Predicting the impact of outdoor vector control interventions on malaria transmission intensity from semi-field studies

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Abstract

Background

Semi-field experiments with human landing catch (HLC) measure as the outcome are an important step in the development of novel vector control interventions against outdoor transmission of malaria since they provide good estimates of personal protection. However, it is often infeasible to determine whether the reduction in HLC counts is due to mosquito mortality or repellency, especially considering that spatial repellents based on volatile pyrethroids might induce both. Due to the vastly different impact of repellency and mortality on transmission, the community-level impact of spatial repellents can not be estimated from such semi-field experiments.

Methods

We present a new stochastic model that is able to estimate for any product inhibiting outdoor biting, its repelling effect versus its killing and disarming (preventing host-seeking until the next night) effects, based only on time-stratified HLC data from controlled semi-field experiments. For parameter inference, a Bayesian hierarchical model is used to account for nightly variation of semi-field experimental conditions. We estimate the impact of the products on the vectorial capacity of the given Anopheles species using an existing mathematical model. With this methodology, we analysed data from recent semi-field studies in Kenya and Tanzania on the impact of transfluthrin-treated eave ribbons, the odour-baited Suna trap and their combination (push–pull system) on HLC of Anopheles arabiensis in the peridomestic area.

Results

Complementing previous analyses of personal protection, we found that the transfluthrin-treated eave ribbons act mainly by killing or disarming mosquitoes. Depending on the actual ratio of disarming versus killing, the vectorial capacity of An. arabiensis is reduced by 41 to 96% at 70% coverage with the transfluthrin-treated eave ribbons and by 38 to 82% at the same coverage with the push–pull system, under the assumption of a similar impact on biting indoors compared to outdoors.

Conclusions

The results of this analysis of semi-field data suggest that transfluthrin-treated eave ribbons are a promising tool against malaria transmission by An. arabiensis in the peridomestic area, since they provide both personal and community protection. Our modelling framework can estimate the community-level impact of any tool intervening during the mosquito host-seeking state using data from only semi-field experiments with time-stratified HLC.

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Most cited references 39

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Stan: A Probabilistic Programming Language

Daniel Z Lee, Michael Betancourt, Marcus A. Brubaker … (2017)

Stan is a probabilistic programming language for specifying statistical models. A Stan program imperatively defines a log probability function over parameters conditioned on specified data and constants. As of version 2.14.0, Stan provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods such as the No-U-Turn sampler, an adaptive form of Hamiltonian Monte Carlo sampling. Penalized maximum likelihood estimates are calculated using optimization methods such as the limited memory Broyden-Fletcher-Goldfarb-Shanno algorithm. Stan is also a platform for computing log densities and their gradients and Hessians, which can be used in alternative algorithms such as variational Bayes, expectation propagation, and marginal inference using approximate integration. To this end, Stan is set up so that the densities, gradients, and Hessians, along with intermediate quantities of the algorithm such as acceptance probabilities, are easily accessible. Stan can be called from the command line using the cmdstan package, through R using the rstan package, and through Python using the pystan package. All three interfaces support sampling and optimization-based inference with diagnostics and posterior analysis. rstan and pystan also provide access to log probabilities, gradients, Hessians, parameter transforms, and specialized plotting.

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Increased proportions of outdoor feeding among residual malaria vector populations following increased use of insecticide-treated nets in rural Tanzania

Tanya Russell, Nicodem Govella, Salum Azizi … (2011)

Background Insecticide-treated nets (ITNs) and indoor residual spraying (IRS) represent the front-line tools for malaria vector control globally, but are optimally effective where the majority of baseline transmission occurs indoors. In the surveyed area of rural southern Tanzania, bed net use steadily increased over the last decade, reducing malaria transmission intensity by 94%. Methods Starting before bed nets were introduced (1997), and then after two milestones of net use had been reached-75% community-wide use of untreated nets (2004) and then 47% use of ITNs (2009)-hourly biting rates of malaria vectors from the Anopheles gambiae complex and Anopheles funestus group were surveyed. Results In 1997, An. gambiae s.l. and An. funestus mosquitoes exhibited a tendency to bite humans inside houses late at night. For An. gambiae s.l., by 2009, nocturnal activity was less (p = 0.0018). At this time, the sibling species composition of the complex had shifted from predominantly An. gambiae s.s. to predominantly An. arabiensis. For An. funestus, by 2009, nocturnal activity was less (p = 0.0054) as well as the proportion biting indoors (p < 0.0001). At this time, An. funestus s.s. remained the predominant species within this group. As a consequence of these altered feeding patterns, the proportion (mean ± standard error) of human contact with mosquitoes (bites per person per night) occurring indoors dropped from 0.99 ± 0.002 in 1997 to 0.82 ± 0.008 in 2009 for the An. gambiae complex (p = 0.0143) and from 1.00 ± <0.001 to only 0.50 ± 0.048 for the An. funestus complex (p = 0.0004) over the same time period. Conclusions High usage of ITNs can dramatically alter African vector populations so that intense, predominantly indoor transmission is replaced by greatly lowered residual transmission, a greater proportion of which occurs outdoors. Regardless of the underlying mechanism, the residual, self-sustaining transmission will respond poorly to further insecticidal measures within houses. Additional vector control tools which target outdoor biting mosquitoes at the adult or immature stages are required to complement ITNs and IRS.

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The dominant Anopheles vectors of human malaria in Africa, Europe and the Middle East: occurrence data, distribution maps and bionomic précis

Marianne Sinka, Michael J Bangs, Sylvie Manguin … (2011)

Background This is the second in a series of three articles documenting the geographical distribution of 41 dominant vector species (DVS) of human malaria. The first paper addressed the DVS of the Americas and the third will consider those of the Asian Pacific Region. Here, the DVS of Africa, Europe and the Middle East are discussed. The continent of Africa experiences the bulk of the global malaria burden due in part to the presence of the An. gambiae complex. Anopheles gambiae is one of four DVS within the An. gambiae complex, the others being An. arabiensis and the coastal An. merus and An. melas. There are a further three, highly anthropophilic DVS in Africa, An. funestus, An. moucheti and An. nili. Conversely, across Europe and the Middle East, malaria transmission is low and frequently absent, despite the presence of six DVS. To help control malaria in Africa and the Middle East, or to identify the risk of its re-emergence in Europe, the contemporary distribution and bionomics of the relevant DVS are needed. Results A contemporary database of occurrence data, compiled from the formal literature and other relevant resources, resulted in the collation of information for seven DVS from 44 countries in Africa containing 4234 geo-referenced, independent sites. In Europe and the Middle East, six DVS were identified from 2784 geo-referenced sites across 49 countries. These occurrence data were combined with expert opinion ranges and a suite of environmental and climatic variables of relevance to anopheline ecology to produce predictive distribution maps using the Boosted Regression Tree (BRT) method. Conclusions The predicted geographic extent for the following DVS (or species/suspected species complex*) is provided for Africa: Anopheles (Cellia) arabiensis, An. (Cel.) funestus*, An. (Cel.) gambiae, An. (Cel.) melas, An. (Cel.) merus, An. (Cel.) moucheti and An. (Cel.) nili*, and in the European and Middle Eastern Region: An. (Anopheles) atroparvus, An. (Ano.) labranchiae, An. (Ano.) messeae, An. (Ano.) sacharovi, An. (Cel.) sergentii and An. (Cel.) superpictus*. These maps are presented alongside a bionomics summary for each species relevant to its control.

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Author and article information

Contributors

Adrian Denz: adrian.denz@unibas.ch

Journal

Journal ID (nlm-ta): Parasit Vectors

Journal ID (iso-abbrev): Parasit Vectors

Title: Parasites & Vectors

Publisher: BioMed Central (London )

ISSN (Electronic): 1756-3305

Publication date (Electronic): 20 January 2021

Publication date PMC-release: 20 January 2021

Publication date Collection: 2021

Volume: 14

Electronic Location Identifier: 64

Affiliations

[1 ]GRID grid.416786.a, ISNI 0000 0004 0587 0574, Department of Epidemiology and Public Health, , Swiss Tropical and Public Health Institute, ; Socinstrasse 57, 4051 Basel, Switzerland

[2 ]GRID grid.6612.3, ISNI 0000 0004 1937 0642, University of Basel, ; Petersplatz 1, Basel, Switzerland

[3 ]GRID grid.419326.b, ISNI 0000 0004 1794 5158, Human Health Theme, , International Centre of Insect Physiology and Ecology (icipe), ; 00100 Nairobi, Kenya

[4 ]GRID grid.4818.5, ISNI 0000 0001 0791 5666, Laboratory of Entomology, , Wageningen University and Research, ; P.O. Box 16, 6700 AA Wageningen, The Netherlands

[5 ]GRID grid.414543.3, ISNI 0000 0000 9144 642X, Environmental Health and Ecological Sciences Department, , Ifakara Health Institute, ; P.O. Box 53, Ifakara, Tanzania

[6 ]GRID grid.8991.9, ISNI 0000 0004 0425 469X, ARCTEC, , London School of Hygiene and Tropical Medicine, ; Keppel Street, WC1E 7HT London, UK

[7 ]GRID grid.11951.3d, ISNI 0000 0004 1937 1135, School of Public Health, Faculty of Health Science, , University of the Witwatersrand, ; Johannesburg, South Africa

[8 ]GRID grid.451346.1, ISNI 0000 0004 0468 1595, School of Life Science and Biotechnology, , Nelson Mandela African Institution of Science and Technology, ; P.O. Box 447, Arusha, Tanzania

[9 ]GRID grid.8756.c, ISNI 0000 0001 2193 314X, Institute of Biodiversity, Animal Health and Comparative Medicine, , University of Glasgow, ; Glasgow, UK

Article

Publisher ID: 4560

DOI: 10.1186/s13071-020-04560-x

PMC ID: 7819244

PubMed ID: 33472661

SO-VID: ff733b26-dcf5-4917-ac86-245a191b8c01

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.

History

Date received : 17 July 2020

Date accepted : 21 December 2020

Funding

Funded by: Innovative Vector Control Consortium

Award ID: 44

Award Recipient : Adam Saddler

Funded by: FundRef http://dx.doi.org/10.13039/501100001711, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung;

Award ID: 163473

Award Recipient : Sarah J. Moore

Funded by: FundRef http://dx.doi.org/10.13039/100000865, Bill and Melinda Gates Foundation;

Award ID: OPP1032350

Award Recipient : Nakul Chitnis

Custom metadata

ScienceOpen disciplines: Parasitology

Keywords: malaria,anopheles arabiensis,vector control,outdoor transmission,spatial repellent,volatile pyrethroids,semi-field experiments,community-level impact,stochastic modelling,hierarchical bayesian model

Data availability:

ScienceOpen disciplines: Parasitology

Keywords: malaria, anopheles arabiensis, vector control, outdoor transmission, spatial repellent, volatile pyrethroids, semi-field experiments, community-level impact, stochastic modelling, hierarchical bayesian model

Predicting the impact of outdoor vector control interventions on malaria transmission intensity from semi-field studies

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Abstract

Background

Methods

Results

Conclusions

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Malaria vaccine development

Most cited references 39

Stan: A Probabilistic Programming Language

Increased proportions of outdoor feeding among residual malaria vector populations following increased use of insecticide-treated nets in rural Tanzania

The dominant Anopheles vectors of human malaria in Africa, Europe and the Middle East: occurrence data, distribution maps and bionomic précis

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