previous studies (C-H)

 

 

 

Centers for Disease Control and Prevention. 1998. Preventing Emerging Infectious Diseases, A Strategy for the 21st Century. Atlanta, GA: U.S. Department of Health and Human Services.

 

Chen, S., and J. Hu. 1991. Geo-ecological zones and endemic diseases in China - A sample study by remote sensing. Prev. Vet. Med. 11:235-244.

Cherlet, M., and A. Di Gregorio. 1993. Calibration and integrated modelling of remote sensing data for desert locust habitat monitoring. RSC Series No. 64, Food and Agriculture Organization. 115p.

 

Chucalin, A., and Y. Novikov. 1994. Urban eco-epidemiology with satellite. Sistema Terra Year III:18-20.

Cibula, W.G. 1976. Application of remotely sensed multispectral data to automated analysis of marshland vegetation. NASA Technical Note TN D-8139. Johnson Space Center, Houston, Texas.

 

Clarke, K.C., J.R. Osleeb, J.M. Sherry, J.P. Meert, and R.W. Larsson. 1990. The use of remote sensing and geographic information systems in UNICEF'S dracunculiasis (Guinea worm) eradication effort. Prev. Vet. Med. 11:229-235.

 

Cline, B.L. 1970. New eyes for epidemiologists: Aerial photography and other remote sensing techniques. Am. J. Epidem. 92:85-89.

 

Connor, S.J. 1999. Malaria in Africa: The view from space. Biologist 46(1):22-25.

 

Connor, S.J., S.P. Flasse, A.H. Perryman, and M.C. Thomson. 1997. The contribution of satellite derived information to malaria stratification, monitoring and early warning. World Health Organization WHO/MAL/97.1079. 32 p.

 

Cross, E.R., W.W. Newcomb, and C.J. Tucker. 1996. Use of weather data and remote sensing to predict the geographic and seasonal distribution of Phlebotomus paptasi in Southwest Asia. Am. J. Trop. Med. Hyg. 54(5):530-536.

 

Cross, E.R., R. Perrine, C. Sheffield, and G. Pazzaglia. 1984. Predicting areas endemic for schistosomiasis using weather variables and a Landsat data base. Military Med. 149:542-544.

 

Curran, P.J., P.M. Atkinson, G.M. Foody, and E.J. Milton. 2000. Linking remote sensing, land cover, and disease. Book chapter: Remote Sensing and GIS in Public Health. Advances in Parasitol., vol. 47 [S. Hay, D. Rogers, S. Randolph, eds.]. Academic Press. pp. 38-80.

 

Dale, P.E., and C.D. Morris. 1996. Culex annulirostris breeding sites in urban areas: Using remote sensing and digital image analysis to develop a rapid predictor of potential breeding areas. J. Am. Mosq. Control Assoc. 12:316-20.

 

Dale, P.E., S.A. Ritchie, B.M. Territo, C.D. Morris, A. Muhar, and B.H. Kay. 1998. An overview of remote sensing and GIS for surveillance of mosquito vector habitats and risk assessment. J. Vector Ecol. 23(1):54-61.

 

Daniel, M. and J. Kolár. 1990. Using satellite data to forecast the occurrence of the common tick Ixodes ricinus (L.). J. Hyg. Epidem. Microbiol. Immunol. 34:243-252.

 

Daniel, M., J. Kolár, P. Zeman, K. Pavelka, and J. Sadlo. 1998. Predictive map of Ixodes ricinus high-incidence habitats and a tick-borne encephalitis risk assessment using satellite data. Experimental & Applied Acarology 22:417-433.

 

Dister, S.W., L.R. Beck, B.L. Wood, R. Falco, and D. Fish. 1993. The use of GIS and remote sensing technologies in a landscape approach to the study of Lyme disease transmission risk. Proc., GIS '93: Geographic Information Systems in Forestry, Environmental and Natural Resource Management. Vancouver, B.C., Canada, 15-18 February 1993.

 

Dister, S.W., D. Fish, S. Bros, D.H. Frank, and B.L. Wood. 1997. Landscape characterization of peridomestic risk for Lyme disease using satellite imagery. Am. J. Trop. Med. Hyg. 57(6):687-692.

 

Epstein, P.R. 1995. Health applications of remote sensing and climate modeling. The Earth Observer, Sept-Oct, pp. 7-10.

 

Epstein, P.R., D.J. Rogers, and R. Slooff. 1993. Satellite imaging and vector-borne disease. The Lancet 341:1404-1406.

 

Estrada-Peña, A. 1998. Geostatistics and remote sensing as predictive tools of tick distribution: A cokriging system to estimate Ixodes scapularis (Acari: Ixodidae) habitat suitability in the United States and Canada from Advanced Very High Resolution Radiometer satellite imagery. J. Med. Entomol. 35(6):989-995.

 

Flasse, S., C. Walker, H. Biggs, P. Stephenson, and P. Hutchinson. 1998. Using remote sensing to predict outbreaks of Oestrus ovis in Namibia. Prev. Vet. Med. 33(1-4):31-8.

 

Fuller, C.E. 1972. Public Health Implications of Remote Sensing. Final Report, NASA contract NAS-9-11522. University of Texas, School of Public Health, Houston, TX.

 

Giddings, L.E. 1976. Remote sensing for the control of tsetse flies. Technical Memorandum, Health Applications Office, Johnson Space Center, Houston, TX.

 

Glass, G.E., J.E. Cheek, J.A. Patz, T.M. Shields, T.J. Doyle, D.A. Thoroughman, D.K. Hunt, R.E. Enscore, K.L. Gage, C. Irland, C.J. Peters, and R. Bryan. 2000. Using remotely sensed data to identify areas at risk for hantavirus pulmonary syndrome. Emerg. Infect. Dis.6(3):238-247.

 

Goetz, S.J., S.D. Prince, and J. Small. 2000. Advances in satellite remote sensing of environmental variables for epidemiological applications. Book chapter: Remote Sensing and GIS in Public Health. Advances in Parasitol., vol. 47 [S. Hay, D. Rogers, S. Randolph, eds.]. Academic Press. pp. 289-307.

 

Gong, P., R. Spear, E. Seto, Y. Zhou, B. Xu, D. Maszle, S. Liang, G. Davis, and X. Gu. 1999. Remote sensing and GIS for schistosomiasis control in Sichuan, China: An overview. Proc. of Geoinformatics '99, Ann Arbor, MI, 19-21 June, pp. 1-9.

 

Hacker, C.S., and D.R. Roberts. 1994. Public health applications of satellite remote sensing. Sistema Terra Year III:34-36.

 

Hassan, A.N., L.R. Beck, and S. Dister. 1998. Prediction of villages at risk for filariasis transmission in the Nile Delta using remote sensing and geographic information system technologies. J. Egypt. Soc. Parasitol. 28(1):75-87.

 

Hay, S.I. 1997. Remote sensing and disease control: Past, present and future. Trans. Royal Soc. Trop. Med. Hyg. 91:105-106.

 

Hay, S.I., and J.J. Lennon. 1999. Deriving meteorological variables across Africa for the study and control of vector-borne disease: A comparison of remote sensing and spatial interpolation of climate. Tropical Medicine and International Health 4(1):58-71.

 

Hay, S.I., M.J. Packer, and D.J. Rogers. 1997. The impact of remote sensing on the study and control of invertebrate intermediate hosts and vectors for disease. Intl J. Remote Sens. 18(14):2899-2930.

 

Hay, S.I., R.W. Snow, and D.J. Rogers. 1998a. From predicting mosquito habitat to malaria seasons using remotely sensed data: Practice, problems and perspectives. Parsitol. Today 14(8):306-313.

 

Hay, S.I., R.W. Snow, and D.J. Rogers. 1998b. Predicting malaria seasons in Kenya using multitemporal meteorological satellite sensor data. Trans. Royal Soc. Trop. Med. Hyg. 92:12-20.

 

Hay, S., C. Tucker, D. Rogers, and M. Packer. 1996. Remotely sensed surrogates of meteorological data for the study of the distribution and abundance of arthropod vectors of disease. Ann. Trop. Med. Parasitol. 90(1):1-19.

 

Hayes, R.O., E.L. Maxwell, C.J. Mitchell, and T.L. Woodzick. 1985. Detection, identification, and classification of mosquito larval habitats using remote sensing scanners in earth-orbiting satellites. Bul. World Health Org. 63:361-374.

 

Hibbard, K., R. K. Washino, B. L. Wood, M. J. Pitcairn, E. Rejmánková, J. Salute, and L. Beck. 1990. Predicting mosquito populations in California rice fields. Proc., Int. Geoscience and Remote Sensing Symp. (IGARSS '90). College Park, MD, 23-27 May 1990.

 

Hielkema, J. U. 1983. Use of NOAA/AVHRR and Landsat MSS/TM data for ecological monitoring: The desert locust example. In: Renewable Resource Inventories for Monitoring Changes and Trends, An International Conference, 15-19 August 1983, Corvallis, OR.

 

Hopps, H.C., R.J. Cuffey, J. Morenoff, W.L. Richmond, and D.H. Sidley. 1968. Computerized Mapping of Disease and Environmental Data: A Report of the Mapping of Disease (MOD) Project. Advanced Research Projects Agency (ARPA) of the Department of Defense, Life Sciences Division, U.S. Army Research Office Contract No. DA 49-092-ARO-130.

 

Hugh-Jones, M. 1989. Applications of remote sensing to the identification of the habitats of parasites and disease vectors. Parasitol. Today 5:244-251.

 

Hugh-Jones, M. 1991a. Remote sensing and geographic information systems, epidemiology and Igor Piskun's Rule. Proc., 6th International Symposium on Veterinary Epidemiology and Economics. Ottawa, Canada.

 

Hugh-Jones, M. 1991b. Satellite imaging as a technique for obtaining disease-related data. Rev. Sci. Tech. Off. Int. Epid. 10:197-204.

Hugh-Jones, M. 1991c. The remote recognition of tick habitats. J. Agric. Entomol. 8:309-315.

 

Hugh-Jones, M., N. Barre, G. Nelson, C. Wehnes, J. Warner, G. Garris, and W. Hubbert. 1988. Remote recognition of Amblyomma variegatum habitats in Guadeloupe using Landsat-TM imagery. Acta Veterinaria Scandinavica, pp. 259-261.

 

Hugh-Jones, M., N. Barre, G. Nelson, K. Wehnes, J. Warner, J. Garvin, and G. Garris. 1992. Landsat-TM identification of Amblyomma variegatum (Acari: Ixodidae) habitats in Guadeloupe. Remote Sens. Environ. 40:43-55.

 

Huh, O.K., and J.B. Malone. 2001. New tools: Potential medical applications of data from new and old environmental satellites. Acta Tropica 79:35-47.

Jovanovic, P. 1987. Remote sensing of environmental factors affecting health. Adv. Space Res. 7:11-18.