語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Epidemics = models and data using R /
~
SpringerLink (Online service)
Epidemics = models and data using R /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Epidemics/ by Ottar N. Bjornstad.
其他題名:
models and data using R /
作者:
Bjornstad, Ottar N.
出版者:
Cham :Springer International Publishing : : 2018.,
面頁冊數:
xiii, 312 p. :ill. (some col.), digital ; : 24 cm.;
Contained By:
Springer eBooks
標題:
Epidemics - Data processing. -
電子資源:
https://doi.org/10.1007/978-3-319-97487-3
ISBN:
9783319974873
Epidemics = models and data using R /
Bjornstad, Ottar N.
Epidemics
models and data using R /[electronic resource] :by Ottar N. Bjornstad. - Cham :Springer International Publishing :2018. - xiii, 312 p. :ill. (some col.), digital ;24 cm. - Use R!,2197-5736. - Use R!..
Chapter 1. Introduction -- Chapter 2. SIR -- Chapter 3. R0 -- Chapter 4. FoI and age-dependent incidence -- Chapter 5. Seasonality -- Chapter 6. Time Series Analysis -- Chapter 7. TSIR -- Chapter 8 -- Trajectory Matching -- Chapter 9. Stability and Resonant Periodicity -- Chapter 10. Exotica -- Chapter 11. Spatial Dynamics -- Chapter 12. Transmission on Networks -- Chapter 13. Spatial and Spatiotemporal Patterns -- Chapter 14. Parasitoids -- Chapter 15. Non-Independent Data -- Chapter 16. Quantifying In-Host Patterns -- Bibliography -- Index.
This book is designed to be a practical study in infectious disease dynamics. The book offers an easy to follow implementation and analysis of mathematical epidemiology. The book focuses on recent case studies in order to explore various conceptual, mathematical, and statistical issues. The dynamics of infectious diseases shows a wide diversity of pattern. Some have locally persistent chains-of-transmission, others persist spatially in 'consumer-resource metapopulations'. Some infections are prevalent among the young, some among the old and some are age-invariant. Temporally, some diseases have little variation in prevalence, some have predictable seasonal shifts and others exhibit violent epidemics that may be regular or irregular in their timing. Models and 'models-with-data' have proved invaluable for understanding and predicting this diversity, and thence help improve intervention and control. Using mathematical models to understand infectious disease dynamics has a very rich history in epidemiology. The field has seen broad expansions of theories as well as a surge in real-life application of mathematics to dynamics and control of infectious disease. The chapters of Epidemics: Models and Data using R have been organized in a reasonably logical way: Chapters 1-10 is a mix and match of models, data and statistics pertaining to local disease dynamics; Chapters 11-13 pertains to spatial and spatiotemporal dynamics; Chapter 14 highlights similarities between the dynamics of infectious disease and parasitoid-host dynamics; Finally, Chapters 15 and 16 overview additional statistical methodology useful in studies of infectious disease dynamics. This book can be used as a guide for working with data, models and 'models-and-data' to understand epidemics and infectious disease dynamics in space and time.
ISBN: 9783319974873
Standard No.: 10.1007/978-3-319-97487-3doiSubjects--Topical Terms:
1210576
Epidemics
--Data processing.
LC Class. No.: RA652.2.D38 / B567 2018
Dewey Class. No.: 614.4
Epidemics = models and data using R /
LDR
:03416nam a2200349 a 4500
001
929798
003
DE-He213
005
20190326150440.0
006
m d
007
cr nn 008maaau
008
190626s2018 gw s 0 eng d
020
$a
9783319974873
$q
(electronic bk.)
020
$a
9783319974866
$q
(paper)
024
7
$a
10.1007/978-3-319-97487-3
$2
doi
035
$a
978-3-319-97487-3
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
RA652.2.D38
$b
B567 2018
072
7
$a
PBT
$2
bicssc
072
7
$a
MED090000
$2
bisacsh
072
7
$a
PBT
$2
thema
072
7
$a
MBNS
$2
thema
082
0 4
$a
614.4
$2
23
090
$a
RA652.2.D38
$b
B626 2018
100
1
$a
Bjornstad, Ottar N.
$3
1210575
245
1 0
$a
Epidemics
$h
[electronic resource] :
$b
models and data using R /
$c
by Ottar N. Bjornstad.
260
$a
Cham :
$c
2018.
$b
Springer International Publishing :
$b
Imprint: Springer,
300
$a
xiii, 312 p. :
$b
ill. (some col.), digital ;
$c
24 cm.
490
1
$a
Use R!,
$x
2197-5736
505
0
$a
Chapter 1. Introduction -- Chapter 2. SIR -- Chapter 3. R0 -- Chapter 4. FoI and age-dependent incidence -- Chapter 5. Seasonality -- Chapter 6. Time Series Analysis -- Chapter 7. TSIR -- Chapter 8 -- Trajectory Matching -- Chapter 9. Stability and Resonant Periodicity -- Chapter 10. Exotica -- Chapter 11. Spatial Dynamics -- Chapter 12. Transmission on Networks -- Chapter 13. Spatial and Spatiotemporal Patterns -- Chapter 14. Parasitoids -- Chapter 15. Non-Independent Data -- Chapter 16. Quantifying In-Host Patterns -- Bibliography -- Index.
520
$a
This book is designed to be a practical study in infectious disease dynamics. The book offers an easy to follow implementation and analysis of mathematical epidemiology. The book focuses on recent case studies in order to explore various conceptual, mathematical, and statistical issues. The dynamics of infectious diseases shows a wide diversity of pattern. Some have locally persistent chains-of-transmission, others persist spatially in 'consumer-resource metapopulations'. Some infections are prevalent among the young, some among the old and some are age-invariant. Temporally, some diseases have little variation in prevalence, some have predictable seasonal shifts and others exhibit violent epidemics that may be regular or irregular in their timing. Models and 'models-with-data' have proved invaluable for understanding and predicting this diversity, and thence help improve intervention and control. Using mathematical models to understand infectious disease dynamics has a very rich history in epidemiology. The field has seen broad expansions of theories as well as a surge in real-life application of mathematics to dynamics and control of infectious disease. The chapters of Epidemics: Models and Data using R have been organized in a reasonably logical way: Chapters 1-10 is a mix and match of models, data and statistics pertaining to local disease dynamics; Chapters 11-13 pertains to spatial and spatiotemporal dynamics; Chapter 14 highlights similarities between the dynamics of infectious disease and parasitoid-host dynamics; Finally, Chapters 15 and 16 overview additional statistical methodology useful in studies of infectious disease dynamics. This book can be used as a guide for working with data, models and 'models-and-data' to understand epidemics and infectious disease dynamics in space and time.
650
0
$a
Epidemics
$x
Data processing.
$3
1210576
650
0
$a
Communicable diseases
$x
Data processing.
$3
782801
650
0
$a
R (Computer program language)
$3
679069
650
1 4
$a
Statistics for Life Sciences, Medicine, Health Sciences.
$3
670172
650
2 4
$a
Epidemiology.
$3
635923
650
2 4
$a
Infectious Diseases.
$3
668393
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer eBooks
830
0
$a
Use R!.
$3
1197575
856
4 0
$u
https://doi.org/10.1007/978-3-319-97487-3
950
$a
Mathematics and Statistics (Springer-11649)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入