- Open Access
Using the human blood index to investigate host biting plasticity: a systematic review and meta-regression of the three major African malaria vectors
© The Author(s) 2018
- Received: 4 October 2018
- Accepted: 14 December 2018
- Published: 18 December 2018
The proportion of mosquito blood-meals that are of human origin, referred to as the ‘human blood index’ or HBI, is a key determinant of malaria transmission.
A systematic review was conducted followed by meta-regression of the HBI for the major African malaria vectors.
Evidence is presented for higher HBI among Anopheles gambiae (M/S forms and Anopheles coluzzii/An. gambiae sensu stricto are not distinguished for most studies and, therefore, combined) as well as Anopheles funestus when compared with Anopheles arabiensis (prevalence odds ratio adjusted for collection location [i.e. indoor or outdoor]: 1.62; 95% CI 1.09–2.42; 1.84; 95% CI 1.35–2.52, respectively). This finding is in keeping with the entomological literature which describes An. arabiensis to be more zoophagic than the other major African vectors. However, analysis also revealed that HBI was more associated with location of mosquito captures (R2 = 0.29) than with mosquito (sibling) species (R2 = 0.11).
These findings call into question the appropriateness of current methods of assessing host preferences among disease vectors and have important implications for strategizing vector control.
- Blood meal analysis
- Host preference
- Biting preference
- Blood index
Malaria is transmitted through mosquito bites, making the vectors’ choice of which blood-host species to bite a central component of malaria epidemiology and ecology. In Africa, the majority of infections are transmitted by Anopheles gambiae sensu stricto (s.s.), Anopheles coluzzii, Anopheles funestus and Anopheles arabiensis. Conventional wisdom indicates that the first three vectors are anthropophagic while the latter sibling species is more zoophagic. Levels of anthropophagy/zoophagy are typically assessed using PCR to identify the host species from blood-meals in field-caught mosquitoes, and are then quantified according to the human blood index (HBI), defined as the proportion of blood-meals that are of human origin . Because two mosquito bites on a human are required to complete the malaria parasite’s life-cycle, HBI has an inflated impact on metrics of transmission such as the basic reproduction number, the vectorial capacity and the critical density of mosquitoes for sustained transmission .
However, the HBI should not be perceived to have a singular, fixed value; all major African malaria vectors have demonstrable plasticity in the host species that they bite [3–5]. It has long been recognized that the same mosquito population will often adjust its biting towards a more locally available host species [1, 6]. This has important implications for malaria control policy. For example, recent studies have observed that increased outdoor biting followed the distribution of insecticide-treated bed nets . In such circumstances, vector control tools that operate effectively outdoors become a critical component for eliminating local malaria transmission. Unfortunately, the huge malaria burden reduction achieved in the years since 2000 has relied disproportionately on control tools operating indoors , and there are limited effective malaria-vector control options for outdoor use.
One technology that shows promise for targeting mosquitoes regardless of whether they bite indoors or outdoors involves the use of systemic insecticides—chemicals applied directly to blood-hosts to kill mosquitoes that take a blood meal. This technology arose from the observation that mosquito mortality was increased following the consumption of sugar-meals  or blood-meals  containing ivermectin—a drug used for onchocerciasis control. Drugs approved for veterinary use, such as fipronil, have subsequently been demonstrated to have similar impact when livestock are dosed orally, or when the chemical is applied topically . More recently, systemic insecticides have had durations of their efficacy extended through dosing with higher concentrations , combined dosing with adjuvants , and with use of sustained-release devices . The stage is set for progress in development and evaluation of ivermectin for vector control . Therefore, arguably it has never been more important to understand the distribution of malaria-vector bites on alternative host species. Here, the current evidence is systematically reviewed and a meta-regression conducted to identify the factors associated with higher HBI in sub-Saharan Africa.
Inclusion and exclusion criteria for systematic review
Studies which used blood meal analysis (PCR, ELISA or precipitin tests) to report the HBI
Semi field studies, studies using baited traps or choice experiments to investigate host preference
Studies performed in sub-Saharan Africa
Entomological studies not specifically reporting the HBI
Studies reporting the HBI for individual mosquito species
Studies not reporting total number of mosquitoes caught
Reporting HBI for Anopheles gambiae, Anopheles funestus complex or Anopheles arabiensis mosquito species
Data points based on less than 50 blood-fed mosquitoes in total for target species
Studies reporting trapping methodology including location of traps (indoors or outdoors)
Search strategy for systematic review
Ovid MEDLINE® Database
Human blood index OR HBI OR host preference OR trophic preference OR blood meal preference OR blood host preference OR blood meal OR blood meal analysis OR blood-meal analysis OR blood meal source OR host blood OR host blood meal OR blood meal identification
[multiple posting = MeSH subject heading word, abstract, title, original title, text word (title, abstract), key word heading, name of substance, key word heading word, protocol supplementary concept word, synonym]
Anopheles OR Anopheles arabiensis OR Anopheles gambiae OR Anopheles funestus [multiple posting = MeSH subject heading word, abstract, title, original title, text word (title, abstract), key word heading, name of substance, key word heading word, protocol supplementary concept word, synonym]
After eliminating duplications, abstracts for all publications retrieved were reviewed for relevance. Full-text reviews were then conducted on all articles to decide on its inclusion in accordance with the pre-specified inclusion and exclusion criteria. If the inclusion criteria were satisfied the estimated human blood index (HBI) reported was retrieved. Other variables that could have a significant effect on the reported HBI were also retrieved. These variables included (sibling) species (complex), trapping location (indoors, outdoors or both), trap type(s) used and total number of mosquitoes collected. The primary effect measure of interest was the HBI.
The double arcsine square root transformed HBI (expressed as a proportion of all blood-meals) was used to stabilize the variance across the studies  and then back transformed for ease of interpretation. A linear model was performed on all eligible studies to gain additional insight into the effect of trapping location and Anopheles species on the proportion of HBI. The linear model was fit using the HBI (proportion) as the response variable weighted by the inverse of each study’s variance to allow the observations with the least variance to provide the most information to the model, and using robust error variances. All tests were two-tailed and a p-value < 0.05 was deemed statistically significant. Inverse variance weights were obtained using MetaXL (version 5.3, EpiGear Int Pty Ltd; Sunrise Beach, Australia) and the regression models were run using Stata MP (version 14, Stata Corp, College Station, TX, USA).
Data points extracted from eligible studies for each collection location and trapping methodology
Both (indoor + outdoor)
Pyrethroid spray catch (PSC)
CDC light trap
CDC light trap
CDC light trap + PSC
CDC light trap
Anopheles funestus s.l.
Predictors of human blood index: univariable and multivariable regression models
POR (95% CI)
POR (95% CI)
Control of vector-borne diseases is largely, often entirely, dependent on vector control. For malaria, vector control is achieved primarily through targeting mosquitoes that are host-seeking . The major African malaria vectors, An. gambiae s.s., An. coluzzii and An. funestus, are regularly cited as paragons of anthropophagy, and any non-human biting exhibited by these species has historically been ignored when strategizing control. Here, their biting behaviour was systematically reviewed and clearly demonstrated that the difference in their host choice compared with the zoophilic vector An. arabiensis was dwarfed by the difference found when comparing indoor with outdoor collections. In other words, where the mosquito was collected was substantially and significantly more influential on host choice than which mosquito species was collected.
This raises an important question: where should vectors be collected from in order to provide the most useful HBI estimates? Results indicate that a single HBI for a given location risks presenting quite a biased estimate for local vector biting behaviour. A standardized HBI accounting for both indoor and outdoor behaviours would probably constitute an invalid metric because of the increased difficulty posed by collecting blood-fed mosquitoes outdoors i.e., tools are lacking for the estimation of indoor versus outdoor mosquito numbers with any confidence. Therefore, current best practice should be to present both estimates for an indoor HBI and an outdoor HBI. Longitudinal assessments initiated before rolling out control tools, and followed up over the time course of the programme would provide a valuable source of information. For example, these would determine the timeframe across which LLIN-derived exophagy , as well as zoophagy  occurs, as well as provide unbiased estimates of the magnitude of effect. These entomological data would also be able to inform on whether there is a reversion to behavioural norm after a certain period post-distribution, and the rate at which this occurred.
Better data on this behaviour and its temporality will do much more than inform a fundamental aspect of mosquito ecology: it will have considerable ramifications pertaining to malaria control. For example, if significantly reduced HBI is detected immediately following the distribution of LLINs, this may present an excellent opportunity to synergize bed nets with systemic insecticide-treated livestock. Saul  described the potential for zooprophylaxis to switch into zoopotentiation if the availability of alternative blood meals increases mosquito survival more than counters the impact of diverting feeds. This risk could be reduced or eliminated with systemic insecticidal dosing that is judiciously timed with LLIN roll-out. Mathematical models already exist for optimal systemic insecticide deployment  including its integration with LLINs . These could immediately be capitalized upon once the temporal HBI data became available.
One further, important unknown pertaining to HBI is the spatial scale across which within-mosquito population plasticity occurs. Over 50 years ago, Garrett-Jones described differing HBI estimates for mosquitoes collected from proximal locations . Given the current concerns over altered biting behaviour potentially compromising recent gains in malaria burden reduction , a fuller comprehension of the scale and magnitude of this variability is timely. A recent study conducted in southern Ghana describes the successful piloting of a novel experimental design to address exactly this phenomenon . It demonstrated that statistically significant alteration in host choice for An. coluzzii was detectable over a range of 250 m . Heterogeneity in mosquito biting rates has been demonstrated to be key to malaria transmission, first by theoretical work , but more recently with empirical studies using genotyping of blood-meals . Future modelling frameworks will need to account for this additional form of village-level heterogeneity in biting behaviour.
Results demonstrate that where mosquitoes are collected from (indoors versus outdoors) is significantly more associated with the HBI than which of the major African malaria-vector mosquito (sibling) species is collected. Some of the more important consequences to disease control of this behaviour are described. Some new theoretical and empirical developments that may improve both HBI assessment and how this metric can inform malaria control optimisation are discussed.
LY conceived the study. JO, LFK and LY performed the systematic review and meta-regression. All authors contributed to results interpretation and manuscript drafting. All authors read and approved the final manuscript.
The authors declare that they have no competing interests.
Availability of data and materials
All data generated or analysed during this study are included in this published article and its additional file.
Consent for publication
Ethics approval and consent to participate
JO has an MRC London Intercollegiate Doctoral Training Partnership Studentship. TW and CLJ are funded through a Wellcome Trust/Royal Society Sir Henry Dale Fellowship (101285/Z/13/Z) awarded to TW. LY received funds from a Royal Society Research Project (RSG\R1\180203). Funding bodies had no role in the design of the study and collection, analysis and interpretation of data nor in writing the manuscript.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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.
- Garrett-Jones C. The human blood index of malaria vectors in relation to epidemiological assessment. Bull World Health Organ. 1964;30:241–61.PubMedPubMed CentralGoogle Scholar
- Waite H. Mosquitoes and malaria. A study of the relation between the number of mosquitoes in a locality and the malaria rate. Biometrika. 1910;7:421–36.Google Scholar
- Bogh C, Pedersen EM, Mukoko DA, Ouma JH. Permethrin-impregnated bednet effects on resting and feeding behaviour of lymphatic filariasis vector mosquitoes in Kenya. Med Vet Entomol. 1998;12:52–9.View ArticleGoogle Scholar
- Takken W, Verhulst NO. Host preferences of blood-feeding mosquitoes. Annu Rev Entomol. 2013;58:433–53.View ArticleGoogle Scholar
- Lefèvre T, Gouagna L-C, Dabiré KR, Elguero E, Fontenille D, Renaud F, et al. Beyond nature and nurture: phenotypic plasticity in blood-feeding behavior of Anopheles gambiae s.s. when humans are not readily accessible. Am J Trop Med Hyg. 2009;81:1023–9.View ArticleGoogle Scholar
- Chandler JA, Boreham PF, Highton RB, Hill MN. A study of the host selection patterns of the mosquitoes of the Kisumu area of Kenya. Trans R Soc Trop Med Hyg. 1975;69:415–25.View ArticleGoogle Scholar
- Russell TL, Govella NJ, Azizi S, Drakeley CJ, Kachur SP, Killeen GF. Increased proportions of outdoor feeding among residual malaria vector populations following increased use of insecticide-treated nets in rural Tanzania. Malar J. 2011;10:80.View ArticleGoogle Scholar
- Bhatt S, Weiss DJ, Cameron E, Bisanzio D, Mappin B, Dalrymple U, et al. The effect of malaria control on Plasmodium falciparum in Africa between 2000 and 2015. Nature. 2015;526:207–11.View ArticleGoogle Scholar
- Pampiglione S, Majori G, Petrangeli G, Romi R. Avermectins, MK-933 and MK-936, for mosquito control. Trans R Soc Trop Med Hyg. 1985;79:797–9.View ArticleGoogle Scholar
- Chaccour C, Lines J, Whitty CJM. Effect of ivermectin on Anopheles gambiae mosquitoes fed on humans: the potential of oral insecticides in malaria control. J Infect Dis. 2010;202:113–6.View ArticleGoogle Scholar
- Poche R, Burruss D, Polyakova L, Poche D, Garlapati R. Treatment of livestock with systemic insecticides for control of Anopheles arabiensis in western Kenya. Malar J. 2015;14:351.View ArticleGoogle Scholar
- Smit MR, Ochomo EO, Aljayyoussi G, Kwambai TK, Abong’o BO, Chen T, et al. Safety and mosquitocidal efficacy of high-dose ivermectin when co-administered with dihydroartemisinin-piperaquine in Kenyan adults with uncomplicated malaria (IVERMAL): a randomised, double-blind, placebo-controlled trial. Lancet Infect Dis. 2018;18:615–26.View ArticleGoogle Scholar
- Chaccour CJ, Hammann F, Alustiza M, Castejon S, Tarimo BB, Abizanda G, et al. Cytochrome P450/ABC transporter inhibition simultaneously enhances ivermectin pharmacokinetics in the mammal host and pharmacodynamics in Anopheles gambiae. Sci Rep. 2017;7:8535.View ArticleGoogle Scholar
- Chaccour CJ, Ngha’bi K, Abizanda G, Irigoyen Barrio A, Aldaz A, Okumu F, et al. Targeting cattle for malaria elimination: marked reduction of Anopheles arabiensis survival for over 6 months using a slow-release ivermectin implant formulation. Parasit Vectors. 2018;11:287.View ArticleGoogle Scholar
- Rabinovich NR. Ivermectin: repurposing an old drug to complement malaria vector control. Lancet Infect Dis. 2018;18:584–5.View ArticleGoogle Scholar
- Moher D, Liberati A, Tetzlaff J, Altman DG, The PG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6:e1000097.View ArticleGoogle Scholar
- Barendregt JJ, Doi SA, Lee YY, Norman RE, Vos T. Meta-analysis of prevalence. J Epidemiol Comm Health. 2013;67:974–8.View ArticleGoogle Scholar
- Pombi M, Calzetta M, Guelbeogo WM, Manica M, Perugini E, Pichler V, et al. Unexpectedly high Plasmodium sporozoite rate associated with low human blood index in Anopheles coluzzii from a LLIN-protected village in Burkina Faso. Sci Rep. 2018;8:12806.View ArticleGoogle Scholar
- Saul A. Zooprophylaxis or zoopotentiation: the outcome of introducing animals on vector transmission is highly dependent on the mosquito mortality while searching. Malar J. 2003;2:32.View ArticleGoogle Scholar
- Yakob L. Endectocide-treated cattle for malaria control: a coupled entomological–epidemiological model. Parasit Epidemiol Control. 2016;1:2–9.View ArticleGoogle Scholar
- Yakob L, Cameron M, Lines J. Combining indoor and outdoor methods for controlling malaria vectors: an ecological model of endectocide-treated livestock and insecticidal bed nets. Malar J. 2017;16:114.View ArticleGoogle Scholar
- Sokhna C, Ndiath MO, Rogier C. The changes in mosquito vector behaviour and the emerging resistance to insecticides will challenge the decline of malaria. Clin Microbiol Infect. 2013;19:902–7.View ArticleGoogle Scholar
- Orsborne J, Furuya-Kanamori L, Jeffries CL, Kristan M, Mohammed AR, Afrane YA, et al. Assessing the blood-host plasticity and dispersal rate of the malaria vector Anopheles coluzzii. bioRxiv. 2018;26:49–52.Google Scholar
- Dye C, Hasibeder G. Population dynamics of mosquito-borne disease: effects of flies which bite some people more frequently than others. Trans R Soc Trop Med Hyg. 1986;80:69–77.View ArticleGoogle Scholar
- Guelbéogo WM, Gonçalves BP, Grignard L, Bradley J, Serme SS, Hellewell J, et al. Variation in natural exposure to anopheles mosquitoes and its effects on malaria transmission. eLife. 2018;7:e32625.View ArticleGoogle Scholar