Browse Source

update cluster graphics and revert bib style

FlipediFlop 9 months ago
parent
commit
5e03cf57d1

+ 24 - 4
chapters/appendix/appendix.tex

@@ -11,6 +11,26 @@
 \chapter{Appendix}
 \chapter{Appendix}
 \label{chap:appendix}
 \label{chap:appendix}
 
 
+\begin{figure}[t]
+    \centering
+    \includegraphics[width=\textwidth]{state_sir_cluster_1.pdf}
+    \caption{Part 1 of the results}
+    \label{fig:SIR_state_results_1}
+\end{figure}
+
+\begin{figure}[t]
+    \centering
+    \begin{subfigure}{\textwidth}
+        \includegraphics[width=\textwidth]{state_sir_cluster_2.pdf}
+    \end{subfigure}
+    \quad
+    \begin{subfigure}{0.4\textwidth}
+        \includegraphics[width=\textwidth]{germany_single_sir.pdf}
+    \end{subfigure}
+    \caption{Part 1 of the results}
+    \label{fig:SIR_state_results_2}
+\end{figure}
+
 \begin{figure}[t]
 \begin{figure}[t]
     \centering
     \centering
     \begin{subfigure}{0.45\textwidth}
     \begin{subfigure}{0.45\textwidth}
@@ -20,7 +40,7 @@
         \includegraphics[width=\textwidth]{I_cluster_0.pdf}
         \includegraphics[width=\textwidth]{I_cluster_0.pdf}
     \end{subfigure}
     \end{subfigure}
     \caption{Part 1 of the results}
     \caption{Part 1 of the results}
-    \label{fig:state_results_1}
+    \label{fig:I_state_results_1}
 \end{figure}
 \end{figure}
 
 
 
 
@@ -33,7 +53,7 @@
         \includegraphics[width=\textwidth]{I_cluster_1.pdf}
         \includegraphics[width=\textwidth]{I_cluster_1.pdf}
     \end{subfigure}
     \end{subfigure}
     \caption{Part 2 of the results}
     \caption{Part 2 of the results}
-    \label{fig:state_results_2}
+    \label{fig:I_state_results_2}
 \end{figure}
 \end{figure}
 
 
 \begin{figure}[t]
 \begin{figure}[t]
@@ -45,7 +65,7 @@
         \includegraphics[width=\textwidth]{I_cluster_2.pdf}
         \includegraphics[width=\textwidth]{I_cluster_2.pdf}
     \end{subfigure}
     \end{subfigure}
     \caption{Part 3 of the results}
     \caption{Part 3 of the results}
-    \label{fig:state_results_3}
+    \label{fig:I_state_results_3}
 \end{figure}
 \end{figure}
 
 
 \begin{figure}[t]
 \begin{figure}[t]
@@ -57,6 +77,6 @@
         \includegraphics[width=\textwidth]{I_cluster_3.pdf}
         \includegraphics[width=\textwidth]{I_cluster_3.pdf}
     \end{subfigure}
     \end{subfigure}
     \caption{Part 3 of the results}
     \caption{Part 3 of the results}
-    \label{fig:state_results_4}
+    \label{fig:I_state_results_4}
 \end{figure}
 \end{figure}
 
 

+ 5 - 51
chapters/chap04/chap04.tex

@@ -53,46 +53,8 @@ representing the time span during which the COVID-19 disease was the most
 active and severe.
 active and severe.
 
 
 \begin{figure}[h]
 \begin{figure}[h]
-    %\centering
-    \setlength{\unitlength}{1cm} % Set the unit length for coordinates
-    \begin{picture}(12, 9.5) % Specify the size of the picture environment (width, height)
-        \put(1.5, 4.5){
-            \begin{subfigure}{0.3\textwidth}
-                \centering
-                \includegraphics[width=\textwidth]{SIR_synth.pdf}
-                \label{fig:synthetic_SIR}
-            \end{subfigure}
-        }
-        \put(8, 4.5){
-            \begin{subfigure}{0.3\textwidth}
-                \centering
-                \includegraphics[width=\textwidth]{datasets_states/Germany_SIR_14.pdf}
-                \label{fig:germany_sir}
-            \end{subfigure}
-        }
-        \put(0, 0){
-            \begin{subfigure}{0.3\textwidth}
-                \centering
-                \includegraphics[width=\textwidth]{datasets_states/Schleswig_Holstein_SIR_14.pdf}
-                \label{fig:schleswig_holstein_sir}
-            \end{subfigure}
-        }
-        \put(4.75, 0){
-            \begin{subfigure}{0.3\textwidth}
-                \centering
-                \includegraphics[width=\textwidth]{datasets_states/Berlin_SIR_14.pdf}
-                \label{fig:berlin_sir}
-            \end{subfigure}
-        }
-        \put(9.5, 0){
-            \begin{subfigure}{0.3\textwidth}
-                \centering
-                \includegraphics[width=\textwidth]{datasets_states/Thueringen_SIR_14.pdf}
-                \label{fig:thüringen_sir}
-            \end{subfigure}
-        }
-
-    \end{picture}
+    \centering
+    \includegraphics[width=\textwidth]{in_text_SIR.pdf}
     \caption{Synthetic and real-world training data. The synthetic data is
     \caption{Synthetic and real-world training data. The synthetic data is
         generated with $\alpha=\nicefrac{1}{3}$ and $\beta=\nicefrac{1}{2}$
         generated with $\alpha=\nicefrac{1}{3}$ and $\beta=\nicefrac{1}{2}$
         and~\Cref{eq:modSIR}. The Germany data is taken from the death case
         and~\Cref{eq:modSIR}. The Germany data is taken from the death case
@@ -370,22 +332,14 @@ is shorter, but the peak value is higher.\\
 \begin{figure}[t]
 \begin{figure}[t]
     \centering
     \centering
     \begin{subfigure}{0.45\textwidth}
     \begin{subfigure}{0.45\textwidth}
-        \includegraphics[width=\textwidth]{I_prediction/Thueringen_I_prediction.pdf}
-    \end{subfigure}
-    \quad
-    \begin{subfigure}{0.45\textwidth}
-        \includegraphics[width=\textwidth]{I_prediction/Bremen_I_prediction.pdf}
+        \includegraphics[width=\textwidth]{r_t_cluster_intext.pdf}
     \end{subfigure}
     \end{subfigure}
     \begin{subfigure}{0.45\textwidth}
     \begin{subfigure}{0.45\textwidth}
-        \includegraphics[width=\textwidth]{R_t/Thueringen_R_t_statistics.pdf}
-    \end{subfigure}
-    \quad
-    \begin{subfigure}{0.45\textwidth}
-        \includegraphics[width=\textwidth]{R_t/Bremen_R_t_statistics.pdf}
+        \includegraphics[width=\textwidth]{I_cluster_intext.pdf}
     \end{subfigure}
     \end{subfigure}
     \label{fig:state_results}
     \label{fig:state_results}
     \caption{Visualization of the prediction of the training and  the graphs of
     \caption{Visualization of the prediction of the training and  the graphs of
-        $\Rt$ for Thuringia (left) and Bremen (right) with both
+        $\Rt$ for Thuringia (upper) and Bremen (lower) with both
         $\alpha = \nicefrac{1}{14}$ and $\alpha = \nicefrac{1}{5}$. Events~\cite{COVIDChronik} like
         $\alpha = \nicefrac{1}{14}$ and $\alpha = \nicefrac{1}{5}$. Events~\cite{COVIDChronik} like
         the peak of an influential variant or the start of the vaccination of the public are marked horizontally. Further
         the peak of an influential variant or the start of the vaccination of the public are marked horizontally. Further
         visualizations can be found in~\Cref{chap:appendix}.}
         visualizations can be found in~\Cref{chap:appendix}.}

+ 0 - 2
header.tex

@@ -43,8 +43,6 @@
 \usepackage{setspace}
 \usepackage{setspace}
 \onehalfspacing
 \onehalfspacing
 
 
-\usepackage[numbers]{natbib}
-
 \usepackage{cleveref}
 \usepackage{cleveref}
 \usepackage{todonotes}
 \usepackage{todonotes}
 \usepackage{nicefrac}
 \usepackage{nicefrac}

BIN
images/I_cluster_intext.pdf


BIN
images/germany_single_sir.pdf


BIN
images/in_text_SIR.pdf


BIN
images/r_t_cluster_intext.pdf


BIN
images/state_sir_cluster_1.pdf


BIN
images/state_sir_cluster_2.pdf


+ 263 - 0
thesis.bbl

@@ -0,0 +1,263 @@
+\begin{thebibliography}{10}
+
+\bibitem{WHO}
+WHO.
+\newblock Coronavirus disease (covid-19).
+\newblock \url{https://www.who.int/health-topics/coronavirus#tab=tab_1}.
+\newblock {Accessed: 2024-09-06}.
+
+\bibitem{RKI}
+RKI.
+\newblock Covid-19-strategiepapiere und nationaler pandemieplan.
+\newblock
+  \url{https://www.rki.de/DE/Content/InfAZ/N/Neuartiges_Coronavirus/ZS/Pandemieplan_Strategien.html}.
+\newblock {Accessed: 2024-09-06}.
+
+\bibitem{RKIa}
+RKI.
+\newblock Sars-cov-2: Virologische basisdaten sowie virusvarianten im zeitraum
+  von 2020 - 2022.
+\newblock
+  \url{https://www.rki.de/DE/Content/InfAZ/N/Neuartiges_Coronavirus/Virologische_Basisdaten.html?nn=13490888#doc14716546bodyText10}.
+\newblock {Accessed: 2024-09-05}.
+
+\bibitem{SRD}
+{Statista Research Department}.
+\newblock Anzahl infektionen und todesfälle in zusammenhang mit dem
+  coronavirus (covid-19) in deutschland seit februar 2020.
+\newblock
+  https://de.statista.com/statistik/daten/studie/1102667/umfrage/erkrankungs-und-todesfaelle-aufgrund-des-coronavirus-in-deutschland/.
+\newblock {Accessed: 2024-09-06}.
+
+\bibitem{1927}
+William~Ogilvy Kermack and A.~G. McKendrick.
+\newblock A contribution to the mathematical theory of epidemics.
+\newblock {\em Proceedings of the Royal Society of London. Series A, Containing
+  Papers of a Mathematical and Physical Character}, 115(772):700--721, August
+  1927.
+
+\bibitem{Liu2012}
+Xinzhi Liu and Peter Stechlinski.
+\newblock Infectious disease models with time-varying parameters and general
+  nonlinear incidence rate.
+\newblock {\em Applied Mathematical Modelling}, 36(5):1974--1994, May 2012.
+
+\bibitem{Setianto2023}
+Setianto Setianto and Darmawan Hidayat.
+\newblock Modeling the time-dependent transmission rate using gaussian pulses
+  for analyzing the covid-19 outbreaks in the world.
+\newblock {\em Scientific Reports}, 13(1), March 2023.
+
+\bibitem{Shaier2021}
+Sagi Shaier, Maziar Raissi, and Padmanabhan Seshaiyer.
+\newblock Data-driven approaches for predicting spread of infectious diseases
+  through dinns: Disease informed neural networks, 2021.
+
+\bibitem{Millevoi2023}
+Caterina Millevoi, Damiano Pasetto, and Massimiliano Ferronato.
+\newblock A physics-informed neural network approach for compartmental
+  epidemiological models.
+\newblock 2023.
+
+\bibitem{Smirnova2017}
+Alexandra Smirnova, Linda deCamp, and Gerardo Chowell.
+\newblock Forecasting epidemics through nonparametric estimation of
+  time-dependent transmission rates using the seir model.
+\newblock {\em Bulletin of Mathematical Biology}, 81(11):4343--4365, May 2017.
+
+\bibitem{Berkhahn2022}
+Sarah Berkhahn and Matthias Ehrhardt.
+\newblock A physics-informed neural network to model covid-19 infection and
+  hospitalization scenarios.
+\newblock {\em Advances in Continuous and Discrete Models}, 2022(1), October
+  2022.
+
+\bibitem{Olumoyin2021}
+K.~D. Olumoyin, A.~Q.~M. Khaliq, and K.~M. Furati.
+\newblock Data-driven deep-learning algorithm for asymptomatic covid-19 model
+  with varying mitigation measures and transmission rate.
+\newblock {\em Epidemiologia}, 2(4):471--489, September 2021.
+
+\bibitem{Rudin2007}
+Walter Rudin.
+\newblock {\em Analysis}.
+\newblock Oldenbourg Wissenschaftsverlag GmbH, 2007.
+
+\bibitem{Tenenbaum1985}
+Morris Tenenbaum and Harry Pollard.
+\newblock {\em Ordinary Differential Equations}.
+\newblock Harper and Row, Publishers, Inc., 1985.
+
+\bibitem{Demtroeder2021}
+Wolfgang Demtröder.
+\newblock {\em Experimentalphysik 1}, volume~1 of {\em Lehrbuch}.
+\newblock Springer Spektrum, Berlin, 9. auflage edition, 2021.
+\newblock Auf dem Umschlag: Mit über 2,5 h Lösungsvideos zu ausgewählten
+  Aufgaben.
+
+\bibitem{Kirchhoff1845}
+Studiosus Kirchhoff.
+\newblock Ueber den durchgang eines elektrischen stromes durch eine ebene,
+  insbesondere durch eine kreisförmige.
+\newblock {\em Annalen der Physik}, 140(4):497--514, January 1845.
+
+\bibitem{Oksendal2000}
+Bernt Oksendal.
+\newblock {\em Stochastic Differential Equations}.
+\newblock Universitext Ser. Springer Berlin / Heidelberg, Berlin, Heidelberg,
+  5th ed. edition, 2000.
+\newblock Description based on publisher supplied metadata and other sources.
+
+\bibitem{EdelsteinKeshet2005}
+Leah Edelstein-Keshet.
+\newblock {\em Mathematical Models in Biology}.
+\newblock Society for Industrial and Applied Mathematics, 2005.
+
+\bibitem{Anderson1991}
+Robert~M. Anderson, Roy Malcolm;~May.
+\newblock {\em Infectious diseases of humans : dynamics and control}.
+\newblock Oxford University Press, 1991.
+
+\bibitem{Rumelhart1986}
+David~E. Rumelhart, Geoffrey~E. Hinton, and Ronald~J. Williams.
+\newblock Learning representations by back-propagating errors.
+\newblock {\em Nature}, 323(6088):533--536, October 1986.
+
+\bibitem{Goodfellow-et-al-2016}
+Ian Goodfellow, Yoshua Bengio, and Aaron Courville.
+\newblock {\em Deep Learning}.
+\newblock MIT Press, 2016.
+\newblock \url{http://www.deeplearningbook.org}.
+
+\bibitem{Rosenblatt1958}
+F.~Rosenblatt.
+\newblock The perceptron: A probabilistic model for information storage and
+  organization in the brain.
+\newblock {\em Psychological Review}, 65(6):386--408, 1958.
+
+\bibitem{Minsky1972}
+Marvin Minsky and Seymour~A. Papert.
+\newblock {\em Perceptrons}.
+\newblock The MIT Press, Cambridge/Mass. [u.a.], 2. print. with corr edition,
+  1972.
+\newblock Literaturangaben.
+
+\bibitem{Hornik1989}
+Kurt Hornik, Maxwell Stinchcombe, and Halbert White.
+\newblock Multilayer feedforward networks are universal approximators.
+\newblock {\em Neural Networks}, 2(5):359--366, January 1989.
+
+\bibitem{Lagaris1997}
+I.~E. Lagaris, A.~Likas, and D.~I. Fotiadis.
+\newblock Artificial neural networks for solving ordinary and partial
+  differential equations.
+\newblock 1997.
+
+\bibitem{Raissi2019}
+M.~Raissi, P.~Perdikaris, and G.E. Karniadakis.
+\newblock Physics-informed neural networks: A deep learning framework for
+  solving forward and inverse problems involving nonlinear partial differential
+  equations.
+\newblock {\em Journal of Computational Physics}, 378:686--707, February 2019.
+
+\bibitem{Moseley}
+Ben Moseley.
+\newblock So, what is a physics-informed neural network?
+\newblock
+  \url{https://benmoseley.blog/my-research/so-what-is-a-physics-informed-neural-network/}.
+\newblock {Accessed: 2024-09-08}.
+
+\bibitem{GHDead}
+RKI.
+\newblock Github covid-19-todesfälle in deutschland.
+\newblock
+  \url{https://github.com/robert-koch-institut/COVID-19-Todesfaelle_in_Deutschland}.
+\newblock {Accessed: 2024-09-05}.
+
+\bibitem{GHInf}
+RKI.
+\newblock Github sars-cov-2 infektionen in deutschland.
+\newblock
+  \url{https://github.com/robert-koch-institut/SARS-CoV-2-Infektionen_in_Deutschland}.
+\newblock {Accessed: 2024-09-05}.
+
+\bibitem{Paszke2019}
+Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory
+  Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban
+  Desmaison, Andreas Köpf, Edward Yang, Zach DeVito, Martin Raison, Alykhan
+  Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu~Fang, Junjie Bai, and Soumith
+  Chintala.
+\newblock Pytorch: An imperative style, high-performance deep learning library,
+  2019.
+
+\bibitem{FMH}
+{Federal Ministry of Health}.
+\newblock Übersicht zum impfstatus - covid-19-impfung in deutschland bis zum
+  8. april 2023.
+\newblock \url{https://impfdashboard.de/}.
+\newblock {Accessed: 2024-09-08}.
+
+\bibitem{COVInfo}
+{Federal Centre for Health Education}.
+\newblock Ansteckung, Übertragung und krankheitsverlauf.
+\newblock
+  \url{https://www.infektionsschutz.de/coronavirus/fragen-und-antworten/ansteckung-uebertragung-und-krankheitsverlauf/}.
+\newblock {Accessed: 2024-09-05}.
+
+\bibitem{COVIDChronik}
+{Federal Ministry of Health}.
+\newblock Coronavirus-pandemie: Was geschah wann?
+\newblock
+  \url{https://www.bundesgesundheitsministerium.de/coronavirus/chronik-coronavirus.html}.
+\newblock {Accessed: 2024-09-05}.
+
+\bibitem{Desson2022}
+Zachary Desson, Lukas Kauer, Thomas Otten, Jan~Willem Peters, and Francesco
+  Paolucci.
+\newblock Finding the way forward: Covid-19 vaccination progress in germany,
+  austria and switzerland.
+\newblock {\em Health Policy and Technology}, 11(2):100584, June 2022.
+
+\bibitem{Korolev2021}
+Ivan Korolev.
+\newblock Identification and estimation of the seird epidemic model for
+  covid-19.
+\newblock {\em Journal of Econometrics}, 220(1):63--85, January 2021.
+
+\bibitem{Doerre2022}
+Achim Doerre and Gabriele Doblhammer.
+\newblock The influence of gender on covid-19 infections and mortality in
+  germany: Insights from age- and gender-specific modeling of contact rates,
+  infections, and deaths in the early phase of the pandemic.
+\newblock {\em PLOS ONE}, 17(5):e0268119, May 2022.
+
+\bibitem{Cooke1996}
+K.~L. Cooke and P.~van~den Driessche.
+\newblock Analysis of an seirs epidemic model with two delays.
+\newblock {\em Journal of Mathematical Biology}, 35(2):240--260, December 1996.
+
+\bibitem{Gilbert2010}
+G.~Nigel Gilbert.
+\newblock {\em Agent-based models}.
+\newblock Number 153 in Quantitative applications in the social sciences. Sage
+  Publ., Los Angeles [u.a.], 3. pr. edition, 2010.
+
+\bibitem{Kerr2021}
+Cliff~C. Kerr, Robyn~M. Stuart, Dina Mistry, Romesh~G. Abeysuriya, Katherine
+  Rosenfeld, Gregory~R. Hart, Rafael~C. Núñez, Jamie~A. Cohen, Prashanth
+  Selvaraj, Brittany Hagedorn, Lauren George, Michał Jastrzębski, Amanda~S.
+  Izzo, Greer Fowler, Anna Palmer, Dominic Delport, Nick Scott, Sherrie~L.
+  Kelly, Caroline~S. Bennette, Bradley~G. Wagner, Stewart~T. Chang, Assaf~P.
+  Oron, Edward~A. Wenger, Jasmina Panovska-Griffiths, Michael Famulare, and
+  Daniel~J. Klein.
+\newblock Covasim: An agent-based model of covid-19 dynamics and interventions.
+\newblock {\em PLOS Computational Biology}, 17(7):e1009149, July 2021.
+
+\bibitem{Maziarz2020}
+Mariusz Maziarz and Martin Zach.
+\newblock Agent‐based modelling for sars‐cov‐2 epidemic prediction and
+  intervention assessment: A methodological appraisal.
+\newblock {\em Journal of Evaluation in Clinical Practice}, 26(5):1352--1360,
+  August 2020.
+
+\end{thebibliography}

BIN
thesis.pdf


+ 1 - 1
thesis.tex

@@ -81,7 +81,7 @@
 
 
 \interlinepenalty10000 % so no bib-entry will be separated by a pagebreak
 \interlinepenalty10000 % so no bib-entry will be separated by a pagebreak
 \bibliography{thesis.bib}
 \bibliography{thesis.bib}
-\bibliographystyle{numeric} % change the bib-style if you want to
+\bibliographystyle{unsrt} % change the bib-style if you want to