The DOI matches its Crossref record; 142 of the 143 references it cites were found in a registry or an index.
Characterizing, controlling and eliminating residual malaria transmission
Open accessAbstract
Long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) interventions can reduce malaria transmission by targeting mosquitoes when they feed upon sleeping humans and/or rest inside houses, livestock shelters or other man-made structures. However, many malaria vector species can maintain robust transmission, despite high coverage of LLINs/IRS containing insecticides to which they are physiologically fully susceptible, because they exhibit one or more behaviours that define the biological limits of achievable impact with these interventions: (1) Natural or insecticide-induced avoidance of contact with treated surfaces within houses and early exit from them, thus minimizing exposure hazard of vectors which feed indoors upon humans; (2) Feeding upon humans when they are active and unprotected outdoors, thereby attenuating personal protection and any consequent community-wide suppression of transmission; (3) Feeding upon animals, thus minimizing contact with insecticides targeted at humans or houses; (4) Resting outdoors, away from insecticide-treated surfaces of nets, walls and roofs. Residual malaria transmission is, therefore, defined as all forms of transmission that can persist after achieving full universal coverage with effective LLINs and/or IRS containing active ingredients to which local vector populations are fully susceptible. Residual transmission is sufficiently intense across most of the tropics to render malaria elimination infeasible without new or improved vector control methods. Many novel or improved vector control strategies to address residual transmission are emerging that either: (1) Enhance control of adult vectors that enter houses to feed and/or rest by killing, repelling or excluding them; (2) Kill or repel adult mosquitoes when they attack people outdoors; (3) Kill adult mosquitoes when they attack livestock; (4) Kill adult mosquitoes when they feed upon sugar or; (5) Kill immature mosquitoes in aquatic habitats. To date, none of these options has sufficient supporting evidence to justify full-scale programmatic implementation. Concerted investment in their rigorous selection, development and evaluation is required over the coming decade to enable control and, ultimately, elimination of residual malaria transmission. In the meantime, national programmes may assess options for addressing residual transmission under programmatic conditions through pilot studies with strong monitoring, evaluation and operational research components, similar to the Onchocerciasis Control Programme.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Figures
![Figure 1 The importance of feeding upon humans as a determinant of malaria transmission and vector control impact. A and B: Simulated relationship between malaria transmission intensity mediated by an Anopheles mosquito population and the proportion of blood meals that these vectors obtain from humans, in the presence and absence of long-lasting insecticidal nets (LLINs) with a mean nightly usage rate of 80%, presented with a linear (A) and logarithmic (B) vertical axis (Adapted from reference 11). C: Frequency distribution for the mean proportion of blood meals obtained from humans for the 33 most important locally dominant malaria vectors worldwide as reviewed in reference [7].](/paper-figures/ba68285886234dfa8cdbe139acb781c7/characterizing-controlling-and-eliminating-residual-malaria-transmission-figure-1.jpg)

![Figure 3 Progressive dramatic reduction of mosquito survival and infection probability as an increasing proportion of available blood meals are covered with LLINs or IRS. The probability curves presented represent the outputs of simulations implemented exactly as previously described [14] at 0, 20, 40 and 60% biological coverage of all available blood resources [10, 13] with LLINs that kill 60% of all mosquitoes encountering them.](/paper-figures/4ed50ec8d68a4653b8e66a8cca6c94b4/characterizing-controlling-and-eliminating-residual-malaria-transmission-figure-3.jpg)
![Figure 4 A schematic illustration of the differing trajectories of impact of an intervention upon malaria transmission by a vector population under the distinctive scenarios of either (A) Stable limitation of sustained impact arising from expression of pre-existing behavioural traits within a resilient vector population, or (B) Failure of impact and resurgence of malaria transmission when, either intervention programme implementation quality and coverage weakens, or selected behavioural or physiological traits emerge within an increasingly resistant, rebounding vector population [31] .](/paper-figures/85da83cc99734040bb697c55ea1b2efa/characterizing-controlling-and-eliminating-residual-malaria-transmission-figure-4.jpg)
![Figure 5 A schematic illustration of how mosquitoes may survive despite high coverage of long-lasting insecticidal nets or indoor residual spraying by entering, but then rapidly leaving houses protected with LLINs or IRS without exposing themselves to lethal doses of the active ingredients, and then continuing to forage until an unprotected blood host is found [38–41] .](/paper-figures/720420c50a8f420d9e76e2c9c5f4835e/characterizing-controlling-and-eliminating-residual-malaria-transmission-figure-5.jpg)
![Figure 6 Frequency distribution of the preferred biting times for 25 separate populations of 11 Latin American Anopheles species, which were classified as either: 1) potent primary vectors; 2) weak, incidental or secondary vectors; or 3) non-vectors (Adapted from reference [19] ).](/paper-figures/291d80fcb451479e93b28fd9f9251016/characterizing-controlling-and-eliminating-residual-malaria-transmission-figure-6.jpg)
![Figure 7 Estimates of the proportion of human exposure to African malaria vector populations that occurs indoors for both unprotected residents ( π h,i ) and users of long-lasting insecticidal nets ( π h,i,n ), from field sites across eastern, southern and western Africa[16], as previously calculated [71, 72] and presented in summary form [29]. Original data kindly provided by Bernadette Huho, Olivier Briët, Aklilu Seyoum, Chadwick Sikaala, Nabie Bayoh, John Gimnig, Fredros Okumu, Diadier Diallo, Salim Abdulla and Tom Smith.](/paper-figures/b109983e1041423ebb6365c15e3c56ed/characterizing-controlling-and-eliminating-residual-malaria-transmission-figure-7.jpg)
![Figure 8 Historical estimates of the proportion of human exposure to Latin American malaria vector populations in Colombia that would have occured indoors for both unprotected residents ( π h,i ) and users of modern long-lasting insecticidal nets ( π h,i,n ), calculated as originally described [19, 20] , except for the breakdown of indoor exposure into the fractions that would and would not be prevented by net use [71, 72] .](/paper-figures/c75f34d0aa704dcbb3b9a5c345907946/characterizing-controlling-and-eliminating-residual-malaria-transmission-figure-8.jpg)
![Figure 9 Estimates of the proportion of human exposure to Asian malaria vector populations that occurs indoors for both unprotected residents ( π h,i ) and users of long-lasting insecticidal nets ( π h,i,n ), from the Solomon Islands [75], Laos [76], Iran [17] and Myanmar [77, 78], calculated as previously described [71, 72], except that in the Iranian examples, indoor and outdoor biting densities were assumed to be equal because they were not reported separately [17]. Original data from the Solomon Islands and Myanmar were kindly provided by Hugo Bugoro, Tanya Russell, Frank Smithuis and Nick White.](/paper-figures/3123e360772b461583f9fb58beae6fe4/characterizing-controlling-and-eliminating-residual-malaria-transmission-figure-9.jpg)
![Figure 10 A graphic illustration of the estimated maximum achievable biological coverage of all blood resources (C v,max ) utilized by the vector species described in Figures 1 , 2 , 7 , 8 and 9 , for which estimates of both the proportion of blood meals obtained from humans ( Q h ) and the proportion of human blood meals obtained indoors ( π h,i ) were available. The width of the grey rectangles relative to that of the white squares represents the limit of personal protection and derived community-wide reduction of mutual human-vector exposure, while their relative area represents the achievable limit of biological coverage of all blood resources that determines the extent to which the density and survival of the vector population can be controlled [8, 10, 11, 13].](/paper-figures/1548c9a6c242445fb8c064576d0e372d/characterizing-controlling-and-eliminating-residual-malaria-transmission-figure-10.jpg)
![Figure 11 A schematic representation of the sequential layers of interventions required to eliminate malaria from the most staunchly endemic regions of Africa, adapted from references [64] and [29]. White arrows crudely illustrate the impacts of intervention strategies for which reasonable experience and understanding already exists (suppression of high transmission with LLINs or IRS and elimination of sparse residual human parasite reservoirs with drugs). Dark arrows illustrate the potential impact of interventions that urgently need to be developed and evaluated to either maximize impact of existing control measures (adequate and sustainable financing, long-term resistance management) or make more meaningful progress towards elimination (programmatic-scale interruption of residual transmission by behaviourally resilient and/or resistant mosquitoes using novel vector control tools, possibly supplemented with vaccines or chemoprophylaxis).](/paper-figures/ede59a955e31401e8971a4e71c837014/characterizing-controlling-and-eliminating-residual-malaria-transmission-figure-11.jpg)
![Figure 12 A schematic summary of how specific behaviours enable mosquito populations to survive and mediate residual malaria transmission despite high coverage of long-lasting insecticidal nets and/or indoor residual sprays, and how these might be tackled with new or improved vector control strategies [27, 84, 85] .](/paper-figures/2e99923013634201b4d46526690416e0/characterizing-controlling-and-eliminating-residual-malaria-transmission-figure-12.jpg)
![Figure 13 A schematic representation of how various alternative strategies for targeting vector mosquitoes when they utilize specific resources can suppress (Green) or redistribute, stabilize and even increase (Red) malaria transmission, depending on values for measurable behavioural parameters of the mosquito population and its interaction with interventions [8, 10, 11, 13–15, 80]. Red and green ovals indicate effects upon malaria transmission, with the magnitude of their impact indicated by their size. The relative magnitude of persisting transmission after intervention (ψ) is expressed as a function of: (1) the utilization rate (α) or probability (Q) of targetable subsets (x) of a defined resource (R, which may be specified as blood (v), resting sites (r), sugar (s) or aquatic larval habitat (a)); (2) the coverage of that resource subset (R x) achieved ; (3) the mortality probability (μ) of mosquitoes utilizing covered forms of that resource subset; where human blood is the targeted resource, (4) the personal protection (ρ) afforded as a result of repellence, irritance or physical deterrence (Δ) combined with fast-acting toxicity that occurs before the mosquito can feed (μ pre); and (5) the proportion of exposure that would otherwise occur when that intervention is used . For all parameters described, values approaching or exceeding one are considered high and values approaching zero are considered low. The subscripts h, l and i refer to the subsets human, livestock and indoors.](/paper-figures/9f7b479939e34417aff09a36638295f1/characterizing-controlling-and-eliminating-residual-malaria-transmission-figure-13.jpg)
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Nevertheless despite the proof of principle of their potential efficacy, the randomized control trials showing the benefit to use them at community scale are scarce [49], and their ecological scope of the application does not seem to be global.”
From Mapping insecticide resistance in Anopheles gambiae (s.l.) from Côte d'Ivoire (2018) · cites this paper as [49]
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Insecticide-treated bed nets and curtains for preventing malaria
Lengeler, C. (2004) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd000363.pub2 · Cited by 1,700
Ranson, H., N’Guessan, R., Lines, J., Moiroux, N., Nkuni, Z., & Corbel, V. (2011) · Trends in Parasitology · doi:10.1016/j.pt.2010.08.004 · Cited by 1,142
Silver, J. B. (2007) · Springer eBooks · doi:10.1007/978-1-4020-6666-5 · Cited by 1,005
A supplement to the Anophelinae of Africa south of the Sahara (Afrotropical Region).
Gillies, M. T., & Coetzee, M. (1987) · IHI Repository · Cited by 812
A global map of dominant malaria vectors
Sinka, M. E., Bangs, M. J., Manguin, S., Rubio-Palis, Y., Chareonviriyaphap, T., Coetzee, M., Mbogo, C. M., Hemingway, J., Patil, A. P., Temperley, W. H., et al. (2012) · Parasites & Vectors · doi:10.1186/1756-3305-5-69 · Cited by 792
Habicht, J. (1999) · International Journal of Epidemiology · doi:10.1093/ije/28.1.10 · Cited by 729
Mosquito Sugar Feeding and Reproductive Energetics
Foster, W. A. (1995) · Annual Review of Entomology · doi:10.1146/annurev.en.40.010195.002303 · Cited by 709
Russell, T. L., Govella, N. J., Azizi, S., Drakeley, C. J., Kachur, S. P., & Killeen, G. F. (2011) · Malaria Journal · doi:10.1186/1475-2875-10-80 · Cited by 698
Self-citationA GLOBAL INDEX REPRESENTING THE STABILITY OF MALARIA TRANSMISSION
Kiszewski, A. E., Mellinger, A. D., Spielman, A., Malaney, P. N., Sachs, S. E., & Sachs, J. D. (2004) · American Journal of Tropical Medicine and Hygiene · doi:10.4269/ajtmh.2004.70.486 · Cited by 664
Griffin, J. T., Hollingsworth, T. D., Okell, L. C., Churcher, T. S., White, M., Hinsley, W., Bousema, T., Drakeley, C. J., Ferguson, N. M., Basáñez, M.-G., et al. (2010) · PLoS Medicine · doi:10.1371/journal.pmed.1000324 · Cited by 595
Research works printed but not linked: 7
- WHO Global Malaria Control Programme: Global plan for insecticide resistance management in malaria vectors (GPIRM). 2012, Geneva: World Health Organization, 130-
- WHO: Guidelines for efficacy testing of spatial repellents. 2013, Geneva: World Health Organization
- WHO: Larval source management-A supplementary measure for malaria vector control: An Operational Manual. 2013, Geneva: World Health Organization
- WHO: Guidance note on capacity building in malaria entomology and vector control. 2013, Geneva: Global Malaria Programme, World Health Organization, 3-
- WHO: World Malaria Report 2013. 2013, Geneva: World Health Organization
- WHO: Global Strategic Framework for Integrated Vector Management. 2004, Geneva: World Health Organization
- WHO: Guidelines for testing mosquito adulticides for indoor residual spraying and treatment of mosquito nets. 2006, Geneva, Switzerland: World Health Organization
Cited by
Sorted by citations
Items 401–498 of 498
Maharaj, R., Lakan, V., & Maharaj, K. (2022) · Research Square · doi:10.21203/rs.3.rs-1557057/v1
Residual Malaria Among Migrant Workers in Myanmar: Why Still Persistent and How to Eliminate?Preprint
Nyunt, M. H., Aye, K. M., Naing, S. T., Mon, A. S., Htwe, M. M., Win, S. M. K., Thwe, W. M., Thi, A., & Kyaw, M. P. (2020) · doi:10.21203/rs.3.rs-100620/v1
Maharaj, R., Lakan, V., & Maharaj, K. (2020) · Research Square · doi:10.21203/rs.3.rs-52165/v1
Arifin, S. M. N., Madey, G. R., & Collins, F. H. (2016) · Wiley eBooks · doi:10.1002/9781118964385.refs
Sanou, R., Maïga, H., Sow, B. B. D., Ouema, A., Millogo, A. A., Bayili, K., Hien, A. S., Sawadogo, S. P., Millogo, S. A., Bélem, A. M. G., et al. (2023) · Research Square · doi:10.21203/rs.3.rs-2432364/v1
Spatially explicit sampling frameworks to identify regions of increased mosquito abundancePreprint
Kemei, B. J., Ochomo, E., Ombok, M., Midega, J. T., Lucas, E. R., Donnelly, M. J., Sedda, L., & McDermott, D. P. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.11.21.568008
Helmi, N. M. (2024) · Journal of Vector Borne Diseases · doi:10.4103/0972-9062.393977
Denz, A., Njoroge, M. M., Tambwe, M. M., Kamber, L., Cavelan, A., Smith, T. A., van Loon, J. J. A., Hiscox, A., Saddler, A., Fillinger, U., et al. (2024) · medRxiv · doi:10.1101/2024.01.29.24301958
Marcombe, S., Maithaviphet, S., Reyburn, R., Kunlaya, K., Silavong, K., Hongvanthong, B., Vanisaveth, V., Sengsavath, V., Banouvong, V., Chindavongsa, K., et al. (2023) · Figshare · doi:10.6084/m9.figshare.24417578
Emerging Global Population Health Risks: From Epidemiological Perspectives
(2024) · Frontiers research topics · doi:10.3389/978-2-8325-5352-7
The effects of landscape on malaria vectors of the neotropics
Lainhart, W. (2015) · Scholars Archive - University at Albany (University at Albany, State University of New York) · doi:10.54014/g7eh-mfbx
Malaria prevention in the age of climate change: A community survey in rural Senegal
Sherman, A. C. L., Matthews, J. D., & Aligne, C. A. (2025) · PLoS ONE · doi:10.1371/journal.pone.0313456
Harvey, S. A., Ekodir, S. M., Baker, L., Odero, J. I., Ekisa, M., Ikapesi, J. K. A., Tsang, S. W., Casella, A., McCoy, K. D., Passaniti, A., et al. (2026) · American Journal of Tropical Medicine and Hygiene · doi:10.4269/ajtmh.25-0413
Neelakantan, A., Srikanth, V. S., John, B. M., & Prabhakar, S. (2025) · Medical Journal of Dr D Y Patil Vidyapeeth · doi:10.4103/mjdrdypu.mjdrdypu_525_25
Elias, S., & Massebo, F. (2023) · Research Square · doi:10.21203/rs.3.rs-3328089/v1
Sumruayphol, S., Chaiphongpachara, T., Samung, Y., Ruangsittichai, J., Cui, L., Zhong, D., Sattabongkot, J., & Sriwichai, P. (2020) · Figshare · doi:10.6084/m9.figshare.13226042
Stanton, M. C., Kalonde, P. K., Zembere, K., Spaans, R. H., & Jones, C. M. (2021) · Figshare · doi:10.6084/m9.figshare.14707759
Stanton, M. C., Kalonde, P. K., Zembere, K., Spaans, R. H., & Jones, C. M. (2021) · Figshare · doi:10.6084/m9.figshare.14707753
Coleman, S., Yihdego, Y. Y.-E., Gyamfi, F., Kolyada, L., Tongren, J. E., Zigirumugabe, S., Dery, D. B., Badu, K., Obiri‐Danso, K., Boakye, D., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26598251
Stanton, M. C., Kalonde, P. K., Zembere, K., Spaans, R. H., & Jones, C. M. (2021) · Figshare · doi:10.6084/m9.figshare.14707750
Stanton, M. C., Kalonde, P. K., Zembere, K., Spaans, R. H., & Jones, C. M. (2021) · Figshare · doi:10.6084/m9.figshare.14707768
Coleman, S., Yihdego, Y. Y.-E., Gyamfi, F., Kolyada, L., Tongren, J. E., Zigirumugabe, S., Dery, D. B., Badu, K., Obiri‐Danso, K., Boakye, D., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26598248
Govella, N. J., Johnson, P. C. D., Killeen, G. F., & Ferguson, H. M. (2023) · Figshare · doi:10.6084/m9.figshare.23972829
Self-citationAl‐Amin, H. M., Rodriguez, I., Phru, C. S., Khan, W. A., Haque, R., Nahlen, B. L., Burton, T. A., Alam, M. S., & Lobo, N. F. (2023) · Figshare · doi:10.6084/m9.figshare.23304838
Stanton, M. C., Kalonde, P. K., Zembere, K., Spaans, R. H., & Jones, C. M. (2021) · Figshare · doi:10.6084/m9.figshare.14707756
Marcombe, S., Maithaviphet, S., Bobichon, J., Phommavan, N., Nambanya, S., Corbel, V., & Brey, P. T. (2020) · Figshare · doi:10.6084/m9.figshare.13212211
Tizifa, T. A., Kabaghe, A. N., McCann, R. S., Gowelo, S., Malenga, T., Nkhata, R. M., Chapeta, Y., Nkhono, W., Kadama, A., Takken, W., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26701414
Abossie, A., Demissew, A., Getachew, H., Tsegaye, A., Degefa, T., Habtamu, K., Zhong, D., Wang, X., Lee, M.-C., Zhou, G., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26677712
Abossie, A., Demissew, A., Getachew, H., Tsegaye, A., Degefa, T., Habtamu, K., Zhong, D., Wang, X., Lee, M.-C., Zhou, G., et al. (2024) · Figshare · doi:10.6084/m9.figshare.25157407
Ngowo, H. S., Hape, E. E., Matthiopoulos, J., Ferguson, H. M., & Okumu, F. O. (2021) · Figshare · doi:10.6084/m9.figshare.14211509
Phiri, M. D., McCann, R. S., Kabaghe, A. N., van den Berg, H., Malenga, T., Gowelo, S., Tizifa, T. A., Takken, W., van Vugt, M., Phiri, K. S., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14776603
Orondo, P. W., Nyanjom, S. G., Atieli, H., Githure, J., Ondeto, B. M., Ochwedo, K. O., Omondi, C. J., Kazura, J. W., Lee, M.-C., Zhou, G., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14853477
Permana, D. H., Zubaidah, S., Syahrani, L., Asih, P. B. S., Syafruddin, D., Rozi, I. E., Hidayati, A. P. N., Kosasih, S., Dewayanti, F. K., Rachmawati, N., et al. (2022) · Figshare · doi:10.6084/m9.figshare.20000078
McCann, R. S., Kabaghe, A. N., Moraga, P., Gowelo, S., Mburu, M. M., Tizifa, T. A., Chipeta, M. G., Nkhono, W., Pasquale, A. D., Maire, N., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14650839
Denz, A., Njoroge, M. M., Tambwe, M. M., Champagne, C., Okumu, F., van Loon, J. J. A., Hiscox, A., Saddler, A., Fillinger, U., Moore, S. J., et al. (2021) · Figshare · doi:10.6084/m9.figshare.13619893
Stanton, M. C., Kalonde, P. K., Zembere, K., Spaans, R. H., & Jones, C. M. (2021) · Figshare · doi:10.6084/m9.figshare.14707774
Tizifa, T. A., Kabaghe, A. N., McCann, R. S., Gowelo, S., Malenga, T., Nkhata, R. M., Chapeta, Y., Nkhono, W., Kadama, A., Takken, W., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26701426
Natchema S. Fonkou, B., Tchouakui, M., Menze, B. D., Mugenzi, L. M. J., Fofie, D., Nguiffo-Nguete, D., Lucia, N., Tombi, J., & Wondji, C. S. (2023) · Figshare · doi:10.6084/m9.figshare.24452418
Arnzen, A., Wagman, J., Chishya, C., Orange, E., Eisele, T. P., Yukich, J. O., Ashton, R. A., Chanda, J., Sakala, J., Chanda, B., et al. (2024) · Figshare · doi:10.6084/m9.figshare.25854704
Govella, N. J., Johnson, P. C. D., Killeen, G. F., & Ferguson, H. M. (2023) · Figshare · doi:10.6084/m9.figshare.23972826
Self-citationAbossie, A., Demissew, A., Getachew, H., Tsegaye, A., Degefa, T., Habtamu, K., Zhong, D., Wang, X., Lee, M.-C., Zhou, G., et al. (2024) · Figshare · doi:10.6084/m9.figshare.25157807
Govella, N. J., Johnson, P. C. D., Killeen, G. F., & Ferguson, H. M. (2023) · Figshare · doi:10.6084/m9.figshare.23972823
Self-citationGebhardt, M. E., Krizek, R. S., Coetzee, M., Koekemoer, L. L., Dahan-Moss, Y., Mbewe, D., Lupiya, J. S., Muleba, M., Stevenson, J. C., Moss, W. J., et al. (2022) · Figshare · doi:10.6084/m9.figshare.20222533
Phiri, M. D., McCann, R. S., Kabaghe, A. N., van den Berg, H., Malenga, T., Gowelo, S., Tizifa, T. A., Takken, W., van Vugt, M., Phiri, K. S., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14776597
Martin, J. A., Hendershot, A. L., Portilla, I. A. S., English, D. J., Woodruff, M., Vera-Arias, C. A., Salazar-Costa, B. E., Bustillos, J. J., Saénz, F. E., Ocaña-Mayorga, S., et al. (2020) · Figshare · doi:10.6084/m9.figshare.13047326
Sumruayphol, S., Chaiphongpachara, T., Samung, Y., Ruangsittichai, J., Cui, L., Zhong, D., Sattabongkot, J., & Sriwichai, P. (2020) · Figshare · doi:10.6084/m9.figshare.13226051
Orondo, P. W., Nyanjom, S. G., Atieli, H., Githure, J. I., Ondeto, B. M., Ochwedo, K. O., Omondi, C. J., Kazura, J. W., Lee, M.-C., Zhou, G., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14853483
Tizifa, T. A., Kabaghe, A. N., McCann, R. S., Gowelo, S., Malenga, T., Nkhata, R. M., Chapeta, Y., Nkhono, W., Kadama, A., Takken, W., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26701417
Phiri, M. D., McCann, R. S., Kabaghe, A. N., van den Berg, H., Malenga, T., Gowelo, S., Tizifa, T. A., Takken, W., van Vugt, M., Phiri, K. S., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14776591
Tizifa, T. A., Kabaghe, A. N., McCann, R. S., Gowelo, S., Malenga, T., Nkhata, R. M., Chapeta, Y., Nkhono, W., Kadama, A., Takken, W., et al. (2024) · Figshare · doi:10.6084/m9.figshare.25530450
Ngowo, H. S., Limwagu, A. J., Ferguson, H. M., Matthiopoulos, J., Okumu, F. O., & Nelli, L. (2022) · Figshare · doi:10.6084/m9.figshare.20508710
Gleave, K., Guy, A., Mechan, F., Emery, M., Murphy, A., Voloshin, V., Towers, C. E., Towers, D. P., Ranson, H., Foster, G. M., et al. (2023) · Figshare · doi:10.6084/m9.figshare.22681086
Perugini, E., Guelbeogo, W. M., Guglielmo, F., Poggi, C., Gabrieli, E., Ranson, H., della Torre, A., & Pombi, M. (2023) · Figshare · doi:10.6084/m9.figshare.22624544
Perugini, E., Guelbeogo, W. M., Guglielmo, F., Poggi, C., Gabrieli, E., Ranson, H., della Torre, A., & Pombi, M. (2023) · Figshare · doi:10.6084/m9.figshare.22624547
Cansado-Utrilla, C., Jeffries, C. L., Kristan, M., Brugman, V. A., Heard, P., Camara, G., Sylla, M., Béavogui, A. H., Messenger, L. A., Irish, S. R., et al. (2020) · Figshare · doi:10.6084/m9.figshare.12028398
Tizifa, T. A., Kabaghe, A. N., McCann, R. S., Gowelo, S., Malenga, T., Nkhata, R. M., Chapeta, Y., Nkhono, W., Kadama, A., Takken, W., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26701432
Orondo, P. W., Nyanjom, S. G., Atieli, H., Githure, J., Ondeto, B. M., Ochwedo, K. O., Omondi, C. J., Kazura, J. W., Lee, M.-C., Zhou, G., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14853486
Orondo, P. W., Nyanjom, S. G., Atieli, H., Githure, J., Ondeto, B. M., Ochwedo, K. O., Omondi, C. J., Kazura, J. W., Lee, M.-C., Zhou, G., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14853474
Phiri, M. D., McCann, R. S., Kabaghe, A. N., van den Berg, H., Malenga, T., Gowelo, S., Tizifa, T. A., Takken, W., van Vugt, M., Phiri, K. S., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14776594
Govella, N. J., Johnson, P. C. D., Killeen, G. F., & Ferguson, H. M. (2023) · Figshare · doi:10.6084/m9.figshare.23972820
Self-citationTizifa, T. A., Kabaghe, A. N., McCann, R. S., Gowelo, S., Malenga, T., Nkhata, R. M., Chapeta, Y., Nkhono, W., Kadama, A., Takken, W., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26701411
Abong’o, B., Gimnig, J. E., Longman, B., Odongo, T., Wekesa, C. N., Webwile, A., Oloo, B., Nduta, M., Muchoki, M., Omoke, D., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14775646
Arnzen, A., Wagman, J., Chishya, C., Orange, E., Eisele, T. P., Yukich, J. O., Ashton, R. A., Chanda, J., Sakala, J., Chanda, B., et al. (2024) · Figshare · doi:10.6084/m9.figshare.25854625
Marcombe, S., Maithaviphet, S., Bobichon, J., Phommavan, N., Nambanya, S., Corbel, V., & Brey, P. T. (2020) · Figshare · doi:10.6084/m9.figshare.13212202
Stanton, M. C., Kalonde, P. K., Zembere, K., Spaans, R. H., & Jones, C. M. (2021) · Figshare · doi:10.6084/m9.figshare.14707765
Permana, D. H., Zubaidah, S., Syahrani, L., Asih, P. B. S., Syafruddin, D., Rozi, I. E., Hidayati, A. P. N., Kosasih, S., Dewayanti, F. K., Rachmawati, N., et al. (2022) · Figshare · doi:10.6084/m9.figshare.20000075
Tizifa, T. A., Kabaghe, A. N., McCann, R. S., Gowelo, S., Malenga, T., Nkhata, R. M., Chapeta, Y., Nkhono, W., Kadama, A., Takken, W., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26701420
Stanton, M. C., Kalonde, P. K., Zembere, K., Spaans, R. H., & Jones, C. M. (2021) · Figshare · doi:10.6084/m9.figshare.14707762
Perugini, E., Guelbeogo, W. M., Guglielmo, F., Poggi, C., Gabrieli, E., Ranson, H., della Torre, A., & Pombi, M. (2023) · Figshare · doi:10.6084/m9.figshare.22624541
Soumare, H. M., Dabira, E. D., Camara, M. M., Jadama, L., Gaye, P. M., Kanteh, S., Jawara, E. A., Njie, A. K., Sanneh, F., Ndiath, M. O., et al. (2022) · Figshare · doi:10.6084/m9.figshare.21582709
Tizifa, T. A., Kabaghe, A. N., McCann, R. S., Gowelo, S., Malenga, T., Nkhata, R. M., Chapeta, Y., Nkhono, W., Kadama, A., Takken, W., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26701423
Marcombe, S., Maithaviphet, S., Bobichon, J., Phommavan, N., Nambanya, S., Corbel, V., & Brey, P. T. (2020) · Figshare · doi:10.6084/m9.figshare.13212205
Hast, M. A., Mharakurwa, S., Shields, T. M., Lubinda, J., Searle, K. M., Gwanzura, L., Munyati, S., & Moss, W. J. (2023) · Figshare · doi:10.6084/m9.figshare.22601576
Marcombe, S., Maithaviphet, S., Bobichon, J., Phommavan, N., Nambanya, S., Corbel, V., & Brey, P. T. (2020) · Figshare · doi:10.6084/m9.figshare.13212217
Cansado-Utrilla, C., Jeffries, C. L., Kristan, M., Brugman, V. A., Heard, P., Camara, G., Sylla, M., Béavogui, A. H., Messenger, L. A., Irish, S. R., et al. (2020) · Figshare · doi:10.6084/m9.figshare.12028392
Permana, D. H., Zubaidah, S., Syahrani, L., Asih, P. B. S., Syafruddin, D., Rozi, I. E., Hidayati, A. P. N., Kosasih, S., Dewayanti, F. K., Rachmawati, N., et al. (2022) · Figshare · doi:10.6084/m9.figshare.20000072
Zhou, G., Githure, J. I., Lee, M.-C., Zhong, D., Wang, X., Atieli, H., Githeko, A. K., Kazura, J. W., & Yan, G. (2024) · Figshare · doi:10.6084/m9.figshare.26692516
Orondo, P. W., Nyanjom, S. G., Atieli, H., Githure, J., Ondeto, B. M., Ochwedo, K. O., Omondi, C. J., Kazura, J. W., Lee, M.-C., Zhou, G., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14853489
Killeen, G. F., Monroe, A. C., & Govella, N. J. (2021) · Figshare · doi:10.6084/m9.figshare.15102801
Self-citationPhiri, M. D., McCann, R. S., Kabaghe, A. N., van den Berg, H., Malenga, T., Gowelo, S., Tizifa, T. A., Takken, W., van Vugt, M., Phiri, K. S., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14776600
Orondo, P. W., Nyanjom, S. G., Atieli, H., Githure, J., Ondeto, B. M., Ochwedo, K. O., Omondi, C. J., Kazura, J. W., Lee, M.-C., Zhou, G., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14853480
Stanton, M. C., Kalonde, P. K., Zembere, K., Spaans, R. H., & Jones, C. M. (2021) · Figshare · doi:10.6084/m9.figshare.14707771
Tizifa, T. A., Kabaghe, A. N., McCann, R. S., Gowelo, S., Malenga, T., Nkhata, R. M., Chapeta, Y., Nkhono, W., Kadama, A., Takken, W., et al. (2024) · Figshare · doi:10.6084/m9.figshare.25530214
Wagman, J., Chanda, B., Chanda, J., Saili, K., Orange, E., Mambo, P., Muyabe, R., Kaniki, T., Mwenya, M., Ng’andu, M., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26333204
Matsuda, I., Manin, B. O., Yahiro, T., Lambut, P., Tangah, J., Huffman, M. A., Bernard, H., Kumar, V. S., & Chua, T. H. (2026) · PLoS neglected tropical diseases · doi:10.1371/journal.pntd.0014849
Opiyo, M., Oppong, S. K., Vajda, É. A., Lobo, N. F., Tatarsky, A., & Thomsen, E. K. (2026) · medRxiv · doi:10.64898/2026.05.12.26352987
Chinula, D., Mumba, K., Zulu, R., Ndhlovu, K., Kavishe, D. R., Hobbs, N. P., Kiware, S. S., Reed, T., Hamainza, B., & Killeen, G. F. (2026) · Medical and Veterinary Entomology · doi:10.1111/mve.70080
Self-citationMalaria Prevalence in Children Under Five and Pregnant Women in Hong LGA
Atinga, A., Galaya, T., Emmanuel, W. B., Benson, O., Thomas, B. W., & Kaduna, B. A. (2026) · Trends in Biological Sciences · doi:10.21124/tbs.2026.219.227
Changes in malaria vector bionomics in Timor Leste between 2009 and 2016; a longitudinal study
Yapabandara, A. M. G. M., Mota, M. D. R. D. F., Sarmento, R., Bosco, J. D., Gusmão, M., Kahagallage, M. P. C., Munasinghe, T. U., & Wickremasinghe, A. R. (2026) · Malaria Journal · doi:10.1186/s12936-026-05966-1
Gutiérrez, A. S., Otuko, R., Xie, K., Omondi, I., Kariukiu, M., Ruiz-Castillo, P., Wanjiku, C., Brazeal, A., Ngama, M., Onyango, T., et al. (2026) · BMJ Global Health · doi:10.1136/bmjgh-2025-022607
Bello, A. B., Hassan, A. A., & Popoola, K. O. (2026) · Discover Public Health · doi:10.1186/s12982-026-02637-z
Saeung, M., Jupatanakul, N., Jampeesri, N., Lertlumnaphakul, W., Nobleza, J. A., Kim, D.-Y., Phuanukoonnon, S., Manguin, S., & Chareonviriyaphap, T. (2026) · Journal of Medical Entomology · doi:10.1093/jme/tjag148
Narpon, Q., Toto, J.-C., Lucarz, E., Santos, M. A. D., Ingles, A., Girault, C., Besnard, P., Cabinda, A. M., Martins, J. F., Poinsignon, A., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.09.14.751460
Bikoy, E. N., Nwane, P. B., Ekoko, W. E., Enama, S. E., Chadou, M. P., Alenou, L. D., Mandeng, S. E., Niamsi-Emalio, Y., Kamgno, J., & Etang, J. (2026) · Frontiers in Public Health · doi:10.3389/fpubh.2026.1870575
Yeshanew, S., Kendie, F. A., Atenafu, G., & Nibret, E. (2026) · Research Square · doi:10.21203/rs.3.rs-10946928/v1
Cheng, N. I., Dibbasey, M., Chu, C. E., Ndang, N. H., Amambua-Ngwa, B. N., Baah, C. A., Ntui, V. N., Adu, G. A., Owusu, D., Naabil, D. T., et al. (2026) · Research Square · doi:10.21203/rs.3.rs-11052787/v1
Metadata
- Authors
- Killeen, G. F.
- Affiliations
- Ifakara Health Institute (TZ)
- Corresponding author
- Killeen, Gerry F
- Venue
- Malaria Journal
- Published
- 2014-08-23
- Volume
- 13
- Issue
- 1
- Pages
- 330-330
- ISSN
- 1475-2875 (ISSN-L)
- PMC
- PMC4159526
- OpenAlex
- W2152400766
- Cited by
- 506
- References
- 143
- Citations by year
- 2026: 16 · 2025: 22 · 2024: 51 · 2023: 44 · 2022: 41 · 2021: 70 · 2020: 70 · 2019: 41 · 2018: 41 · 2017: 46 · 2016: 36 · 2015: 28
- FWCI
- 5.72
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Malaria Journal (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- LSTM Online Archive (Liverpool School of Tropical Medicine) (acceptedVersion)
- Funders
- World Health Organization
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Malaria Research and Control
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Mosquito-borne diseases and control
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Dengue and Mosquito Control Research
- Keywords
- residual malaria transmission, malaria vector control, long-lasting insecticidal nets, indoor residual spraying, vector behavior, vector control, malaria elimination, larval source management, pilot study
- MeSH terms
- Animals, Humans, Insect Vectors, Malaria, Mosquito Control, Culicidae, Disease Transmission, Infectious
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review