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Heidi E Brown

  • Associate Professor, Public Health
  • Associate Professor, Geography/Regional Devel
  • Associate Professor, Entomology / Insect Science - GIDP
  • Associate Professor, Remote Sensing / Spatial Analysis - GIDP
Contact
  • (520) 626-2262
  • Roy P. Drachman Hall, Rm. A249
  • Tucson, AZ 85721
  • heidibrown@email.arizona.edu
  • Bio
  • Interests
  • Courses
  • Scholarly Contributions

Degrees

  • M.Phil. Epidemiology of Microbial Diseases
    • Yale University, New Haven, Connecticut
  • Ph.D. Epidemiology of Microbial Diseases
    • Yale University, New Haven, Connecticut
    • Into the Environment of Mosquito-Borne Disease: Spatial Analysis of Vector Distribution Using Traditional and Remotely Sensed Methods
  • MPH International Health Promotion
    • George Washington University, Washington, D.C.
    • Rabies in Fairfax County, VA, USA

Awards

  • Fulbright-CAPES Award
    • Fulbright Commission, the Council for International Exchange of Scholars (CIES), Summer 2019
  • College Teaching Award
    • UA, Spring 2018
  • Chikungunya Challenge
    • DARPA/Innocentive, Spring 2015

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Interests

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Courses

2020-21 Courses

  • Health Data Analy Comm Methods
    BIOS 452 (Spring 2021)
  • Health Data Analy Comm Methods
    EPID 452 (Spring 2021)
  • Independent Study
    EPID 699 (Spring 2021)
  • Intro to Epidemiology
    EPID 309 (Spring 2021)
  • Master's Report
    EPID 909 (Spring 2021)
  • Preceptorship
    EPID 491 (Spring 2021)
  • Spatial Epidemiology
    EPID 676 (Spring 2021)
  • Honors Thesis
    EPID 498H (Fall 2020)
  • Intro to Epidemiology
    EPID 309 (Fall 2020)
  • Master's Report
    EPID 909 (Fall 2020)

2019-20 Courses

  • Independent Study
    EPID 699 (Summer I 2020)
  • Intro to Epidemiology
    EPID 309 (Summer I 2020)
  • Master's Report
    EPID 909 (Summer I 2020)
  • Preceptorship
    EPID 491 (Summer I 2020)
  • Thesis
    EHS 910 (Summer I 2020)
  • Health Data Analy Comm Methods
    BIOS 452 (Spring 2020)
  • Health Data Analy Comm Methods
    EPID 452 (Spring 2020)
  • Honors Thesis
    EPID 498H (Spring 2020)
  • Honors Thesis
    PSIO 498H (Spring 2020)
  • Independent Study
    EPID 699 (Spring 2020)
  • Intro to Epidemiology
    EPID 309 (Spring 2020)
  • Master's Report
    EPID 909 (Spring 2020)
  • Preceptorship
    EPID 491 (Spring 2020)
  • Thesis
    EPID 910 (Spring 2020)
  • Honors Independent Study
    EPID 399H (Fall 2019)
  • Honors Thesis
    EPID 498H (Fall 2019)
  • Honors Thesis
    PSIO 498H (Fall 2019)
  • Master's Report
    EPID 909 (Fall 2019)

2018-19 Courses

  • Master's Report
    EPID 909 (Summer I 2019)
  • Independent Study
    EPID 499 (Spring 2019)
  • Independent Study
    EPID 599 (Spring 2019)
  • Independent Study
    EPID 699 (Spring 2019)
  • Intro to Epidemiology
    EPID 309 (Spring 2019)
  • Preceptorship
    EPID 491 (Spring 2019)
  • Spatial Epidemiology
    EPID 676 (Spring 2019)
  • Independent Study
    EPID 599 (Fall 2018)
  • Intro to Epidemiology
    EPID 309 (Fall 2018)
  • Preceptorship
    EPID 491 (Fall 2018)

2017-18 Courses

  • Intro to Epidemiology
    EPID 309 (Spring 2018)
  • Master's Report
    EPID 909 (Spring 2018)
  • Preceptorship
    EPID 491 (Spring 2018)
  • Independent Study
    EPID 699 (Fall 2017)
  • Master's Report
    EPID 909 (Fall 2017)

2016-17 Courses

  • Intro to Epidemiology
    CPH 309 (Spring 2017)
  • Intro to Epidemiology
    EPID 309 (Spring 2017)
  • Master's Report
    CPH 909 (Spring 2017)
  • Preceptorship
    CPH 491 (Spring 2017)
  • Thesis
    CPH 910 (Spring 2017)
  • Independent Study
    CPH 499 (Fall 2016)
  • Master's Report
    CPH 909 (Fall 2016)
  • Thesis
    CPH 910 (Fall 2016)

2015-16 Courses

  • Master's Report
    CPH 909 (Summer I 2016)
  • Thesis
    CPH 910 (Summer I 2016)
  • Honors Thesis
    CPH 498H (Spring 2016)
  • Independent Study
    CPH 399 (Spring 2016)
  • Intro to Epidemiology
    CPH 309 (Spring 2016)
  • Master's Report
    CPH 909 (Spring 2016)
  • Preceptorship
    CPH 491 (Spring 2016)
  • Thesis
    CPH 910 (Spring 2016)

Related Links

UA Course Catalog

Scholarly Contributions

Chapters

  • Udall, B. H., Middleton, B. R., McAfee, S., Margolis, H. G., Mantua, N. J., Maldonado, J. K., Huntly, N., Gunasekara, A., Elias, E. H., Brooks, K. M., Brown, H. E., Breshears, D. D., Garfin, G. M., & Gonzalez, P. (2018). Southwest. In Impacts, Risks, and Adaptation in the United States: Fourth National Climate Assessment, Volume II(pp 1101–1184). Washington, DC: U.S. Global Change Research Program. doi:doi: 10.7930/NCA4.2018.CH25
    More info
    Chapter 25 in the Fourth National Climate Assessment
  • Ernst, K. C., Morin, C., & Brown, H. E. (2015). Extreme Weather Events and Vector-borne Diseases. In Public Health in Natural Disasters: Nutrition, Food, Remediation and Preparation. Wageningen Academic Publishers.
  • Brown, H. E., Comrie, A. C., Tamerius, J., Khan, M., Tabor, J. A., & Galgiani, J. N. (2014). Climate, wind storms, and the risk of valley fever (coccidioidomycosis). In The Influence of Global Environmental Change on Infectious Disease Dynamics(pp Chapter A12). Washington, D.C.: The National Academies Press.
  • Brown, H. E., Comrie, A. C., Drechsler, D., Barker, C. M., Basu, R., Brown, T., Gershunov, A., Reisen, W. K., & Ruddell, D. (2013). Health Effects of Climate Change in the Southwest. In Assessment of Climate Change in the Southwest United States: a Technical Report Prepared for the U.S. National Climate Assessment.(pp 312-339). Southwest Climate Alliance.
    More info
    Review Editor: English, P. Health Effects of Climate Change in the Southwest. Chapter 15, in: Assessment of Climate Change in the Southwest United States: a Technical Report Prepared for the U.S. National Climate Assessment. A report by the Southwest Climate Alliance [Garfin, G., Jardine, A., Merideth, R., Black, M., and Overpeck, J. (eds.)]. 2013, Tucson, AZ: Southwest Climate Alliance.
  • Liverman, D., Moser, S. C., Weiland, P. S., Dilling, L., Boykoff, M. T., Brown, H. E., Gordon, E. S., Greene, C., Holthaus, E., Niemeier, D. A., & others, . (2013). Climate choices for a sustainable Southwest. In Assessment of Climate Change in the Southwest United States(pp 405--435). Island Press/Center for Resource Economics.

Journals/Publications

  • Baum, C. E., Brown, H. E., Seifeldin, I., Ramadan, M. E., Lott, B., Nguyen, A., & Hablas, A. (2020). Regional variation of pancreatic cancer incidence in the Nile delta region of Egypt over a twelve-year period. J Cancer Epi, 2020, 6031708. doi:https://doi.org/10.1155/2020/6031708
  • Brown, H. E., Roach, M., Keith, L., Owen, G., McMahan, B., Berisha, V., & Austhof, E. (2020). Engaging public health stakeholders in climate and health adaptation. Atmosphere, 11(3), 265. doi:https://doi.org/10.3390/atmos11030265
  • Cook, A., Harris, R., Brown, H. E., & Bedrick, E. (2020). Geospatial characteristics of non-motor vehicle and assault-related trauma events in greater Phoenix, Arizona. Injury epidemiology, 7(1), 34.
    More info
    Injury-causing events are not randomly distributed across a landscape, but how they are associated with the features and characteristics of the places where they occur in Arizona (AZ) remains understudied. Clustering of trauma events and associations with areal sociodemographic characteristics in the greater Phoenix (PHX), AZ region can promote understanding and inform efforts to ameliorate a leading cause of death and disability for Arizonans. The outcomes of interest are trauma events unrelated to motor vehicle crashes (MVC) and the subgroup of trauma events due to interpersonal assaults.
  • Lega, J. C., Brown, H. E., & Barrera, R. (2020). A 70 percent reduction in mosquito populations does not require removal of 70 percent of mosquitoes. Journal of Medical Entomology, 57(5), 1668-1670.
  • Dennis, L. K., Brown, H. E., & Farland, L. V. (2019). DSM II Colormeter for measuring skin color: its usefulness and reliability of its measurement of melanin. J Dermatol Cosmet Treat, 1(1), 1-5.
  • Florea, A., Brown, H. E., Harris, R. B., & Oren, E. (2019). Ethnic Disparities in Gastric Cancer Presentation and Screening Practice in the United States: Analysis of 1997-2010 Surveillance, Epidemiology, and End Results-Medicare Data. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 28(4), 659-665.
    More info
    Chronic infection with () is the strongest risk factor for distal gastric cancer. Although gastric cancer incidence has decreased, variation by race and ethnicity is observed. This study describes gastric cancer presentation and screening services among Medicare patients by race/ethnicity, place of birth, and history of gastric cancer-related conditions.
  • Isoe, J., Koch, L. E., Isoe, Y. E., Rascón, A. A., Brown, H. E., Massani, B. B., & Miesfeld, R. L. (2019). Identification and characterization of a mosquito-specific eggshell organizing factor in Aedes aegypti mosquitoes. PLoS Biology, 17(1), e3000068.
    More info
    Mosquito-borne diseases are responsible for several million human deaths annually around the world. One approach to controlling mosquito populations is to disrupt molecular processes or antagonize novel metabolic targets required for the production of viable eggs. To this end, we focused our efforts on identifying proteins required for completion of embryonic development that are mosquito selective and represent potential targets for vector control. We performed bioinformatic analyses to identify putative protein-coding sequences that are specific to mosquito genomes. Systematic RNA interference (RNAi) screening of 40 mosquito-specific genes was performed by injecting double-stranded RNA (dsRNA) into female Aedes aegypti mosquitoes. This experimental approach led to the identification of eggshell organizing factor 1 (EOF1, AAEL012336), which plays an essential role in the formation and melanization of the eggshell. Eggs deposited by EOF1-deficient mosquitoes have nonmelanized fragile eggshells, and all embryos are nonviable. Scanning electron microscopy (SEM) analysis identified that exochorionic eggshell structures are strongly affected in EOF1-deficient mosquitoes. EOF1 is a potential novel target, to our knowledge, for exploring the identification and development of mosquito-selective and biosafe small-molecule inhibitors.
  • Luz, P., Brown, H. E., & Struchiner, C. (2019). Disgust as an emotional driver of vaccine attitudes and uptake? A mediation analysis. Epidemiology and Infection, 147(e182), 1-8.
  • Oren, E., Pelley, E., Purve, J., Lauro, P. L., Dennis, L. K., & Brown, H. E. (2019). Emerging evidence for infectious causes of cancer in the United States.. Epidemiologic Reviews.
  • Thompson, C., Saxberg, K., Lega, J. C., Tong, D., & Brown, H. E. (2019). A new gravity model for spatial interaction. Journal of Transport Geography, 79.
  • Barrera, R., Comrie, A. C., Cox, J. T., & Brown, H. E. (2017). Habitat and density of oviposition opportunity influences Aedes aegypti (Diptera: Culicidae) flight distance. Journal of Medical Entomology, 54(5), 1385–1389. doi:https://doi.org/10.1093/jme/tjx083
  • Bui, D. P., Oren, E., Roe, D. J., Brown, H. E., Harris, R. B., Knight, G. M., Gilman, R. H., & Grandjean, L. (2018). A case control study to identify community venues associated with genetically clustered multidrug-resistant Tuberculosis Disease in Lima, Peru. Clinical Infectious Diseases.
    More info
    The majority of tuberculosis transmission occurs in community settings. The primary aim of this study was to assess the association between exposure to community venues and multidrug-resistant tuberculosis (MDR-TB) disease. The secondary aim was to describe the social networks of MDR-TB cases and controls.
  • Del Valle, S. Y., McMahon, B. H., Asher, J., Hatchett, R., Lega, J. C., Brown, H. E., Leany, M. E., Pantazis, Y., Roberts, D., Moore, S., Peterson, T., Escobar, L. E., Qiao, H., Hengartner, N. W., & Mukundan, H. (2018). Summary Results of the 2014-2015 DARPA Chikungunya Challenge. BMC Infectious Diseases, 18, 245. doi:http://dx.doi.org/10.1186/s12879-018-3124-7
  • Langston, M. E., Dennis, L. K., Lynch, C. F., Roe, D., & Brown, H. E. (2017). Temporal Trends in Satellite-Derived Erythemal UVB and Implications for Ambient Sun Exposure Assessment. Int J Environ Res Public Health.
  • Barrera, R., Brown, H. E., & Lega, J. C. (2017). Aedes aegypti (Diptera: Culicidae) abundance model improved with relative humidity and precipitation-driven egg hatching. Journal of Medical Entomology, 54(5), 1375–1384. doi:https://doi.org/10.1093/jme/tjx077
  • Brown, H. E., Barrera, R., Comrie, A. C., & Lega, J. (2017). Effect of temperature thresholds on modeled Aedes aegypti (Diptera: Culicidae) population dynamics. Journal of Medical Entomology, 54(4), 869-877.
    More info
    Dynamic simulation models provide vector abundance estimates using only meteorological data. However, model outcomes may heavily depend on the assumptions used to parameterize them. We conducted a sensitivity analysis for a model of Aedes aegypti (L.) abundance using weather data from two locations where this vector is established, La Margarita, Puerto Rico and Tucson, Arizona. We tested the effect of simplifying temperature-dependent development and mortality rates and of changing development and mortality thresholds as compared with baselines estimated using biophysical models. The simplified development and mortality rates had limited effect on abundance estimates in either location. However, in Tucson, where the vector is established but has not transmitted viruses, a difference of 5 °C resulted in populations either surviving or collapsing in the hot Arizona mid-summer, depending on the temperature thresholds. We find three important implications of the observed sensitivity to temperature thresholds. First, this analysis indicates the need for better estimates of the temperature tolerance thresholds to refine entomologic risk mapping for disease vectors. Second, our results highlight the importance of extreme temperatures on vector survival at the marginal areas of this vector's distribution. Finally, the model suggests that adaptation to warmer temperatures may shift regions of pathogen transmission.
  • Driscoll, L. J., Brown, H. E., Harris, R. B., & Oren, E. (2017). Population knowledge, attitude, and practice regarding Helicobacter pylori transmission and outcomes: A Literature Review. Frontiers in Public Health, 5, 144.
    More info
    Helicobacter pylori infection is associated with the development of chronic gastritis, peptic ulcer disease, and gastric cancer. Current clinical recommendations are that H. pylori test-and-treat should be individualized based on comorbidities and patient preferences among populations at increased risk for certain morbidities. However, knowledge, attitudes and practices regarding H. pylori among potential patient populations are largely unknown.
  • Heidi E, B., Wangshu, M., Mohammed, K., Clarisse, T., Jian, L., & Daoqin, T. (2017). Spatial scale in environmental risk mapping: A Valley fever case study. Journal of Public Health Research, 6(2), 886.
    More info
    Valley fever is a fungal infection occurring in desert regions of the U.S. and Central and South America. Environmental risk mapping for this disease is hampered by challenges with detection, case reporting, and diagnostics as well as challenges common to spatial data handling.
  • Luz, P. M., Johnson, R. E., & Brown, H. E. (2017). Workplace availability, risk group and perceived barriers predictive of 2016-17 influenza vaccine uptake in the United States: A cross-sectional study. Vaccine, 35(43), 5890-5896.
    More info
    Seasonal influenza, though mostly self-limited in the healthy adult, may lead to severe disease and/or complications in subpopulations. Annual influenza vaccination is available in many countries with coverage goals rarely being met. We conducted a cross-sectional study of influenza vaccine uptake and explored socio-demographic, economic, and psychological factors that explained vaccine uptake.
  • Murakami, T. T., Scranton, R., Brown, H. E., Harris, R. B., Chen, Z., Musuku, S., & Oren, E. (2017). Management of Helicobacter Pylori in the United States: Results from a national survey of gastroenterology physicians. Preventive Medicine, 100, 216-222.
    More info
    We sought to determine current knowledge and practices among gastroenterology physicians and assess adherence to current guidelines for H. pylori management.
  • Brown, H. E., Smith, C., & Lashway, S. (2016). Influence of the length of storage on Aedes aegypti (Diptera: Culicidae) egg viability. Journal of Medical Entomology.
    More info
    Aedes aegypti (L.) is one of the most important arboviral vectors worldwide. Vector control is targeted at immature and adult stages; however, eggs are resistant to desiccation and may repopulate treated areas long after treatment ceases. We investigated the effect of age on Ae. aegypti egg hatching rates using newly colonized populations (F2) from an arid region. We found a strongly negative association where older eggs had lower hatch rates. The capacity of eggs to survive for long periods of time has implications on mosquito control. In addition, the accumulation of eggs in containers should be accounted for in abundance modeling efforts where populations may grow rapidly early in the season.
  • Bui, D., Brown, H. E., Harris, R. B., & Oren, E. (2016). Serologic Evidence for Fecal-Oral Transmission of Helicobacter pylori. The American Journal of Tropical Medicine and Hygiene, 94(1), 82-8.
    More info
    Helicobacter pylori infection is among the most prevalent infections in the world and a key cause of gastric diseases; however, its route of transmission remains unclear. This study aimed to assess the potential for fecal-oral transmission of H. pylori by leveraging its association with a disease with known etiology. Utilizing serology data from the National Health and Nutrition Examination Survey (NHANES 1999; N = 6,347), the association between H. pylori and hepatitis A virus (HAV), a sensitive indicator for fecal-oral exposure, was assessed. Survey-weighted kappa and multiple logistic regression were used to quantify the association between H. pylori and HAV after controlling for age, sex, race, poverty, birthplace, crowding, smoking, and alcohol use. Concordant serological results were found among 69.8% of participants (survey-weighted κ = 0.30, 95% confidence interval [CI] = 0.26, 0.35). The adjusted odds of H. pylori seropositivity were over two times higher after adjusting for confounders (odds ratio = 2.27, 95% CI = 1.79, 2.87). Results from this study suggest H. pylori and HAV infections are strongly associated. Since HAV is primarily transmitted through the fecal-oral route, fecal-oral transmission may be an important pathway for H. pylori spread.
  • Haenchen, S., Hayden, M., Dickinson, K., Walker, K. R., Jacobs, E. T., Brown, H. E., Gunn, J., Kohler, L., & Ernst, K. C. (2015). Mosquito avoidance practices and knowledge of arboviral diseases in cities with differing recent history of disease. American Journal of Tropical Medicine and Hygiene.
  • Hansen, V., Oren, E., Dennis, L. K., & Brown, H. E. (2016). Infectious Disease Mortality Trends in the United States, 1980-2014. JAMA, 316(20), 2149-2151.
  • Lega, J. C., & Brown, H. E. (2016). Data-driven outbreak forecasting with a simple nonlinear growth model. Epidemics, 17, 19-26. doi:http://dx.doi.org/10.1016/j.epidem.2016.10.002
    More info
    Recent events have thrown the spotlight on infectious disease outbreak response. We developed a data-driven method, EpiGro, which can be applied to cumulative case reports to estimate the order of magnitude of the duration, peak and ultimate size of an ongoing outbreak. It is based on a surprisingly simple mathematical property of many epidemiological data sets, does not require knowledge or estimation of disease transmission parameters, is robust to noise and to small data sets, and runs quickly due to its mathematical simplicity. Using data from historic and ongoing epidemics, we present the model. We also provide modeling considerations that justify this approach and discuss its limitations. In the absence of other information or in conjunction with other models, EpiGro may be useful to public health responders.
  • Shelly, E. M., Acuna-Soto, R., Ernst, K. C., Sterling, C. R., & Brown, H. E. (2016). A Critical Assessment of Officially Reported Chagas Disease Surveillance Data in Mexico.. Public Health Reports, 131.
  • Brown, H. E., Young, A., Lega, J., Andreadis, T. G., Schurich, J., & Comrie, A. (2015). Projection of Climate Change Influences on U.S. West Nile Virus Vectors. Earth Interactions, 19.
    More info
    While estimates of the impact of climate change on health are necessary for health care planners and climate change policy makers, models to produce quantitative estimates remain scarce. We describe a freely available dynamic simulation model parameterized for three West Nile virus vectors, which provides an effective tool for studying vector-borne disease risk due to climate change. The Dynamic Mosquito Simulation Model is parameterized with species specific temperature-dependent development and mortality rates. Using downscaled daily weather data, we estimate mosquito population dynamics under current and projected future climate scenarios for multiple locations across the country. Trends in mosquito abundance were variable by location, however, an extension of the vector activity periods, and by extension disease risk, was almost uniformly observed. Importantly, mid-summer decreases in abundance may be off-set by shorter extrinsic incubation periods resulting in a greater proportion of infective mosquitoes. Quantitative descriptions of the effect of temperature on the virus and mosquito are critical to developing models of future disease risk.
  • Clark, R., Taylor, A., Garcia, F., Krone, T., & Brown, H. E. (2015). Recognizing the Role of Skunks in Human and Animal Rabies Exposures in the Southwest. Vector borne and Zoonotic Diseases, 15(8), 494-501.
    More info
    Rabies is arguably the most important viral zoonotic disease worldwide with an estimated 55,000 human deaths each year. Globally, dogs are the primary animals affected. In the United States, especially on the East Coast, raccoons and bats are the primary reservoir. However, in the southwestern United States, skunk and bat rabies play a large role. We describe the epidemiology and environmental risk factors associated with rabies in the US Southwest using exposure data for 2004-2012 from one Arizona county as a case study. Unlike other parts of the country, here bats and skunks are the most commonly collected positive animals (62% and 32%, respectively). Even though most of the positive animals were bats, human and domestic animal exposures were primarily a result of skunk interactions (58% and 50%, respectively). Consequently, the majority of exposures occur early in the year, January and February, when the majority of skunk pickups also occur. Using public health surveillance data, our study highlights the importance of recognizing the role of skunks in human and animal exposures in the southwestern United States. Consistent with a "One Health" approach, our data show how wildlife and domestic animal and human exposures are associated and informative to one another.
  • Nsoesie, E. O., Ricketts, R. P., Brown, H. E., Fish, D., Durham, D. P., Ndeffo Mbah, M. L., Christian, T., Ahmed, S., Marcellin, C., Shelly, E., Owers, K., Wenzel, N., Galvani, A. P., & Brownstein, J. S. (2015). Spatial and temporal clustering of chikungunya virus transmission in Dominica. PLoS Neglected Tropical Diseases, 9(8), e0003977.
    More info
    Using geo-referenced case data, we present spatial and spatio-temporal cluster analyses of the early spread of the 2013-2015 chikungunya virus (CHIKV) in Dominica, an island in the Caribbean. Spatial coordinates of the locations of the first 417 reported cases observed between December 15th, 2013 and March 11th, 2014, were captured using the Global Positioning System (GPS). We observed a preponderance of female cases, which has been reported for CHIKV outbreaks in other regions. We also noted statistically significant spatial and spatio-temporal clusters in highly populated areas and observed major clusters prior to implementation of intensive vector control programs suggesting early vector control measures, and education had an impact on the spread of the CHIKV epidemic in Dominica. A dynamical identification of clusters can lead to local assessment of risk and provide opportunities for targeted control efforts for nations experiencing CHIKV outbreaks.
  • Reyes-Castro, P. A., Harris, R. B., Brown, H. E., Christopherson, G. L., & Ernst, K. C. (2017). Spatio-temporal and neighborhood characteristics of two dengue outbreaks in two arid cities of Mexico. Acta Tropica, 167, 174-182.
    More info
    Little is currently known about the spatial-temporal dynamics of dengue epidemics in arid areas. This study assesses dengue outbreaks that occurred in two arid cities of Mexico, Hermosillo and Navojoa, located in northern state of Sonora. Laboratory confirmed dengue cases from Hermosillo (N=2730) and Navojoa (N=493) were geocoded by residence and assigned neighborhood-level characteristics from the 2010 Mexican census. Kernel density and Space-time cluster analysis was performed to detect high density areas and space-time clusters of dengue. Ordinary Least Square regression was used to assess the changing socioeconomic characteristics of cases over the course of the outbreaks. Both cities exhibited contiguous patterns of space-time clustering. Initial areas of dissemination were characterized in both cities by high population density, high percentage of occupied houses, and lack of healthcare. Future research and control efforts in these regions should consider these space-time and socioeconomic patterns.
  • Sedda, L., Morley, D., & Brown, H. E. (2015). Characteristics of Wind-Infective Farms of the 2006 Bluetongue Serotype 8 Epidemic in Northern Europe. EcoHealth, 12(3), 461-7.
    More info
    Bluetongue is a Culicoides-borne viral disease of livestock. In 2006, northern Europe experienced a major outbreak of this disease with devastating effects on the livestock industry. The outbreak quickly spread over the region, primarily affecting cattle and sheep. A previous analysis of the role of vector flight and wind in the spread of this virus across northern Europe indicated that infection at 1,326 (65%) of the reported infected farms could be traced back to just 599 (29%) farms (wind-infective farms). Rather than focusing on presence or absence of vectors or difference between infected and non-infected farms, we investigate the zoological and environmental characteristics of these 599 wind-infective farms (which can be thought of as super-spreaders) in order to characterize what makes them distinct from non-infective farms. Differences in temperature, precipitation, and the density of sheep at individual farms were identified between these two groups. These environmental and zoological factors are known to affect vector abundance and may have promoted bluetongue virus transmission. Identifying such ecological differences can help in the description and quantification of relative risk in affected areas.
  • Wang, D., Bowman, D. D., Brown, H. E., Harrington, L. C., Kaufman, P. E., McKay, T., Nelson, C. T., Sharp, J. L., & Lund, R. (2014). Factors influencing U.S. canine heartworm (Dirofilaria immitis) prevalence. Parasites & Vectors, 7, 264.
    More info
    This paper examines the individual factors that influence prevalence rates of canine heartworm in the contiguous United States. A data set provided by the Companion Animal Parasite Council, which contains county-by-county results of over nine million heartworm tests conducted during 2011 and 2012, is analyzed for predictive structure. The goal is to identify the factors that are important in predicting high canine heartworm prevalence rates.
  • Borchert, J. N., Eisen, R. J., Holmes, J. L., Atiku, L. A., Mpanga, J. T., Brown, H. E., Graham, C. B., Babi, N., Montenieri, J. A., Enscore, R. E., & others, . (2012). Evaluation and modification of off-host flea collection techniques used in northwest Uganda: laboratory and field studies. Journal of Medical Entomology, 49, 210--214.
  • Brown, H. E., Harrington, L. C., Kaufman, P. E., McKay, T., Bowman, D. D., Nelson, C. T., Wang, D., & Lund, R. (2012). Key factors influencing canine heartworm, Dirofilaria immitis, in the United States. Parasites & Vectors, 5.
    More info
    An examination of the Companion Animal Parasite Council's (CAPC) canine heartworm data to clarify the spatial prevalence of heartworm in the United States. Factors thought to influence the spatial risk of disease, as identified in a recent CAPC workshop, are discussed.
  • Craciunescu, V., Brown, H., Comrie, A., Zelicoff, A., Ward, T., Ragain, R., Simpson, G., Stanhope10, W., Kass-Hout11, T., Scharl12, A., & others, . (2012). Information and decision support systems. Environmental Tracking for Public Health Surveillance, 11, 369.
  • Sedda, L., Brown, H. E., Purse, B. V., Burgin, L., Gloster, J., & Rogers, D. J. (2012). A new algorithm quantifies the roles of wind and midge flight activity in the bluetongue epizootic in northwest Europe. Proceedings of the Royal Society of London B: Biological Sciences, rspb20112555.
  • Brown, H. E., Doyle, M. S., Cox, J., Eisen, R. J., & Nasci, R. S. (2011). The effect of spatial and temporal subsetting on Culex tarsalis abundance models-a design for sensible reduction of vector surveillance. Journal of the American Mosquito Control Association, 27, 120--128.
  • Brown, H. E., Levy, C. E., Enscore, R. E., Schriefer, M. E., DeLiberto, T. J., Gage, K. L., & Eisen, R. J. (2011). Annual seroprevalence of Yersinia pestis in coyotes as predictors of interannual variation in reports of human plague cases in Arizona, United States. Vector-Borne and Zoonotic Diseases, 11, 1439--1446.
  • Brown, H. E., Yates, K. F., Dietrich, G., MacMillan, K., Graham, C. B., Reese, S. M., Helterbrand, W. S., Nicholson, W. L., Blount, K., Mead, P. S., & others, . (2011). An acarologic survey and Amblyomma americanum distribution map with implications for tularemia risk in Missouri. American Journal of Tropical Medicine and Hygiene, 84, 411--419.
  • Cox, J., Brown, H. E., & Rico-Hesse, R. (2011). Variation in vector competence for dengue viruses does not depend on mosquito midgut binding affinity. PLoS Negl Trop Dis, 5, e1172.
  • Brown, H. E., Ettestad, P., Reynolds, P. J., Brown, T. L., Hatton, E. S., Holmes, J. L., Glass, G. E., Gage, K. L., & Eisen, R. J. (2010). Climatic predictors of the intra-and inter-annual distributions of plague cases in New Mexico based on 29 years of animal-based surveillance data. American Journal of Tropical Medicine and Hygiene, 82, 95--102.
  • Hartemink, N., Purse, B., Meiswinkel, R., Brown, H., De Koeijer, A., Elbers, A., Boender, G., Rogers, D., & Heesterbeek, J. (2009). Mapping the basic reproduction number (R 0) for vector-borne diseases: a case study on bluetongue virus. Epidemics, 1, 153--161.
  • Brown, H. E., Childs, J. E., Diuk-Wasser, M. A., & Fish, D. (2008). Ecological factors associated with west nile virus transmission, northeastern United States. Emerging Infectious Diseases, 14(10), 1539-1545.
  • Brown, H. E., Diuk-Wasser, M. A., Guan, Y., Caskey, S., & Fish, D. (2008). Comparison of three satellite sensors at three spatial scales to predict larval mosquito presence in Connecticut wetlands. Remote Sensing of Environment, 112(5), 2301-2308.
  • Brown, H. E., Paladini, M., Cook, R. A., Kline, D., Barnard, D., & Fish, D. (2008). Effectiveness of mosquito traps in measuring species abundance and composition. Journal of Medical Entomology, 45(3), 517-521.
  • Brown, H., Duik-Wasser, M., Andreadis, T., & Fish, D. (2008). Remotely-sensed vegetation indices identify mosquito clusters of West Nile virus vectors in an urban landscape in the northeastern United States. Vector-borne and Zoonotic Diseases, 8(2), 197-206.
    More info
    Heterogeneity in urban landscapes can influence the effectiveness of mosquito-borne disease control. We used remotely sensed vegetation indices to discriminate among mosquito habitats within a densely populated urban environment in New Haven, CT. ASTER derived vegetation indices were identified for 16 sites where adult mosquitoes were trapped over the summer of 2004. Canonical correlation analysis showed a significant relationship between the environmental variables (normalized difference vegetation index, disease/water stress index and distance to water) and four local West Nile virus competent vectors (Cx. pipiens, Cx. restuans, Cx. salinarius, and Ae. vexans) (0.93, P = 0.03) explaining 86% of the variance in the environmental and mosquito measures. Sites were clustered based on these remotely sensed environmental variables. Three clusters were identified which provide insight into the distribution of West Nile virus vectors in an urban area. Identification of habitat differences of mosquitoes within the urban landscape has important implications for understanding West Nile virus transmission and for control of vector-competent mosquito species.
  • Purse, B. V., Brown, H. E., Harrup, L., Mertens, P., & Rogers, D. J. (2008). Invasion of bluetongue and other orbivirus infections into Europe: the role of biological and climatic processes. Revue Scientifique et Technique-Office International des Epizooties, 27(2), 427-442.
  • Diuk-Wasser, M. A., Brown, H. E., Andreadis, T. G., & Fish, D. (2006). Modeling the spatial distribution of mosquito vectors for West Nile virus in Connecticut, USA. Vector-borne and Zoonotic Diseases, 6(3), 283-295.
  • Eden, G. F., Joseph, J. E., Brown, H. E., Brown, C. P., & Zeffiro, T. A. (1999). Utilizing hemodynamic delay and dispersion to detect fMRI signal change without auditory interference: The behavior interleaved gradients technique. Magnetic Resonance in Medicine, 41(1), 13-20.
  • Helmbrecht, G. D., Farhat, M. Y., Lochbaum, L., Brown, H. E., Yadgarova, K. T., Eglinton, G. S., & Ramwell, P. W. (1996). L-Arginine reverses the adverse pregnancy changes induced by nitric oxide synthase inhibition in the rat. American Journal of Obstetrics and Gynecology, 175(4), 800-805.

Presentations

  • Beamer, P., O'Rourke, M. K., Guerra, S., Brown, H. E., Lopez-Galvez, N., & Lothrop, N. (2018, August). Escape to America: Adapting European Study for Cohorts for Air Pollution Effects (ESCAPE) Methods to the Desert Southwestern US. Joint meeting of the International Society of Exposure Science and the International Society of Environmental Epidemiology.
  • Beamer, P., O'Rourke, M. K., Guerra, S., Furlong, M., Brown, H. E., Bell, M. L., & Lothrop, N. (2017, Fall). Modeling Historic Air Pollution Concentrations with Land Use Regression in Tucson, AZ. International Society of Exposure Science Conference. Research Triangle Park, NC.
  • Lega, J. C., & Brown, H. E. (2015, May). Modeling the Spread of Chikungunya in the Caribbean and Central America. DARPA Chikungunya Challenge Finale. DARPA: DARPA.
  • Lega, J. C., & Brown, H. E. (2015, October). Modeling the Spread of Chikungunya in the Caribbean and Central America. UA Microlunch SeriesUniversity of Arizona.

Poster Presentations

  • Murakami, T., Scranton, R., Brown, H. E., Harris, R. B., Zhao, C., Musuku, S., & Oren, E. (2014, October). A Survey of Screening and Treatment Practices for Helicobacter pylori in the United States. American College of Gastroenterology.. Philadelphia, PA.
    More info
    Murakami T, Scranton R, Brown H, Harris RB, Chen Z, Musuku S, Oren E. A Survey of Screening and Treatment Practices for Helicobacter pylori in the United States. Poster presentation at the American College of Gastroenterology 79th Annual Scientific Meeting, Philadelphia, PA, October 2014.

Case Studies

  • Tabor, J., Schweers, N., Rabby, Q., Lega, J. C., Hondula, D., Clark, R., Brown, H. E., & Roach, M. (2017. Projections of Climate Impacts on Vector-Borne Diseases and Valley Fever in Arizona(p. 20).

Profiles With Related Publications

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  • John N Galgiani

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