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Uelmen JA, Mapes CD, Prasauskas A, Boohene C, Burns L, Stuck J, Carney RM. A Habitat Model for Disease Vector Aedes aegypti in the Tampa Bay Area, FloridA. JOURNAL OF THE AMERICAN MOSQUITO CONTROL ASSOCIATION 2023; 39:96-107. [PMID: 37364184 DOI: 10.2987/22-7109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/28/2023]
Abstract
Within the contiguous USA, Florida is unique in having tropical and subtropical climates, a great abundance and diversity of mosquito vectors, and high rates of human travel. These factors contribute to the state being the national ground zero for exotic mosquito-borne diseases, as evidenced by local transmission of viruses spread by Aedes aegypti, including outbreaks of dengue in 2022 and Zika in 2016. Because of limited treatment options, integrated vector management is a key part of mitigating these arboviruses. Practical knowledge of when and where mosquito populations of interest exist is critical for surveillance and control efforts, and habitat predictions at various geographic scales typically rely on ecological niche modeling. However, most of these models, usually created in partnership with academic institutions, demand resources that otherwise may be too time-demanding or difficult for mosquito control programs to replicate and use effectively. Such resources may include intensive computational requirements, high spatiotemporal resolutions of data not regularly available, and/or expert knowledge of statistical analysis. Therefore, our study aims to partner with mosquito control agencies in generating operationally useful mosquito abundance models. Given the increasing threat of mosquito-borne disease transmission in Florida, our analytic approach targets recent Ae. aegypti abundance in the Tampa Bay area. We investigate explanatory variables that: 1) are publicly available, 2) require little to no preprocessing for use, and 3) are known factors associated with Ae. aegypti ecology. Out of our 4 final models, none required more than 5 out of the 36 predictors assessed (13.9%). Similar to previous literature, the strongest predictors were consistently 3- and 4-wk temperature and precipitation lags, followed closely by 1 of 2 environmental predictors: land use/land cover or normalized difference vegetation index. Surprisingly, 3 of our 4 final models included one or more socioeconomic or demographic predictors. In general, larger sample sizes of trap collections and/or citizen science observations should result in greater confidence in model predictions and validation. However, given disparities in trap collections across jurisdictions, individual county models rather than a multicounty conglomerate model would likely yield stronger model fits. Ultimately, we hope that the results of our assessment will enable more accurate and precise mosquito surveillance and control of Ae. aegypti in Florida and beyond.
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Uelmen JA, Lamcyzk B, Irwin P, Bartlett D, Stone C, Mackay A, Arsenault-Benoit A, Ryan SJ, Mutebi JP, Hamer GL, Fritz M, Smith RL. Human biting mosquitoes and implications for West Nile virus transmission. Parasit Vectors 2023; 16:2. [PMID: 36593496 PMCID: PMC9806905 DOI: 10.1186/s13071-022-05603-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 11/30/2022] [Indexed: 01/03/2023] Open
Abstract
BACKGROUND West Nile virus (WNV), primarily vectored by mosquitoes of the genus Culex, is the most important mosquito-borne pathogen in North America, having infected thousands of humans and countless wildlife since its arrival in the USA in 1999. In locations with dedicated mosquito control programs, surveillance methods often rely on frequent testing of mosquitoes collected in a network of gravid traps (GTs) and CO2-baited light traps (LTs). Traps specifically targeting oviposition-seeking (e.g. GTs) and host-seeking (e.g. LTs) mosquitoes are vulnerable to trap bias, and captured specimens are often damaged, making morphological identification difficult. METHODS This study leverages an alternative mosquito collection method, the human landing catch (HLC), as a means to compare sampling of potential WNV vectors to traditional trapping methods. Human collectors exposed one limb for 15 min at crepuscular periods (5:00-8:30 am and 6:00-9:30 pm daily, the time when Culex species are most actively host-seeking) at each of 55 study sites in suburban Chicago, Illinois, for two summers (2018 and 2019). RESULTS A total of 223 human-seeking mosquitoes were caught by HLC, of which 46 (20.6%) were mosquitoes of genus Culex. Of these 46 collected Culex specimens, 34 (73.9%) were Cx. salinarius, a potential WNV vector species not thought to be highly abundant in upper Midwest USA. Per trapping effort, GTs and LTs collected > 7.5-fold the number of individual Culex specimens than HLC efforts. CONCLUSIONS The less commonly used HLC method provides important insight into the complement of human-biting mosquitoes in a region with consistent WNV epidemics. This study underscores the value of the HLC collection method as a complementary tool for surveillance to aid in WNV vector species characterization. However, given the added risk to the collector, novel mitigation methods or alternative approaches must be explored to incorporate HLC collections safely and strategically into control programs.
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Affiliation(s)
- Johnny A. Uelmen
- Department of Pathobiology, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, 3505 Veterinary Medicine Basic Sciences Building, 2001 S. Lincoln Ave, Urbana, IL 61802 USA
| | - Bennett Lamcyzk
- Department of Pathobiology, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, 3505 Veterinary Medicine Basic Sciences Building, 2001 S. Lincoln Ave, Urbana, IL 61802 USA
| | - Patrick Irwin
- Northwest Mosquito Abatement District, 147 W. Hintz Rd, Wheeling, IL 60090 USA
| | - Dan Bartlett
- Northwest Mosquito Abatement District, 147 W. Hintz Rd, Wheeling, IL 60090 USA
| | - Chris Stone
- Illinois Natural History Survey, Prairie Research Institute, University of Illinois at Urbana-Champaign, Forbes Natural History Building, 1816 S. Oak Street, M/C 652, Champaign, IL 61820 USA
| | - Andrew Mackay
- Illinois Natural History Survey, Prairie Research Institute, University of Illinois at Urbana-Champaign, Forbes Natural History Building, 1816 S. Oak Street, M/C 652, Champaign, IL 61820 USA
| | - Arielle Arsenault-Benoit
- Department of Entomology, College of Computer, Mathematical, and Natural Sciences, University of Maryland, 4112 Plant Sciences Building, College Park, MD 20742 USA
| | - Sadie J. Ryan
- Department of Geography, College of Liberal Arts and Sciences, University of Florida, 3141 Turlington Hall, 330 Newell Dr, Gainesville, FL 32611 USA
| | - John-Paul Mutebi
- Division of Vector-Borne Diseases, Arboviral Disease Branch, US Centers for Disease Control and Prevention, 3156 Rampart Rd., Fort Collins, CO 80521 USA
| | - Gabriel L. Hamer
- Department of Entomology. College of Agriculture & Life Sciences, Texas A&M University, TAMU 2475, College Station, TX 77843 USA
| | - Megan Fritz
- Department of Entomology, College of Computer, Mathematical, and Natural Sciences, University of Maryland, 4112 Plant Sciences Building, College Park, MD 20742 USA
| | - Rebecca L. Smith
- Department of Pathobiology, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, 3505 Veterinary Medicine Basic Sciences Building, 2001 S. Lincoln Ave, Urbana, IL 61802 USA
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Keyel AC, Gorris ME, Rochlin I, Uelmen JA, Chaves LF, Hamer GL, Moise IK, Shocket M, Kilpatrick AM, DeFelice NB, Davis JK, Little E, Irwin P, Tyre AJ, Helm Smith K, Fredregill CL, Elison Timm O, Holcomb KM, Wimberly MC, Ward MJ, Barker CM, Rhodes CG, Smith RL. A proposed framework for the development and qualitative evaluation of West Nile virus models and their application to local public health decision-making. PLoS Negl Trop Dis 2021; 15:e0009653. [PMID: 34499656 PMCID: PMC8428767 DOI: 10.1371/journal.pntd.0009653] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
West Nile virus (WNV) is a globally distributed mosquito-borne virus of great public health concern. The number of WNV human cases and mosquito infection patterns vary in space and time. Many statistical models have been developed to understand and predict WNV geographic and temporal dynamics. However, these modeling efforts have been disjointed with little model comparison and inconsistent validation. In this paper, we describe a framework to unify and standardize WNV modeling efforts nationwide. WNV risk, detection, or warning models for this review were solicited from active research groups working in different regions of the United States. A total of 13 models were selected and described. The spatial and temporal scales of each model were compared to guide the timing and the locations for mosquito and virus surveillance, to support mosquito vector control decisions, and to assist in conducting public health outreach campaigns at multiple scales of decision-making. Our overarching goal is to bridge the existing gap between model development, which is usually conducted as an academic exercise, and practical model applications, which occur at state, tribal, local, or territorial public health and mosquito control agency levels. The proposed model assessment and comparison framework helps clarify the value of individual models for decision-making and identifies the appropriate temporal and spatial scope of each model. This qualitative evaluation clearly identifies gaps in linking models to applied decisions and sets the stage for a quantitative comparison of models. Specifically, whereas many coarse-grained models (county resolution or greater) have been developed, the greatest need is for fine-grained, short-term planning models (m-km, days-weeks) that remain scarce. We further recommend quantifying the value of information for each decision to identify decisions that would benefit most from model input.
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Affiliation(s)
- Alexander C. Keyel
- Division of Infectious Diseases, Wadsworth Center, New York State Department of Health, Albany, New York, United States of America
- Department of Atmospheric and Environmental Sciences, University at Albany, Albany, New York, United States of America
| | - Morgan E. Gorris
- Information Systems and Modeling & Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America
| | - Ilia Rochlin
- Center for Vector Biology, Rutgers University, New Brunswick, New Jersey, United States of America
| | - Johnny A. Uelmen
- Department of Pathobiology, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America
| | - Luis F. Chaves
- Instituto Costarricense de Investigación y Enseñanza en Nutrición y Salud (INCIENSA), Tres Rios, Cartago, Costa Rica
| | - Gabriel L. Hamer
- Department of Entomology, Texas A&M University, College Station, Texas, United States of America
| | - Imelda K. Moise
- Department of Geography & Regional Studies, University of Miami, Coral Gables, Florida, United States of America
| | - Marta Shocket
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, California, United States of America
| | - A. Marm Kilpatrick
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, California, United States of America
| | - Nicholas B. DeFelice
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York, United States of America
| | - Justin K. Davis
- Department of Geography and Environmental Sustainability, University of Oklahoma, Norman, Oklahoma, United States of America
| | - Eliza Little
- Connecticut Agricultural Experimental Station, New Haven, Connecticut, United States of America
| | - Patrick Irwin
- Northwest Mosquito Abatement District, Wheeling, Illinois, United States of America
- Department of Entomology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Andrew J. Tyre
- School of Natural Resources, University of Nebraska-Lincoln, Lincoln, Nebraska, United States of America
| | - Kelly Helm Smith
- National Drought Mitigation Center, University of Nebraska-Lincoln, Lincoln, Nebraska, United States of America
| | - Chris L. Fredregill
- Mosquito and Vector Control Division, Harris County Public Health, Houston, Texas, United States of America
| | - Oliver Elison Timm
- Department of Atmospheric and Environmental Sciences, University at Albany, Albany, New York, United States of America
| | - Karen M. Holcomb
- Department of Pathology, Microbiology, and Immunology, University of California Davis, California, United States of America
| | - Michael C. Wimberly
- Department of Geography and Environmental Sustainability, University of Oklahoma, Norman, Oklahoma, United States of America
| | - Matthew J. Ward
- Environmental Analytics Group, Universities Space Research Association, NASA Ames Research Center, Moffett Field, California, United States of America
- Department of Tropical Medicine, Tulane University School of Public Health & Tropical Medicine, New Orleans, Louisiana, United States of America
| | - Christopher M. Barker
- Department of Pathology, Microbiology, and Immunology, University of California Davis, California, United States of America
| | - Charlotte G. Rhodes
- Department of Entomology, Texas A&M University, College Station, Texas, United States of America
| | - Rebecca L. Smith
- Department of Pathobiology, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America
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