{"id":36322,"date":"2026-03-19T12:27:56","date_gmt":"2026-03-19T06:42:56","guid":{"rendered":"https:\/\/www.revoscience.com\/en\/?p=36322"},"modified":"2026-03-19T12:27:58","modified_gmt":"2026-03-19T06:42:58","slug":"new-model-predicts-how-mosquitoes-will-fly","status":"publish","type":"post","link":"https:\/\/www.revoscience.com\/en\/new-model-predicts-how-mosquitoes-will-fly\/","title":{"rendered":"New model predicts how mosquitoes will fly\u00a0"},"content":{"rendered":"\n<p><em><strong>Their flight patterns change in response to different sensory cues, a new study finds. The work could lead to more effective traps and mosquito control strategies.<\/strong><\/em><\/p>\n\n\n<div class=\"wp-block-post-author\"><div class=\"wp-block-post-author__content\"><p class=\"wp-block-post-author__name\">Jennifer Chu<\/p><\/div><\/div>\n\n\n<figure class=\"wp-block-image size-full\"><img data-dominant-color=\"283939\" data-has-transparency=\"false\" style=\"--dominant-color: #283939;\" loading=\"lazy\" decoding=\"async\" width=\"900\" height=\"600\" sizes=\"auto, (max-width: 900px) 100vw, 900px\" src=\"https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2026\/03\/MIT-MosquitoFlight-01-press_0.webp\" alt=\"\" class=\"wp-image-36323 not-transparent\" title=\"\" srcset=\"https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2026\/03\/MIT-MosquitoFlight-01-press_0.webp 900w, https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2026\/03\/MIT-MosquitoFlight-01-press_0-675x450.webp 675w, https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2026\/03\/MIT-MosquitoFlight-01-press_0-768x512.webp 768w, https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2026\/03\/MIT-MosquitoFlight-01-press_0-150x100.webp 150w\" \/><\/figure>\n\n\n\n<p>Cambridge, Mass. &#8212; A mosquito finds its target with the help of certain cues in its environment, such as a person\u2019s silhouette and the carbon dioxide they exhale.&nbsp;<\/p>\n\n\n\n<p>Now researchers at MIT and Georgia Tech have found that these visual and chemical cues help determine the insects\u2019 flight paths. The team has developed the first three-dimensional model of mosquito flight, based on experiments with mosquitoes flying in the presence of different sensory cues.&nbsp;<\/p>\n\n\n\n<p>Their model, reported today in the journal&nbsp;<em>Science Advances<\/em>, identifies three flight patterns that mosquitoes exhibit in response to sensory stimuli.&nbsp;<\/p>\n\n\n\n<p>When they can only see a potential target, mosquitoes take a \u201cfly-by\u201d approach, quickly diving in toward the target, then flying back out if they do not detect any other host-confirming cues.&nbsp;<\/p>\n\n\n\n<p>When they can\u2019t see a target but can smell a chemical cue such as carbon dioxide, mosquitoes will do \u201cdouble-takes,\u201d slowing down and flitting back and forth to keep close to the source.&nbsp;<\/p>\n\n\n\n<p>Interestingly, when mosquitoes receive both visual and chemical cues, such as seeing a silhouette and smelling carbon dioxide, they switch to an \u201corbiting\u201d pattern, flying around a target at a steady speed as they prepare to land, much like a shark circling its prey.&nbsp;<\/p>\n\n\n\n<p>The researchers say the new model can be used to predict how mosquitoes will fly in response to other cues, such as heat, humidity, and certain odors. Such predictions could help to design more effective traps and mosquito control strategies.&nbsp;<\/p>\n\n\n\n<p>\u201cOur work suggests that mosquito traps need specifically calibrated, multisensory lures to keep mosquitoes engaged long enough to be captured,\u201d says study author J\u00f6rn Dunkel, MathWorks Professor of Mathematics at MIT. \u201cWe hope this establishes&nbsp;a new paradigm for studying pest behavior by using 3D tracking and data-driven modeling to decode their movement and solve major public health challenges.\u201d<\/p>\n\n\n\n<p>The study\u2019s MIT co-authors are Chenyi Fei,&nbsp;a postdoc in MIT\u2019s Department of Mathematics,&nbsp;and Alexander Cohen PhD \u201926,&nbsp;a recent MIT chemical engineering PhD student advised by Dunkel and Professor Martin Bazant, along with Christopher Zuo, Soohwan Kim, and David L. Hu \u201901, PhD \u201906 of Georgia Tech, and Ring Carde of the University of California at Riverside.&nbsp;<\/p>\n\n\n\n<p><strong>Flight by numbers<\/strong><\/p>\n\n\n\n<p>Mosquitoes are considered to be the most dangerous animals in the world, given their collective impact on human health. The blood-sucking insects transmit malaria, dengue fever, West Nile virus, and other deadly diseases that together cause over 770,000 deaths each year.&nbsp;<\/p>\n\n\n\n<p>Of the 3,500 known species of mosquitoes, around 100 have evolved to specifically target humans, including&nbsp;<em>Aedes aegypti<\/em>, a species that uses a variety of cues to seek out human hosts. Scientists have studied how certain cues attract mosquitoes, mainly by setting up experiments in wind tunnels, where they can waft cues such as carbon dioxide and study how mosquitoes respond. Such experiments have mainly recorded data such as where and when the insects land. The researchers say no study has explored how mosquitoes fly as they hunt for a host.&nbsp;<\/p>\n\n\n\n<p>\u201cThe big question was: How do mosquitoes find a human target?\u201d says Fei.&nbsp;\u201cThere were previous experimental studies on what kind of cues might be important. But nothing has been especially quantitative.\u201d<\/p>\n\n\n\n<p>At MIT, Dunkel\u2019s group develops mathematical models to describe and predict the behavior of complex living systems, such as how&nbsp;<a href=\"https:\/\/link.mediaoutreach.meltwater.com\/ls\/click?upn=u001.aGL2w8mpmadAd46sBDLfbO9-2BvfSNt10TDlykjxxOUgyHrSB5L-2B9dr6ORnkr-2Fyy9-2FbCN9CSSs-2Bhf54bpcj5MQCZGFefMXAZgXwAWXXwz5lOg-3D6hk8_Gmh-2FjktplCfWo1o-2BFbkY3J9eYBJUJc-2BSUmMkHo42Dqe4Z0qTEKCmSFnQfWCe8-2B8jgXgQQcW-2Fb1rLKfKZRu-2BLLGScwMYc-2FOCX9RDmpXEBR4BY9i7y-2BNgpMuREG7n76alZH4-2FbTFM-2BcJqx1OyFxTjzQT9Ng2qNexYz9yH63iFPkLzye8yrV9-2B-2ByZOT4zdWXkCcTVTALdmLwcCpBVIxn-2FgzXtUHmkF7X2on1JP045yihgE51wPQ-2BbamKbCtHzo4EFCZwEB3cKf0RTc4hPNWXDF9b60BKUz7NAZH9tBAvm7m-2BMvK0fQ-2FUIlJslM0kWg1hwXxjx2DgCEzXRgiFv-2F2N57SGxBQR4LK54DYZkmnCQYfJHYtltB4tWJZRhPzlS-2F0nBCZ6VaYwOoeRNAuJbk34eYKCA-3D-3D\" target=\"_blank\" rel=\"noreferrer noopener\">worms untangle<\/a>,&nbsp;<a href=\"https:\/\/link.mediaoutreach.meltwater.com\/ls\/click?upn=u001.aGL2w8mpmadAd46sBDLfbO9-2BvfSNt10TDlykjxxOUgyYenOw-2BLa-2BFMy8idVzvCxz6aTwmLWEp5NIJCz0yECD7uoJens3ASrrGuXh6BFuxa4-3DYavf_Gmh-2FjktplCfWo1o-2BFbkY3J9eYBJUJc-2BSUmMkHo42Dqe4Z0qTEKCmSFnQfWCe8-2B8jgXgQQcW-2Fb1rLKfKZRu-2BLLGScwMYc-2FOCX9RDmpXEBR4BY9i7y-2BNgpMuREG7n76alZH4-2FbTFM-2BcJqx1OyFxTjzQT9Ng2qNexYz9yH63iFPkLzye8yrV9-2B-2ByZOT4zdWXkCcTVTALdmLwcCpBVIxn-2FgzXtUHmkF7X2on1JP045yihgEAq6ZKqf38F45nlMhNQLOctv4GiaL0NLkZyUa5mHfCKx1bsG3itU8nDO8Q8rSChUOwfYxLM13UVm14DD0ir4dQCjzrz2noxG8EP2oB0fECjiH-2FBqK6tEgg5PsVVxSdnLwBo3wa3Yz3qwsYSP8Yn3DlcC-2F-2FNj1eOfPAA8vVDVj-2BJA-3D-3D\" target=\"_blank\" rel=\"noreferrer noopener\">how&nbsp;starfish embryos<\/a>&nbsp;develop and swim, and how microbes evolve their community structure over time.&nbsp;<\/p>\n\n\n\n<p>Dunkel looked to apply similar quantitative techniques to predict flight patterns of mosquitoes after giving a talk at Georgia Tech. David Hu, a former MIT graduate student who is now a professor of mechanical engineering at Georgia Tech, proposed a collaboration; Hu\u2019s lab was carrying out experiments with mosquitoes at a facility at the Centers of Disease Control and Prevention in Atlanta, where they were studying the insects\u2019 behavior in response to sensory cues. Could Dunkel\u2019s group use the collected data to identify significant flight behavior that could ultimately help scientists control mosquito populations?&nbsp;<\/p>\n\n\n\n<p>\u201cOne of the original motivations was designing better traps for mosquitoes,\u201d says Cohen. \u201cFiguring out how they fly around a human gives insights on how we can avoid them.\u201d<\/p>\n\n\n\n<p><strong>Taking cues<\/strong><\/p>\n\n\n\n<p>For their new study, Hu and his colleagues at Georgia Tech carried out experiments with 50 to 100 mosquitoes of the&nbsp;<em>Aedes aegypti<\/em>&nbsp;species. The insects flew around inside a long, white, slightly angled rectangular room as cameras around the room captured detailed three-dimensional trajectories of each mosquito as it flew around. In the center of the room, they placed an object to represent a certain visual or chemical cue.&nbsp;<\/p>\n\n\n\n<p>In some trials, they placed a black Styrofoam sphere on a stand to represent a simple visual cue. (Mosquitoes would be able to see the black sphere against the room\u2019s white background). In other trials, they set up a white sphere with a tube running through to pump out carbon dioxide at rates similar to what humans breathe out. These trials represented the presence of a chemical cue, but not a visual cue.&nbsp;<\/p>\n\n\n\n<p>The researchers also studied the mosquitoes\u2019 response to both visual and chemical cues, using a black sphere that emitted carbon dioxide. Finally, they observed how mosquitoes behaved around a human volunteer who wore protective clothing that was black on one side and white on the other.<\/p>\n\n\n\n<p>Across 20 experiments, the team generated more than 53 million data points and over 477,220 mosquito flight paths. Hu shared the data with Dunkel, whose group used the measurements to develop a model for mosquito flight behavior.&nbsp;<\/p>\n\n\n\n<p>\u201cWe are proposing a very broad range of dynamical equations, and when you start out, the equation to predict a mosquito\u2019s flight path is very complicated, with a lot of terms, including the relative importance of a visual versus a chemical cue,\u201d Dunkel explains. \u201cThen through iteration against data, we reduce the complexity of that equation until we get the simplest model that still agrees with the data.\u201d<\/p>\n\n\n\n<p>In the end, the group whittled down a simple model that accurately predicts how a mosquito will fly, given the presence of a visual cue, a chemical cue, or both. The flight paths in response to one or the other cue are markedly different. And interestingly, when both cues are present, the researchers noted that the resulting path is not \u201cadditive.\u201d In other words, a mosquito does not simply combine the paths that it would separately take when it can both see and smell a target. Instead, the insects take a distinct path, circling, rather than diving or darting around their target.&nbsp;<\/p>\n\n\n\n<p>\u201cOur work suggests that&nbsp;mosquito traps need specifically calibrated \u2018multisensory\u2019 lures to keep mosquitoes engaged long enough to be captured,\u201d Dunkel says.<\/p>\n\n\n\n<p>\u201cObviously there are additional cues that humans emit, like odor, heat, and humidity,\u201d Cohen notes. \u201cFor&nbsp;the species we study, visual and carbon dioxide cues are the most important. But we can apply this model to study different species and how they respond to other sensory cues.\u201d<\/p>\n\n\n\n<p>The researchers have developed an&nbsp;<a href=\"https:\/\/link.mediaoutreach.meltwater.com\/ls\/click?upn=u001.aGL2w8mpmadAd46sBDLfbMq85o5OU78rarhVjIdbV3CEdQbcvxyACPLJWodHANY2HZjH_Gmh-2FjktplCfWo1o-2BFbkY3J9eYBJUJc-2BSUmMkHo42Dqe4Z0qTEKCmSFnQfWCe8-2B8jgXgQQcW-2Fb1rLKfKZRu-2BLLGScwMYc-2FOCX9RDmpXEBR4BY9i7y-2BNgpMuREG7n76alZH4-2FbTFM-2BcJqx1OyFxTjzQT9Ng2qNexYz9yH63iFPkLzye8yrV9-2B-2ByZOT4zdWXkCcTVTALdmLwcCpBVIxn-2FgzXtUHmkF7X2on1JP045yihgF0k2ensRJI8WmSeLE8cwfuFxkXj63iBSZcUuPi-2BAcAmMZzE5RO6GC7XdoE-2Fv6hs5FcrfeawwaVURxcbzlyNpnLQq2NSEfK-2FWsKpJ05WExj2O0jvZoUKbgc74bXrmN2y-2F5F2-2FACm-2FxhXzZx-2FVHGE0t4seh5sZAxq5k74vQOyDPwRg-3D-3D\" target=\"_blank\" rel=\"noreferrer noopener\">interactive app<\/a>&nbsp;that incorporates the new mosquito flight model. Users can experiment with different objects and set parameters such as the number of mosquitoes around the object and the type of sensory cue that is present. The model then visualizes how the mosquitoes would fly in response.&nbsp;<\/p>\n\n\n\n<p>\u201cThe original hope was to have a quantitative model that can simulate mosquito behavior around various trap designs,\u201d Cohen says. \u201cNow that we have a model, we can start to design more intelligent traps.\u201d<\/p>\n\n\n\n<p>This work was supported, in part, by the National Science Foundation, Schmidt Sciences, LLC, the NDSEG Fellowship Program, and the MIT MathWorks Professorship Fund.&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Cambridge, Mass. &#8212; A mosquito finds its target with the help of certain cues in its environment, such as a person\u2019s silhouette and the carbon dioxide they exhale.\u00a0<\/p>\n","protected":false},"author":2,"featured_media":36323,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[17],"tags":[],"class_list":["post-36322","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-research"],"featured_image_urls":{"full":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2026\/03\/MIT-MosquitoFlight-01-press_0.webp",900,600,false],"thumbnail":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2026\/03\/MIT-MosquitoFlight-01-press_0-200x200.webp",200,200,true],"medium":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2026\/03\/MIT-MosquitoFlight-01-press_0-675x450.webp",675,450,true],"medium_large":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2026\/03\/MIT-MosquitoFlight-01-press_0-768x512.webp",750,500,true],"large":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2026\/03\/MIT-MosquitoFlight-01-press_0.webp",750,500,false],"1536x1536":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2026\/03\/MIT-MosquitoFlight-01-press_0.webp",900,600,false],"2048x2048":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2026\/03\/MIT-MosquitoFlight-01-press_0.webp",900,600,false],"ultp_layout_landscape_large":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2026\/03\/MIT-MosquitoFlight-01-press_0.webp",900,600,false],"ultp_layout_landscape":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2026\/03\/MIT-MosquitoFlight-01-press_0-870x570.webp",870,570,true],"ultp_layout_portrait":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2026\/03\/MIT-MosquitoFlight-01-press_0-600x600.webp",600,600,true],"ultp_layout_square":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2026\/03\/MIT-MosquitoFlight-01-press_0-600x600.webp",600,600,true],"newspaper-x-single-post":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2026\/03\/MIT-MosquitoFlight-01-press_0-760x490.webp",760,490,true],"newspaper-x-recent-post-big":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2026\/03\/MIT-MosquitoFlight-01-press_0-550x360.webp",550,360,true],"newspaper-x-recent-post-list-image":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2026\/03\/MIT-MosquitoFlight-01-press_0-95x65.webp",95,65,true],"web-stories-poster-portrait":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2026\/03\/MIT-MosquitoFlight-01-press_0-640x600.webp",640,600,true],"web-stories-publisher-logo":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2026\/03\/MIT-MosquitoFlight-01-press_0-96x96.webp",96,96,true],"web-stories-thumbnail":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2026\/03\/MIT-MosquitoFlight-01-press_0-150x100.webp",150,100,true]},"author_info":{"info":["Jennifer Chu"]},"category_info":"<a href=\"https:\/\/www.revoscience.com\/en\/category\/news\/research\/\" rel=\"category 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