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Household Possession and Use of Insecticide-Treated Mosquito Nets in Sierra Leone 6 Months after a National Mass-Distribution Campaign
research-article
Author(s):
Adam Bennett
1
,
* ,
Samuel Juana Smith
2 ,
Sahr Yambasu
3 ,
Amara Jambai
4 ,
Wondimagegnehu Alemu
5 ,
Augustin Kabano
6 ,
Thomas P. Eisele
1
Publication date (Electronic):
29 May 2012
Journal:
PLoS ONE
Publisher:
Public Library of Science
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Abstract
Background
In November 2010, Sierra Leone distributed over three million long-lasting insecticide-treated nets (LLINs) with the objective of providing protection from malaria to individuals in all households in the country.
Methods
We conducted a nationally representative survey six months after the mass distribution campaign to evaluate its impact on household insecticide-treated net (ITN) ownership and use. We examined factors associated with household ITN possession and use with logistic regression models.
Results
The survey included 4,620 households with equal representation in each of the 14 districts. Six months after the campaign, 87.6% of households own at least one ITN, which represents an increase of 137% over the most recent estimate of 37% in 2008. Thirty-six percent of households possess at least one ITN per two household members; rural households were more likely than urban households to have ≥1∶2 ITN to household members, but there was no difference by socio-economic status or household head education. Among individuals in households possessing ≥1 ITN, 76.5% slept under an ITN the night preceding the survey. Individuals in households where the household head had heard malaria messaging, had correct knowledge of malaria transmission, and where at least one ITN was hanging, were more likely to have slept under an ITN.
Conclusions
The mass distribution campaign was effective at achieving high coverage levels across the population, notably so among rural households where the malaria burden is higher. These important gains in equitable access to malaria prevention will need to be maintained to produce long-term reductions in the malaria burden.
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Most cited references25
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Preventing Childhood Malaria in Africa by Protecting Adults from Mosquitoes with Insecticide-Treated Nets
Gerry F. Killeen, Tom Smith, Heather M Ferguson … (2007)
Introduction The massive malaria burden in Africa merits particular attention as the world struggles to realize a better life for the poorest [1,2]. The Anopheles mosquitoes that act as vectors for human Plasmodium parasites must access sugar, blood, and aquatic oviposition sites to complete their life cycle and maintain parasite transmission. The availability of such ecological resources to mosquitoes has long been recognized as a crucial determinant of malaria transmission [3], but quantitative understanding of this process, as well as viable means to prevent it, remain poorly developed compared with other disease [4] and pest systems [5]. Recent theoretical work highlights the enormous influence of blood source and aquatic habitat availability in determining malaria transmission intensity, disease burden, and their responsiveness to various forms of control [6–12]. Here we apply field-parameterized kinetic models of mosquito host availability [11,13] to identify important shortcomings of current global targets for delivering insecticide treated nets (ITNs) [2,14,15], the most important vector control tool in Africa today. Not only does the model outline the limitations of existing strategies that emphasize targeting of vulnerable groups such as young children and pregnant women [16–18], it also indicates how complementary strategies to promote coverage of whole populations, including nonvulnerable adults and older children [19], will achieve greater and more equitable reduction of disease burden than otherwise would be possible. Insecticide-treated nets (ITNs) represent a practical and effective means to prevent malaria in Africa [20], so scaling up coverage to at least 80% use by young children and pregnant women by 2010 is a consensus target of the Millennium Development Goals (MDGs), the Roll Back Malaria Partnership, and the US President's Malaria Initiative [2,14,15]. Targeting individual protection to these vulnerable groups [16–18] is a well-founded and explicitly accepted priority of all three initiatives, because these groups bear the highest risk of morbidity and mortality from malaria. However, this strategy largely ignores the potentially greater community-wide benefits of broader population coverage [19], and no explicit resources, targets, or strategies have been proposed to achieve these benefits. ITNs can protect not only the individuals and households that use them, but also members of the surrounding community [19,21–26]. This is because they kill adult mosquitoes directly or force them to undertake longer, more hazardous foraging expeditions in search of vertebrate blood and aquatic habits [11]. Plasmodium falciparum, the malaria parasite responsible for the bulk of deaths in Africa, requires at least 8 d to develop from imbibed gametocytes into mature sporozoites within the salivary glands of the vector mosquito. This means that most malaria transmission is carried out by mosquitoes that are at least 10 d old and have taken several previous blood meals at intervals of 2–5 d [27,28]. By even modestly increasing mosquito mortality while they attempt to feed on humans, ITNs can greatly reduce the number of mosquitoes that survive repeated hazardous encounters with protected humans [11]. Also, the excito-repellent properties of ITNs can reduce the frequency with which mosquitoes successfully acquire blood, often diverting them to feed on other mammals that do not host the malaria parasite, resulting in greatly reduced prevalence of sporozoite infection [11]. This theoretical rationale is strongly supported by detailed observations from experimental hut studies [29–34] and from larger village-scale trials: ITNs have been clearly shown to reduce malaria risk among unprotected individuals by suppressing the density [35–37], survival [35–37], human blood indices [38,39], and feeding frequency [39] of malaria vector populations. Large reductions of transmission are required to appreciably reduce malaria burden in most of Africa [17,40], particularly in the longer term as exposure and immunity re-equilibrate [41]. ITNs can address this challenging need through direct personal protection and area-wide suppression of the malaria transmission intensity that benefits even nonusers. It has been suggested that such communal benefits can make large impacts on disease burden only if appreciable levels of coverage are achieved in the human population as a whole [11,12,19], but precise coverage targets for achieving this remain to be determined. So how much coverage is enough to protect individuals who do not use an ITN? Methods Overview Here we used recently developed kinetic models of mosquito behaviour and mortality [11,13] to answer this question by considering the impact of ITNs on human host availability and feeding hazards to mosquitoes, as well as the consequences of such changes for malaria transmission intensity. Protection was estimated in terms of protection against exposure to infectious mosquito bites, expressed as the relative change in the entomological inoculation rate (EIR). EIR is a proven epidemiological indicator of malaria transmission intensity and a key determinant of disease burden [17,40]. Two common but ecologically distinct African malaria transmission systems are considered. First, we modelled an Anopheles gambiae Giles or An. arabienis Patton (sibling species from the same species complex known as An. gambiae sensu lato) population with access to human blood only. Second, we considered An. arabiensis populations in the presence of abundant cattle, which can act as alternative blood sources. An. gambiae greatly prefers humans, but An. arabiensis will readily feed upon cattle [42,43], so populations of these species respond quite differently to increasing ITN coverage, with malaria transmission by the latter typically being lower to begin with but less sensitive to control with ITNs [11]. In both transmission systems we considered ITNs with properties typical of those evaluated in rigorous clinical trials [20] or those of emerging technologies with improved operational durability [44–47]. Note that coverage is expressed as the proportion of the total human population using an ITN each night, rather than in terms of ownership, because this value is the most direct indicator of both personal and communal protection. Figure 1 provides an overview of how mosquito behaviour and survival were modelled as a function of host availability, ITN properties, compliance, and coverage. The approach described is essentially a behaviourally explicit extension of existing vector biodemography [48] models, which predict epidemiologically relevant outcomes such as exposure to transmission (the biodemography–epidemiology model). The principles and utility of the biodemography–epidemiology models we have used [27,49,50], as well as several others that are based on similar assumptions [6,18,28,51], are well established. Notably, this family of models realistically assumes that mosquito behaviour cycles between host seeking, feeding, resting, oviposition-site seeking, oviposition, and back to host seeking again [51]. Similarly to recent analyses of the importance of oviposition [7,8,10] and host acquisition [11,12] processes, here we explicitly modelled the underlying behavioural events that determine the input parameters of these biodemographic processes (the behaviour–biodemography model). Detailed consideration of mosquito behaviour and mortality upon encounter with individual hosts (the individual-level submodel) allows simulation of the impact of ITNs upon the foraging requirements and risks for mosquito populations at the community level (the community-level submodel). This hierarchical approach links individual- and community-level submodels into an integrated behaviour–biodemography model, which drives the outcome of the biodemography–epidemiology model and allows the influence of ITNs upon malaria transmission intensity to be estimated in terms of EIR experienced by both users and nonusers [11,27,50]. Figure 1 A Schematic Outline of the Two-Tier Model Used for This Analysis, Adapted from Previous Detailed Descriptions A detailed model of mosquito behaviour and survival as a function of host availability, ITN properties, compliance, and coverage [11,13] was used to estimate the key biodemographic parameters that determine malaria transmission intensity (behaviour–biodemography model). This model allowed the influence of ITN usage upon malaria transmission intensity to be estimated (biodemography–epidemiology model) in terms of EIR experienced by both users and nonusers [11,27,50]. All terms and symbols are defined in detail elsewhere [11,27,50,52] and are summarized in Methods. The specific modelling approach described here is almost identical to our recent exploration of the optimal properties of ITNs as a function of local ecology [11], apart from subtle improvements in terms calculating mosquito diversion, mortality, and feeding probabilities per host encounter. It is also similar to and consistent with the approaches of others [6,12] but accounts for the fact that ITNs can act only during times of the night when they are actually in use, so that their overall protection is also influenced by subtle variations in the behavioural interactions between humans and mosquitoes [13]. This model has already been evaluated through improved iterations in terms of sensitivity to variations in the assumed parameter values for the insecticidal and excito-repellent properties of ITNs [11], the survival rate of mosquitoes while foraging for resources [11], the innate resource preferences of vector populations [11,50,52], and the availability of those resources, including oviposition sites [50] and alternative blood meal hosts [11,50]. While the analysis outlined here could be implemented with either of the recently developed (and perhaps more elegant) alternative models [6,12], this particular form captures all of the same processes without necessitating the mathematical subtleties of integration, differentiation, equilibrium analysis, or limits. While these are inherently valuable tools for mathematical modelling, they often constitute “black boxes” to nonmathematicians, including several authors of this article. We therefore chose a model that does not require mathematical complexities that might limit accessibility to some of the field biologists and epidemiologists for whom this analysis is most relevant. The model is presented as a downloadable spreadsheet (see Protocol S1) and has proven valuable for teaching the ecological basis of malaria epidemiology and control to students in both the developed and developing world. Modelling Mosquito Behaviour and Mortality at the Individual Level Here we describe a submodel of behavioural and mortality processes that occur at the level of individual mosquitoes seeking, encountering, attacking, and feeding upon individual blood hosts. Another important simplification to consider is that, like most deterministic malaria transmission models, our approach assumed a “malaria in a bottle” scenario in which populations of identical parasites, vectors, and hosts are mixed homogenously within an enclosed system [53]. One important corollary of this assumption is that well-established variations of vulnerability to malaria infection within human populations [16,17] or associated variations in attractiveness and availability to mosquitoes [9,54–56] are not explicitly modelled. As defined previously [52], the availability (a) of any host (j) of any species (s) is the product of the rate at which individual vectors encounter it (ɛs,j) and the probability that, once encountered, they will feed upon it (φs,j): Note that this kinetic definition of availability as a rate per unit time is consistent with applications of the same term to acquisition of oviposition sites [10], the term attraction rate for blood sources [6,57], and the terms feeding rate and oviposition rate for both resources [8,12]. We considered successful feeding as just one of three possible outcomes of a host encounter by a female vector, the other two being death while attempting to feed and diversion to seek another host (Figure 1). We considered this a two-stage process in which the vector first either attacks the encountered host or is diverted away and searches for another, the probabilities of which we denote as γ and Δ, respectively. This definition of diversion includes the combined effects of noncontact repellency and contact-mediated irritancy, often referred to as excito-repellency [58,59]. Considering mean values for hosts of any given species (s), the sum of these two probabilities is: We then considered the second stage of the blood acquisition process, namely feeding. Knowing the probabilities that the vector will either feed successfully (φs) or die in the attempt (μs) per attack (rather than per encounter) allowed us to calculate the probability of a successful feed per encounter: Specifically, the cases of cattle (c) and unprotected humans (h,u) were dealt with in a straightforward manner as follows, where Δu and μu represent a common parameter value for both types of host (Table 1): Table 1 Behavioural and Host Availability Input Parameters for Both Vector Species Personal protection measures such as bed nets, repellents, or domestic insecticide use were envisaged as three possible outcomes, the probabilities of which sum to 1: For a vector that would normally choose to feed upon an encountered unprotected human with a probability of φh,u, the presence of a net or other intervention is expected to influence this probability for protected humans (φh,p) as a function of the excess probability of diverting (Δp) and killing (μp) that vector (Figure 1). The combined baseline and net-induced probabilities of diversion (Δu + p ) or mortality (μu + p) were calculated as follows: and These parameters allowed us to calculate the feeding probability for a human who always uses and is protected by a net (φh,p): These equations are parameterized using data from experimental hut trials in which the human participants slept within the net throughout the period of data collection (Table 1). However, very few human beings spend their entire day asleep or using a net [13] so the true probability of feeding upon a typical net user ( ) is calculated by weighting φh,u and φh,p according to the proportion of normal exposure during which the host is actually covered (πi): Equations 5-7 differ slightly from those previously proposed [11], which treated diversion and killing as independent events, conditional on the host having and using a net. At low values of πi these changes relative to [11] make little difference, but the model described here is more realistic at high values of πi . Extrapolating Impacts of Insecticide-Treated Nets to the Community Level Given the above submodel for the interactions of mosquitoes with individual mammalian hosts, it was possible to extrapolate the likely large-area effects of these small-scale influences on entire vector populations and the human communities they feed upon. For any given number of cattle (Nc), unprotected humans (Nh,u), and protected humans (Nh,p), the mean seeking interval for vertebrate hosts (ηv) can be calculated as the reciprocal of total host availability (A) [52], using estimates of these feeding probabilities and their corresponding encounter rates, adapting Equation 1 from our original formulation [50]: where As refers to the total availability of all hosts of species s. In this case, the species or species categories considered were unprotected humans (h,u), protected humans (h,p), and cattle (c). Values for ac and ah,u (previously ah [50]) were estimated exactly as described previously [50] and ah,p was calculated as follows: where λp is the relative availability of protected versus unprotected hosts, estimated in terms of the ratio of their feeding probabilities: Foraging for resources is an intrinsically dangerous undertaking for mosquitoes, and it is commonly assumed that survival during these phases is lower than while resting in houses [6,60]. We adapted Equation 3 from our previous formulation [50] to estimate the survival rate per feeding cycle (Pf) as the product of the probability of surviving the eventual attack on a host that may be protected (Pγ) and the probabilities of surviving the gestation (g), oviposition site-seeking (ηo), and vertebrate host-seeking (ηv) intervals, with distinct daily survival probabilities for the resting (P), foraging for either oviposition sites or vertebrate hosts (Pov), and attacking (Pγ) phases: The mean probability of mosquitoes surviving their eventual chosen host attack (Pγ) was calculated assuming that the proportion of all attacks that end in death is the sum of the mortality probabilities for attacking protected and unprotected hosts, weighted according to the proportion of all encounters that will occur on such hosts. Assuming that protection does not affect encounter rates, and that these rates are proportional to availability when unprotected, we applied this weighting approach to estimate total attack-related mortality rate and consequent survival as follows: Similarly, the human blood index is calculated as the proportion of total host availability accounted for by humans [52], similarly to Equation 9: The EIR for protected and unprotected individuals was then calculated from the total number of infectious bites upon humans that occur in the population as a whole (β E) [27,49], the share of the total human availability represented by that group, and the population size of that group: where β is the mean number of infectious human bites each emerging mosquito takes in its lifetime and E is the emergence rate of mosquitoes [27]. Dividing Equation 16 by Equation 15, substituting with Equation 10, and rearranging also leads to an intuitively satisfactory solution, consistent with independently formulated models of personal protection [13]: Otherwise, we modelled malaria transmission exactly as previously described [50]. Note that this model has been adapted [11,50] from its original formulation [27] to account for superinfection of mosquitoes [28] and daily time increments to smooth the effects of changing host availability patterns on feeding cycle length [50]. For ease of comparison and interpretation, the impact of ITNs is presented in terms of the relative transmission intensity EIR C /EIR 0 at a given coverage level (C; note distinction from c, which denotes cattle hosts) as a result of personal and communal protection amongst users and nonusers: Baseline Mosquito Behaviour, Host Availability, and Survival Parameters The parameter definitions and values used to implement this analysis are summarized in Table 1. Namwawala, in the Kilombero Valley, southern Tanzania is the primary centre for parameterising our model because of the exceptionally detailed quantitative characterisation of malaria transmission and vector biodemography in this village and the surrounding area. This is a holoendemic village with intense seasonal transmission, stable high parasite prevalence in humans, and a heavy burden of clinical malaria [61–68]. At this site the bulk of transmission is mediated by An. gambiae sensu lato (of which the main species involved in transmission is An. arabiensis) and transmission intensity has been modelled with available field data [27,49]. As previously described [27,49], we based our estimate of human population size [62] approximately upon those reported for this particular village during the early 1990s. Nevertheless, we used a human population size of 1,000 and, where relevant, a bovine population of the same size so that the EIR experienced by users and nonusers could be easily calculated at net coverage levels approaching 0% and 100%. By setting coverage to 0.001 or 0.999, this model simulates a single user or nonuser in the population, respectively. Infectiousness of humans (κ) is set to 0.030, reflecting a more precise recent estimate [69] than was available previously [61,63]. In a typical holoendemic scenario, the infectiousness of the human population is thought to be largely insensitive to reductions in transmission intensity [69]. In the interests of making conservative and generalizable predictions, we assumed that increasing coverage with ITNs will not affect κ [69], even though reduction of κ is likely at EIR values below 10 infectious bites per person per year [56]. We set mean daily survival of the resting phase (P) at 0.90, reflecting a median value of daily survival at four well-characterised holoendemic sites [27] and estimated daily indoor survival for An. gambiae s.l. in Tanzania [70]. As previously described, the daily survival rate of mosquitoes while foraging for blood or oviposition sites (Pov) was set at 0.80, representing a median value of plausible field values [11]. The results of experimental hut studies [34] were combined with host-choice evaluations [71] and appropriate analytical models [50,52] to define the attack and mortality probabilities of An. arabiensis encountering cattle or humans: we set the probability that An. arabiensis will attack unprotected cattle or humans (γu), conditional upon encountering them, to be 0.90 and the chance that they will die in the attempt (μu) at 0.10. Using these parameters and Equation 3, we calculated that, for An. arabiensis, the overall feeding probability upon either cattle (φc) or unprotected humans (φh,u) would be 0.81, a value similar to previous estimates of approximately 0.80–0.85 for the feeding success of An. gambiae sensu lato on sleeping humans in Tanzania [34,62]. We also applied these same probabilities of attacking (γu), feeding (φh,u), and dying (μu) to An. gambiae sensu stricto encountering unprotected humans. The availabilities of unprotected humans and cattle were calculated for An. arabiensis using field measurements of the duration of the feeding cycle and were extended to An. gambiae s.s., accounting for the lower estimated relative availability of cattle (λc) to this mosquito species as previously described [52]. Note that λc is assumed to modify a c by affecting the encounter rate only, indicating that these mosquitoes can differentiate between preferred and nonpreferred hosts at long ranges [72–74]. In the case of An. arabiensis this assumption is consistent with the longer spatial range of attraction of cows relative to humans for zoophilic members of the An. gambiae complex [72–74]. Parameters Reflecting the Effects of Insecticide-Treated Bed Nets The parameter definitions and values describing the impacts of ITNs on vector behaviour and mortality at the level of individual interactions are listed in Table 1. The impacts of ITNs very much depend on their excito-repellent and insecticidal properties, which are most representatively evaluated using well-established experimental hut methodologies [59,75,76] that have been extensively applied to this particular intervention [29–34]. Furthermore, the interaction of these two properties, to yield varying levels of personal and communal protection, is complex and has crucial implications for ITN programmes across Africa [11]. Sensitivity analysis of models similar to those used in this paper [11] have previously been used to explore the influence that these properties might have upon the magnitude and equity of protection afforded by ITNs (Figure 2). In order to validate this slightly revised model (see Equations 4-8) and similarly investigate such interactions at ITN coverage levels that can be plausibly sustained, we examined usage data collected during routine socioeconomic status surveys of a long-standing demographic surveillance system in the Kilombero Valley, southern Tanzania, where social marketing programmes have been well established since 1997 [77,78]. Data from the annual ITN usage survey in 2004 were used because they overlap with detailed entomological surveys of malaria transmission (which will be reported elsewhere). These surveys of randomly sampled residents from across two rural districts indicate that 75% (11,982/16,086) net use was achieved although most of these nets were not effectively treated [79]. In this sensitivity analysis, we assumed that new long-lasting ITN technologies [44–47] will enable sustained coverage with nets that are effectively treated even under the most rigorous programmatic field conditions. Figure 2 The Simulated Protection ITNs Afford against Exposure to Malaria Transmission as a Function of Their Ability to Divert and Kill Host-Seeking Mosquitoes Protection is expressed as relative exposure to malaria transmission (EIR C /EIR o ) for individuals with (Equation 19) and without (Equation 18) nets is plotted as a function of their ability to divert (Δp) and kill (μp) mosquitoes attacking protected humans. To simulate the likely field properties of existing long-lasting insecticidal nets with a full range of insecticidal and excito-repellent properties, the parameters of this model reflecting increased mosquito mortality (μp) and diversion (Δp) were varied across a plausible range of 0–0.8. As described in the main text and previous publications, these results represent simulations in two distinctive scenarios: An. gambiae sensu lato in the absence of cattle (results for both sibling species are identical) and An. arabiensis in the presence of one head of cattle per person. The biodemographic parameters of the interacting vector and parasite are also exactly as described previously [11,13] with survival of foraging mosquitoes (Pov) set at 0.8 per day. Coverage levels of 75% net usage was assumed, consistent with the results of surveys in the Kilombero Valley, southern Tanzania (see Methods: Parameters Reflecting the Effects of Insecticide-Treated Bed Nets). Figure 2 shows that, for the comparatively zoophilic vector An. arabiensis, in the presence of alternative hosts, excito-repellency consistently enhances the benefits for both users and nonusers, regardless of the insecticidal properties of the net. Consistent with previous analyses using this model [11], this simulation suggests that nets that are purely excito-repellent and lack insecticidal properties could slightly increase exposure of nonusers to An. gambiae sensu lato by diverting mosquitoes to them where no alternative sources of blood are available. Thus, purely diversionary vector control strategies may indeed be ethically questionable, as was previously suggested [31,34,80,81]. Nevertheless, even modest insecticidal properties are expected to counterbalance this inequity and confer a useful communal reduction of EIR. While repellent properties do slightly reduce the benefits to nonusers exposed to anthropophagic vectors lacking an alternative host, this slight disadvantage is likely to be outweighed in practice by the advantage of improved personal protection for users: Excito-repellent properties and physical barriers add to the effectiveness of insecticides for personal protection because these two incentives constitute the major motivating force behind ITN uptake and use at the individual and subsequently the community level. It is also reassuring to note that the predictions and epidemiological implications of this slightly revised model are very similar to those reported for its previous iteration [11]. We therefore concluded that the simulations described in the main text should consider ITNs with both insecticidal and excito-repellent properties, consistent with those of products currently on the market that have been evaluated in a variety of settings and experimental designs. To simulate the likely properties of established ITNs under programmatic conditions, we conservatively assumed they will both divert and kill 40% more mosquitoes than an unprotected human (μp = 0.4 and Δp = 0.4). A net with such proper-ties would protect against 64% of indoor exposure (1 − [(1 − 0.4) × (1 − 0.4)] = 0.64), as measured in a typical experimental hut trial [46,76]. To explore the best possible future scenario for the development of highly durable ITNs [44–47] or regular retreatment services [82], we also simulated increasing co-verage with nets that divert and kill 80% more mosquitoes than with an unprotected human (μp = 0.8 and Δp = 0.8), providing 96% protection (1 − [(1 − 0.8) × (1 − 0.8)] = 0.96). The proportion of normal biting exposure that occurs while nets are actually in use (πi) has been estimated as 90% for A. gambiae in southern Tanzania [13], so we set πi to a value of 0.90. Results Figure 3 illustrates how increasing community-level protection of ITN nonusers and users alike combines with constant individual protection to reduce exposure to malaria. Regardless of vector species or the availability of alternative hosts, modestly effective conventional ITNs achieve much greater impact upon human exposure, even that of users, if approximately half or more of the whole human population is covered. While this principle has already been suggested by field trials [19] and two independently formulated models [11,12], here we have identified specific coverage thresholds at which communal protection becomes greater than or equal to individual personal protection. Where alternative hosts for vector mosquitoes are absent, 35% of the human population must sleep under regular ITNs to achieve equivalence of personal and communal protection mechanisms, resulting in major community-wide suppression of exposure. The same target is achieved at 55% coverage where alternative hosts such as cattle are present. Figure 3 Relative Exposure to Malaria Transmission (EIR C /EIR o ) as a Function of Increasing Coverage with Insecticide-Treated Nets We express coverage as the proportion of the total human population using an ITN each night, and protection as the proportional reduction of infectious bites to which a resident is exposed (see Methods). Individual protection afforded to users (thin solid line; Equation 20) and communal protection afforded to nonusers (thick dashed line; Equation 18), as well as their combined effect on users (thick solid line; Equation 19) are separately calculated [11,13]. Two distinct but common and broadly distributed ecological scenarios in Africa are considered: (1) An. gambiae or An. arabienis (sibling species of the same species complex known as An. gambiae sensu lato) populations in the absence of alternative blood sources and (2) vector populations dominated by An. arabiensis in the presence of abundant cattle as alternative hosts. Both scenarios are simulated with ITNs that have either standard or improved properties (See Methods). Grey shading represents an approximate absolute maximum for community-level coverage achievable by covering vulnerable under five years of age and pregnant population groups only with perfect targeting efficiency. Arrows extrapolate the thresholds at which communal and personal protection are equivalent. The insecticidal and excito-repellent properties of ITNs that define levels of personal protection also determine the extent of community-wide alleviation of exposure amongst users and nonusers alike [11], so improved ITN properties consistently result in improved overall impact. In our model, slightly higher usage rates were required to achieve equivalence of individual and communal effects, with thresholds of 40% and 64% coverage for vector populations with and without alternative hosts, respectively (Figure 3). While emerging ITN technologies with long-lasting insecticidal properties under programmatic conditions [44] would confer useful personal protection even at low coverage levels, personal protection was greatly enhanced by communal protection. At the 75% total population coverage recently achieved with largely untreated nets in southern Tanzania (Killeen et al., unpublished data), net users and nonusers are predicted to receive >98% and >90% protection, respectively, regardless of ecological scenario, if those nets were to be replaced with improved long-lasting insecticidal nets. Even for users of improved ITNs, this level of protection against African vector species is impossible without the contribution of community-level transmission suppression, because at least 10% of exposure occurs outdoors during times of the night when nets are not in use [13,83]. We conclude that modest coverage (thresholds of approximately 35%–65% use, depending on ecological scenario) of entire malaria-endemic populations, rather than just the most vulnerable minority, is needed to realize the full potential of ITNs, even with longer-lasting products or regular retreatment services [14,44]. This range of modelled thresholds is remarkably consistent with the figure of 50% suggested by large-scale field trials using approximately equivalent technology [19]. Discussion In addition to the direct impacts on vector populations explicitly modelled above, coverage of adults and older children is likely to have further benefits arising from subtleties of mosquito resource utilization that are often under-appreciated. Over 80% of human-to-mosquito transmission originates from adults and children over five years of age, because these groups constitute the bulk of the population and are more attractive to mosquitoes [56]. Where the entomological inoculation rate is fewer than ten infectious bites per person per year, the distributions of infectiousness [56,69], morbidity, and mortality will all shift into these older age groups, necessitating protection of all members of the population. Under such conditions, ITNs could suppress transmission not only through direct impacts on mosquito mortality, host choice, and feeding frequency [11], but also by limiting the prevalence, density, and infectiousness of malaria parasites in the human population [56]. An under-emphasized feature of communal protection is the enhancement of ITN programme equity, regardless of ecological scenario or ITN effectiveness: If the majority of people living in malaria-endemic Africa regularly used existing ITN technologies, nonusers would receive communal protection at least equivalent to using the only ITN in an otherwise unprotected population (Figure 3). This means that all children would equitably receive communal protection at least equivalent to the personal protection of an ITN, with users receiving multiplicative combined effects on exposure of both personal and communal benefits. While the wisdom of targeting interventions to protect at-risk individuals is based on solid scientific grounds [9,18,84] and is widely accepted [16], this approach should not preclude efforts to maximize communal protection through less selective delivery mechanisms. Targeting limited subsidies to maximize personal protection of the most vulnerable should remain a priority, but more equitable and effective suppression of risk for entire populations, including vulnerable groups, can be attained with quite modest coverage across all ages. Most field evaluations of ITNs have been conducted at reasonably high coverage levels [19], and all five mortality trials [21,85–88] that estimated that ITNs save 5.5 lives for every 1,000 children protected [20] covered large portions of entire communities rather than only the children themselves. The choice of ITN delivery strategy has proven contentious in recent years [89,90], but proponents of both market-based and public-sector approaches equally emphasize targeting strategies [9,16,84] to enhance equity and minimize leakage of subsidized ITNs beyond intended target groups [91–94]. While optimal targeting of finite subsidies is highly desirable, there are fundamental limitations to the impact that can be achieved: Even if resources were perfectly targeted, 80% coverage of pregnant women and children under five years of age could be accomplished with less than 20% coverage of the whole population, and even less of the total human host availability [11,56], as well as the infectious parasite reservoir [56,69]. Even if the ITN coverage targets of the MDGs were attained with flawless targeting efficiency, the substantial and equitable benefits of communal protection would not be achieved. Specifically, the target of 70% less exposure to transmission [13] would not be attained by the remaining minority of vulnerable individuals who are not covered and do not use an ITN, regardless of ecological scenario or ITN properties (Figure 3). We therefore highlight an important caveat to the following conclusion of the current Global Strategic Framework for ITN scaleup in Africa [95]: “In order to achieve maximum public health impact, ITN coverage needs to be maximized amongst those population groups that are most vulnerable to malaria infection and its consequences, primarily pregnant women and children under five years of age.” Specifically, we conclude that protecting the vulnerable can achieve maximum public health impact only if complemented by strategies that also achieve broad coverage of the population as a whole. In reality, the targets for coverage of vulnerable groups will not be reached without some leakage and inequity. Our analysis suggests that such concerns may be less of a problem than the targets themselves and may be minimized by extending coverage priorities to include all age groups. Fortunately, consensus is finally emerging that a range of approaches to ITN deployment merit investigation, development, and comparative evaluation at scales for which no precedent yet exists [95]. Note that this analysis supports the implementation of any of the diverse and rapidly emerging delivery strategies as long as high coverage with long-lasting ITNs is sustained across entire malaria-endemic populations on national scales. Perhaps the most important remaining question is: How can such population-wide coverage levels be affordably and cost-effectively sustained? Growing financial support for malaria control globally [14,15,95] may enable fully subsidized provision to entire populations [82] of the world's most impoverished, malaria-afflicted nations. Existing evidence, based largely on individual protection alone, indicates that ITNs are as cost-effective as childhood immunization [96], and future analyses should explicitly consider the additional benefits of communal protection. Implementing this goal may be relatively straightforward for programmes that are primarily subsidized and implemented through the public sector, such as recent successful initiatives associated with vaccination campaigns [91]. By comparison, social marketing approaches, including hybrid systems that deliver public subsidies through the private sector, may require more detailed consideration, particularly where cost sharing with the target population is substantial and biased toward the nonpregnant adults and older children who are key to communal protection. Although social marketing approaches to ITN distribution face substantial challenges [93,97,98], notable success in terms of coverage and impact have been reported in a variety of settings [94,99,100], including the KINET programme in Kilombero Valley, southern Tanzania where ITNs have been promoted and subsidized since 1996 [77,78]. Much of the essential experience generated by KINET was later integrated into the ITN promotion strategy of the National Malaria Control Programme of Tanzania, which supports private sector distribution through a voucher system that subsidizes purchase by vulnerable priority groups [101]. In the meantime, the preceding KINET pilot in Kilombero has achieved 75 % net use amongst randomly sampled residents of all ages (Killeen et al., unpublished data). It is particularly noteworthy that substantial levels of communal protection were achieved [102] (unpublished data) even though most of these nets were untreated or poorly treated at the time of evaluation [79] (unpublished data). Reassuringly, the model applied here approximately reproduces these patterns of communal protection using plausible parameter estimates for the net properties, vector behaviours, and host demographics of the area (unpublished data). We therefore recommend that the cost-effectiveness of such hybrid approaches be explicitly evaluated in terms of the complementary respective contributions of public-sector subsidies and cost-sharing by target populations to personal and communal protection. While appropriate engagement and sensitization of malaria-afflicted populations is essential to the success of any ITN promotion programme, this is likely to be especially true where cost-sharing by the target population will be needed to complement limited public subsidies. Such cost-sharing schemes may be the only affordable means to support full population coverage where available subsidies are inadequate. In such resource-limited circumstances, high levels of awareness, acceptance, and willingness to pay will be essential to enable concerted use of ITNs by adults and shared protection of all children within their communities. Overly confident extrapolation from mathematical models to set operational targets for malaria control has proved to be a grave mistake in the past [103]. A number of complications not captured by this model could emerge as ITN coverage increases, not least of which might be increased selection for insecticide resistance [104,105]. While we urge caution in interpreting the numerical results of our analysis, the phenomenon outlined is well established and has clear implications for malaria control in Africa and beyond [19]. In fact, the analysis presented here provides a generalizable rationale that strongly supports the conclusions of the most recent and meticulous evaluations of the community-level benefits of ITNs: “High coverage with ITNs will do more for public health in Africa than previously imagined” [19]. We therefore suggest that further field data, analyzed with appropriate theoretical models and cost-effectiveness frameworks, are required to verify and quantify the levels of communal protection afforded by increasing ITN use across Africa. International targets [2,14,15] should be amended to include thresholds for coverage of entire populations and monitored accordingly. By making life increasingly difficult for mosquitoes through programmes that promote ITN use by the majority of their human victims, it may be possible to protect the 15%–20% of children and pregnant women in African communities who would not otherwise be covered even if existing personal protection targets of the MDGs [2], the Roll Back Malaria Partnership [14], or the U.S. President's Malaria Initiative [15] were to be achieved. Supporting Information Protocol S1 Model Spreadsheet A Microsoft Excel spreadsheet version of all model simulations presented here is available to download. (1.1 MB XLS) Click here for additional data file.
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Assessment of insecticide-treated bednet use among children and pregnant women across 15 countries using standardized national surveys.
Thomas P Eisele, Megan Littrell, Joseph Keating … (2009)
Impact of insecticide-treated bednets (ITNs) on preventing malaria may be minimized if they are not used by vulnerable populations. Among ITN-owning households from 15 standardized national surveys from 2003 to 2006, we identify factors associated with ITN use among children younger than 5 years of age and make comparisons of ITN use among children and pregnant women across countries. Within ITN-owning households, many children and pregnant women are still not using them. Between-country analysis with linear regression showed child ITN use increases as intra-household access to ITNs increases (P = 0.020, R2 = 0.404), after controlling for season and survey year. Results from within-country logistic regression analyses were consistent with between-country analysis showing intra-household access to ITNs is the strongest and most consistent determinant of use among children. The gaps in ITN use and possession will likely persist in the absence of achieving a ratio of no more than two people per ITN.
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Net Benefits: A Multicountry Analysis of Observational Data Examining Associations between Insecticide-Treated Mosquito Nets and Health Outcomes
Stephen Lim, Nancy Fullman, Andrew Stokes … (2011)
Introduction Several sub-Saharan African countries, with support from international donors, have rapidly scaled up the fraction of households that own insecticide-treated mosquito nets (ITNs) from essentially zero to above 60% over the last decade [1]. Although there has been variable progress across countries, the push to increase ITN coverage continues with more dramatic improvements seen in the last few years [2]. The large expansion in the distribution of ITNs has been motivated by evidence from cluster-randomized controlled trials (RCTs) that showed pooled relative reductions in child mortality of 18% [3] and parasite prevalence of 13% as a result of net use [4]. There are several reasons why improvements in health outcomes of the same magnitude might not be observed under routine conditions [5]. These include, for example, reduced net integrity and improper use. As a result, efforts should be made to measure not only the coverage of ITNs, but also their impact on health outcomes under real-world settings [6],[7]. Evaluating the impact of malaria control strategies, including the scale-up of ITNs on health outcomes, is difficult. Weak routine health information and vital registration systems mean that it is often not possible to accurately determine malaria-specific mortality and morbidity. Evidence about the impact of ITNs under routine conditions has been limited to selected studies such as those conducted in rural Kenya [8], the Gambia [9], Tanzania [10],[11], and rural Somalia [12]. These studies, however, have used different approaches to assess the relationship between ITNs and health outcomes and represent only some of the countries where ITN coverage has been scaled up. In this paper, using routinely collected household surveys, we demonstrate an approach to measure in a comparable way the association between use and ownership of ITNs and parasitemia prevalence and child mortality across a large number of countries where ITNs have been distributed. This method quantifies the impact of ITNs, under routine conditions, to allow a better understanding of the effect on child health of the recent ITN scale-up. Methods Data We considered all demographic and health surveys (DHS) and malaria indicator surveys (MIS) from sub-Saharan Africa countries conducted since 2000 for which the unit-record data were available. Prior to 2000, ITN ownership and use in sub-Saharan Africa was universally low [13]. We included only surveys that collected data on the health outcomes of interest (child mortality or parasitemia prevalence) as well as information on ITN ownership and use (including when the ITN was received or purchased, and when it was retreated) and all covariates specified in the analyses. We excluded the Ghana DHS conducted in 2003 as no child deaths were observed in the small number of households that owned ITNs. The results on the association between ITNs and child mortality are based on 29 DHS in 22 sub-Saharan African countries, while the results on the association between ITNs and parasitemia prevalence are based on 6 MIS and one DHS from seven sub-Saharan African countries. Ownership and Use of ITNs Mosquito nets were classified as conventional ITNs, which require retreatment at least every year, or long-lasting insecticide-treated mosquito nets (LLINs), which should be replaced after 3 y [14]. While the data collection procedure varied slightly across surveys, in general survey interviewers visually confirmed presence of nets in the household and recorded the following information for each net in a net roster: how long ago it was acquired; brand, specifically, if it is an LLIN; and for conventional ITNs, how long ago the net was last treated. We considered a net to be an ITN if it was an LLIN that was less than or equal to 3 y old or a conventional ITN that was less than or equal to 1 y old or had been retreated in the last year. The net roster was linked to the household roster and this was used to identify which member slept under the net the previous night. Using this information, we estimated three variables of net ownership and use, two at the household level and one at the child (aged less than 5 y) level: (i) whether or not the household owned an ITN, (ii) how many ITNs each household owned per household member, and (iii) whether the child slept under an ITN the night prior to the survey. Health Outcomes Parasitemia in children under the age of 5 y of age was ascertained in surveys using a rapid diagnostic test (RDT) and/or microscopy using thick or thin blood smears. Survey data and documentation did not always indicate whether the positive result was determined from RDT or microscopy. Survival of children from age 1 mo to 59 mo was determined from complete birth histories of women of reproductive age (15 to 49 y). We examined mortality between age 1 mo and 59 mo as this is the same age period used in RCTs and previous observational studies [4],[8]; malaria deaths in the neonatal period are very rare. Malaria Transmission Intensity All analyses controlled for the effect of malaria transmission intensity. To determine malaria transmission intensity, we used global positioning system (GPS) coordinates for each of the primary sampling units (PSUs) in the MIS or DHS and linked this to data on malaria transmission from the Malaria Atlas Project (http://www.map.ox.ac.uk; [15]) using ArcGIS. All households in the PSU were assigned the malaria transmission based on the PSU-level GPS coordinates. We categorized malaria transmission intensity into the following categories: (i) high transmission, defined as PfPR2–10 or P. falciparum parasite rate (2 to 10 y) between 40%–100%; (ii) medium transmission, defined as PfPR2–10 between 5%–40%; and (iii) low transmission, defined as PfPR2–10 between 0%–5% [16]. Seven DHS did not have PSU-level GPS coordinates available (Benin 2006, Congo 2005, Eritrea 2002, Niger 2006, Rwanda 2000, São Tomé & Príncipe 2008, and Zambia 2001–2002). For these seven surveys, households were assigned a malaria transmission category on the basis of the average population-weighted parasite rate in the province where the household was located. Effect of ITN Ownership and Use in Children under 5 on Parasitemia Prevalence We examined the effect of ITN ownership and use on parasitemia prevalence using exact matching. The literature on the use of matching for causal inferences is sophisticated and growing, and includes several applications in global health and evaluations of health policies [17]–[21]. Matching provides a way of preprocessing the data so that the treated group is as similar to the control group as possible, thus making the treatment variable (in this case, ITN ownership or ITN use) as independent of the background characteristics as possible. By breaking or reducing the link between the treatment variable and the control variables, matching makes estimates based on subsequent analyses less dependent on model specification. Within each survey, we exactly matched children who live in a household that owns an ITN or children who slept under an ITN the night prior to the survey to children from households without an ITN on the basis of the following covariates: (i) age of the child (0–1, 2–3, 4+ y); (ii) mother's education (none, any); (ii) urban/rural residence; and (iv) malaria transmission intensity. We implemented the exact matching procedure using the MatchIt software in R [22]. We then used logistic regression on the matched dataset to provide added control of potential confounders using the following covariates: (i) age of the child (0–1, 2–3, 4+ y); (ii) mother's education (none, primary, secondary or more); (iii) urban/rural residence; (iv) household wealth quintile; (v) malaria transmission intensity category; and (vi) wet or dry season at the time of the survey. We estimated household wealth using information on asset ownership [23]–[25]. A separate analysis was conducted for each survey and we determined the odds ratio (OR) associated with ITN ownership or use. We determined a pooled OR across all surveys using DerSimonian-Laird random effects meta-analysis [26]. Effect of ITN Ownership on Child Mortality We used complete birth history data from DHS to construct a retrospective cohort that traces survival of children from age 1 mo to 59 mo for the 3 y prior to the survey. From the household net roster, using the information on when each net was acquired and/or retreated, we determined household ownership of an ITN for each month during the 3 y prior to the survey. As the surveys only record use of ITNs for children who are alive at the time of the survey, we were not able to study the relationship between ITN use and child mortality. We analyzed the relationship between household ownership of ITNs and child mortality using Cox proportional hazards models where analysis time was the age of the child in months. We controlled for the following covariates: (i) maternal age (in 5-y age groups); (ii) parity and birth interval (less than 12 mo, 12–23 mo, greater or equal to 24 mo or first born); (iii) sex of the child; (iv) single or multiple birth; (v) maternal education (no education, less than primary, less than secondary, secondary or more); (vi) household wealth quintile; (vii) urban/rural residence; (viii) skilled birth attendance (SBA) coverage at the PSU level; (ix) three-dose diphtheria, pertussis and tetanus (DPT3) immunization coverage at the PSU-level; (x) calendar year; (xi) malaria transmission intensity; and (xii) wet or dry season specific to the month of the observation. Wet and dry seasons were determined from the Mapping Malaria Risk in Africa project (http://www.mara.org.za/). A separate analysis was conducted for each survey and we determined the relative risk (RR) of child mortality associated with ITN ownership. We determined a pooled RR across all surveys using DerSimonian-Laird random effects meta-analysis [26]. We examined the sensitivity of the results to recall bias by restricting the analysis to observations for just the one year prior to the survey. Effect of ITNs by Malaria Transmission Intensity, Number of ITNs Owned, and Urban and Rural Residence Malaria transmission varies considerably within countries and it is likely that the effect of ITNs varies by transmission level. The effect of ITN ownership may also vary according to the number of ITNs owned by the household. Finally, the majority of RCTs and observational studies of ITNs were conducted in rural areas and the effect of ITNs in urban areas is less well characterized. To test for these effects, we pooled individual observations from all surveys and grouped observations by transmission intensity (high, medium, and low), the number of ITNs owned per household member (0, 0.05). 10.1371/journal.pmed.1001091.g001 Figure 1 Effect of (A) ITN household ownership; and (B) ITN use in children under five, on prevalence of parasitemia. Figure 2 shows the results of the analysis of the effect of household ownership of at least one ITN on child mortality. In the individual surveys, there were statistically significant reductions in five surveys: Zambia 2001–2002 with a 69% RR reduction in child mortality (95% CI 24%–87%); Kenya 2008–2009 with a 68% RR reduction (95% CI 29%–86%); Rwanda 2007–2008 with a 55% RR reduction (95% CI 28%–72%); Niger 2006 with a 41% RR reduction (95% CI 14%–59%); and Madagascar 2008 with a 30% RR reduction (95% CI 2%–50%). Across the 29 surveys, there was a statistically significant pooled RR reduction in child mortality of 23% (95% CI 13%–31%) with the effect being consistent across the 29 surveys (I 2 = 25.6%, p>0.05 for the I 2 value). Restricting the analysis of ITN ownership on child mortality to observations in the 1 y prior to the survey, and thereby reducing the influence of recall bias, did not markedly change the estimated mean effect of ITN ownership (unpublished data). 10.1371/journal.pmed.1001091.g002 Figure 2 Effect of ITN household ownership on all-cause mortality among children 1 mo to 59 mo of age. Tables 3 and 4 show results of the logistic regression of ITN household ownership and use in children under-five on parasitemia by malaria transmission risk. The effect of ITN household ownership and use in children under-five were statistically the same across the three levels of transmission risk (p>0.05). In general, wet season, increasing child age, lower maternal education, and lower household wealth were significantly associated with higher odds of parasitemia (Tables 3 and 4). Table 5 shows the result of the Cox Proportional Hazards model of ITN household ownership on child mortality by transmission level. There were no statistically significant differences in the effect of ITNs on child mortality by malaria transmission level (p>0.05). In general, wet season, shorter birth intervals, a multiple birth, older maternal age, lower maternal education, lower household wealth, fewer household members, lower coverage of other childhood immunization, and skilled birth attendance were associated with higher probability of child mortality (Table 5). All the relationships observed between child mortality and parasitemia and the covariates controlled for are as expected and support the validity of the analytical approach. 10.1371/journal.pmed.1001091.t003 Table 3 Results from the logistic regression of ITN household ownership on parasitemia prevalence by malaria transmission risk. Indicator High Medium Low OR p-Value 95% CI OR p-Value 95% CI OR p-Value 95% CI ITN ownership 0.94 0.404 (0.81–1.09) 0.76 0.000 (0.67–0.87) 0.72 0.314 (0.38–1.37) Seasonality Dry 1.00 — 1.00 1.00 — — 1.00 — — Wet 1.14 0.199 (0.94–1.38) 1.89 0.000 (1.61–2.23) 3.48 0.008 (1.39–8.70) Child's age (y) 0–1 1.00 — 1.00 1.00 — — 1.00 — — 2–3 2.26 0.000 (1.91–2.68) 1.90 0.000 (1.56–2.26) 1.75 0.170 (0.79–3.90) 4–5 2.47 0.000 (2.02–3.02) 2.34 0.000 (1.95–2.81) 2.12 0.140 (0.78–5.72) Maternal education None 1.00 — 1.00 1.00 — — 1.00 — — Primary 0.79 0.004 (0.67–0.92) 0.87 0.107 (0.74–1.03) 4.43 0.002 (1.77–11.1) ≥Secondary 0.61 0.002 (0.44–0.83) 0.55 0.000 (0.39–0.76) 1.06 0.934 (0.29–3.81) Household wealth (quintiles) Poorest 1.00 — 1.00 1.00 — — 1.00 — — Quintile 2 1.27 0.013 (1.05–1.54) 0.75 0.001 (0.63–0.89) 0.71 0.580 (0.21–2.38) Quintile 3 0.82 0.073 (0.65–1.02) 0.51 0.000 (0.42–0.61) 0.69 0.511 (0.23–2.06) Quintile 4 0.63 0.001 (0.48–0.83) 0.50 0.000 (0.41–0.62) 0.58 0.340 (0.19–1.83) Richest 0.31 0.000 (0.21–0.46) 0.36 0.000 (0.26–0.49) 0.59 0.362 (0.19–1.83) Urban residence Rural 1.00 — 1.00 1.00 — — 1.00 — — Urban 0.70 0.002 (0.56–0.88) 0.40 0.000 (0.30–0.53) 0.46 0.196 (0.14–1.50) 10.1371/journal.pmed.1001091.t004 Table 4 Results from the logistic regression of ITN use in children under five on prevalence of parasitemia by malaria transmission risk. Indicator High Medium Low OR p-Value 95% CI OR p-Value 95% CI OR p-Value 95% CI ITN use 0.91 0.315 (0.77–1.09) 0.75 0.000 (0.64–0.88) 0.95 0.902 (0.45–2.02) Seasonality Dry 1.00 — 1.00 1.00 — — 1.00 — — Wet 1.08 0.531 (0.86–1.35) 1.93 0.000 (1.60–2.31) 4.05 0.013 (1.35–12.2) Child's age (y) 0–1 1.00 — 1.00 1.00 — — 1.00 — — 2–3 2.27 0.000 (1.86–2.76) 1.76 0.000 (1.47–2.10) 1.23 0.645 (0.51–2.95) 4–5 2.29 0.000 (1.81–2.90) 2.46 0.000 (1.99–3.04) 1.25 0.687 (0.42–3.78) Maternal education None 1.00 — 1.00 1.00 — — 1.00 — — Primary 0.76 0.004 (0.62–0.91) 0.87 0.150 (0.71–1.05) 4.48 0.003 (1.66–12.0) ≥Secondary 0.51 0.001 (0.35–0.75) 0.54 0.001 (0.37–0.79) 0.85 0.818 (0.21–3.46) Household wealth (quintiles) Poorest 1.00 — 1.00 1.00 — — 1.00 — — Quintile 2 1.31 0.022 (1.04–1.64) 0.82 0.053 (0.67–1.00) 0.47 0.295 (0.11–1.94) Quintile 3 0.80 0.097 (0.62–1.04) 0.58 0.000 (0.46–0.72) 0.61 0.384 (0.20–1.84) Quintile 4 0.70 0.026 (0.51–0.96) 0.56 0.000 (0.43–0.72) 0.47 0.210 (0.14–1.53) Richest 0.34 0.000 (0.22–0.53) 0.39 0.000 (0.27–0.57) 0.24 0.058 (0.21–3.46) Urban residence Urban 1.00 — 1.00 1.00 — — 1.00 — — Rural 0.67 0.003 (0.52–0.88) 0.36 0.000 (0.26–0.51) 0.39 0.187 (0.09–1.59) 10.1371/journal.pmed.1001091.t005 Table 5 Results from the logistic regression of ITN household ownership on all-cause mortality among children 1 mo to 59 mo of age by malaria transmission risk. Indicator High Medium Low RR p-Value 95% CI RR p-Value 95% CI RR p-Value 95% CI ITN ownership 0.82 0.001 (0.73–0.93) 0.81 0.003 (0.70–0.93) 0.74 0.094 (0.53–1.05) Seasonality Dry 1.00 — — 1.00 — — 1.00 — — Wet 0.98 0.590 (0.93–1.05) 0.95 0.185 (0.88–1.02) 0.89 0.280 (0.72–1.10) Child's sex Male 1.00 — — 1.00 — — 1.00 — — Female 0.98 0.463 (0.93–1.03) 0.92 0.004 (0.87–0.97) 0.94 0.358 (0.84–1.07) Birth interval (mo) 0.05). We found a statistically significant association between ITNs and child mortality in urban areas with high and medium levels of malaria transmission (Figure 4); however, we did not observe statistically significant differences in the effect of ITNs in rural versus urban areas when stratified by transmission level (Figure 4; p>0.05). 10.1371/journal.pmed.1001091.g003 Figure 3 Effect of ITNs on (A) prevalence of parasitemia; and (B) all-cause mortality among children 1 mo to 59 mo of age, stratified by number of ITNs per household member (<0.25 ITNs per household member, ≥0.25 ITNs per household member) and malaria transmission risk (high, medium, low). 10.1371/journal.pmed.1001091.g004 Figure 4 Effect of ITN ownership on (A) prevalence of parasitemia; and (B) all-cause mortality among children 1 mo to 59 mo of age, stratified by area of residence (urban or rural) and malaria transmission risk (high, medium, low). Discussion Our findings from a large number of countries suggest that the rapid scale-up in ITN coverage observed in several sub-Saharan African countries has likely been accompanied by reductions in child mortality. Our results are also highly consistent with findings from previous RCTs. We found a 23% (95% CI 13%–31%) pooled relative reduction in child mortality across 29 surveys compared to the pooled 18% (95% CI 10%–25%) relative reduction observed in three RCTs [3]. For parasitemia, we found a 20% (3%–35%) reduction across seven surveys, which is not statistically distinguishable from the pooled 13% reduction observed in seven RCTs [4]. The lack of a major difference between the RCTs and our analysis may be partly explained by the intention to treat analysis used in RCTs, although ITN coverage in the RCTs was almost universal. It is also important to note that the RCTs targeted provision of ITNs across all age groups, while the scale-up in most sub-Saharan African countries has initially focused on children and pregnant women. Our results are also consistent and statistically indistinguishable from previous observational studies of ITNs on child mortality. A cohort study in Kenya found a 44% (4%–67%) relative reduction in mortality among children age 1 mo to 59 mo associated with ITN use [8]. A case-control study in Tanzania found a 27% (95% CI 3%–45%) relative reduction in mortality among children aged 1 mo to 4 y associated with ITN use [11]. Our analysis adds to the existing literature by providing evidence of the effect of ITNs on health outcomes under routine conditions over a much broader range of transmission levels and countries; previous studies were predominantly in high endemicity areas. Overall, this finding suggests that on average at least, ITNs have a similar and sizeable effect on health outcomes under routine use compared to that seen in efficacy trials. This finding supports the continued scale-up of ITNs in sub-Saharan Africa, such as the more recent efforts in Nigeria and Democratic Republic of Congo that had previously low levels of ITN coverage and large populations at risk of malaria [1]. It also emphasizes the importance of ongoing and future efforts to maintain coverage of ITNs in those countries with successful scale-ups by replacing worn out ITNs. Furthermore, it also suggests that the massive effort to scale up ITN coverage over the past decade has paid off and that it is possible for health systems to increase coverage of interventions and affect health outcomes over a relatively short period of time. Continued coordinated efforts between local and national governments, international organizations, funding agencies, and researchers are needed to ensure that ITNs are reaching all populations at risk of malaria. With the relatively large impact of ITNs on child mortality, our findings also support the continued emphasis on malaria control more generally, including the push towards malaria elimination, as a way of improving child health in endemic countries. We found no evidence of substantial heterogeneity in the effect of ITNs on child mortality across the countries studied here. On the other hand, we found evidence of heterogeneity in the association between ITNs and parasitemia prevalence across countries. One possible explanation is because parasitemia may persist for some time after initial malaria infection; this heterogeneity may reflect different levels of malaria transmission intensity. That is, in high transmission areas, parasitemia may be so prevalent that it is a poor indicator of the incidence of malaria. This heterogeneity in the effect of ITNs on parasitemia prevalence is an important topic for future investigation. We were also not able to detect a significantly different effect on parasitemia of children sleeping under an ITN compared to just household ownership of an ITN; this may simply reflect limited statistical power to detect a true difference. However, we must examine other possible explanations. One possible explanation is that even though MIS data collection is designed to be in high transmission seasons, some of the data collection does occur in low transmission seasons and as the MIS only record information about sleeping under an ITN for the previous night, use of ITNs by children during the low transmission season may not be indicative of use in high transmission seasons. Mothers responding to a question by interviewers about whether their child slept under an ITN the previous night may also be more likely to respond in the positive because of social pressure. In our study we were not able to detect significant differences in the effect of ITNs by transmission level, number of ITNs owned per household member, or urban and rural residence. These findings likely reflect inadequate power, as indicated by the width of the confidence intervals, to detect statistically significant differences. A previous meta-analysis of RCTs suggested that the efficacy of ITNs is lower in areas with higher malaria transmission [4], while an observational study from rural Kenya [8] found greater effects in areas of high malaria transmission. In our pooled analysis we found significant effects of ITNs in urban areas, which supports previous studies that have shown significant impacts of ITNs on malaria outcomes in urban areas [27],[28]. We were also able to detect significant impacts of ITNs in only a limited number of individual surveys because of small sample sizes, and in general, we did not have the power to detect significant differences between surveys. On the basis of our analysis we cannot discount the possibility that the effect of ITNs varies by these and other factors, such as the extent of education on the proper use of ITNs that are accompanied with distribution programs. Given the large investments in malaria control over the past 10 y, future research and better ways to monitor how the impact of malaria control interventions might vary across populations are required. Our study provides a method for understanding the real-world impact of not only ITNs but also other interventions on health outcomes using data that are routinely collected. There are, however, a number of limitations of our analysis. First, several MIS do not specify whether the parasitemia tests were based on microscopy or rapid diagnostic test (RDT), and as a result we were not able to standardize the parasitemia measurements. Second, our analysis was limited to publically available datasets; therefore we were not able to access the full range of MIS that have been conducted, although steps are being taken to make these data more widely accessible (e.g., www.malariasurveys.org). Third, in our analysis of parasitemia, we were limited to a cross-sectional analysis and were therefore not able to determine whether ITN exposure occurred prior to malaria infection. Fourth, we were only able to examine the relationship between ITNs and all-cause mortality as the surveys we used do not include information on cause-specific mortality. Increased use of verbal autopsy may allow for refined assessment of the impact of ITNs on malaria-specific mortality, although concerns have been raised about the predictive power of verbal autopsy for malaria [29]. Sixth, the DHS do not collect information on skilled birth attendance and immunizations for children who have died, so in our analysis we could only control for use of these interventions at the PSU level. Seventh, we were not able to control for the effect of other malaria interventions such as indoor residual spraying or drug treatment. Finally, our analysis, like others based on observational studies, may be prone to residual confounding that has not been controlled for by the methods used. Monitoring and evaluation of interventions to improve population health must include not only measurement of utilization but also whether the delivery of the intervention at scale results in real-world changes in health outcomes. The latter is critical if we are to understand whether interventions are being delivered and used correctly. We used routinely collected survey data to assess the association between intervention use and health outcomes across a large number of countries. Our results suggest that, on average, the scale-up of ITNs in sub-Saharan Africa has led to significant reductions in child mortality—comparable to those found in previous RCTs. While further work is needed to elucidate possible variations in the effect of ITNs, these findings add to the body of evidence that ITNs are effective under usual program conditions and support the continued efforts to scale-up ITN coverage in sub-Saharan Africa.
Author and article information
Contributors
: Role: Editor
Journal
Journal ID (nlm-ta): PLoS One
Journal ID (iso-abbrev): PLoS ONE
Journal ID (publisher-id): plos
Journal ID (pmc): plosone
Title:
PLoS ONE
Publisher:
Public Library of Science
(San Francisco, USA
)
ISSN
(Electronic):
1932-6203
Publication date Collection: 2012
Publication date
(Electronic):
29
May
2012
Volume: 7
Issue: 5
Electronic Location Identifier: e37927
Affiliations
Author notes
* E-mail:
abennett@
123456tulane.edu
Article
Publisher ID: PONE-D-12-02007DOI: 10.1371/journal.pone.0037927
PMC ID: 3362537
PubMed ID: 22666414
SO-VID: ac44bce7-578a-4e40-a6f5-1c6fb6e02804
Copyright © Bennett et al. This is an open-access article distributed under the terms of the Creative
Commons Attribution License, which permits unrestricted use, distribution, and reproduction
in any medium, provided the original author and source are credited.
History
Date
received
: 23
January
2012
Date
accepted
: 30
April
2012
Page count
Pages: 11
Categories
Subject:
Research Article
Subject:
Medicine
Subject:
Epidemiology
Subject:
Survey Methods
Subject:
Global Health
Subject:
Infectious Diseases
Subject:
Parasitic Diseases
Subject:
Malaria
Subject:
Tropical Diseases (Non-Neglected)
Subject:
Malaria
Subject:
Infectious Disease Control
Subject:
Public Health
Subject:
Preventive Medicine
ScienceOpen disciplines: Uncategorized
Data availability:
ScienceOpen disciplines: Uncategorized