Outcome of capacity building intervention for malaria vector surveillance, control and research in Nigerian higher institutions

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Abstract

Background

Despite the availability of effective malaria vector control intervention tools, implementation of control programmes in Nigeria is challenged by inadequate entomological surveillance data. This study was designed to assess and build the existing capacity for malaria vector surveillance, control and research (MVSC&R) in Nigerian institutions.

Methods

Application call to select qualified candidates for the capacity building (CB) intervention training programme was advertised in a widely read newspaper and online platforms of national and international professional bodies. Two trainings were organized to train selected applicants on field activities, laboratory tools and techniques relevant to malaria vector surveillance and control research. A semi-structured questionnaire was administered to collect data on socio-demographic characteristics of participants, knowledge and access of participants to field and laboratory techniques in MVSC&R. Similarly, pre and post-intervention tests were conducted to assess the performance and improvement in knowledge of the participants. Mentoring activities to sustain CB activities after the training were also carried out.

Results

A total of 23 suitable applicants were shortlisted out of the 89 applications received. The South West, South East and North Central geopolitical zones of the country had the highest applications and the highest selected number of qualified applicants compared to the South South and North East geopolitical zones. The distribution with respect to gender indicated that males (72.7%) were more than females (27.3%). Mean score of participants’ knowledge of field techniques was 27.8 (± 10.8) before training and 67.7 (± 9.8) after the training. Similarly, participants’ knowledge on laboratory techniques also improved from 37.4 (± 5.6) to 77.2 (± 10.8). The difference in the mean scores at pre and post-test was statistically significant (p < 0.05). Access of participants to laboratory and field tools used in MVSC&R was generally low with insecticide susceptibility bioassays and pyrethrum spray collection methods being the most significant (p < 0.05).

Conclusions

The capacity available for vector control research and surveillance at institutional level in Nigeria is weak and require further strengthening. Increased training and access of personnel to relevant tools for MVSC&R is required in higher institutions in the six geopolitical zones of the country.

Electronic supplementary material

The online version of this article (10.1186/s12936-018-2344-z) contains supplementary material, which is available to authorized users.

Related collections

Most cited references 11

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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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What is global health?

Robert Beaglehole, Ruth Bonita (2010)

‘Global health’ is coming of age, at least as measured by the increasing number of academic centres, especially in North America, which use this title to describe their interests (1). Most global health centres are in high-income countries although several have strong links with low- and middle-income countries. A task force is establishing a mechanism to coordinate European Academic Global Health initiatives through ASPER. Two recent papers raise important issues about the meaning and scope of global health (2, 3) and highlight, yet again, the need for a common definition of global health which is short, sharp and widely accepted, including by the public (4). Koplan et al. from the Consortium of Universities for Global Health Executive Board point out that without an accepted definition of global health, it will be difficult to agree on what global health is trying to achieve and how progress will be made and monitored (2). This is particularly important given the recent global crises – climate change, economic, food and energy crises – that make global health efforts even more challenging (5). Koplan and colleagues propose a definition of global health which they hope will receive wide acceptance and thus encourage global health efforts. They distinguish between global health, international health and public health; tropical medicine has close connections with international health (1). However, there is widespread confusion and overlap among the three terms. International health, in Koplan's view, focuses on the health issues, especially infectious diseases, and maternal and child health in low-income countries. However, elsewhere international health is also used as a synonym for global health. For example, Merson et al. view international health as ‘the application of the principles of public health to problems and challenges that affect low and middle-income countries and to the complex array of global and local forces that influence them’ (6). The term ‘international health’ has also been used to refer to ‘the involvement of countries in the work of international organizations such as WHO, usually through small departments of international health in the Ministries of Health and as development aid and humanitarian assistance’ (7). Public health is usually viewed as having a focus on the health of the population of a specific country or community, a perspective shared by Koplan et al. (2). Fried et al. dispute any distinction between public health and global health and suggest that ‘public health is global health for the public good’ (3). Their strong arguments are based on the need for both global and public health to address the underlying social, economic, environmental and political determinants of health, irrespective of whether the primary focus is national or global health. Current definitions of global health Koplan et al. define global health as: ‘an area for study, research, and practice that places a priority on improving health and achieving health equity for all people worldwide’. This is a useful definition with a broad focus on health improvement and health equity. However, it is wordy and uninspiring. Kickbush defines global health as: ‘those health issues that transcend national boundaries and governments and call for actions on the global forces that determine the health of people’ (7). This definition also has a broad focus but has no clear goal, is passive in its call for action, and omits the need for collaboration and research. Elsewhere, the European Foundation Centre calls for a European approach which makes global health a policy priority across all sectors based on a global public goods foundation (8). In an important policy document, the UKGovernment refers to global health as ‘health issues where the determinants circumvent, undermine or are oblivious to the territorial boundaries of states, and are thus beyond the capacity of individual countries to address through domestic institutions. Global health is focussed on people across the whole planet rather than the concerns of particular nations. Global health recognises that health is determined by problems, issues and concerns that transcend national boundaries’ (9). This definition contains important ideas but is convoluted and not outcome focussed. Macfarlane et al. usefully describe global health as being the ‘worldwide improvement of health, reduction of disparities, and protection against global threats that disregard national borders’ (1). Proposed definition Our proposed definition for global health is collaborative trans-national research and action for promoting health for all. This definition is based on Koplan et al. but has the advantage of being shorter and sharper, emphasises the critical need for collaboration, and is action orientated. Key aspects of the definition deserve further explanation. The term global health is used rather than global public health to avoid the perception that our endeavours are focussed only on classical, and nationally based, public health actions. Global health builds on national public health efforts and institutions. In many countries public health is equated primarily with population-wide interventions; global health is concerned with all strategies for health improvement, whether population-wide or individually based health care actions, and across all sectors, not just the health sector. Collaborative (or collective) emphasises the critical importance of collaboration in addressing all health issues and especially global issues which have a multiplicity of determinants and a complex array of institutions involved in finding solutions. Trans-national (or cross-national) refers to the concern of global health with issues that transcend national boundaries even though the effects of global health issues are experienced within countries. Trans-national action requires the involvement of more than two countries, with at least one outside the traditional regional groupings, without which it would be considered a localised or regional issue. At the same time, trans-national work is usually based on strong national public health institutions. Research implies the importance of developing the evidence-base for policy based on a full range of disciplines and especially research which highlights the effects of trans-national determinants of health. Action emphasises the importance of using this evidence-based information constructively in all countries to improve health and health equity. Promoting (or improving) implies the importance of using a full range of public heath and health promotion strategies to improve health, including those directed at the underlying social, economic, environmental and political determinants of health. Health for all refers back to the Alma Ata Declaration and positions global health at the forefront of the resurgence of interest in multi-sectoral approaches to health improvement and the need to strengthen primary health care as the basis of all health systems. Global health: a high-income country concern? Although the burden of preventable disease is predominantly in middle- and, especially, low-income countries, most global health centres are located in high-income countries. There are several explanations for this anomaly including the following: Centres in low- and middle-income countries are engaged in global health issues but under other labels. For example, several centres in low- and middle-income countries have recently been funded by the National Heart, Lung and Blood Institutes to undertake chronic disease prevention activities, though the focus seems to be on national programmes of work (see http://www.fogartyscholars.org/articles/nhlbi-centers). Global health builds on international health interests stemming from institutions in high-income countries over a century ago. Global health may be seen to be divorced from the health needs of low- and middle-income countries which are grappling with a range of pressing and challenging health issues. An interest in global health stems from strong national public health institutions which are usually not a feature of low- and middle-income countries. Whatever the explanation, encouraging and supporting the establishment of global health centres in low- and middle-income countries, and south–south collaborations, are essential if countries with the greatest burden of diseases are to have the best opportunity to respond appropriately. Development agencies, foundations and national ministries of health could do much more to build public health capacity at the national level. By doing so, they will also strengthen research and policy interests in global health and its evaluation (10). Robert Beaglehole and Ruth Bonita University of Auckland, New Zealand

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Distribution of the African malaria vectors of the Anopheles gambiae complex.

Maureen Coetzee (2004)

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Author and article information

Contributors

Adedayo O. Oduola:

ORCID: http://orcid.org/0000-0002-4294-6465

+234 8053327203 , dayooduola@yahoo.co.uk

Journal

Journal ID (nlm-ta): Malar J

Journal ID (iso-abbrev): Malar. J

Title: Malaria Journal

Publisher: BioMed Central (London )

ISSN (Electronic): 1475-2875

Publication date (Electronic): 15 May 2018

Publication date PMC-release: 15 May 2018

Publication date Collection: 2018

Volume: 17

Electronic Location Identifier: 193

Affiliations

[1 ]ISNI 0000 0001 0625 9425, GRID grid.412974.d, Vector Biology and Control Research Group, Department of Zoology, , University of Ilorin, ; Ilorin, Nigeria

[2 ]GRID grid.442596.8, Department of Biotechnology, , Kwara State University, ; Malete, Nigeria

[3 ]ISNI 0000 0001 0247 1197, GRID grid.416197.c, Molecular Entomology and Vector Control Research Laboratory, Public Health and Epidemiology Division, , Nigerian Institute of Medical Research, ; Lagos, Nigeria

[4 ]Integrated Vector Management Branch, National Malaria Elimination Programme, Abuja, Nigeria

Author information

Adedayo O. Oduola http://orcid.org/0000-0002-4294-6465

Article

Publisher ID: 2344

DOI: 10.1186/s12936-018-2344-z

PMC ID: 5952629

PubMed ID: 29764426

SO-VID: d5751d59-f755-43d8-99c3-de7086fb02d1

License:

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.