Cost comparison of community-based vector surveillance using VectorCam™, an AI-enabled mosquito identification tool, versus routine entomological surveillance in Uganda

Cost comparison of community-based vector surveillance using VectorCam™, an AI-enabled mosquito identification tool, versus routine entomological surveillance in Uganda | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Cost comparison of community-based vector surveillance using VectorCam™, an AI-enabled mosquito identification tool, versus routine entomological surveillance in Uganda Marina Rincon Torroella, Shreya Raman, Bryan N Patenaude, Sunny Patel, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9430793/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background: National malaria elimination programs depend on timely and reliable vector surveillance data to guide interventions. Current systems rely on analog data collection and microscopy-based morphological identification of mosquitoes by entomologists (vector control officers), a process constrained by limited entomologists, high specimen volumes, and specimen transport from rural collection sites. VectorCam™ is a smartphone-based device that uses AI to classify mosquito species, sex, and abdominal status within seconds, enabling automated workflows and the task-shifting of some entomologist responsibilities to community health workers (CHWs) or village health teams (VHTs). This study evaluatedthe unit cost of integrating VectorCam™ into routine surveillance in Uganda. Methods: Data were extracted from a 12-month pragmatic parallel randomized trial conducted across two districts in Uganda from 2023-2024. This analysis accounted only for costs directly associated with field activities, including personnel, transport, and supplies. Three VectorCam™ implementation models were analyzed. Model 1 represented full task-shifting of mosquito surveillance responsibilities to village health teams, where they were collected, analyzed, mosquito identified and reported data without the involvement of VCO and the use of VectorCam™. Model 2 incorporated quarterly supervision by VCO to support village health team-led activities. Model 3 included monthly VCO supervision, aligning with routine surveillance workflows, to assess the cost implications of adding digital surveillance to existing protocols. Results: The annual cost of routine surveillance (control arm) per district was USD $10,615. In comparison, VectorCam™ reduced costs to USD $8,852 in Model 1 (16.6% savings), USD $9,200 in Model 2 (13.3 savings), and USD $9,896 in Model 3 (6.8%savings). These reductions were driven primarily by reductions in personnel and transport expenditures, although they werepartially offset by higher supply costs associated with devices and service fees. The per-device analysis demonstrated that each VectorCam™ unit represented an annual cost of USD 144.51 but replaced USD 438.29 worth of surveillance functions, resulting in net savings of USD 293.78 per device under Model 1. Sensitivity analyses demonstrated increased savings in scenarios with existing digital infrastructure or the individual usage of VectorCam™ by one VHT. Conclusion: Digitalizing vector surveillance with VectorCam™ offers a cost-saving and scalable approach for low- and middle-income countries. By shifting resources from specialized, labor-intensive methods such asmicroscopy to technology operable by CHW. VectorCam™ supports more efficient data collection while reducing costs. These findings suggest that integrating digital task-shifting tools into national malaria surveillance programs can enhance vector surveillance in resource-constrained settings. Artificial intelligence Cost analysis Digital health Vector surveillance Malaria control Task-shifting Convolutional neural networks Community health workers VectorCam™ Health systems strengthening Full Text Additional Declarations Competing interest reported. The product described in this protocol publication is manufactured by Vector Control Innovations, Inc. (VCI), which is a collaborator in the study. Marina Rincon Torroella, Sunny M. Patel, and Soumyadipta Acharya are cofounders and unpaid members of the board of directors of VCI. This arrangement has been reviewed and approved by Johns Hopkins University in accordance with its conflict-of-interest policies. All the other authors declare that they have no competing interests. Supplementary Files Additionalfile1.CostunitanalysisVectorCam.xlsx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 14 May, 2026 Reviews received at journal 07 May, 2026 Reviewers agreed at journal 24 Apr, 2026 Reviewers invited by journal 22 Apr, 2026 Editor assigned by journal 22 Apr, 2026 Submission checks completed at journal 22 Apr, 2026 First submitted to journal 15 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9430793","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":632046798,"identity":"ef5cb833-ee4b-441f-a649-0d900df7b941","order_by":0,"name":"Marina Rincon 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Current systems rely on analog data collection and microscopy-based morphological identification of mosquitoes by entomologists (vector control officers), a process constrained by limited entomologists, high specimen volumes, and specimen transport from rural collection sites. VectorCam™ is a smartphone-based device that uses AI to classify mosquito species, sex, and abdominal status within seconds, enabling automated workflows and the task-shifting of some entomologist responsibilities to community health workers (CHWs) or village health teams (VHTs). This study evaluatedthe unit cost of integrating VectorCam™ into routine surveillance in Uganda.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eData were extracted from a 12-month pragmatic parallel randomized trial conducted across two districts in Uganda from 2023-2024. This analysis accounted only for costs directly associated with field activities, including personnel, transport, and supplies. 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These findings suggest that integrating digital task-shifting tools into national malaria surveillance programs can enhance vector surveillance in resource-constrained settings.\u003c/p\u003e","manuscriptTitle":"Cost comparison of community-based vector surveillance using VectorCam™, an AI-enabled mosquito identification tool, versus routine entomological surveillance in Uganda","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-30 21:25:55","doi":"10.21203/rs.3.rs-9430793/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"147524645568082328137401462341743347885","date":"2026-05-14T09:54:49+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-07T21:12:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"203462806633122899876594309090613101757","date":"2026-04-24T20:13:32+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-22T20:04:36+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-22T08:42:29+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-22T08:41:32+00:00","index":"","fulltext":""},{"type":"submitted","content":"Malaria Journal","date":"2026-04-15T19:58:02+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"malaria-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"malj","sideBox":"Learn more about [Malaria Journal](http://malariajournal.biomedcentral.com/)","snPcode":"12936","submissionUrl":"https://submission.nature.com/new-submission/12936/3","title":"Malaria Journal","twitterHandle":"@malariajournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fe5b8b16-e839-4af1-8ad8-21442b45e642","owner":[],"postedDate":"April 30th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"147524645568082328137401462341743347885","date":"2026-05-14T09:54:49+00:00","index":12,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-07T21:12:58+00:00","index":8,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-30T21:25:56+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-30 21:25:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9430793","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9430793","identity":"rs-9430793","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}