Livres : « Spatial disease »

1

J, Jeger Michael, dir. Spatial components of plant disease epidemics. Englewood Cliffs, N.J : Prentice Hall, 1989.

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2

Thomas, R. W. Some spatial representation problems in disease modelling. Manchester : University of Manchester, Centre for Urban Policy Studies, 1988.

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3

Lai, Poh C. Spatial epidemiological approaches in disease mapping and analysis. Boca Raton : Taylor & Francis, 2009.

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4

Bhunia, Gouri Sankar, et Pravat Kumar Shit. Spatial Mapping and Modelling for Kala-azar Disease. Cham : Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-41227-2.

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5

Lai, Poh C. Spatial epidemiological approaches in disease mapping and analysis. Boca Raton : Taylor & Francis, 2009.

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6

Lawson, Andrew. Bayesian disease mapping : Hierarchical modeling in spatial epidemiology. Boca Raton : Taylor & Francis, 2008.

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7

Montana, Livia. Spatial modeling of HIV prevalence in Kenya. Calverton, MD : Macro International, 2007.

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8

Peter, Haggett, et Ord J. K, dir. Spatial aspects of influenza epidemics. London : Pion Ltd., 1986.

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9

Cliff, A. D. Spatial aspects of influenza epidemics. London, England : Pion Ltd., 1986.

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10

C, Gatrell Anthony, et North West Regional Research Laboratory., dir. Tests for spatial clustering in epidemiology : With special reference to Motor Neurone disease. Lancaster : North West Regional Research Laboratory, 1991.

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11

Nuttal, Pat, dir. Climate, ticks and disease. Wallingford : CABI, 2021. http://dx.doi.org/10.1079/9781789249637.0000.

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Abstract This book is a collection of 77 expert opinions arranged in three sections. Section 1 on "Climate" sets the scene, including predictions of future climate change, how climate change affects ecosystems, and how to model projections of the spatial distribution of ticks and tick-borne infections under different climate change scenarios. Section 2 on "Ticks" focuses on ticks (although tick-borne pathogens creep in) and whether or not changes in climate affect the tick biosphere, from physiology to ecology. Section 3 on "Disease" focuses on the tick-host-pathogen biosphere, ranging from the triangle of tick-host-pathogen molecular interactions to disease ecology in various regions and ecosystems of the world. Each of these three sections ends with a synopsis that aims to give a brief overview of all the expert opinions within the section. The book concludes with Section 4 (Final Synopsis and Future Predictions). This synopsis attempts to summarize evidence provided by the experts of tangible impacts of climate change on ticks and tick-borne infections. In constructing their expert opinions, contributors give their views on what the future might hold. The final synopsis provides a snapshot of their expert thoughts on the future.

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12

Zaremba, Jeffrey Donald. Spatial memory in health and disease : Hippocampal stability deficits in the Df(16)A+/- mouse model of schizophrenia. [New York, N.Y.?] : [publisher not identified], 2017.

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13

Page, Deaglan. Spatial learning deficits in rats carrying the Swedish mutation for amyloid precursor protein overexpression as a model for Alzheimer's disease. (s.l : The Author), 2001.

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14

Jessica, White, United Nations Development Programme. South East Asia HIV and Development Programme. et CICRED, dir. Development, spatial mobility and HIV/AIDS : A workshop on interrelations and programmatic responses, 1-3 September 2004, Paris, France. Bangkok : UNDP South East Asia HIV and Development Programme, 2004.

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15

Ölgen, M. Kirami. Spatial clustering of notifiable communicable diseases in Turkey. Istanbul : Kriter, 2020.

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16

Chen, Dongmei, Bernard Moulin et Jianhong Wu, dir. Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases. Hoboken, NJ, USA : John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118630013.

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17

Bosch, Frank van den. The velocity of spatial population expansion. [Amsterdam, Netherlands] : F. van den Bosch, 1990.

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18

Beirne, Raymond Oliver. Spatial vision for short-wavelength stimuli in normal and diseased eyes. [S.l : The Author], 2005.

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19

1938-, Majumdar Shyamal K., dir. Wildlife diseases : Landscape epidemiology, spatial distribution and utilization of remote sensing technology. Easton, PA : Pennsylvania Academy of Science, 2005.

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20

1965-, Sullivan Thomas, dir. Resource-constrained spatial hot spot identification. Santa Monica, CA : RAND, 2011.

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21

Nelson, Trisalyn Anna-Lisa. Large-area mountain pine beetle infestations : Spatial data representation and accuracy. Victoria, British Columbia : Pacific Forestry Centre, 2006.

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22

Nelson, Trisalyn Anna-Lisa. Large-area mountain pine beetle infestations : Spatial data representation and accuracy. Victoria, British Columbia : Pacific Forestry Centre, 2006.

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23

M, Liebhold Andrew, Barrett Hope R, United States Forest Service, Northeastern Forest Experiment Station (Radnor, Pa.) et Virginia Polytechnic Institute and State University, dir. Proceedings, spatial analysis and forest pest management : April 27-30, 1992, Mountain Lakes, Virginia. Radnor, Pa. (5 Radnor Corporate Center, 100 Matsonford Rd., Suite 200, Radnor 19087-8775) : U.S. Dept. of Agriculture, Forest Service, Northeastern Forest Experiment Station, 1993.

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24

McKee, Gregory J. Modeling the effect of spatial externalities on invasive species management. Fargo, N.D : Dept. of Agribusiness and Applied Economics, Agricultural Experiment Station, North Dakota State University, 2006.

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25

Nelson, Trisalyn. Using conditional spatial randomization to identify insect infestation hot spots. Victoria, B.C : Pacific Forestry Centre, 2007.

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26

National Council on Radiation Protection and Measurements. Potential impact of individual genetic susceptibility and previous radiation exposure on radiation risk for astronauts. Bethesda, Md : National Council on Radiation Protection and Measurements, 2011.

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27

Joanne, White, Mountain Pine Beetle Initiative (Canada) et Pacific Forestry Centre, dir. Detection of red attack stage mountain pine beetle infestation with high spatial resolution satellite imagery. Victoria, B.C : Canadian Forest Service, Pacific Forestry Centre, 2005.

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28

Bentz, Barbara J. Localized spatial and temporal attack dynamics of the mountain pine beetle in lodgepole pine. Ogden, UT (324 25th St., Ogden 84401) : U.S. Dept. of Agriculture, Forest Service, Intermountain Research Station, 1996.

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29

Bentz, Barbara J. Localized spatial and temporal attack dynamics of the mountain pine beetle in lodgepole pine. Ogden, UT (324 25th St., Ogden 84401) : U.S. Dept. of Agriculture, Forest Service, Intermountain Research Station, 1996.

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30

Bentz, Barbara J. Localized spatial and temporal attack dynamics of the mountain pine beetle in lodgepole pine. Ogden, UT (324 25th St., Ogden 84401) : U.S. Dept. of Agriculture, Forest Service, Intermountain Research Station, 1996.

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31

George, Christakos, dir. Interdisciplinary public health reasoning and epidemic modelling : The case of Black Death. Berlin : Springer, 2005.

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32

Aukema, Brian H. Landscape-level analysis of mountain pine beetle in British Columbia : Spatiotemporal development and spatial synchrony within the present outbreak. Victoria, B.C : Pacific Forestry Centre, 2009.

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33

National Council on Radiation Protection and Measurements., dir. Information needed to make radiation protection recommendations for space missions beyond low-earth orbit. Bethesda, MD : National Council on Radiation Protection and Measurements, 2006.

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34

Isabel, Dyck, dir. Women, body, illness : Space and identity in the everyday lives of women with chronic illness. Lanham, MD : Rowman & Littlefield, 2002.

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35

Lai, Poh-Chin, Fun-Mun So et Ka Wing Chan. Spatial Epidemiological Approaches in Disease Mapping and Analysis. Taylor & Francis Group, 2008.

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36

Bayesian Disease Mapping Hierarchical Modeling In Spatial Epidemiology. Taylor & Francis Inc, 2013.

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37

Lawson, Andrew B. Bayesian Disease Mapping : Hierarchical Modeling in Spatial Epidemiology. Taylor & Francis Group, 2013.

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38

Spatial Epidemiological Approaches in Disease Mapping and Analysis. CRC, 2008.

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39

Keiding, Niels, Andrew B. Lawson, Terry Speed, Byron J. Morgan et Peter Van Der Heijden. Bayesian Disease Mapping : Hierarchical Modeling in Spatial Epidemiology. Taylor & Francis Group, 2008.

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40

Shit, Pravat Kumar, et Gouri Sankar Bhunia. Spatial Mapping and Modelling for Kala-azar Disease. Springer, 2020.

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41

Lai, Poh Chin, Fun Mun So et Ka Wing Chan. Spatial Epidemiological Approaches in Disease Mapping and Analysis. Taylor & Francis Group, 2009.

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42

Lawson, Andrew B. Bayesian Disease Mapping : Hierarchical Modeling in Spatial Epidemiology. Taylor & Francis Group, 2008.

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43

Lai, Poh Chin, Fun Mun So et Ka Wing Chan. Spatial Epidemiological Approaches in Disease Mapping and Analysis. Taylor & Francis Group, 2008.

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44

Bayesian Disease Mapping : Hierarchical Modeling in Spatial Epidemiology, Third Edition. Chapman and Hall/CRC, 2018.

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45

Lawson, Andrew B. Bayesian Disease Mapping : Hierarchical Modeling in Spatial Epidemiology, Third Edition. Taylor & Francis Group, 2018.

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46

Lawson, Andrew B. Bayesian Disease Mapping : Hierarchical Modeling in Spatial Epidemiology, Third Edition. Taylor & Francis Group, 2018.

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47

Lawson, Andrew B. Bayesian Disease Mapping : Hierarchical Modeling in Spatial Epidemiology, Second Edition. Taylor & Francis Group, 2013.

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48

Lawson, Andrew B. Bayesian Disease Mapping : Hierarchical Modeling in Spatial Epidemiology, Third Edition. Taylor & Francis Group, 2018.

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49

Lawson, Andrew B. Bayesian Disease Mapping : Hierarchical Modeling in Spatial Epidemiology, Third Edition. Taylor & Francis Group, 2018.

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50

Viboud, Cécile, Hélène Broutin et Gerardo Chowell. Spatial-temporal transmission dynamics and control of infectious diseases : Ebola virus disease (EVD) as a case study. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198789833.003.0004.

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Disentangling the spatial-temporal dynamics of infectious disease transmission is important to address issues of disease persistence, epidemic growth and optimal control. In this chapter, we review key concepts relating to the spatial-temporal dynamics of infectious diseases in meta-populations, whereby geographically separate subpopulations are connected by migration or mobility rates. We review the dynamics of colonization, persistence and extinction of emerging and recurrent pathogens in meta-populations; the role of demographic and environmental factors; and geographic heterogeneity in epidemic growth rate. We illustrate theoretical concepts by reviewing the spatial dynamics of childhood diseases and other acute infections in low- and middle-income countries, and provide a detailed description of the spatial-temporal dynamics of the 2014–16 Ebola epidemic in West Africa. We further discuss how increased availability of empirical data and recent methodological developments provide a deeper mechanistic understanding of transmission processes in space and time, and make recommendations for future work.

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