Documentation_COVID19_Local.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# Local analysis of the case numbers of COVID19 for Germany\n",
    "\n",
    "#### Analyse der Corona Fallzahlen auf Landkreisebene in Deutschland (Deutsche Version auf Nachbarseite)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## TODAY'S DATASET\n",
    "\n",
    "Description further down."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "New data for July available.\n",
    "\n",
    "### Dataset downloaded 2020-07-23\n",
    "\n",
    "* THERE IS NO GLORY IN PREVENTION BUT STILL LET'S TRY.\n",
    "\n",
    "\n",
    "* DT evolution https://github.com/koepferl/COVID19Dahoam/blob/master/DT_Bavaria.pdf: \n",
    "    Changed y axis to log now. Most counties have now higher doubling times, isolation works. Stay put.\n",
    "    \n",
    "* Semi-log plots https://github.com/koepferl/COVID19Dahoam/tree/master/plots: \n",
    "     Counties with still very low DTs show also no flattening; with high DT almost a horizontal trend.\n",
    "     \n",
    "* loglog plot https://github.com/koepferl/COVID19Dahoam/blob/master/loglog_Bavaria.pdf\n",
    "     Almost all counties move steep downwards (less infections every day) this means people are recovering faster than new once are becoming infected. This is good, our health system does not break down.\n",
    "\n",
    "* expert plots: In some counties now there a again more cases coming in, this causes the slope to steepen in the semilog plot, the DTs get shorter again and in the log-log plot the droping trend is revercing. In the expert plot we can see that also the reproduction time is goint up once the DT drops. The end of the loc-down is now visible."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "More interpretation follows soon. \n",
    "Find the interpretation history at the end of this page.\n",
    "\n",
    "## Recommendation\n",
    "Social distancing is key to slow down the case numbers further to not overburden our local health system. Show solidarity through and from the distance. THERE IS NO GLORY IN PREVENTION BUT STILL LET'S TRY."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Documentation\n",
    "\n",
    "Here the diagrams for the 96 Bavarian counties (more coming) of the evolution of the Corona cases are provided, analysed and the doubling times are given. The corresponding code to perform this analysis is provided as well. The plots are updated every day.\n",
    "\n",
    "#### Work for you - Mithilfe\n",
    "HELP: We need the number of min. and max. number of beds for intensive care (respirator) in all Bavarian/German counties. Input is very welcome.\n",
    "HILFE: Wir brauchen noch die min. und max. Anzahl von Beatmungsgeräten in den jeweiligen Landkreisen in Bayern/Deutschland. Input is very welcome.\n",
    "\n",
    "\n",
    "\n",
    "#### Disclaimer\n",
    "This is currently work in progress before using convince yourself that the analysis and numbers are correct. No guarantee is given.\n",
    "\n",
    "#### Credit\n",
    "When using this dataset or code please reference accordingly:  \n",
    "\n",
    "<a href=\"https://zenodo.org/badge/latestdoi/252294531\"><img src=\"https://zenodo.org/badge/252294531.svg\" alt=\"DOI\"></a>\n",
    "\n",
    "\n",
    "* Christine Greif http://www.usm.uni-muenchen.de/~koepferl\n",
    "* Images are licensed under CC-BY-SA 4.0\n",
    "* Data source: NPGEO-DE\n",
    "* Special thanks to Prof. Andreas Burkert at the LMU Munich"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Logarithmic Plot of the COVID-19 Cases \n",
    "\n",
    "The plots for the 96 Bavarian counties are provided. An example is provided below.\n",
    "\n",
    "#### Axis\n",
    "Note that this is a semilogarithmic plot. The numbers on y axis are not equally spaced.\n",
    "\n",
    "#### Data points\n",
    "The data points of the cumulative evolution over time are shown with black + signs. The data was extracted from the online catalog of the Robert-Koch-Institute at https://npgeo-corona-npgeo-de.hub.arcgis.com/datasets/dd4580c810204019a7b8eb3e0b329dd6_0?orderBy=IdLandkreis&orderByAsc=false&where=Bundesland%20%3D%20%27Bayern%27 .\n",
    "\n",
    "After 2020-04-12 also recovered cases (o) and fatal cases (*) added.\n",
    "\n",
    "#### Fitting \n",
    "Once eight data points are available a non-linear least square fit is performed for a specific date. For the following dates also a similar fit is performed also using the eight most recent available data points. In this case the fit is weighted towards the most recent development and is not contaminated by the early evolution with is currently of secondary interest. Fits of early dates are dark blue. Most recent fits are yellow. \n",
    "\n",
    "For the fit the routine ``curve_fit`` of the ``scipy.optimize`` module was used with respect to the following theoretical function ``y = a * exp(b * x)``. For further information see: https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.curve_fit.html\n",
    "\n",
    "From the 2020-04-10 onwards changed to log-linare least square fit (to overcome breake of curve_fit at turnover point).\n",
    "\n",
    "#### Hospital Capacity\n",
    "It is possible to add the minimal and maximal hospital capacity of intensive care in the code (horizontal dotted lines). Currently the data is only available for the county \"Landkreis Miesbach\". We would appreciate input very much. \n",
    "\n",
    "#### Approximated Demand for Intensive Care\n",
    "It is possible to display the approximated demand of intensive care facilities as a function of time. This a very rough approximation currently using 5% of the currently approximated cases. This number can be changed. We would appreciate input of which number best to used. If the Hospital capacity of the specific county is available the corresponding availability can be color-coded in a traffic light manner. \n",
    "\n",
    "* green: enough facilities available in this county\n",
    "* orange: sufficient facilities available in this county\n",
    "* red: to few facilities available in this county\n",
    "\n",
    "The corresponding black dashed lines represent the errors of such a rough approximation."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "=> see Figure ``plots/LK Miesbach.pdf`` on https://github.com/koepferl/COVID19Dahoam/blob/master/plots/LK%20Miesbach.pdf\n",
    "\n",
    "In the expert plot I show the cumulative case number, the daily cases, the doubeling time and the reproduction number.\n",
    "\n",
    "=> see Figure ``expert/LK Miesbach_expert.pdf`` at https://github.com/koepferl/COVID19Dahoam/blob/master/expert/LK%20Miesbach_expert.pdf\n",
    "\n",
    "![title](expert/LK Miesbach_expert.pdf)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Doubling Time\n",
    "\n",
    "Below the evolution of the estimated doubling time is given for every county. The number of data points differs per county due to the different outbreak times. The doubling time was calculated from every fit, using the extracted fitting parameter `b`.\n",
    "\n",
    "$y = a * exp(b * x)$\n",
    "\n",
    "$2a = a * exp(b * x_{double})$\n",
    "\n",
    "$2 = exp(b * x_{double})$\n",
    " \n",
    "$ln(2) = b * x_{double}$\n",
    "\n",
    "$x_{double} = \\frac{ln(2)}{b}$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "=> see ``DT_Bavaria.pdf`` on https://github.com/koepferl/COVID19Dahoam/blob/master/DT_Bavaria.pdf \n",
    "\n",
    "![title](DT_Bavaria.pdf)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note: The raw data contains the individal cases transmitted by the local authorities to the RKI. For certain counties the number of cases for a certain day are corrected afterwards. Therefore it is possible that the doubling time variates in the DT.pdf when comparing different days. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Log-Log Plot\n",
    "\n",
    "The number of total cases until a certain day (y axis) is plotted against the number of new cases in the past week for a certain day (x axis). Once there are fewer new infections the curve will drop downwards. Once this drops steep the uncontroled exponential growth is broken. You can see a beginning trend for with high DTs.\n",
    "     Compare with https://www.youtube.com/watch?v=54XLXg4fYsc and https://aatishb.com/covidtrends/\n",
    "     \n",
    "=> see ``loglog_Bavaria.pdf`` on https://github.com/koepferl/COVID19Dahoam/blob/master/loglog_Bavaria.pdf \n",
    "\n",
    "![title](loglog_Bavaria.pdf)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Interpretation\n",
    "\n",
    "### Dataset downloaded 2020-04-02\n",
    "We can see from the semi logarithmic plot and the evolution of the doubling time that some counties have slowed down their exponential growth of the case numbers. However some are still on doubling times smaller than 5 days (e. g. LK Bad Kissingen, LK Guenzburg, LK Neustadt a.d.Waldnaab, LK Straubing-Bogen, SK Amberg, SK Hof, SK Ingolstadt, SK Kaufbeuren, SK Schweinfurt). For some of the counties a turn over in the case number evolution is not yet visible (e. g. LK Dillingen, LK Amberg-Sulzbach, LK Bad Kissingen).\n",
    "\n",
    "However I need to emphasize that even though an improve in the doubling times and a turn over in case numbers in the logarithmic plot is visible (e. g. LK Miesbach), still the capacities of the local hospital facilities are limited. \n",
    "\n",
    "### Dataset downloaded 2020-04-04\n",
    "\n",
    "* News: I included the average of the State Bavaria in the DT_Bavaria.pdf. Everything above that average doubling time is encouraging. For the counties below, the situation is not as good. Unfortunately some counties are lacking behind in their data transmission, or correcting some numbers afterwards, this is why there might be still some fluctuation (see above).\n",
    "* Semi-log plot: Many counties show flattening now. No flattening can be seen in:\n",
    "    * Conties with no flattening: SK Amberg, SK Ansbach, SK Hof, SK Kempten\n",
    "    * Counties with steeper slopes (!!!): LK Amberg-Sulzbach, LK Donau-Ries, LK Erlangen-Hoechstadt, LK Regen, LK Straubing-Bogen, SK Erlangen, SK Straubing, SK Weiden i.d.OPf.    \n",
    "* DT evolution: \n",
    "    * Most counties move towards the 8 day margin, however there are still many with relative low doubling times (the lower the DT, the faster the spread of COVID19). \n",
    "    * Counties smaller than 5 days: SK Ingolstadt, SK Amberg, LK Straubing-Bogen, LK Neustadt a.d.Waldnaab, LK Donau-Ries, LK Amberg-Sulzbach   \n",
    "* Task: Find reliable numbers of the ventilation capacities in as many counties as possible to populate the traffic light estimation (e.g. LK Miesbach).\n",
    "\n",
    "### Dataset downloaded 2020-04-06\n",
    "\n",
    "Datadownload crashed at the weekend. Sorry.\n",
    "\n",
    "* News: x-Axis extended to mid-April\n",
    "* DT evolution: \n",
    "    * Counties smaller than 6 days: \n",
    "         * 5.99 d: LK Berchtesgadener Land\n",
    "         * 5.68 d: LK Dillingen a.d.Donau\n",
    "         * 5.98 d: LK Nuenberger Land\n",
    "         * 5.37 d: LK Schwandorf\n",
    "         * 5.53 d: SK Hof\n",
    "         * 5.40 d: SK Straubing\n",
    "         * 5.91 d: SK Weiden i.d.OPf.\n",
    "    * Counties smaller than 5 days:\n",
    "         * 4.62 d: LK Amberg-Sulzbach\n",
    "         * 4.79 d: LK Donau-Ries\n",
    "         * 4.62 d: LK Straubing-Bogen\n",
    "         * 4.15 d: SK Amberg\n",
    "         * 4.54 d: SK Ansbach\n",
    "         * 4.53 d: SK Ingolstadt\n",
    "         \n",
    "* Semi-log plot: \n",
    "     * no signigicant flattening\n",
    "         * LK Amberg-Sulzbach\n",
    "         * LK Erlangen-Hoechstadt\n",
    "         * LK Kitzingen\n",
    "         * LK Schwandorf\n",
    "         * SK Amberg\n",
    "         * SK Ansbach\n",
    "         * SK Aschaffenburg\n",
    "         * SK Hof\n",
    "     * increase\n",
    "         * LK Amberg-Sulzbach\n",
    "         * (small) LK Bayreuth\n",
    "         * (small) LK Berchtesgadener Land\n",
    "         * (small) LK Dingolfing-Landau\n",
    "         * LK Donau-Ries\n",
    "         * LK Erlangen-Hoechstadt\n",
    "         * (small) LK Garmisch-Partenkirchen\n",
    "         * (small) LK Hassberge\n",
    "         * (small) LK Hof\n",
    "         * (small) LK Kelheim\n",
    "         * LK Kitzingen\n",
    "         * LK Regen\n",
    "         * (small) LK Rhoen-Grabfeld\n",
    "         * LK Schwandorf\n",
    "         * LK Straubing-Bogen\n",
    "         * SK Amberg\n",
    "         * SK Erlangen\n",
    "         * SK Straubing\n",
    "\n",
    "### Dataset downloaded 2020-04-08\n",
    "\n",
    "* News: new plot type available where you can see once the exponential growth is broken.\n",
    "* DT evolution https://github.com/koepferl/COVID19Dahoam/blob/master/DT_Bavaria.pdf: \n",
    "    Most counties have now higher doubling times (average is 12 d), isolation works. Stay put.\n",
    "    * Counties smaller than 6 days (the larger the better): \n",
    "         * LK Amberg-Sulzbach\n",
    "         * LK Donau-Ries\n",
    "    * Counties larger than 20 days (the larger the better):\n",
    "         * SK München (Munich)\n",
    "         * SK Deggendorf\n",
    " \n",
    "* Semi-log plots https://github.com/koepferl/COVID19Dahoam/tree/master/plots: \n",
    "\n",
    "     Counties with very low DTs show also no flattening; with high DT almost a horizontal trend.\n",
    "     \n",
    "     \n",
    "* loglog plot https://github.com/koepferl/COVID19Dahoam/blob/master/loglog_Bavaria.pdf: \n",
    "\n",
    "     The number of total cases until a certain day (y axis) is plotted against the number of new cases in the past week for a certain day (x axis). Once there are fewer new infections the curve will drop downwards. Once this drops steep the uncontroled exponential growth is broken. You can see a beginning trend for with high DTs.\n",
    "     Compare with https://www.youtube.com/watch?v=54XLXg4fYsc and https://aatishb.com/covidtrends/\n",
    "\n",
    "### Dataset downloaded 2020-04-09\n",
    "\n",
    "* DT evolution https://github.com/koepferl/COVID19Dahoam/blob/master/DT_Bavaria.pdf: \n",
    "    Most counties have now higher doubling times (average is 12 d), isolation works. Stay put.\n",
    "    * Counties smaller than 7 days (the larger the better): \n",
    "         * 5.92 7.4 LK Amberg-Sulzbach\n",
    "         * 5.39 6.4 SK Amberg\n",
    "         * 6.03 8.4 SK Ingolstadt\n",
    "         * 6.78 8.4 LK Donau-Ries\n",
    "    * Counties larger than 20 days (the larger the better):\n",
    "         * 22.67 8.4 LK Cham\n",
    "         * 23.64 8.4 LK Deggendorf\n",
    "         * 24.28 8.4 LK Weilheim-Schongau\n",
    "         * 29.81 8.4 SK Muenchen\n",
    " \n",
    "* Semi-log plots https://github.com/koepferl/COVID19Dahoam/tree/master/plots: \n",
    "\n",
    "     Counties with very low DTs show also no flattening; with high DT almost a horizontal trend.\n",
    "     \n",
    "     \n",
    "* loglog plot https://github.com/koepferl/COVID19Dahoam/blob/master/loglog_Bavaria.pdf: \n",
    "\n",
    "     The number of total cases until a certain day (y axis) is plotted against the number of new cases in the past week for a certain day (x axis). Once there are fewer new infections the curve will drop downwards. Once this drops steep the uncontroled exponential growth is broken. You can see a beginning trend for with high DTs.\n",
    "     Compare with https://www.youtube.com/watch?v=54XLXg4fYsc and https://aatishb.com/covidtrends/\n",
    "\n",
    "### Dataset downloaded 2020-04-10\n",
    "\n",
    "* NEW: Now fitting with log-linear least square fit to overcome the break down of the alorithm at turn-over. This is actually good. It means that in some counties we move away from a theory of exponential growth. Numbers and plots might be a little different now (but not much).\n",
    "* DT evolution https://github.com/koepferl/COVID19Dahoam/blob/master/DT_Bavaria.pdf: \n",
    "    Most counties have now higher doubling times (average is 15 d), isolation works. Stay put.\n",
    "    * Counties smaller than 7 days (the larger the better): \n",
    "         * 5.75d 8.4 SK Amberg\n",
    "         * 5.79d 9.4 LK Amberg-Sulzbach\n",
    "         * 6.23d 9.4 SK Ansbach\n",
    "         * 7.06d 9.4 SK Ingolstadt\n",
    "\n",
    "    * Counties larger than 30 days (the larger the better):\n",
    "         * 35.45d 9.4 LK Starnberg\n",
    "         * 32.70d 9.4 LK Weilheim-Schongau\n",
    "         * 30.97d 9.4 SK Muenchen\n",
    "\n",
    "* Semi-log plots https://github.com/koepferl/COVID19Dahoam/tree/master/plots: \n",
    "\n",
    "     Counties with very low DTs show also no flattening; with high DT almost a horizontal trend.\n",
    "     \n",
    "     \n",
    "* loglog plot https://github.com/koepferl/COVID19Dahoam/blob/master/loglog_Bavaria.pdf: \n",
    "\n",
    "     The number of total cases until a certain day (y axis) is plotted against the number of new cases in the past week for a certain day (x axis). Once there are fewer new infections the curve will drop downwards. Once this drops steep the uncontroled exponential growth is broken. You can see a beginning trend for with high DTs.\n",
    "     Compare with https://www.youtube.com/watch?v=54XLXg4fYsc and https://aatishb.com/covidtrends/\n",
    "\n",
    "\n",
    "### Dataset downloaded 2020-04-12\n",
    "\n",
    "* NEW: Added reported numbers of deaths (*) and recovered cases (o).\n",
    "* DT evolution https://github.com/koepferl/COVID19Dahoam/blob/master/DT_Bavaria.pdf: \n",
    "    Most counties have now higher doubling times (average is 17.69 d), isolation works. Stay put.\n",
    "    * Counties smaller than 10 days (the larger the better): \n",
    "         * 5.70 10.4 LK Amberg-Sulzbach\n",
    "         * 7.47 10.4 SK Amberg\n",
    "         * 8.85 42 SK Ingolstadt\n",
    "         * 9.31 10.4 LK Weissenburg-Gunzenhausen\n",
    "         * 9.47 11.4 LK Traunstein\n",
    "         * 9.49 11.4 LK Altoetting\n",
    "         * 9.59 8.4 LK Coburg\n",
    "         * 9.95 42 SK Ansbach\n",
    "\n",
    "    * Counties larger than 30 days (the larger the better):\n",
    "         * 39.99 11.4 LK Weilheim-Schongau\n",
    "         * 33.55 11.4 SK Wuezburg\n",
    "         * 31.24 10.4 LK Starnberg\n",
    "         * 30.23 10.4 LK Garmisch-Partenkirchen\n",
    "\n",
    "\n",
    "* Semi-log plots https://github.com/koepferl/COVID19Dahoam/tree/master/plots: \n",
    "\n",
    "     Counties with very low DTs show also no flattening; with high DT almost a horizontal trend.\n",
    "     \n",
    "     \n",
    "* loglog plot https://github.com/koepferl/COVID19Dahoam/blob/master/loglog_Bavaria.pdf: \n",
    "\n",
    "     The number of total cases until a certain day (y axis) is plotted against the number of new cases in the past week for a certain day (x axis). Once there are fewer new infections the curve will drop downwards. Once this drops steep the uncontroled exponential growth is broken. You can see a beginning trend for with high DTs.\n",
    "     Compare with https://www.youtube.com/watch?v=54XLXg4fYsc and https://aatishb.com/covidtrends/\n",
    "\n",
    "### Dataset downloaded 2020-04-13\n",
    "\n",
    "* NEW: Added percent statements in comparison to total number of people in a county. We can see that there is still a long way to go to herd immunity (60% of the population)\n",
    "* DT evolution https://github.com/koepferl/COVID19Dahoam/blob/master/DT_Bavaria.pdf: \n",
    "    Most counties have now higher doubling times (average is 18.84 d), isolation works. Stay put.\n",
    "    * Counties smaller than 10 days (the larger the better): \n",
    "         * 9.96 12.4 LK Dillingen a.d.Donau\n",
    "         * 9.95 11.4 SK Ansbach\n",
    "         * 9.95 11.4 LK Schweinfurt\n",
    "         * 9.59 8.4 LK Coburg\n",
    "         * 9.32 12.4 LK Traunstein\n",
    "         * 9.31 11.4 LK Weissenburg-Gunzenhausen\n",
    "         * 8.85 11.4 SK Ingolstadt\n",
    "         * 7.47 10.4 SK Amberg\n",
    "         * 5.70 10.4 LK Amberg-Sulzbach\n",
    "\n",
    "    * Counties larger than 30 days (the larger the better):\n",
    "         * 39.99 11.4 LK Weilheim-Schongau\n",
    "         * 36.69 12.4 LK Miesbach\n",
    "         * 38.90 12.4 LK Fueth\n",
    "         * 32.90 12.4 SK Aschaffenburg\n",
    "         * 30.93 12.4 SK Wuezburg\n",
    "         * 31.47 11.4 LK Garmisch-Partenkirchen\n",
    "         * 30.46 11.4 LK Starnberg\n",
    "         * 30.10 12.4 SK Muenchen\n",
    "\n",
    "\n",
    "* Semi-log plots https://github.com/koepferl/COVID19Dahoam/tree/master/plots: \n",
    "\n",
    "     Counties with very low DTs show also no flattening; with high DT almost a horizontal trend.\n",
    "     \n",
    "     \n",
    "* loglog plot https://github.com/koepferl/COVID19Dahoam/blob/master/loglog_Bavaria.pdf: \n",
    "\n",
    "     The number of total cases until a certain day (y axis) is plotted against the number of new cases in the past week for a certain day (x axis). Once there are fewer new infections the curve will drop downwards. Once this drops steep the uncontroled exponential growth is broken. You can see a beginning trend for with high DTs.\n",
    "     Compare with https://www.youtube.com/watch?v=54XLXg4fYsc and https://aatishb.com/covidtrends/\n",
    "\n",
    "### Dataset downloaded 2020-04-15\n",
    "\n",
    "* DT evolution https://github.com/koepferl/COVID19Dahoam/blob/master/DT_Bavaria.pdf: \n",
    "    Most counties have now higher doubling times (average is 27.60 d), isolation works. Stay put.\n",
    "    * Counties smaller than 10 days (the larger the better): \n",
    "\n",
    "         * 9.37 11.4 LK Altoetting\n",
    "         * 9.23 14.4 LK Amberg-Sulzbach\n",
    "         * 9.06 13.4 LK Dillingen a.d.Donau\n",
    "\n",
    "    * Counties larger than 40 days (the larger the better):\n",
    "         * 54.39 14.4 LK Weilheim-Schongau\n",
    "         * 51.60 14.4 LK Fueth\n",
    "         * 49.50 14.4 LK Bamberg\n",
    "         * 45.49 13.4 SK Aschaffenburg\n",
    "         * 45.44 14.4 LK Cham\n",
    "         * 43.54 14.4 LK Fuestenfeldbruck\n",
    "         * 42.68 13.4 LK Miesbach\n",
    "\n",
    "\n",
    "* Semi-log plots https://github.com/koepferl/COVID19Dahoam/tree/master/plots: \n",
    "\n",
    "     Counties with very low DTs show also no flattening; with high DT almost a horizontal trend.\n",
    "     \n",
    "* loglog plot https://github.com/koepferl/COVID19Dahoam/blob/master/loglog_Bavaria.pdf: \n",
    "\n",
    "### Dataset downloaded 2020-04-17\n",
    "\n",
    "* DT evolution https://github.com/koepferl/COVID19Dahoam/blob/master/DT_Bavaria.pdf: \n",
    "    Most counties have now higher doubling times (average is 36.41 d), isolation works. Stay put.\n",
    "    * Counties smaller than 20 days (the larger the better): \n",
    "         * 18.91 16.4 SK Straubing\n",
    "         * 18.54 16.4 LK Bad Kissingen\n",
    "         * 18.43 16.4 LK Altoetting\n",
    "         * 16.82 15.4 SK Hof\n",
    "         * 16.52 15.4 SK Coburg\n",
    "         * 16.50 15.4 LK Rhoen-Grabfeld\n",
    "         * 15.33 16.4 SK Kempten\n",
    "         * 14.04 15.4 SK Amberg\n",
    "         * 12.80 13.4 LK Neumarkt i.d.OPf.\n",
    "         * 12.53 16.4 LK Coburg\n",
    "         *  8.56 15.4 LK Dillingen a.d.Donau\n",
    "    * Counties larger than 60 days (the larger the better):\n",
    "         * 98.68 16.4 LK Miesbach\n",
    "         * 66.00 16.4 LK Lindau\n",
    "         * 65.19 16.4 LK Oberallgaeu\n",
    "         * 65.01 16.4 LK Cham\n",
    "         * 62.22 15.4 LK Weilheim-Schongau\n",
    "         * 61.65 16.4 LK Augsburg\n",
    "         * 60.81 16.4 LK Bamberg\n",
    "         * 60.42 16.4 LK Fueth\n",
    "\n",
    "\n",
    "* Semi-log plots https://github.com/koepferl/COVID19Dahoam/tree/master/plots: \n",
    "\n",
    "     Counties with still very low DTs show also no flattening; with high DT almost a horizontal trend.\n",
    "     \n",
    "* loglog plot https://github.com/koepferl/COVID19Dahoam/blob/master/loglog_Bavaria.pdf\n",
    "     Almost all counties move steep downwards (less infections every day) this means people are recovering faster than new once are becoming infected. This is good, our health system does not break down.\n",
    "     \n",
    "### Dataset downloaded 2020-04-19\n",
    "\n",
    "* DT evolution https://github.com/koepferl/COVID19Dahoam/blob/master/DT_Bavaria.pdf: \n",
    "    Most counties have now higher doubling times, isolation works. Stay put.\n",
    "    \n",
    "    * Bavaria with 36.42 d:\n",
    "    * 5 counties with lowest DTS (the larger the better):\n",
    "        * 11.07 17.4 LK Dillingen a.d.Donau\n",
    "        * 13.47 18.4 LK Coburg\n",
    "        * 16.37 17.4 SK Amberg\n",
    "        * 16.55 17.4 LK Neumarkt i.d.OPf.\n",
    "        * 16.95 18.4 LK Neustadt a.d.Aisch-Bad Windsheim\n",
    "    * 5 counties with highest DTs (the larger the better):\n",
    "        * 71.15 18.4 LK Pfaffenhofen a.d.Ilm\n",
    "        * 72.40 18.4 LK Weissenburg-Gunzenhausen\n",
    "        * 77.91 18.4 LK Weilheim-Schongau\n",
    "        * 92.78 18.4 LK Cham\n",
    "        * 94.13 18.4 LK Miesbach\n",
    "\n",
    "* Semi-log plots https://github.com/koepferl/COVID19Dahoam/tree/master/plots: \n",
    "\n",
    "     Counties with still very low DTs show also no flattening; with high DT almost a horizontal trend.\n",
    "     \n",
    "* loglog plot https://github.com/koepferl/COVID19Dahoam/blob/master/loglog_Bavaria.pdf\n",
    "     Almost all counties move steep downwards (less infections every day) this means people are recovering faster than new once are becoming infected. This is good, our health system does not break down.\n",
    "\n",
    "### Dataset downloaded 2020-04-21\n",
    "\n",
    "* DT evolution https://github.com/koepferl/COVID19Dahoam/blob/master/DT_Bavaria.pdf: \n",
    "    Most counties have now higher doubling times, isolation works. Stay put.\n",
    "    \n",
    "    * Bavaria with 39.20 d:\n",
    "    * 5 counties with lowest DTS (the larger the better):\n",
    "        * 13.35 19.4 LK Neustadt a.d.Aisch-Bad Windsheim\n",
    "        * 13.47 18.4 LK Coburg\n",
    "        * 16.37 17.4 SK Amberg\n",
    "        * 17.24 18.4 SK Coburg\n",
    "        * 18.30 20.4 SK Straubing\n",
    "    * 5 counties with highest DTs (the larger the better):\n",
    "        * 80.64 20.4 LK Lindau\n",
    "        * 82.61 20.4 LK Landsberg a.Lech\n",
    "        * 93.78 20.4 LK Augsburg\n",
    "        * 98.49 19.4 LK Cham\n",
    "        * 104.10 19.4 LK Miesbach\n",
    "\n",
    "* Semi-log plots https://github.com/koepferl/COVID19Dahoam/tree/master/plots: \n",
    "\n",
    "     Counties with still very low DTs show also no flattening; with high DT almost a horizontal trend.\n",
    "     \n",
    "* loglog plot https://github.com/koepferl/COVID19Dahoam/blob/master/loglog_Bavaria.pdf\n",
    "     Almost all counties move steep downwards (less infections every day) this means people are recovering faster than new once are becoming infected. This is good, our health system does not break down.\n",
    "\n",
    "### Dataset downloaded 2020-04-23\n",
    "\n",
    "* DT evolution https://github.com/koepferl/COVID19Dahoam/blob/master/DT_Bavaria.pdf: \n",
    "    Most counties have now higher doubling times, isolation works. Stay put.\n",
    "    \n",
    "    * Bavaria with 50.65 d:\n",
    "    * 5 counties with lowest DTS (the larger the better):\n",
    "        * 14.59 21.4 LK Neustadt a.d.Aisch-Bad Windsheim\n",
    "        * 21.54 21.4 LK Kitzingen\n",
    "        * 21.72 21.4 SK Coburg\n",
    "        * 21.82 22.4 LK Kronach\n",
    "        * 22.22 21.4 LK Neumarkt i.d.OPf.\n",
    "    * 5 counties with highest DTs (the larger the better):\n",
    "        * 98.77 19.4 LK Cham\n",
    "        * 99.51 22.4 LK Freising\n",
    "        * 109.27 21.4 LK Weilheim-Schongau\n",
    "        * 120.56 21.4 LK Miesbach\n",
    "        * 131.96 22.4 LK Starnberg\n",
    "\n",
    "\n",
    "* Semi-log plots https://github.com/koepferl/COVID19Dahoam/tree/master/plots: \n",
    "\n",
    "     Counties with still very low DTs show also no flattening; with high DT almost a horizontal trend.\n",
    "     \n",
    "     Quite interesting. For some counties there are small \"easter dents\" roughly one week after easter. Apparently the disciplin was not as high around easter. I am worried about now, were even more is possible. I hope it does not get too bad, although I am expecting it - actually.\n",
    "\n",
    "     \n",
    "* loglog plot https://github.com/koepferl/COVID19Dahoam/blob/master/loglog_Bavaria.pdf\n",
    "     Almost all counties move steep downwards (less infections every day) this means people are recovering faster than new once are becoming infected. This is good, our health system does not break down.\n",
    "\n",
    "\n",
    "### Dataset downloaded 2020-04-26\n",
    "\n",
    "* DT evolution https://github.com/koepferl/COVID19Dahoam/blob/master/DT_Bavaria.pdf: \n",
    "    Most counties have now higher doubling times, isolation works. Stay put.\n",
    "    \n",
    "    * Bavaria with 57.55 d:\n",
    "    * 5 counties with lowest DTS (the larger the better):\n",
    "        *  12.08 25.4 LK Kitzingen\n",
    "        *  17.82 22.4 LK Neustadt a.d.Aisch-Bad Windsheim\n",
    "        *  19.39 25.4 LK Rhoen-Grabfeld\n",
    "        *  20.80 25.4 LK Straubing-Bogen\n",
    "        *  21.67 25.4 SK Rosenheim\n",
    "    * 5 counties with highest DTs (the larger the better):\n",
    "        * 142.42 24.4 LK Weilheim-Schongau\n",
    "        * 143.91 25.4 LK Tirschenreuth\n",
    "        * 156.10 25.4 LK Starnberg\n",
    "        * 168.22 25.4 LK Rottal-Inn\n",
    "        * 206.06 25.4 LK Miesbach\n",
    "\n",
    "* Semi-log plots https://github.com/koepferl/COVID19Dahoam/tree/master/plots: \n",
    "\n",
    "     Counties with still very low DTs show also no flattening; with high DT almost a horizontal trend.\n",
    "     \n",
    "     Quite interesting. For some counties there are small \"easter dents\" roughly one week after easter. Apparently the disciplin was not as high around easter. I am worried about now, were even more is possible. I hope it does not get too bad, although I am expecting it - actually.\n",
    "\n",
    "     \n",
    "* loglog plot https://github.com/koepferl/COVID19Dahoam/blob/master/loglog_Bavaria.pdf\n",
    "     Almost all counties move steep downwards (less infections every day) this means people are recovering faster than new once are becoming infected. This is good, our health system does not break down.\n",
    "\n",
    "\n",
    "### Dataset downloaded 2020-04-28\n",
    "\n",
    "* DT evolution https://github.com/koepferl/COVID19Dahoam/blob/master/DT_Bavaria.pdf: \n",
    "    Most counties have now higher doubling times, isolation works. Stay put.\n",
    "    \n",
    "    * Bavaria with 67.58 d:\n",
    "    * 5 counties with lowest DTS (the larger the better):\n",
    "        *  15.26 27.4 LK Kitzingen\n",
    "        *  21.67 25.4 SK Rosenheim\n",
    "        *  21.93 27.4 LK Rhoen-Grabfeld\n",
    "        *  22.24 27.4 LK Passau\n",
    "        *  23.20 26.4 SK Ansbach\n",
    "    * 5 counties with highest DTs (the larger the better):\n",
    "        * 162.99 27.4 LK Tirschenreuth\n",
    "        * 177.11 27.4 LK Weilheim-Schongau\n",
    "        * 187.67 27.4 LK Miesbach\n",
    "        * 192.55 27.4 LK Rottal-Inn\n",
    "        * 206.24 27.4 LK Cham\n",
    "\n",
    "* Semi-log plots https://github.com/koepferl/COVID19Dahoam/tree/master/plots: \n",
    "\n",
    "     Counties with still very low DTs show also no flattening; with high DT almost a horizontal trend.\n",
    "     \n",
    "     Quite interesting. For some counties there are small \"easter dents\" roughly one week after easter. Apparently the disciplin was not as high around easter. I am worried about now, were even more is possible. I hope it does not get too bad, although I am expecting it - actually.\n",
    "\n",
    "     \n",
    "* loglog plot https://github.com/koepferl/COVID19Dahoam/blob/master/loglog_Bavaria.pdf\n",
    "     Almost all counties move steep downwards (less infections every day) this means people are recovering faster than new once are becoming infected. This is good, our health system does not break down.\n",
    "\n",
    "### Dataset downloaded 2020-05-01\n",
    "\n",
    "* DT evolution https://github.com/koepferl/COVID19Dahoam/blob/master/DT_Bavaria.pdf: \n",
    "    Most counties have now higher doubling times, isolation works. Stay put.\n",
    "    \n",
    "    * Bavaria with 96.10 d:\n",
    "    * 5 counties with lowest DTS (the larger the better):\n",
    "        *  17.73 30.4 LK Kitzingen\n",
    "        *  27.24 24.4 SK Coburg\n",
    "        *  28.90 27.4 LK Neumarkt i.d.OPf.\n",
    "        *  29.21 30.4 LK Passau\n",
    "        *  30.58 30.4 LK Rhoen-Grabfeld\n",
    "    * 5 counties with highest DTs (the larger the better):\n",
    "        * 217.76 28.4 LK Lindau\n",
    "        * 223.33 29.4 LK Ostallgaeu\n",
    "        * 223.42 30.4 LK Tirschenreuth\n",
    "        * 247.88 30.4 LK Rottal-Inn\n",
    "        * 282.06 30.4 SK Ingolstadt\n",
    "\n",
    "* Semi-log plots https://github.com/koepferl/COVID19Dahoam/tree/master/plots: \n",
    "\n",
    "     Counties with still very low DTs show also no flattening; with high DT almost a horizontal trend.\n",
    "     \n",
    "* loglog plot https://github.com/koepferl/COVID19Dahoam/blob/master/loglog_Bavaria.pdf\n",
    "     Almost all counties move steep downwards (less infections every day) this means people are recovering faster than new once are becoming infected. This is good, our health system does not break down.\n",
    "     \n",
    "### Dataset downloaded 2020-05-04\n",
    "\n",
    "* THERE IS NO GLORY IN PREVENTION BUT STILL LET'S TRY.\n",
    "\n",
    "\n",
    "* DT evolution https://github.com/koepferl/COVID19Dahoam/blob/master/DT_Bavaria.pdf: \n",
    "    Most counties have now higher doubling times, isolation works. Stay put.\n",
    "    \n",
    "    * Bavaria with 122.17 d:\n",
    "    * 5 counties with lowest DTS (the larger the better):\n",
    "        *  23.92 03.5 LK Kitzingen\n",
    "        *  34.86 01.5 LK Kulmbach\n",
    "        *  35.11 30.4 LK Dillingen a.d.Donau\n",
    "        *  41.09 03.5 LK Coburg\n",
    "        *  51.72 23.4 SK Kempten\n",
    "    * 5 counties with highest DTs (the larger the better):\n",
    "        * 233.92 02.5 LK Starnberg\n",
    "        * 272.11 03.5 LK Rottal-Inn\n",
    "        * 279.70 02.5 LK Lindau\n",
    "        * 300.66 02.5 LK Nuenberger Land\n",
    "        * 322.21 02.5 LK Weilheim-Schongau\n",
    "\n",
    "* Semi-log plots https://github.com/koepferl/COVID19Dahoam/tree/master/plots: \n",
    "\n",
    "     Counties with still very low DTs show also no flattening; with high DT almost a horizontal trend.\n",
    "     \n",
    "* loglog plot https://github.com/koepferl/COVID19Dahoam/blob/master/loglog_Bavaria.pdf\n",
    "     Almost all counties move steep downwards (less infections every day) this means people are recovering faster than new once are becoming infected. This is good, our health system does not break down.\n",
    "\n",
    "* New: In some counties now there a again more cases coming in, this causes the slope to steepen in the semilog plot, the DTs get shorter again and in the log-log plot the droping trend is revercing. In the expert plot we can see that also the reproduction time is goint up once the DT drops. The end of the loc-down is now visible.\n",
    "     \n",
    "More interpretation follows tomorrow.\n",
    "\n",
    "### Dataset downloaded 2020-05-07\n",
    "\n",
    "* THERE IS NO GLORY IN PREVENTION BUT STILL LET'S TRY.\n",
    "\n",
    "\n",
    "* DT evolution https://github.com/koepferl/COVID19Dahoam/blob/master/DT_Bavaria.pdf: \n",
    "    Most counties have now higher doubling times, isolation works. Stay put.\n",
    "    \n",
    "    * Bavaria with 122.17 d:\n",
    "\n",
    "* Semi-log plots https://github.com/koepferl/COVID19Dahoam/tree/master/plots: \n",
    "\n",
    "     Counties with still very low DTs show also no flattening; with high DT almost a horizontal trend.\n",
    "     \n",
    "* loglog plot https://github.com/koepferl/COVID19Dahoam/blob/master/loglog_Bavaria.pdf\n",
    "     Almost all counties move steep downwards (less infections every day) this means people are recovering faster than new once are becoming infected. This is good, our health system does not break down.\n",
    "\n",
    "* expert plots: In some counties now there a again more cases coming in, this causes the slope to steepen in the semilog plot, the DTs get shorter again and in the log-log plot the droping trend is revercing. In the expert plot we can see that also the reproduction time is goint up once the DT drops. The end of the loc-down is now visible.\n",
    "     \n",
    "### Dataset downloaded 2020-05-09\n",
    "\n",
    "* THERE IS NO GLORY IN PREVENTION BUT STILL LET'S TRY.\n",
    "\n",
    "\n",
    "* DT evolution https://github.com/koepferl/COVID19Dahoam/blob/master/DT_Bavaria.pdf: \n",
    "    Changed y axis to log now. Most counties have now higher doubling times, isolation works. Stay put.\n",
    "    \n",
    "    * Bavaria with 179.68 d:\n",
    "    * 5 counties with lowest DTS (the larger the better):\n",
    "        *  41.09 3.5 LK Coburg\n",
    "        *  46.46 7.5 LK Neuburg-Schrobenhausen\n",
    "        *  50.97 2.5 SK Schweinfurt\n",
    "        *  51.22 6.5 LK Kitzingen\n",
    "        *  51.72 23.4 SK Kempten\n",
    "    * 5 counties with highest DTs (the larger the better):\n",
    "        * 397.80 7.5 LK Schwandorf\n",
    "        * 398.74 5.5 LK Ostallgaeu\n",
    "        * 424.42 7.5 LK Weilheim-Schongau\n",
    "        * 473.93 6.5 SK Wuezburg\n",
    "        * 526.26 6.5 LK Tirschenreuth\n",
    "\n",
    "* Semi-log plots https://github.com/koepferl/COVID19Dahoam/tree/master/plots: \n",
    "\n",
    "     Counties with still very low DTs show also no flattening; with high DT almost a horizontal trend.\n",
    "     \n",
    "* loglog plot https://github.com/koepferl/COVID19Dahoam/blob/master/loglog_Bavaria.pdf\n",
    "     Almost all counties move steep downwards (less infections every day) this means people are recovering faster than new once are becoming infected. This is good, our health system does not break down.\n",
    "\n",
    "* expert plots: In some counties now there a again more cases coming in, this causes the slope to steepen in the semilog plot, the DTs get shorter again and in the log-log plot the droping trend is revercing. In the expert plot we can see that also the reproduction time is goint up once the DT drops. The end of the loc-down is now visible.\n",
    "\n",
    "### Dataset downloaded 2020-05-13\n",
    "\n",
    "* THERE IS NO GLORY IN PREVENTION BUT STILL LET'S TRY.\n",
    "\n",
    "\n",
    "* DT evolution https://github.com/koepferl/COVID19Dahoam/blob/master/DT_Bavaria.pdf: \n",
    "    Changed y axis to log now. Most counties have now higher doubling times, isolation works. Stay put.\n",
    "    \n",
    "    * Bavaria with 187.17 d:\n",
    "    * 5 counties with lowest DTS (the larger the better):\n",
    "        *  40.16 12.5 LK Regen\n",
    "        *  50.97 02.5 SK Schweinfurt\n",
    "        *  51.72 23.4 SK Kempten\n",
    "        *  56.30 10.5 LK Neuburg-Schrobenhausen\n",
    "        *  61.56 07.5 SK Coburg\n",
    "    * 5 counties with highest DTs (the larger the better):\n",
    "        * 539.14 12.5 LK Roth\n",
    "        * 553.20 12.5 LK Weilheim-Schongau\n",
    "        * 617.51 09.5 LK Ostallgaeu\n",
    "        * 716.90 12.5 SK Wuezburg\n",
    "        * 936.20 12.5 LK Tirschenreuth\n",
    "\n",
    "* Semi-log plots https://github.com/koepferl/COVID19Dahoam/tree/master/plots: \n",
    "\n",
    "     Counties with still very low DTs show also no flattening; with high DT almost a horizontal trend.\n",
    "     \n",
    "* loglog plot https://github.com/koepferl/COVID19Dahoam/blob/master/loglog_Bavaria.pdf\n",
    "     Almost all counties move steep downwards (less infections every day) this means people are recovering faster than new once are becoming infected. This is good, our health system does not break down.\n",
    "\n",
    "* expert plots: In some counties now there a again more cases coming in, this causes the slope to steepen in the semilog plot, the DTs get shorter again and in the log-log plot the droping trend is revercing. In the expert plot we can see that also the reproduction time is goint up once the DT drops. The end of the loc-down is now visible.\n",
    "\n",
    "### Dataset downloaded 2020-05-15\n",
    "\n",
    "* THERE IS NO GLORY IN PREVENTION BUT STILL LET'S TRY.\n",
    "\n",
    "\n",
    "* DT evolution https://github.com/koepferl/COVID19Dahoam/blob/master/DT_Bavaria.pdf: \n",
    "    Changed y axis to log now. Most counties have now higher doubling times, isolation works. Stay put.\n",
    "    \n",
    "    * Bavaria with 208.37 d:\n",
    "    * 5 counties with lowest DTS (the larger the better):\n",
    "        *  38.95 13.5 LK Coburg\n",
    "        *  41.74 14.5 LK Regen\n",
    "        *  50.97 2.5 SK Schweinfurt\n",
    "        *  51.72 23.4 SK Kempten\n",
    "        *  59.07 13.5 SK Coburg\n",
    "    * 5 counties with highest DTs (the larger the better):\n",
    "        * 555.90 14.5 LK Cham\n",
    "        * 625.96 13.5 LK Lindau\n",
    "        * 698.62 14.5 LK Ostallgaeu\n",
    "        * 787.77 13.5 SK Wuezburg\n",
    "        * 937.88 12.5 LK Tirschenreuth\n",
    "\n",
    "* Semi-log plots https://github.com/koepferl/COVID19Dahoam/tree/master/plots: \n",
    "\n",
    "     Counties with still very low DTs show also no flattening; with high DT almost a horizontal trend.\n",
    "     \n",
    "* loglog plot https://github.com/koepferl/COVID19Dahoam/blob/master/loglog_Bavaria.pdf\n",
    "     Almost all counties move steep downwards (less infections every day) this means people are recovering faster than new once are becoming infected. This is good, our health system does not break down.\n",
    "\n",
    "* expert plots: In some counties now there a again more cases coming in, this causes the slope to steepen in the semilog plot, the DTs get shorter again and in the log-log plot the droping trend is revercing. In the expert plot we can see that also the reproduction time is goint up once the DT drops. The end of the loc-down is now visible.\n",
    "\n",
    "### Dataset downloaded 2020-05-18\n",
    "\n",
    "* THERE IS NO GLORY IN PREVENTION BUT STILL LET'S TRY.\n",
    "\n",
    "\n",
    "* DT evolution https://github.com/koepferl/COVID19Dahoam/blob/master/DT_Bavaria.pdf: \n",
    "    Changed y axis to log now. Most counties have now higher doubling times, isolation works. Stay put.\n",
    "    \n",
    "    * Bavaria with 212.3 d:\n",
    "    * 5 counties with lowest DTS (the larger the better):\n",
    "        *  21.04 16.5 LK Coburg\n",
    "        *  41.74 14.5 LK Regen\n",
    "        *  48.39 15.5 LK Straubing-Bogen\n",
    "        *  50.97 2.5 SK Schweinfurt\n",
    "        *  51.72 23.4 SK Kempten\n",
    "    * 5 counties with highest DTs (the larger the better):\n",
    "        * 625.96 13.5 LK Lindau\n",
    "        * 645.49 14.5 LK Roth\n",
    "        * 756.17 15.5 LK Ostallgaeu\n",
    "        * 787.77 13.5 SK Wuezburg\n",
    "        * 1102.61 15.5 LK Tirschenreuth\n",
    "\n",
    "* Semi-log plots https://github.com/koepferl/COVID19Dahoam/tree/master/plots: \n",
    "\n",
    "     Counties with still very low DTs show also no flattening; with high DT almost a horizontal trend.\n",
    "     \n",
    "* loglog plot https://github.com/koepferl/COVID19Dahoam/blob/master/loglog_Bavaria.pdf\n",
    "     Almost all counties move steep downwards (less infections every day) this means people are recovering faster than new once are becoming infected. This is good, our health system does not break down.\n",
    "\n",
    "* expert plots: In some counties now there a again more cases coming in, this causes the slope to steepen in the semilog plot, the DTs get shorter again and in the log-log plot the droping trend is revercing. In the expert plot we can see that also the reproduction time is goint up once the DT drops. The end of the loc-down is now visible.\n",
    "\n",
    "### Dataset downloaded 2020-05-23\n",
    "\n",
    "* THERE IS NO GLORY IN PREVENTION BUT STILL LET'S TRY.\n",
    "\n",
    "\n",
    "* DT evolution https://github.com/koepferl/COVID19Dahoam/blob/master/DT_Bavaria.pdf: \n",
    "    Changed y axis to log now. Most counties have now higher doubling times, isolation works. Stay put.\n",
    "    \n",
    "    * Bavaria with 212.3 d:\n",
    "    * 5 counties with lowest DTS (the larger the better):\n",
    "        *  32.56 22.5 LK Coburg\n",
    "        *  36.40 22.5 SK Regensburg\n",
    "        *  41.66 22.5 SK Coburg\n",
    "        *  48.51 16.5 LK Regen\n",
    "        *  48.63 21.5 LK Erlangen-Hoechstadt\n",
    "    * 5 counties with highest DTs (the larger the better):\n",
    "        * 680.21 22.5 LK Muehldorf a.Inn\n",
    "        * 690.42 22.5 LK Kelheim\n",
    "        * 730.47 18.5 LK Ostallgaeu\n",
    "        * 748.32 22.5 LK Tirschenreuth\n",
    "        * 887.32 16.5 SK Wuezburg\n",
    "\n",
    "* Semi-log plots https://github.com/koepferl/COVID19Dahoam/tree/master/plots: \n",
    "\n",
    "     Counties with still very low DTs show also no flattening; with high DT almost a horizontal trend.\n",
    "     \n",
    "* loglog plot https://github.com/koepferl/COVID19Dahoam/blob/master/loglog_Bavaria.pdf\n",
    "     Almost all counties move steep downwards (less infections every day) this means people are recovering faster than new once are becoming infected. This is good, our health system does not break down.\n",
    "\n",
    "* expert plots: In some counties now there a again more cases coming in, this causes the slope to steepen in the semilog plot, the DTs get shorter again and in the log-log plot the droping trend is revercing. In the expert plot we can see that also the reproduction time is goint up once the DT drops. The end of the loc-down is now visible.\n",
    "\n",
    "### Dataset downloaded 2020-05-27\n",
    "\n",
    "* THERE IS NO GLORY IN PREVENTION BUT STILL LET'S TRY.\n",
    "\n",
    "\n",
    "* DT evolution https://github.com/koepferl/COVID19Dahoam/blob/master/DT_Bavaria.pdf: \n",
    "    Changed y axis to log now. Most counties have now higher doubling times, isolation works. Stay put.\n",
    "    \n",
    "    * Bavaria with 298.54 d:\n",
    "    * 5 counties with lowest DTS (the larger the better):\n",
    "        *  23.37 25.5 SK Regensburg\n",
    "        *  32.70 25.5 SK Coburg\n",
    "        *  46.24 16.5 LK Regen\n",
    "        *  46.50 23.5 LK Lichtenfels\n",
    "        *  48.63 21.5 LK Erlangen-Hoechstadt\n",
    "    * 5 counties with highest DTs (the larger the better):\n",
    "        * 819.71 21.5 LK Ostallgaeu\n",
    "        * 821.26 25.5 LK Altoetting\n",
    "        * 822.05 23.5 LK Wunsiedel i.Fichtelgebirge\n",
    "        * 887.32 16.5 SK Wuezburg\n",
    "        * 1219.71 25.5 LK Landshut\n",
    "\n",
    "* Semi-log plots https://github.com/koepferl/COVID19Dahoam/tree/master/plots: \n",
    "\n",
    "     Counties with still very low DTs show also no flattening; with high DT almost a horizontal trend.\n",
    "     \n",
    "* loglog plot https://github.com/koepferl/COVID19Dahoam/blob/master/loglog_Bavaria.pdf\n",
    "     Almost all counties move steep downwards (less infections every day) this means people are recovering faster than new once are becoming infected. This is good, our health system does not break down.\n",
    "\n",
    "* expert plots: In some counties now there a again more cases coming in, this causes the slope to steepen in the semilog plot, the DTs get shorter again and in the log-log plot the droping trend is revercing. In the expert plot we can see that also the reproduction time is goint up once the DT drops. The end of the loc-down is now visible.\n",
    "\n",
    "### Dataset downloaded 2020-05-31\n",
    "\n",
    "* THERE IS NO GLORY IN PREVENTION BUT STILL LET'S TRY.\n",
    "\n",
    "\n",
    "* DT evolution https://github.com/koepferl/COVID19Dahoam/blob/master/DT_Bavaria.pdf: \n",
    "    Changed y axis to log now. Most counties have now higher doubling times, isolation works. Stay put.\n",
    "    \n",
    "    * Bavaria with 339.68 d:\n",
    "    * 5 counties with lowest DTS (the larger the better):\n",
    "        *  36.62 29.5 SK Regensburg\n",
    "        *  38.13 28.5 SK Coburg\n",
    "        *  39.09 29.5 LK Coburg\n",
    "        *  60.78 30.5 LK Lichtenfels\n",
    "        * 114.50 3.5 SK Memmingen\n",
    "    * 5 counties with highest DTs (the larger the better):\n",
    "        * 930.65 28.5 LK Wunsiedel i.Fichtelgebirge\n",
    "        * 958.20 28.5 LK Muehldorf a.Inn\n",
    "        * 1094.84 26.5 LK Ostallgaeu\n",
    "        * 1102.67 29.5 LK Altoetting\n",
    "        * 1202.25 27.5 SK Wuezburg\n",
    "\n",
    "* Semi-log plots https://github.com/koepferl/COVID19Dahoam/tree/master/plots: \n",
    "\n",
    "     Counties with still very low DTs show also no flattening; with high DT almost a horizontal trend.\n",
    "     \n",
    "* loglog plot https://github.com/koepferl/COVID19Dahoam/blob/master/loglog_Bavaria.pdf\n",
    "     Almost all counties move steep downwards (less infections every day) this means people are recovering faster than new once are becoming infected. This is good, our health system does not break down.\n",
    "\n",
    "* expert plots: In some counties now there a again more cases coming in, this causes the slope to steepen in the semilog plot, the DTs get shorter again and in the log-log plot the droping trend is revercing. In the expert plot we can see that also the reproduction time is goint up once the DT drops. The end of the loc-down is now visible.\n",
    "\n",
    "### Dataset downloaded 2020-06-09\n",
    "\n",
    "* THERE IS NO GLORY IN PREVENTION BUT STILL LET'S TRY.\n",
    "\n",
    "\n",
    "* DT evolution https://github.com/koepferl/COVID19Dahoam/blob/master/DT_Bavaria.pdf: \n",
    "    Changed y axis to log now. Most counties have now higher doubling times, isolation works. Stay put.\n",
    "    \n",
    "    * Bavaria with 699.3 d:\n",
    "    * 5 counties with lowest DTS (the larger the better):\n",
    "        *  62.11 39.5 LK Coburg\n",
    "        *  78.22 38.5 SK Coburg\n",
    "        * 108.08 37.5 LK Lichtenfels\n",
    "        * 114.50 03.5 SK Memmingen\n",
    "        * 121.87 28.5 LK Hof\n",
    "    * 5 counties with highest DTs (the larger the better):\n",
    "        * 1094.84 26.5 LK Ostallgaeu\n",
    "        * 1373.69 35.5 LK Tirschenreuth\n",
    "        * 1401.59 39.5 LK Muehldorf a.Inn\n",
    "        * 1429.39 38.5 LK Nuenberger Land\n",
    "        * 1700.70 36.5 SK Wuezburg\n",
    "\n",
    "* Semi-log plots https://github.com/koepferl/COVID19Dahoam/tree/master/plots: \n",
    "\n",
    "     Counties with still very low DTs show also no flattening; with high DT almost a horizontal trend.\n",
    "     \n",
    "* loglog plot https://github.com/koepferl/COVID19Dahoam/blob/master/loglog_Bavaria.pdf\n",
    "     Almost all counties move steep downwards (less infections every day) this means people are recovering faster than new once are becoming infected. This is good, our health system does not break down.\n",
    "\n",
    "* expert plots: In some counties now there a again more cases coming in, this causes the slope to steepen in the semilog plot, the DTs get shorter again and in the log-log plot the droping trend is revercing. In the expert plot we can see that also the reproduction time is goint up once the DT drops. The end of the loc-down is now visible."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "More interpretation follows soon.\n",
    "\n",
    "\n",
    "\n",
    "## Recommendation\n",
    "Social distancing is key to slow down the case numbers further to not overburden our local health system. Show solidarity through and from the distance. THERE IS NO GLORY IN PREVENTION BUT STILL LET'S TRY.\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}