of life. Some children suffered only one episode of clinical malaria, whilst others suffered up to 20 episodes [9]. In Kenya, researchers noted that malaria exposure could not be homogenous as malaria incidence did not follow a Poisson distribution, a phenomenon they describe as over-dispersion [10]. Over-dispersion is commonly recognized in other infectious diseases, where a small proportion (20%) of the population is responsible for the majority (80%) of transmission, the so-called “20/80 rule” [8],[11]–[13].

Two related but distinct geographical units in malaria transmission can be defined: (1) The World Health Organization defines a focus of malaria transmission as a defined and circumscribed locality situated in a currently or former malarious area containing the continuous or intermittent epidemiological factors necessary for malaria transmission. Foci of malaria transmission can be classified as residual active, residual nonactive, cleared up, new potential, new active, endemic, or pseudofoci [1]. In more academic terms, an active focus of malaria transmission is a geographical area that supports malaria transmission, where the local Anopheles population sustains the basic reproductive rate (R0; average number of secondary infections arising in a susceptible population as a result of a single individual with malaria over the course of their malaria infection) at a level above 1 [16]. Its size depends on the mosquito breeding site that forms the centre of the focus and the effective dispersal range of vector mosquitoes, which is several kilometres. The border is the furthest location where malaria is still supported by the breeding site. (2) A hotspot of malaria transmission is defined as a geographical part of a focus of malaria transmission where transmission intensity exceeds the average level. Several hotspots of malaria transmission may be present in a single focus of malaria transmission. Micro-epidemiological conditions for malaria transmission are favourable in a hotspot of malaria transmission, resulting in R0 estimates that exceed the average for the focus of malaria transmission. The size of a hotspot of malaria transmission is variable but typically <1 km2 and smaller than the maximum dispersal range of vector mosquitoes; its borders are defined by the distance from the centre of the hotspot where transmission intensity is no longer (statistically significantly) higher than the average for the focus of malaria transmission [14],[21]. Heterogeneity in mosquito exposure is key to understanding the differences between foci and hotspots of malaria transmission and their implications for malaria control. Individuals who are bitten most often are most likely to be infected and can amplify transmission by transmitting the malaria parasites to a large number of mosquitoes. Estimates of R0 are very susceptible to variations in mosquito biting behaviour. R0 may increase considerably as a consequence of heterogeneity in this behaviour [8],[12]; the susceptibility of R0 to heterogeneous bitingthis is illustrated by Table 1 where estimates of R0 increased 1.5- to 4.5-fold as a consequence of introducing heterogeneous biting into a mathematical model of malaria [24] in four villages exposed to moderate transmission intensity in northern Tanzania [14]. Having argued that hotspots should be targeted, the next obvious question is how can they be identified? Spatial patterns in malaria transmission have been described using (combinations of) micro-epidemiological elevations in malaria incidence [11],[14],[21],[22],[27], asymptomatic parasite carriage [21],[22], reported fever [28], drug use [28], serological responses to malaria-specific antigens [14],[29],[30], mosquito abundance [14],[30], and exposure to infected mosquitoes [14],[30]. Environmental models are very valuable in defining (larger) foci of malaria transmission [31], but currently have limited resolution in identifying small-scale hotspots of malaria transmission within foci of malaria transmission [14],[21]. Three important arguments on hotspots need to be addressed. Firstly, are hotspots stable over time? This is important for practical reasons. Some consistency in the geographical location of hotspots would make implementation of control methods much easier. The predominant observation is that hotspots are remarkably stable even when the intensity of transmission declines [14],[21]–[23],[26],[39],[40]. However, clusters of higher clinical incidence may vary with time [21],[39], especially in settings where outbreaks are related to movement patterns of infected human parasite carriers [22]. In coastal Kenya, evidence was found for the presence of stable and unstable hotspots within the same study population [21]. Spatially targeted interventions will not replace the current practice where LLINs and intermittent preventive treatment (IPT) are preferentially provided to young children and pregnant women, groups that are at the highest risk of severe disease. Rather, it will supplement this approach that aims to reduce severe morbidity and mortality with an approach that specifically aims to reduce malaria transmission. Following scaling up in moderate and low transmission settings where malaria transmission is highly heterogeneous, hotspot-targeted interventions form a logistically attractive alternative to untargeted interventions that may need coverage levels nearing 100% to drive transmission lower [8],[12],[14]. To be financially attractive, the costs of detecting hotspots need to be outweighed by the savings made by targeting only a proportion of the total population. For low transmission areas such as those in pre-elimination or elimination phases of malaria control (i.e., malaria incidence below 5 episodes per 1,000 person-years at risk) and in areas that have succeeded in elimination and are preventing re-introduction, the outcome of this equation is very likely to support hotspot-targeted interventions [25]. Hotspot-targeted interventions will also accelerate malaria control in areas of higher endemicity but will require a low-cost and operationally attractive detection system to be financially attractive. The nature of malaria transmission in hotspots, intense mosquito exposure, and high levels of (asymptomatic) parasite carriage in the human population, will require a combination of interventions that target both the human and vector hosts. In addition to scaling up conventional vector control tools such as LLINs and IRS, several less commonly used tools may be particularly suited for hotspots. Malaria hotspots appear to maintain malaria transmission in low transmission seasons and are the driving force for transmission in the high transmission season. Targeting the hotspots would mean the most infected and most diseased households would be prioritized with the added benefits of reducing transmission to the whole community. Identifying the hotspots is possible by mapping asymptomatic carriers or using serological tools. Treating hotspots by ensuring high coverage of interventions for a few households is likely to be easier and much more efficient, and may allow for more complicated interventions than using untargeted approaches. The recent successes of scaling up interventions for impact on malaria have revealed the policy gap of what to do afterwards when coverage is good yet malaria transmission continues. In this paper we have argued that the next evidence-based step is to tackle malaria hotspots. Although knowledge gaps exist, we argue that hotspot-targeted interventions should take place at all transmission levels where resources are sufficient and rapid reductions in malaria transmission will be seen. Source: http://doi.org/10.1371/journal.pmed.1001165