{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Analyse des données sur la varicelle" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import os\n", "import urllib.request\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import pandas as pd\n", "import isoweek\n", "\n", "%matplotlib inline\n", "plt.style.use('ggplot')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Chargement des données" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Nous utilisons pour cette analyse les données de surveillance continue du **Réseau Sentinelles** en France. Nous récupérons depuis la base de données en ligne le fichier au format csv contenant les données complètes sur **l'incidence hebdomadaire de la varicelle en France métropolitaine** (depuis 1991 jusqu'à la semaine la plus récente disponible). \n", "\n", "Nous avons téléchargé le fichier le 2025/08/27 depuis l'URL suivante : https://www.sentiweb.fr/datasets/all/inc-7-PAY.csv.\n", "Le code qui suit permet de récupérer le fichier en le téléchargeant directement depuis l'URL uniquement si le fichier n'est pas déjà présent localement. " ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
020253471856953617306FRFrance
1202533736277186536519FRFrance
22025327238404809408FRFrance
3202531757030130829020FRFrance
42025307710235901061411616FRFrance
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" ], "text/plain": [ " week indicator inc inc_low inc_up inc100 inc100_low inc100_up \\\n", "0 202534 7 1856 95 3617 3 0 6 \n", "1 202533 7 3627 718 6536 5 1 9 \n", "2 202532 7 2384 0 4809 4 0 8 \n", "3 202531 7 5703 0 13082 9 0 20 \n", "4 202530 7 7102 3590 10614 11 6 16 \n", "\n", " geo_insee geo_name \n", "0 FR France \n", "1 FR France \n", "2 FR France \n", "3 FR France \n", "4 FR France " ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data_file = \"inc-7-PAY.csv\"\n", "data_url = \"https://www.sentiweb.fr/datasets/all/inc-7-PAY.csv\"\n", "\n", "if not os.path.exists(data_file):\n", " urllib.request.urlretrieve(data_url, data_file)\n", " \n", "data = pd.read_csv(\"inc-7-PAY.csv\", skiprows = 1)\n", "data.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Voici l'explication des colonnes données [sur le site du Réseau Sentinelles](https://ns.sentiweb.fr/incidence/json-schema-v1.json) :\n", "\n", "| Nom de colonne | Libellé de colonne |\n", "|----------------|-----------------------------------------------------------------------------------------------------------------------------------|\n", "| week | Semaine calendaire (ISO 8601) |\n", "| indicator | Code de l'indicateur de surveillance |\n", "| inc | Estimation de l'incidence de consultations en nombre de cas |\n", "| inc_low | Estimation de la borne inférieure de l'IC95% du nombre de cas de consultation |\n", "| inc_up | Estimation de la borne supérieure de l'IC95% du nombre de cas de consultation |\n", "| inc100 | Estimation du taux d'incidence du nombre de cas de consultation (en cas pour 100,000 habitants) |\n", "| inc100_low | Estimation de la borne inférieure de l'IC95% du taux d'incidence du nombre de cas de consultation (en cas pour 100,000 habitants) |\n", "| inc100_up | Estimation de la borne supérieure de l'IC95% du taux d'incidence du nombre de cas de consultation (en cas pour 100,000 habitants) |\n", "| geo_insee | Code de la zone géographique concernée (Code INSEE) http://www.insee.fr/fr/methodes/nomenclatures/cog/ |\n", "| geo_name | Libellé de la zone géographique (ce libellé peut être modifié sans préavis) |\n", "\n", "La première ligne étant un commentaire, nous avons indiqué à Pandas de l'ignorer dans notre code à l'aide de l'argument `skiprows = 1`." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Contrôle des données" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Nous vérifions dans un premier temps s'il existe des données manquantes. Il semblerait qu'aucune ligne n'ait de données manquantes." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "week False\n", "indicator False\n", "inc False\n", "inc_low False\n", "inc_up False\n", "inc100 False\n", "inc100_low False\n", "inc100_up False\n", "geo_insee False\n", "geo_name False\n", "dtype: bool" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data[data.isnull().any(axis = 1)]\n", "data.isnull().any()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Comme dans l'exemple du syndrome grippal, nous avons besoin de convertir les dates en un format compréhensible par Pandas." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_nameperiod
020253471856953617306FRFrance2025-08-18/2025-08-24
1202533736277186536519FRFrance2025-08-11/2025-08-17
22025327238404809408FRFrance2025-08-04/2025-08-10
3202531757030130829020FRFrance2025-07-28/2025-08-03
42025307710235901061411616FRFrance2025-07-21/2025-07-27
\n", "
" ], "text/plain": [ " week indicator inc inc_low inc_up inc100 inc100_low inc100_up \\\n", "0 202534 7 1856 95 3617 3 0 6 \n", "1 202533 7 3627 718 6536 5 1 9 \n", "2 202532 7 2384 0 4809 4 0 8 \n", "3 202531 7 5703 0 13082 9 0 20 \n", "4 202530 7 7102 3590 10614 11 6 16 \n", "\n", " geo_insee geo_name period \n", "0 FR France 2025-08-18/2025-08-24 \n", "1 FR France 2025-08-11/2025-08-17 \n", "2 FR France 2025-08-04/2025-08-10 \n", "3 FR France 2025-07-28/2025-08-03 \n", "4 FR France 2025-07-21/2025-07-27 " ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ " def convert_week(year_and_week_int):\n", " year_and_week_str = str(year_and_week_int)\n", " year = int(year_and_week_str[:4])\n", " week = int(year_and_week_str[4:])\n", " w = isoweek.Week(year, week)\n", " return pd.Period(w.day(0), 'W')\n", "\n", "data['period'] = [convert_week(yw) for yw in data['week']]\n", "data.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Nous définissons ici aussi les périodes d’observation comme index du jeu de données pour en faire une suite chronologique, et pouvoir trier les points par période dans l'ordre chronologique." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
period
1990-12-03/1990-12-091990497114302610205FRFrance
1990-12-10/1990-12-16199050711079666015498201228FRFrance
1990-12-17/1990-12-231990517190801380724353342543FRFrance
1990-12-24/1990-12-301990527193751329525455342345FRFrance
1990-12-31/1991-01-061991017155651027120859271836FRFrance
\n", "
" ], "text/plain": [ " week indicator inc inc_low inc_up inc100 \\\n", "period \n", "1990-12-03/1990-12-09 199049 7 1143 0 2610 2 \n", "1990-12-10/1990-12-16 199050 7 11079 6660 15498 20 \n", "1990-12-17/1990-12-23 199051 7 19080 13807 24353 34 \n", "1990-12-24/1990-12-30 199052 7 19375 13295 25455 34 \n", "1990-12-31/1991-01-06 199101 7 15565 10271 20859 27 \n", "\n", " inc100_low inc100_up geo_insee geo_name \n", "period \n", "1990-12-03/1990-12-09 0 5 FR France \n", "1990-12-10/1990-12-16 12 28 FR France \n", "1990-12-17/1990-12-23 25 43 FR France \n", "1990-12-24/1990-12-30 23 45 FR France \n", "1990-12-31/1991-01-06 18 36 FR France " ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sorted_data = data.set_index('period').sort_index()\n", "sorted_data.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Il nous reste à vérifier la cohérence des données au niveau des périodes définies. Entre la fin d’une période et le début de la période qui suit, la différence temporelle doit être très proche de zéro. Ici rien à signaler !" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "periods = sorted_data.index\n", "for p1, p2 in zip(periods[:-1], periods[1:]):\n", " delta = p2.to_timestamp() - p1.end_time\n", " if delta > pd.Timedelta('1s'):\n", " print(p1, p2)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Visualisation des données" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "On peut maintenant regarder le taux d'incidence sur toute la période mesurée." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "image/png": 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I7CtYvP7l993VoIprKLv1aXO1k+MonXkK+JYna2jABcoDLLdvYBkilc2BUroPgJcAuFMknUopvZ9S+i1K6SqRtg7AM1KxLSJtnfitpkfKMMbmAewCMJCGtgVDPWwOy2XVpOsKbruZEglqJf7wvUB4clqNksOK3Ufw8L3Ac8/Cv/7qhW13uXwDdQDftkVxB28OOHsrUUq7AXwfwPsZY6OU0osAnI1gFjgbwBcBvAuGdaQlHQn3ZBo2IlBLgTGGQqGgpTWfzxvvpcVUdzdkBcHAwGp4HV1V1bUjlwMHsKqvD3mJPpne7SKtu6sbnXV6BlfMPnwf+PQU2v7ySGu+kN6xjg5MAujq6kaXoLXkzyEISEFiz6S+k9H2dkwB6O7WP+tQPg/V4VGuY/sFnyz/7m7Jl99TPpfDQEL/xq4HBkA8+1ppu3KtG2NFz0NJc59zjh2aOrsffwDt/+81AICJri6MG9ouDKwGaW2z0meCqf8BYKqzE6MA2ju70FfFeHP91tTvqKO9HT0LPL6B+s4N9QCfmcGOd78HbUe8Av0fj2vTF5NeJ+ZAKW1BwBi+yxj7AQAwxrZL9y8BcL243AJgL6n4egBbRfp6TbpcZgulNA+gD8CQSgdj7GIAF4tLXizq4+IUCgWY7qWFPx79XAeLgyAdVYRGAMDF5DNc3AnS2lFO19E7Pj6GyTo9gytK/xnopXOXXGfNF9LrTwX9MDE5gSlBKx8eDjJxHnsm9dqfDozI4+Pj2mctaXzhTe919Oc3lX/Pz89H8un6N369E8TLIQ10tJTm57X3TZLJrs//J8ZFf/sT5oB8xWKxauagoyeEPxK8r+n778bs734Dsu8Bqep0/db8sbHI9dTkBGYWeHwD9Z0b6gEugjDO3H+3lq5G0Lt27VqnfIlqJaH7vxTAI4yx86X0NVK2twB4UPy+DsCJlNI2Sum+CAzPdzHGtgEYo5QeKeo8CcC1UpmTxe/jANwq7BLNh1rUD6F+XJpAzO1U34wL+LYtKH3hP8FHh+tc8SLF0Hng7oVtLy1q7Y9GdWdo19k1DP/c/2hIE/7NPwC/7CtKYnN+3guOJvZgdJEcXg7gHQAeoJTeK9LOAPA2SulhCB7rKQD/BgCMsYcopQzAwwg8nd7LGAsl7VNQcWW9UfwDAubzbUrpZgQSw4m1PVY6cN8H/nAH8JL/l6haqOkthm6XJRfm0FidLL/+KuCPD4A/cj/IX72q2lo0SWm8lRJ8DhaSwdSrqYa9twb1hYvRv0bway7TJGY2BwBNfaZXInNgjP0K+kfQxUwIy5wD4BxN+t0ADtakTwM4PomWRoHfcRv4ZV8GedtGkNe+oXEN5VJIDg1fStRzQ55meNSF/IVkDnVqy1jN4i8NOecg6i5sR+bA5+eA7VtB1u1dH2Iyg7SCxR8fKrId0gAwJXS92+MHtMRQyzvMCZ32vENcmUaL3Q4rFr5rGPyBexwqq5XWZjhTuV7MwfQsDaq31jpcpFgA/KpL4H/6feBDO5MzV0vLSkYT9kfGHACgozP4O+VyQlcdbA5OaqUFGiyWZvz/PgP+V86q0s2zHpNZteUWdYt089ar6xfHvuLh6XnjY/aMrsgkBwUZc2hOlG0BgYjNZ2dQeveb4P+ExfPWMvGkUSu1dyTnqQUu5w2EJ5YlPrNUV10N0kvR5tAgKagu3amZkF113nU/i6T5JsNq4H/7QpRqMeTXMaBAvZExBwCVYGniAxDuZfy2nxizVgUXyaG7J/ibS+dWWTWqjBDLhwfBf3GTU96qUe1EtECSjlaiapTU0ii1kit3KEeZbbD6bYmB334T8ORjNVTQvP2QMQdACrPs8qFU9zL5A3cDwq+f2ySHeoa8NjXx7J/Bf/vzFAXiSf7XzgZmpuM3LGWaGtX0t24lbqynge9zdAT8nl8nZ6zFjrXMDqpqHiyS67cDsvMcABg3as/NAiPKXrwqXiIfH4X/lc9UEqzMofGDJDqRaKQCzoGitB+Y+wAUSWbMEFiunuEzmh3ahXijfBPN/el/7bPAk4/Bu+A7IN29lip0aiVHekMX73q5oGY2hwBN/L1kkgMg8QblQ5mcAP/Rd2qvX/VOKtm8lRZ4JaHTjNzyI/hnbLTmifBR+Xc96W72fQ6aiZK87BXBXxESo6b6XcuHjDwpxHmV/cnn5yttGOrw//fL8G/6fppaq6Jl+aF5+yFjDkDlI2+AWonPz8P/r49EE13USgs2aDSSw+MPJeaJ5n9Yk+hAv+3gs8GdwJ/+mFxH3VCNWkmTFjodxFbwjeQOrlVUmBmfGAO3qQXlYt+/HBjbFVwYVvz8N5uCfK7I1FMByg4ci0uGDhlzACovKGQO9TyucWgHoPqGW72VFmCwyHW7TOJJH/K9d0oX9SHc/9iG6gtXZT+ojxGbX3+V6dbiQ3pG//1vh/+JU4wMmo+NBh57v9kUXSzUbWdzM3ZQ9eCP3FdlwdiPpkHGHAANc3DI6wrd8ZXNtM/BCc1ESxPByjSVezW7smoY0dhosHPZ0GQMKr0jg+a8O4INofwXN0XdqhOeoyTb1mxYZkPKP//MKks2b0dkBmkAMVdWl7yumNMwB5sxLlVsomoh1a372NV+SHVwT3UU1RcLtWlvcW0i/gf/GTj0iBR16MadSXSQGpSZQ5Ih2TkAYlMMlOZBUy0GA2SSA2A2SNvyusIxPEGs/obyhhSb2oz5TX1VJ939QqNOBunKPVVysGWtbq8JAEA+eS5p+FY7ARHNJsda0YST4aJgsaIYOyBjDoD0kSczB/6HO1LWbWvPVmARB4vaDU04cOuOquwUlnuzM+DTk271uLh11mUTXApXVmJwR6uXq65OTfbgPeB3/6o+9S8ZNO+3lTEHQJIcHLKmHbzaXbQO+Rs5IScZpGtSKy3CYG/Y3oIEKJMtl1SI/Je3wH+fHHne0i9ppUsVrvGOtDYSh75rhKuyph7/y2fB/+bna696eBB8ypExLzbKa8HmYxIr3uZQOuu0criMcoiAur4nHXNwkBwWbKy4TBgNsjnUa1L3vGjo6ar6rnbJwb/wXEteS/1J+xM0jUVUUeF4CofOnzcDICB7vyCZBqN2UMq7xNRK/kfeCRT2QO6/LmlYG3VDEzKFEJnksOWpiqtp+A3YXljaCU2rVkqZv5Fw4Q06j6tmgvpOnKLrKqgHQ3nw99VU4namgkqfZYz6n/0g/M9+QFNHFW6otUiRNtjov/pScCeGaUFRPfG78Vi06MUNQsYcZLgEF0s9AFJyhwZ7K/G5WfAbpGizul2+CnfwL04j6i/CYFdP76tqYrHTzZ97Np4oqWn45Hj8vmv9LmMqZuBOIQVYy7gsdiJ6JYf8yeCWevjPrgUevb8u7SwoqjlVr3l5Q8YcImjEea66D9LFP962srrp+8EGJUO4As45+Jan9Pdu+VE0QTfpqdj8SDzNNKksis1BifvUgLg9/tc+q0mtPKv/v1/R3HeEU5c5MIekeqanHAlSUH/ekFxPE0+adUWmVlpiaHh8INsq0p6HjwyVwxTwn12nz7PpOvhnnaYPazE7E80rDOwRkTjxHO0mg6cwqmqYg+Wd861PlzeFRW9I7dz724T6q75pKJK+jP+Z09O3A0WSdFBNcZeTDpfl7L+81EqJBmlK6V4ArgCwJwAfwMWMsS9TSlcDuBrAPgCeAkAZY8OizMcBbABQAnAaY+xmkX44gMsAdCA4g/p0xhinlLaJNg4HMAjgBMbYU3V7Sle4qJVS2xzqbZCWbxho+fMTQc7idpD9D7TTs2sYfPMjwPguC01psAiDXT37whT/x6b6sdmLP3Vq6jKp4GILiNkcqpeO+OiwdOWwXyVikHao/+YfgvwDtWdKCsmySA5oNaHe7tCLDJcl4jyADzHGXgzgSADvpZQeCOBjADYxxvYHsElcQ9w7EcBBAI4BcCGlNPx6LwKwEcD+4t8xIn0DgGHG2H4ALgBwXh2eLT3KBul6VlpnV1YivbJ6uZzfeyf4YLE+lS0Gci3Ra4Pul3/vm5ZKqvmwU0zQtonDpekUm+qs1Tz5GPwPnZyujLzRThdPSmHG/De3utSacL/5uQNXpckmVhFVg0TmwBjbxhj7vfg9BuARAOsAHAsgDMN4OYA3i9/HAriKMTbDGHsSwGYAR1BK1wDoZYzdwRjjCCQFuUxY1zUAjqKULvzoIA3gDlqtksuk4kJDnbpIlYZqcTFdKDdSGXlFADbsG7D6vk822sPJxhyqGA9VSg4xW5TLq5ZDwOgmwBgzrsLArmKx9q6kAFdtccvMWynVPgdK6T4AXgLgTgB7MMa2AQEDoZTuLrKtAyArYLeItDnxW00Pyzwj6pqnlO4CMAAgspyllG5EIHmAMYZCoaB/qHzeeE+F7PDW0dmFnkIBJX8OpnV0S0srVjvWDQAzvT0YUdI62jvQI9Uh0xvS09XZhS5NOyXCy7R5OU/7nLtaWzENoKenGx3K/bGODqhTZEdHB3LdXQi3UrW1t0MN5lxQ6M3l8yhp7s+NDWFISduuqQMARtvbMQWgu6sbnco9kyOiXEeYxyvNQ50qVXoLhQJ29a8qP5dKW8tPrkL/R/T7FEy0rF61CrlCAaWhonG8hO34E23YacizetVq5AYKGO/shIlFrV69GjnpmfzJiVh9q1evRm7VQKS/OefYIeXp6emFfExTd3c35C10Ib2zO/sxDABPPBppo6enG+1K366an4Ecws/jvvY9yWhtacEqyzvv7etDW4rvTFeP7ttIMzckYbK1NdJ3A6tXw+voTFWHPNc0mt60cGYOlNJuAN8H8H7G2CilRp2ijuVzS7qtTASMsYsBXBzeLxb1n2ShUIDpng1TU1OYKRbBh4aMeebm5lLVzXfFdflTU5OYkeqI0CtWHxMT45jStCOrf3yfa2nxZwKj89jYOCaU+75m9Tw1NQWMV/TxMzMzsTxFhd6SsloM7/PhEW0Z3bUvjk0dnxjHpGOfap9XPa1PQ2+xWIQv7ddQ65mZnEw9ZoYGB0Hgge98LpFePmG2dwwNFkE4gT9plmyGBodApNP4uEbSGRoaAilVPptisRhT+YwpJ/iNj0XpKtO7S13SiPK7RjGu9O3wzuj078/OJvbl7MyMNc/orl0gVXzDMnT1Vzs36OAPR8fd4GARpD0dc+CDFbbaaHpDrF271imfk1sKpbQFAWP4LmPsByJ5u1AVQfwNFyhbAOwlFV8PYKtIX69Jj5ShlOYB9AEwz9CNQuj1Us1RoGH8+1//TLmR0pU1yebg4sNfjUhu2hGbvqIUeRdadVDv9sSz1hr+wtZlLz5Un8l1jNbdrdfBhjbn4q2U1EzzqlvKUL2yltkBRonMQej+LwXwCGPsfOnWdQBCy9bJAK6V0k+klLZRSvdFYHi+S6igxiilR4o6T1LKhHUdB+BWYZdoCEpnngL/5zdq7tQwecjx72WkdWVNyiLrmlOQyzk37+Ak0Qb5bFxycG+o+qJ1w9776dPrrccOJ95aXTedvJUcbA5azzglTe2DZ/6U3HakPl2aQovTju+EZ651hzSg37hYT8QY78K4JC8UXCSHlwN4B4DXUkrvFf9eD+BzAI6mlD4O4GhxDcbYQwAYgIcB3ATgvYyx8E2fAuB/EBipnwAQztCXAhiglG4G8EEIz6dGgM/OAM89C/7di+I3SfWSg7GM9mNyck/RJ0cGZHyy40//Cfy3P4+n3/B/8DceC2hURrF6fp8y8myN4FfWGANn3wOi1wO76fOp+yFkEBJIfj+4In37LuFFrN5K1eyQTi4CIFFy4L+8xbGisICOKSnX1jPSBZJW2aXaJR7/zFNqrsOKuniQNS9zSLQ5MMZ+BfMa9ShDmXMAnKNJvxvAwZr0aQDHJ9FSF4Q617aO+D1b6Ip8S7BC1Kw+OefgTz0eXMQ2kDms5nQwMhu7+sc/+/36Yj8VQprjucHVo84uoT19lfOLDSAHvQT8ycccGrIwhwfuCUi58RrgH09yqAsVunUHOjUa2j5Lu6emima5dkkSvXSZ2JOEuDpIDg2Hynir6evm5Q0rcId0OOi0q0jzBjTyhhOCv5LKgouzoPkvbwG/+n9ERodAZYaJPxpp00VySIGQKagbxsrtpayvChWNLTBZ6d1vAtcYlrH2eSBHvsZesfpMRvWZheY/1LgNAAAgAElEQVRq7AZhMy5qOFv/jgrjbyqJ1XH/TLVqC6dNmALVTJJJ40d33sPUJEoffRe44kFlg3/zD53zpkY9JIclrlZanrDFptHcI3/xsuDHqtVBluJ2+Kf8Y2CAjviOO4S7rmXir5Y5hHpxF4mkFtSgPokEBAzhMvF6KnOIXg5+5F/h3/Kj+tscwuepMWqt/7mPmG/m8tG2yoUc31c1EWptqNtklsQcNOP8yceAoSL8a7/r3Aq/9fqUdKVAPSSHJhYdVh5zKHsDWe7pboYTUPhRCobAf39HNL865rUfsYMnkgsDSdxIpGtaJxYRM01pIQs/9/42ahRMolfH+KYmk1UQMWko2s784w+D/9+3GsYc+JyLAb/K/i0/m4O3ki5NJ43VghSScE3N6L6b8P3t2OZeUVt7fQjSIcYMqlGp1oWShmAFHvZjYQC2uEa58CCgcEIQK/EWJXRDbAJK4coamRwNqqd7GnGMIql5kHLOQZRn979+rppJuVY+Lt3kPT2JRO5QhVqJT0+BtGvsTgD8730DGNgd3t//o73dsNPq4bppQllyUJt2XHSonlS1MsgGMQeuOkrYjjQd3AE+NwvS0ppccWtbzbQZUQe1Er+tgZJNjViBzEHA6nVhkRzKE0KgSiAtrdHsTgMmmjjyxTPh9/SDHHNcQjmA3yiH6V4g17mcwzAZ3AEU9oCdpqTVr2bimnewBahqJRPkiXHHNuB5z9dm47fdEPxIYg5p/Npd+l0zcZNczjCEkusrfXQDsNueye2mggNzKO/NSFOtYoDWPZ/s7FGaB1yYQyPDcNRBrRSNW9VcWHnMQRIc4gbSUHLQDMycolaaF3rmllZEPhhTnZGkaNrMrzYBAIg8GekMcqqLadLk5MCYgobt1eCQl8bT1F3BeYNu3NZ0zAdfU6ZUSv7AVQ+xULrzfXDZNVWupy4rSst4MeW1ZrFMiE77HJTroZ2VUw7rBZcx5RTyPWERpbWtSe/P4BEV+6YbafBV30FVTTVvDKkVbHPgmg/OolYqny8tBkS40SeXU+pJ9lYy+pZHNg9pym1XzxSI5nE6plDHULi+vVSoZkJQJwCiqUPxIuJat1Z9n/O7bge/+Qf6fGqwvmpQnhzS9R059u36Gzo347LUtoCTng0um++qGYcuzE/2MDS5urrUUy/EJIcq3kkTBxhcecwhYnMwrV4skoMa3oLY9fWpxkvEIK25HzNnKJmcIovqmIOfsOJPcd5AGm+lpN27QNAncvLWZ+J51HKiH/ml50eSI4cf1WNytZmvTHkBkH3212fRnexXHndqZkebQ72hbdb8Xo0LliRjrtZxQpquTF571Xp1VYPSPNDda27bBRlzaCLIk1jsXVrUBJ7KHMIbiqdPbAJPsXJxMEhH6w6OA/U3CaNWwmYxc7W6vkiJqnb5OhikSyWkFr1NE8eWJ9PVk4RwpZ92Umhrh3eKQxCA3fYEDjhIXEQnXH7bT+L5F0SacLA5yP1v2nQZW3Un3FdhCtERU/U0UHIolRQJNGMOSxwOaiWt5CC6yldUCUlnIaT5YEsOrqxK3f5Zp4FfdTH40E74l/y3QouujOZjSbRdVKkvT8rjYpB2MuQq106xfWqfSP3zPupeV0xKSv70vJPfpze2P3q/8YjYZNgnIx7u9k6zH8b2XqcNkWaTbHNJk7rmPp+dgX/KW6OJDThPvIz5uaizRiPbWgSsPOZgsyvY4OWCiT9U/YR67VuvB3/sISljDSsBWS3kQp80cfAfXAE87RBEzWhQrFE3pqrbXBpXmZKp6xJXV3q1khV1XWWnrIvAccVI9PG+TBsD6+FSetftCRkc1FnyxG1y803S1yfGXoq+Yz4/rz/nu6HMYd7Nk88Gh0XCYqF5KWsUInYFxaC76cdKHgmeF+xp0EXgfG5LPK1cqfsH63/2AzpCzZCNwJ1djo1oJs75efA/bzaXSbUytjEZ9drBIA1EJ1KXObWRkoN6JrdzXeklh+C5Q+ZgyJPGbXSVy6Exhg5+4SGCDpNDg3zN9b8jeRLUSrpy8kQfOQcb8C88F/5Zp2vKNC5GE1fVSpnNYZmA87gIKt2LgXhB8L3ySsh1IFQ5CbkMNJk5tMZ3gnJNWHKu+Vj4ph8D9/zGRkwyLdNTwV+XsypM19V+JzGDdL2OYY3DO3FjdVVF8hC3Z/WI9Gj6Cdc7+liHigB09QBr9krOZ6CLHPSXcTrK9NikAEPnJIW71npFVdL88z4GLqusHrhb347LQqFalOaBXA7k+HcK+qphDvUlqZ5YgcyhilUeEExAeUlyMFUTszmkoc2BBtu1iicejZ9SVs3H4uDx4X/1M+KXu1pJPaUsXE1bpRgXOEkO4m/a8AraPk+rViKO6gSS/I5lm4RtcvI8uNFpaK+830Jzz2ZMDk1zrz8e3jnfkNLtCwV+5cWIQc1zxdf1tFqJqyNK88Gc0LtKNFUNc2jeKbh5KWsUnFQkmjSPBBve5hIC2MXqqvIg+Bs1bo0xmpJfH//jA9GEqnSwDs86KA4CTOXKqjIHkfyH36ImONkcRNt7rLPnc4H8XL39yi2DLcZFnSDnMfVrJHSIpe9z+ZSTl5I3p+zzseWVXVnv/EXwY81eILuvhXfuxUG4/GoOylHK8GHp+EzTt9BIB675QHKovKdMrbTEUa3k4EUlBxPqJjko1XAe32of+SAcG6pGckgzqdSyz8Go00j4gOT7XT2OzCE5izuCyrxPnA/vrK8ptwwN2Q4eKufxUOkTUz2OoUPCzZqJtn3TO7BIDpYNbfzHVwY/JoOzqsluewIvOiTZ5qCDbaFlsrk10r03NEjXckjYmvXJeRYJK485OA3CeCZCCOB5ks7eUJFL4D1IK0pH8DtuBeRNXADIXlJsIFfXw2oMdHVjDva8/MZrDAWJ4XeYVEkjB/+lIwOs46QRVrXbniDdvSAnnRq7yR/6vVLIccWYtCiVJQfbI8V28ie0p8LqcOBgL5CZGPGq212slpmSbA4dJoeMRquVqmcOfHiwYuurhwRbZ6xA5lClWgkIVnJpXWETJm0eqmOSMFSMp8n6cteB+ej9bvlk1Is5uIaAqOV79jQTj7YNkaceYn35OYK6iBzsTqyq+RWSREHitgQ+ZdgPAN3EI/02Hd6kwlXCMHGHsH1t+BV1AaLJI0u5HtG8ewe71rXfiybIJ/CZdPeNlBxKgeRAqmUOTRx0D3AIvEcp/RaANwDYwRg7WKR9GsC7AYRRvc5gjN0g7n0cwAYAJQCnMcZuFumHA7gMQAeAGwCczhjjlNI2AFcAOBzAIIATGGNP1en5NLC8wLJoasnj21ZQuuZM+UT6n59wqyfBS6R8DOhiI4VaifStSu7FNXspgoNu8iLwPnMhMDYC/utNtS0AqkJodSXRv7aGFB25f+6H9PmSmFfO0ZXSWXJIcJ2Vx5xfwvwzT5br9f7jXPibriuftxCRjmXpjnhxyTmBNF4qAeFRvOVEff3GPPVG6MparVrJlbEvElwkh8sAHKNJv4Axdpj4FzKGAwGcCOAgUeZCSmnYAxcB2Ahgf/EvrHMDgGHG2H4ALgBwXpXP4gaHha1/7n/o7xPJ4yMWBE/gkfui17pYQC4EqTpUFy+RRiGNUT2N5GB0razk885Qdn1r3YwBsmY9yAEHi2gmLswhRefJ+wNszkrhvSRDskZygHwokrasgd62tuQ8gGAOaZwRVAO6+Cup7Ph1V2LwtLeDbxNjvKMz+EZ0Rnj5t0660/RTxGvtwXviJKqeeDo0kjnMzYHk8pVJXnPULN/6NPjEmL68U7DKxUMidYyx2wG4Hid1LICrGGMzjLEnAWwGcASldA2AXsbYHYwxjkBSeLNU5nLx+xoAR1FKF8mEnzCQJHHYGFlVrXHb0+mbam0F1u3tUPkCbdevxctFhmsQtLC9XA6kvTOd6keenFzasG1gVPMCwNq9gX0PUDOEjSt/YXnmOtkcXEOPe7l0iwmTs4Bks+KbHwl+jAyKNkigYimroAzjk3iasRsnzj//k5W7SUElF2PGmJ0OVLtt4tCo6XgcKf9Tp8I/xyQVStPvQn3LKVAL6zqVUno/pfRblFLh6It1AOSl8haRtk78VtMjZRhj8wB2ARioga4EuKs9vDO/FL2vM6QloVQC1u8D7L5G35aOnFxL/ON02ZmqQz1WTjVNKpaKEmnTTLYGtVLkvuOOZT45bg4Mp+QtV+958E74V+W2olbyktRKxM1biXMkcgeZOSQZpCHXZ4BJRRKma1bHlXaJsMv58Trk9+YRt+9IfrZwk6URJrVSAyfd2ZmAxvBEQRONJglHVis1YVymagODXATgbATD4mwAXwTwLpiFbhdhXHcvAkrpRgSqKTDGUCjowwHk83njvbmRnUYxiICgUChgu7geeP5+ZaNKoVDAYEsLvJYWrJLy6CC3PZTPA719IG3tmJXOvi0MDIC0tGC6twdqLFXS0oJ8LofVUj3jnR1Q105trS1Imtq6u7vRmUBvElryUVryhrMQCoUCZnp6MGKoZ/Wq1cgNVOqZ6OrCuKaOsc5OTAIACa5H29sRfnZ9fX1oFbSEz9TT24MOkTba0YEZUc72zP19fUBp1ioSh+9xJ/HgS2lzIwPlcoVCAROdnRgXv0lbO2aLqxAGdxhYvQqkvROy20FfeyvQ0o1oAIg4+vr7wT1gRNDbIuiZ7uktj5nCmrXlulf19yNveO6WtnbAL6GjuxujljZ7e3vRXihgpq8v8h67u7owBqCzrR3dgo6hXA5zANo7OjAFYNWqVZhob8cc8VAoFMBnpsu0heMQAHZ1dGKWkMh3MlvcFuuPXHdPOc9EjsTGClB5R8VcDjoftfCbDmGbG9Ji++wMOvpXoWPPNRgE0NOaR7tSd/gudG1O9/WV36PHOQZW9QdqKgn1pDctqmIOjLHy+KOUXgIgPAh1CwBZkbwewFaRvl6TLpfZQinNA+iDQY3FGLsYQLh1kheLGg8eBC/CdI8Pm6YugHM/Um5wvDIci8UiSqUSMDNtrFvOG6I0KzwqyGw0z2ARJN8CPhrXR3LPw9zsbKQefyLuzTIznXyw/fj4GCYT6E3C3NxchBbTYC0Wi+C7zGHDhwYHQXhlLeBPxD/3YrEIX1IhFItF+NLqftfoLhDlecbGxzEh0vyZGfBSKaD3eS8AntYb/EeGRxLdesNn9qVVXbFYBB+Ljgt/IqC3ODgI0toGPlIZY4PFQaAtytZ37djh5N++a2QEGA/Gx8jISPm5+Whlei8OV6bU4ZFhkI5ubV1zvg/MzWF+3KD/FhgdG8d4sRh5BgAYHxsDcjlMjo1iWtBREnt+psSGzeFdu8BnZ8Hng/HCpZX0+FhlHPqzM+Dz89Hv5OP/FqOlREjlHQwOaukN75cMK2/u+7Gxm/T9uoD7JWB+HlNz85jeFbyP0dFRjBvq1rXJpW/aH9yBHce9ErlLotF260WvjLVr1zrlq0qtJGwIId4C4EHx+zoAJ1JK2yil+yIwPN/FGNsGYIxSeqSwJ5wE4FqpzMni93EAbhV2iQbBrlaSBzRaFH2us8pCrtOH9kAgHvtRgetu1ma0OaRRKyVm06iVkhCxOdjetZ/ClqHUo7qFqmoltR21/PwsyO5rQN6midOUQAKfmoR/w/9V0iN6a8vzejmhukh6ZkPf+T5QKkX3ouhUT7Lq1aQq8RyN43I/J20+NaJBU0n4bLlcRUWoPFPiXqZcfPrlM8kLvoWCiyvrlQBeDaBAKd0C4FMAXk0pPQxBzz8F4N8AgDH2EKWUAXgYwDyA9zLGwuXZKai4st4o/gHApQC+TSndjEBiOLEeD2ZEwuTlv/+fylckl4P30fOAnj6RUA1z4AavBJtniY45VDnI6/FtqJvVLH3An3jUnZa6fbdK1FZTyIpI29ydOXAOHPJSeOHxnupHrexziJ3op5paZmaCqN3r90nuAiXwHmeXRlw6ScQzyqUeR6h16SZ6ndHaM3grRbKZbQ7kuHcGBxkN7oi+nzS75CM02oulBeccGC5W5gTPqzBo1fkgyY6Qb4nX/4PL0y0aGohE5sAYe5sm+VJL/nMAnKNJvxvAwZr0aQDHJ9FRNyTt4FV215L9XixdOHrCaNtLYYzN5912Mi+EEUvnH29pV3vUZfmmI71p4xBFJpEUGxWd42NxkFUFkL1fEDZioEP8lc8w0BzBSnRhv01QDMRGt0iXetJ4cal5pZhRfH4eRGd3Iko7NsnBtIu9p7diiI4Ysav0namzdM1v/gH49y8HedkrggTZLVntM53xXobumRLUfguJ5na0XWgkfTzanZ2aaiJRKXkwYRmPNdTUl9dIDjo/cJdlkcuEYAw9AKECiNbhj5rtNuloSaCtmt3LkUkwQa2UhtFHSDG9G5FJ3rnL46JDZQd1wvNFvJUE5m0TToLo4CItDcd1+4RuAPnr11YSTEEW8y2Kt5Lh2NuODmB6Ui+BcqneyK7qhKlqoSSH+38X/P3dL4MEWXJQGVHSAk/n5txEcfhWHnOoxbVT+Gcn6hJV5uARQI2OGi6uvvn5eHmdWknXpKPLZnIWy+pKwxzGvqGh2QXFih8Nn5+3xEBKKTmoeXWulNom3CUHWNU3UZsDj0gOvLYxJ9cDVH8+geMuXn7N/wY/pImNvOTIqPpqu2bDHhBELZaZs6mtjq7gOeZm4/f8ErTvpeoNY3GVqP/rTVbdPvdL4CYbh8qcPc8iOUi7yTmPn6XSyA16dcDKYw5WOKxkfZ4sqsqDwPcNcV8SbA4uIY3rFSZCrqe1VaElfg7AzF2/dKg0Dv/6qyu/T/lH8B9+20CP+BvOR5GPyh54T2v817bBU6wq1RW8gXGH0TN6+5R2LLr3JKhZbKoK23iQmaYL5ElQHb/lsx2U9lpaovYEk1opjAmm22MS2RshG9uTSY7gec/X0jh73+/AL/tyhQlq4H/1bPNBYCqIZzRIRzYM3vIj+P/2FkUtqJMcmkd0WIHMIWk1aUH4gSXt9I2plXReLDbm4BgHp14LD4lecsSrovc0koORnKR8KuNxhekcYh20u281SLuil1/hnsINNdS7K2ol8sJDKv2Yigkp6F9dadhJctA3RE46tbKid5x8IitntUg4XtRgkPkWxeYTP/QnqM8ixfh+Ja+8UTCl7YA8/0XBj+6eSDoXocP5qGWXyYNqBF0J6pnRpXmzQVoONfLrnwU/RoJ2+eAO+N/9BpoZK485WD9U6Wa461GGbZeoDPkDTuUyKaBjDlr9rMMH42K0jkS3VGjNpQi7kDTZ5tMyB8f+HtpZ+e3qrYQUzCGm5SIgL/0boLBHNIPcdy88WKLBJDmYm/TOuxSksIdUZ8gcEvpCh9DAm4ZJ2Wwb4ZgaUewT+RY3g7Rt17fMtNNIDsq4JSdsCJi3Ggq7XE91K3RSfueiuofuNTM7y7fnX3p+xXYTbaEquhqBFcgcbJJD5R55zT/E7wuRmUvqES1kcZnDwBwsdHi61a9hlZWEtJNJTIWQImBbwmRL2l2P5FQm2wQ9O5dXeqbAb7FClklbm1d5h6GKMUKuxvXSavg2TwRk9W76LFa1kkF6K3vUpOAOtn0FJjdUz7OEz0D8t9aO5lfKa6Lbel+8wkCUwhzyLcA+++sa0GV3h3bRaDBI28afMe5UdWQ1AiuPObiqlXR2gnDiSYoGufXPUp2B5OB94vzg+oWHJJKBfKtGctDkczFO2vLomJaalMYQmMREDnqJe10yEp6T7H+QdJHCZdNZraRRx0QmW4vu2Gb4TiNRhlXY+sL0TCFzSKNGszIhy3tOIzmY1EpyXeU2eXB2gnIMq1plLNHEyKqdhWPnnkOyOajPU40+sXm4w8pjDq5qJd07EgM/yYXU//JZUpUcIB7I3vvBu/AakL94WSVdgvfR8+Cd/214n7gApEN3xq4GLlKBbQWoOwBGq1aq0FoOz6xD4uSTYtNZ5NIwYYRJR7wyet/JWykFc5ic0PSj4pWjZR4QK2G3ZvRQJp5n/2zOKueLkJLAHHQLoYjHldKEbWxGJKoEm0OiWkmRHLSmO5H3mSfjN3XBDbV1p4DqcRTZ56AapKXr8LspP7rhXTSRB9PKYw4J4TPK0H0wWnVPUnO8rG4goaufDruvAenpCzZa6Tbb6QaNi+Rg0x1rpQKFPtUgPbgTRiQN7NQ6fkFLkgNARGUheyuZy/HRkYj3lDHflmDS4bffbGxTe8CQrIeW1ZXH/hNSQZpIk4+WtUgOsDEHpZYtTwGRvSzuuvSIQ0A1mzSNkoOGUEMb5G+ODn+ZVT3VMgfdN2cySDuqsCOo5hjfBqHaqKxLF64TlGnw+BwERD/t5PJAaR7klX8vtWcySCs1yOF7das89XrfA5ztCcZJRSs5qHmUMOXzGt90E42x+46TxdRElJakcjIjlycnjsAgqfHL59/+GjBreZY+EYXeFIY5lCKnJ+OGWZkm1bax25p4XhdwJPcDh+EdkEpfOsyJ/lmnJWRwVCslMSOjzUFnkDZ8R6X5+Ilq4SZDTZgOp42jYV5pYVdGbPIm0YVAtAJb5fr0avexNAArUHJwhE4kFSfBlQfYmr1Ajnx1NE93b3RFrhqkTR+GPFHrJBSVERBiX8WEmJ8F5BO1ZGgCf8WQb4kQy21upS6TlwPKbn/lhDSSQ1gkwfBo3WmMygEuquui3BDnkY1OWppUV9a0agN57DitxPWSAzFJDt09kTYiC5sQ6uRro8OTVuvV2hx0q3v1Owqh+wbk8i62O7n5n7AILf7tN8PfdH0kLYIw2CCgkVIs/RTRUlSeK7ZRbhGx8piD88epGYhh+IywCnWCLs1HBiSfmQG2Pws+K+/GNHAHmaFoBnV5u76cR2YYbZInkOy+Nzdnngi1h84rz93SEhWXdbtaQySpf2wfy977Af3KGU+Ou3ojNMsrdmHv0aIlya1WtGk65zdJqjFJDtBPCsnQqIwO+6vkPGE7XnwzIwBgH+VUO0XVSDZ+GER9L7YJzLjPQffcepsDESftke5e+Ya+v3T9b2MOMRqUoj/6TuXCL4F/++vgV11cua97dpNBuhotRSY5NBe8C74D8gYlGKzWkycUU6WVtG6whN/GL0Tg2fvuiterDhxPUSupKxQ1npHKHCT3We/4d1bS5+fMk5Bu4osZpPOIfMQ6HW/Yd442B/6s5ujU3v7KprJKzaJcvE1+96/0NEf6lwN7GGLXt8QjYkIOshg+i5aBCtpsG9xMrqwO80XH66TdufLzKMzXO/5d8cJa5iD+6ph3LocIc5XLd3bBCwPMRdpwNEgnSTq6vvB9kHe8J/jdJZ1NoXMnVulVK3ZRz9qgo1+RFMme6yrvSM1vWyxxwzeVSQ6LCJ03h6oKArTGWqIzFKtqBdnFUbsKMEzUnqo3Nw8s731nmtVKABD6yAOB5CCrDY79J3gfPrfSThKkIIB8ZBDYqkzs+x4g7UJ1kxz8T59quG8y0sXTtTGpgNikTFoNeytyGuYgr1TLzMHQR+F7NkyUJGS88o5fuV6ZVgW9G+Uzh2XDttKWSpvRA4tU6H38YeWWKfw4tCGlAegnzZCWiM0nadWukxx8kK4eoKMzUp7/9FpgRmP/0U3AsmRfxR6TctVfPTueOBuNyUTecIIiJeoI0cDEYDPJYTHh5rFhlBzUj1vm9J3dCQPSTAYxGKT5c8+CjygH4w3sEZcc5Lr22hfep78WqJfmZuMG25B56CY+9bnzwXnW3Pfhf/idwUdqKMNv0dyTYeuWUgkY3FH2DoqWs7uy6iWH8NrQnk5reOK7pTZD8c9S3mgARkXiKKmB5NLaHKSS9/xaaUOd2A30EA+hpBPzulIjn8rlTfYWLXMQzxuOBd+3bPRKsDkEmcpJsfEvI61aKckWJUMNlgkAO7dFr3N5i0FaQ5s6PlU00VnSK485GL9NZbRoN8GRuJpAvExy1BvhffJLeuOzthlRx6oC2o96QzSPZJD2zzwF/of/RXkGEczPssog654HtLQGMXJUV89wALpscAslB92HUq4zqIffwMx5QrpNeOZPAAD/iq9L9YblZLWMafJTfofvKY1ev7svniZoLqs6ZOJ0q/kQ4WTplyxqpXTulPyyryhtaN6fSa1kaIqs36dyoYaKN40P3QSWizIHm1RlNUjLk7f4HRv/uvzRREFTXrOA0hi700CtLxKVNYVaSR4I6/et/O60hM9fYKxA5uBooNJO7DqpILgmLz4UZGD3oGCSq59Mh1+KSg3GdiSE9Se5subE0ZARhiWtDuWBHWIqelY1CVULts10rt+Z7Zl0q1SbS2RE0tLQUlaxOBLX2qoP9CbaJirjKKuVDPWFnmClEvDclkqxLv0Zz2ZYJtLYAkY1fku0GlSV5B+kc7ZyLdEFh3HxYHkfssaomhARsuTgIoFbTqgjbR1xV2SrGcClPVXk98ybDF1dWSX7F3nBi5JpWCCsPObgKtbbwmf84beVpBf9RfAjcnqVaEN4xJBX/J1cSbTOUilu9JSNejqEm+lMbpQy1NVzS0vlgwrVDTL22jd6ncvHpSUVmr7yzvpacMSqDNszhXaL8dFKtaFbpU6tFGnT4K2k3EqELtCbNs6PuOYKbTK8is3B/+8zgt8vPAQ49IgUBMntavrO1eZASGQlHrklj72cEkdLWbSQt58S/NC9R9nmENKiC8mdhEh/u6hnLWqldh1zsOgbXVQ6JruP7pt13dcTcVdOqXZsIFzOkP4WgDcA2MEYO1ikrQZwNYB9EJwhTRljw+LexwFsAFACcBpj7GaRfjgqZ0jfAOB0xhinlLYBuALA4QAGAZzAGHuqbk/oClP4AzVNsTmQv3sLyPNfVDn6UR7T4Qrmrf+iabAiOcS8hixhp71//yjImvVWm0Mls3BflJgIedUxQC4H8rJXgBzzVvjnfDDyDZLXvgHksL8CdmwDv+NW4b4L+3eqC2mx9nmajJZKOsWKWopbRV55TPBD/mDKUo/GziD/NjGz3dcAO7YhPjkQRXJQbA6mjYymdnKSWr+uxdMAACAASURBVCmsYv+DopuqXBiXhTekMkjbVuIHHAQ8cp9Qw0iSg8L0yZGvAv/uRXpi1AXOzufgf+Uz+vZcYitZeAN5zevBb7shWkdk853I2N6hYVCWRYMLc9DtcwD036xNbWZyTKjzsaa1wEVyuAzAMUraxwBsYoztD2CTuAal9EAAJwI4SJS5kFIajpqLAGwEsL/4F9a5AcAwY2w/ABcAUJabdYbRwOhgc5A3+JSLEeVMYGmQhhvGZLdJ9WMvpVMrkcNfXsnj4tngc/hXfK1SvqUVxMvB2/hhkOc9P/bcxPNACnuAHHgYvA0fNKojYvS6wDbwdZ4xoT0nPLgl0qZJrRT1VlJnAe9dH9C3L29mAqSPWJay5PyiX0Ia/+X06P2IQVpgTHFHTtxrAVg5iEqTb5DwQrWHYfB77/k4vDO/JM4ul95RTK1kmdTD5w3LxGJw6SZDy+Rp4w4yQnojdh2RltfZHGx1OXxPyrOXmb3um7Uxmwhz0Iy7JkAic2CM3Q5AdRc4FsDl4vflAN4spV/FGJthjD0JYDOAIyilawD0MsbuYIxxBJLCmzV1XQPgKEppldYiFxi5g/UySPMc4vxIgzrcmxCZ+JQPrKSRHDRMKIbNj7hLDjoPIJUe4+1w0Fue2zVyq1VVpmEOQlVH5H0bISJujTrJQfxHCDpkvbou5DICFRYhBDj4cKBvNcrPq5NUwibllbrKIEWf+D+QQkyrE8u6vbW0aKGdkFXJwcQcEJtrvdM+Ce8DZwW32zvLC4XIvh3dosVESzlvguQmZdEOKdmw7eKGyjUxp0I6czmgVIreFxM2v//ueLXVSA4hdN+sq81Bfo/LwFtpD8bYNgAQf3cX6esAyEuGLSJtnfitpkfKMMbmAewCoGzJrCNcObPRW0kq39VjyAPwiXHwn10rqlJ2P8vwSyCqMdZltT5rPgM3gsRVv1MlCfW4Sg6GlesF39FsgAPI6kLw1+RvX65AZ3MQ+wsI0PuvsrQQp9X78H+BHBcwoNzpnwI59GUVWjWuleVnGduF8gynMo9wJS2HLtE9//NfaHoq0WwKm4Pvw7/kC8HvvfcL/oW0q2Oquw/kQCWEurr50jTp2lRcpiMzoxVF6ucTY+V4SOQNJ0jtW6oI4ftxaf4YsYkw/K6kRRQPJbnIcZ1SXUkwOrTovlnbA1TukXWSCtbm+LHAqHfgPYNi1phuKxMDpXQjAtUUGGMoFApaIvL5vPHeTE8vFOEehUIBE91dGJfSuru70KnUMdrRgRmPIBxCA+/9OPJKnmIuh5bWFnTlPYTh2GRaJru7MQZg9epV8FYNYIfvw2tpieQZ7+rCBOcoFArYrqEVAEZf91ZM3fj9+AOSSp6h1jaQfB6zmvIhtisTjHp/tKMTM4Sgp6cHu5SmcnusRd+/fxjzzz6NUSk9v9+LMCDqGT70ZZi973cAgK7OTrQ89wzUAxp32+f5GGlrh8ruZFrCfujr60Or0i8Dqwfg9a8GAEz2BP3bN7ELw8NFtLV3IC8xnlWrV2EQgJfzyu+xb2AArbvvXs4TPnOhUMBssQ/DAHr7+9Am0bPj93cAAPpb8hgC0NPbhw7p/swzm2PjrK21FX1K/w61tECdDuTxOzvYH7SvG7e77QbS0orJf/8Ixr7xefT29GDk0fuDZzpxA6ZuuAazAHr7+zHT3o4ZUhm7/X29aFHHbj6PXD5XGS/PPBl5B3x2BjsAdHV2oLOvD/I5Zh6C8TrR1Y1xAD3d3ZHxsvqIvyl/K1O9vRgFsGpVP7yOdux895uC/vmbv0X/+mCi3JnLoa29Db3Kuy4UChhtb0coN67q70NuYCBCy257BXVM9PZiHEChvx+kvQNzjz2M4cu/HqlLht+ahynm8MCqVSC5HHbwaOi+sI4dnoeOtjb0SHXO7uiNjfVV/f3IFwooejmEMlrh3R/ATmFD6ch5kTpsc1mjUS1z2E4pXcMY2yZURuG72QJgLynfegBbRfp6TbpcZgulNA+gD3E1FgCAMXYxgDDQCS8Wi7psKBQKMN3jo+oUBxSLRfiTURfO8fEJTCp1+DMz4FKcouGZWRAlT8n3UfrT45g+/1OR+st1TAQsaGhwCJgTexkIieaZmgZ8X/sMYZofU4MJqcbLlfOUSvOx1ZCpX0z3/Zlp8FIJY6Ojsbz8Y5/Hru5e+I9Fd936x72rQoMUqG9ifBxk6xaoKBaL8DUB/XS07hoZDvq8q6e8+hscHgaZF305EbzH4U+8FwAwMzODefmdjQTv3x+vLAV2DQ9H3mP4zMViEVyc+Ts6NhZ913/9WuCWH2Fke2BAHxsfx4R0n+8uPoN8S3k1ODM1FXumkibu1fz8fDkf3xXQO6obt8MjIJ4H3hcI2qMjFfYx1toBX0SdHd21C3xmJqIyGlGeGQBKPkdpOmrAlekNgy5ODA1inL4qks+fnhbf0YSgtzJevDMvwEhnLxCO3bHgvQ0PDQO7KvlmRZ8DgM85pqemMKvQWCwW4UseSMNDQ0C+TUuzPx0sN4o7toN0dqP00X81PhsA67nSOy/+Irzj3xVVux16ROU9gWBqchIz4bVfAr/tplg9w8PDIJ3FyHsflPpganRXuQ7APpdVi7VrDSFlFFSrVroOwMni98kArpXST6SUtlFK90VgeL5LqJ7GKKVHCnvCSUqZsK7jANwq7BKNgSr6lVU6qgCj090qoqM2cisJdPx/+qOBAEmkFgON6FxZAbvfdew4Tw/kTf8E74wvRNuSRW7VTVWmx9gOMXvBlPXtKi2GeETcB5fjTEXaSTkU936BXFj6meB1Fl5GbBbqs0kKet/wjGFww3CyUA37bW0gL3sFMFCRSKrSJ5uM/Yf9VUVdqYvt09Ii2Uu8uEpUu3s3gcawHZ1KRkhu2lASMWO+9EyywV5nm9OhRzoNzuihhYqq0jUkhcU1nP/+DvA/PhhR53pvelslg9K/fNP14D+7TlOR4uiAQG3qnfbJwEHBFkZ+gZH4RVJKrwRwB4AXUkq3UEo3APgcgKMppY8DOFpcgzH2EAAG4GEANwF4L2MsfDOnAPgfBEbqJwCIqHS4FMAApXQzgA9CeD41DpKu7+hj4X3pu+JCyaYznsaMZFqrtb358MMozYNfKYQg1ebgorfVMCbvjSeCyAxAoZe8+nVmeqz0Gj4+J/uNYjz8zabo7VVCZNYxWm2b9iaSPac092Mbm0ilnaRNk2JCicX9BxBzb7SFU0iCQof35n+WLqQ4Ttq2xTiQgzdqnQOIG3PQ9Il32ifLVQR5bF5PAruGorvqZe+t0OCvI+N1b0V4PjS/8xfmdxQat109lqyhyHPwv3BGlI7nSQsU1SA9ZFJQGZ7pkJcChT3Ax+MS+mIhUa3EGHub4dZRhvznADhHk343gIM16dMAjlfTGwb53XR0gZS9Vxw+UvWchaQ4PzYy/vBb8F/eElzo9jkAscFK/lkK4RBrx0CLMXSDpZx63zd4K8krU2OVcvvxOsjrj6/Q6gLdB6zb5xBCNfBpmZCOOfjRe7HAjMo+Bq0DA5T+dzAqaytBLJJtxNPJk4zwMspWPVIZazZaCNEzMPm+oWw5rLfuVDSDNOd/8zxgvCKF8F/dArxtY5jJzBzyLSD7vRj8qcfBb/sJyD9QPb25lJKDzZXVFLq9TJRqkDaMZ9uiY891wHPxg6kWCytwh7QE26TitFqunjlExMqY5KCP8kgOkHirixrGJQhg0ordFiaip09kqcFbKWzfUa3kS7H1ozRqfgPlvSbexz4PcuJGaN9ZTKskSQ7lTVkGdVW4KjVJDpFwzJqJdybB6yysdstTljwatVJ3D8oPoaPNJMXYJtJyO7bJVsNATPslJsajybJKJWmHdNjvXs7M0NJKDlZJPWF8JkU1KLehuEjLVeRbqlM9NggrjzmYdibGeEMNNgcbyvelfCZ/cnWw2VxitRouhV7j7lkL5IlSYPUFV8C78PuSzttxGGknJEVvngTtJGlmDuG5D+QFL4J31BsM7ehcNpWPOGZXESv6koF5hGnSZMt1z286pS9CC+yn9smSwyEvBfpWB2HobSFETJKDZXIiOiYUy1RuQEpTdlqXVU/K4ufYt0frsc21Yb/ncuB3/1qfJ1x06Q670u0xkZ6L/NO/R+8lMgdzVAPyr3IIdvFQgzs0Gb2mOs9h5Z0hDdOKxkFyCE+CM5ZxQHlHpZRkUitxZaDYmINWioFCr25CsNAatsP9SFmvf3XZO0hPiwFa3iTKum6k0yHC5B1WeCpik520CjRNsGX1id4gXU6TV6217H619Y+4x0OaQ+OwLY6QSXJIWrkmSheCTjmmUUztqB8vnrzHIQwxbuqzsF9zefDLv1pJl05EJLlcMORcjtMFos9u+iZNsEU12H1NZeirWcKwMQBi57UvMlag5CD9tk62Gqg6We1q3ZVhSPkM3kqxVbI8YF0m05jkkECHvhKo5wQQx489Vr9uQlI9bqpBGoO07n6s/4FkyUGKuqq7H7Ylr1qrCapWXig45PFLIpCjGnxQ88wDe2jqIQ4rVxJx59bcDpq+6pJovbpM1mZCdaZhNS7ObieHRQMZep/9RuVCswmuDN1zymmaTZkRdCihtW1RDSLPr7zIAelgrpxZ+lgMrDzmoI3xYs9Wya+EzzBNCFaEkkMln6+6BgqVhf+ls5T0aphZkuSQNJkG5aICUxrmIDdvUNWlqUMLm+3IkhcADnoJEImNhWi/GSbYMoN88J7gr07F6HlASTKIV/Phh2FFbJO2rFbifmURYaL99ceD6I5PdZEcPBKbbInsOaWNSWZzWLCAw8xQw93fYmd1UC8BCaUmQLI5JDCCcposOahRCySid1+D3FeuVApXpE3OedQBwBY7SV6YeDm3SMsLhJXHHIz+18Scr5xFmWyrmc80ZeYee1DJE65K1YNFcvE8Mm2xthR6TXF3bAilD5vEVIvNwdFuQY56o+VmCuag3Pbec4ZBElL80Q0Gaf67X+orDiGtsr3X/oOdNh1C339ZHx4L8id5t8kh4E2SQ4/mUCMAMQO6PlNkXHbRd8GTvYVMti+1jiQkSA5ap40DFGdIm+SgZRjy3gOz5OB9UHN8qPytPf1EdB+N1P9888PBKXmae81mc1hxzCEyt8tGKSeDtCo6VmGQLksOlZSut56sr0MdKKkN0gq9JmnIhtBuMSb5X6ttq6tmWe+7XupjXZfGThAz4AUvttCYhjm4SD2SzaF8al6CDjrBW4m84z3xWEYuEMyBS5uviBo8UJ4o/ZJG5aiOFcs7T3L7JAiCPpbbdqi7GntSONnKE+kBB0XvA5H7Ht0QrcMmOSQwB63r6v4HAi88RBzqpWBwR2WhMKdsZJP6iF99adS9Wh43mVppsRF89N6pnwA58LBKsvpx6zi4KnZXs89B463kqUcDGvY5REVQV7WSnKCZncfiYRmUSoKPdEI6hCcWalpRW6ypRFAhbzkJ3kc+F5y0phn45VVU4gRiUbrXIDmYGbxoL5xEVG8hlV7dZCJXbdo1noRQcpDPJYhJbtJE6fsaycFClwx1H48OxFMO0HGVAizXJnCU6SHHvRO5D/9X5Z6n+UZalXEpeStxlRkkqZV0NhkOO+1lt2Z14aBcT+ulikyt1CzYfY2SoDIHi9tl+boayUGTTxVhTXXkLGolOaSAXE+KlUgYwjmaKCZK6eMirdFYNhF6lUN+SD4fnHdhijRr2kdgyqeFIppb4SpxBT/LsXRsOmhAP/nLtOiOQXVBiygnR+FVu1FVK5XHiWRMl4+ftPVRorcSKqceAm4Tv4PNIaaqCRm0afEgR98NofaxdOBS7Pxti+TgffDs+Fkb4bfk8n0nOWxMjuvvKWo9PjxoD6HTYKw85mAMh6Dm03wkTpN42pUr4rGVTFKBPOik34RugCevqmT6ZC8j7els4t7L/9ag9iCB3twWItx0Kptaj864aHO3NICrBny5aJLO1skFWGKq8marSJ4ESUJtq1pX3VwoOUj9r55DLRukJbWS95Z3BK6Se66Dd9KpEl2GtpxcWRW9eIw56PrBweag2gu8XOAVZdqFr5McTO+Ic/Df3ha9p3vO8Ll0Z6uHEnYCc+B+KZlhiuCEsXueV3Zf59uegf+Rd2Lyuqus7TUSK5g5JKz8dIMn6VwBwF3nLTOpGNMxvJaIQbrSDnnF0SCyS5ych3Ng3wOAPdeDvPhQM12GyYs/HkRc1QYR09Frev5QAok1IPp5z3Xxe5F8lbL86kvN+02ekPThLtDQyx97CPB98OL2yGarCEyTlaFum4HTirBeSU9dPre8nCBNlL5fLkMOPhy5L38PpK1dsVcZxpcLcwCJSpEuti8H1+fYXp9VA8Bw0ShZltu1OYjo8oSwqZWIF69rcIe47yDhJj2vapMIkZMkhx3bAACzD9wTrf6WH8G/7Sd2GuqElcccQqjvWB2cOt2fyhyqEfnCDUv3/MbctnGCNXzgBn02Ce0FpXmNGk3kOeKV8bpl7NymT49UItNroF3dEBYmF8QhL6/8+4RGJOZwx63BmcchdGc/h/W/7q1KNepuaE1TmwVDfOwhaTWZ8I60NgdFn+wA79+VuJPl/RSWvQVelDnEJFG1fdP4ctnnEDoomOpycu92kBI7uoCZafDwPevGp7pprFOVqELmoPmWbQZpzzPTmGTr4zxeVu0TOTy97FxAJJuD6OPZe35TDiXOn3wc/P++Bf69b9ppqBNWHnMwSQ7qx63uTgbiR1nqzgBOkhzCQbm5cgaC9iQ4DaKH0zuoLDyhAhgfMwcOC9NNdUxN6NNldHRKdJkyEfDhwWjKye8DER4ohBB7cDMrH5YaVVRXxOblpJbVobwTN4E5JNkcXA3SygKk/M41513E2tmxLTi72TSRVio11OOoVlLLRK5dytibAIQk4ZfAw5PtTF5Q4nsib3xb3ItLltJVOjXMgT8nDrHM5fV9ZJMcZI8x0wl6IeaF5NDZBe/k06J1cF/YGSp1+Fd8HXz7VvjnfggLiZXHHEzByFKqlcjbT4mL1Lp6Te3LcJUcTHlMEw8hwYQxtFMfXwaoPJNJ1eASX142hhtVYiR2DgCJnS9heW6XaKFqvu4ekEOPUDInfLhqXqNaSblO8lZKiupZrtcwCdqOjwzjPAl1Ay+q5weiOslBp4ZUJQsXqaAlwVanO9dbmvjL1ypk+4clzhn3NRO2RkLiV19aaUulsXxehb7vyFveISrh8K9UVvaEANI45HPBt+h95Dxl055sO5LonZsDFiGU98pjDgbBIabzLJ+/K0GWHEwr7Wp2+roapCN5JIO00dgp1WOaXEKpxVSHItV4Hz0vnkeVqLSkePHVWpoVpdWTVSoo75h9nuYdqpKF7X2FKjkgWa1kmrxCGJgDOf6dbvXYmANR6tbptHMuzCGqpiEve0U8z0z0pDgne0KS1KSVCnKKsTlBrWQzhOtUZZxHN6PJyGmYQ2e3XgJR2+IceOLRGJ2evIkzfD8xphmqEKOxzAAsytnSK5A5JKuVyJGvhqf5MCKTsGklWAVziBv1HF6Lk0ud4ianQ4JayfvgZyoX6/YG2U+jponQYvIGI3HpJVVwMzf7Djn6zZULl7MbdJD95cuurAkMXKtWkvKYmINqCzK5glolB6Xftj5tz2P11ZcmUhc36ASm6b3/LE0hB1VULhelxSSlW0OmC8nh+qs1DcBsX/FycaJ83+7KGiabNs/KCN9lXlFLy4c2yfWU5uF/4T/17TYQK485hLCplXRSg1rGMWSE97HPRxNc5jgntZJL+w52idCLxtTm7lIMHpOvfkStY2EOqlE1tl9CXxSAWReubHwi+Xylb3R91D+QqOLx3i8YYi4vfciKdJTaldW0mHBQKeoYq62Mrq8i7Vv05kk76tWmTfsPAJDDXw5ykMY9OqaJMkkOCWolWfWkrUM09Fz83HIA5g1nXi5Oo1+yb4KT7T7xm1H6wzGlStxltVKpEmEXAP74gL7NBmMFMgfDiI/sPrYYeEMYJYdoWSJvPgLcPJzqJTm47BxOUivJ6UZ3TEda1AmurU3NlFyPCl13WqQh4nkg73y/vc6+0IbCgbl5gHhxtaNad9IJdSbG6iKB2PaY6GhJymNTW0Ykh/Rjlch1G9WNquSgoSen7KfQbxCq0Ku1ORgcO458TfDDJDnkcvGyoeRg9MYT2T77gfg9j0TLzRmYQ9kzTaNWWgSsPOZg6nOXcNgR75MENU0NIMpAJy97BbwvXK5kSmu0TrIpJKyIADNziEgOJlo0qpGY5GAZjiYVh24CS5KGHI/mhM8DmlXdsK7u1QV7HtNhPS62iwSoq/eY+y7gJjnE+sthgjIdnwrovfl07WhVaUooCd1E7nlOaiUZHX93LLCP0AyY3IO1kkPo5urwnejuybQYpVGDWmmRUNNhP5TSpwCMASgBmGeMvZRSuhrA1QD2AfAUAMoYGxb5Pw5gg8h/GmPsZpF+OIDLAHQAuAHA6YyxBvWOwVvJiTk4TMhSPd6pnzC3b4PaTksrSN+qaJrTeQ4p6DUNxoi05MAcbDaHJLWSTcdt6jYd3Tk7cyCEJHjGlhXIgfFQ1Q0DUYeAN75NE29Kad/Yd8kG3VQgHrx/PDme7urKKsPlC1THobyAMC4mEtoFgnGZJDm4GqQldLz+OEzfJU6OM0kORNOeX7K7streG1HUSqFB2ng8cKkpmEM9JIfXMMYOY4y9VFx/DMAmxtj+ADaJa1BKDwRwIoCDABwD4EJKaTiTXgRgI4D9xb9j6kCXHqYwxi4+6S7qnrDsCw/RuFHC0eagtKM7b9bJIO2w6s9JqxUtLVI7ph3iMilDRXM9cvjqb/4o7sUi1Cfk8JfDO/vC6D3jx6JJD2PXuEiAJlpFm/y2n0Rj4ejqMKwmuRyK3eZuLKOWE/Fs5XPVMIf4mCByeG4g/g7lRZYxooCDA4anGKQNrqo8peTQsvcLpGitJmlUUzaMruvad5F7GsmhpTVeV/iOkiSH7l7zvTqiEWqlYwGEOpDLAbxZSr+KMTbDGHsSwGYAR1BK1wDoZYzdIaSFK6Qy9YfJW0m+rIfkUOtHHoHOAyJd/cT0oepi1OjuA/FNRjpadBMpEJMctO63oX1m7V4ge66P3jN9LLr0MG3rM/oySe/GFnZBzQOYdduH/VXlwqRWcgnDkQYuDNEYPkNJ10pDKr3qBCeNs5rUSorNIWETnNUgrUIKyKcH16uVrN5KlrnBUySHifHoxtFyHY42hwU6SrTWM6Q5gFsopRzANxljFwPYgzG2DQAYY9sopWHw83UAfiuV3SLS5sRvNT0GSulGBBIGGGMoFDR6XgD5fN54b7K7G2MAVg+sRk7KM1tchWHxu6e3Dx2a8jP9/RgRv3t7etCuyTPS0YkZAK1tbViluT/V3QV5O0vLwX8Zo3dsy58wKeXp+7s3oU2pa7q/D2GwbdOzjszNIjRltvX0ok+Tb6KnF+MA2tta0au5z2emER6F3rF+b/QUCjF65Twmeor5PEoSc9DlGWppwRyAzu4edCv3J3uC96aCdHbH6ipvAdv2DAoaeqf77H1XQglFAN1dXeU21XzzU2MI93t3dXWhSzdeDjy0PF5WF3aLjLcQs/2VcQcA/atWx+hVt7TpaA7zkFzOOB7CPL29vdqxO9zainCHRMuL/gKr3kRju/fHu7sh75nP5Vsi7c0WB8rP073nWnTqnrmvL/LMnuZ7He/uwYQ0Cfb29cVo3pnLI5/LYRZAd09PrK1SjkCVY/P5PHr6+jAKYFVvL/Kafi7svS/4zDR2SuUIODwvh3x7O/o1zzTZ3aMdnwAwMDCA0uwUhsR1y8Qo/N3XYECpZ0rQtbq/D7Od0XlCBoH5m68namUOL2eMbRUM4KeU0kcteXWsVROIpJweg2A+F4d5ikW9CqNQKMB0zx8LXuHQ0P9v78yj7KjKBP671Z0EsrCEJJCFJYQQSYhEQAK4sRhAWSIzw4WIyMzIIgYGR4wiEgcdccSFozOoA6iAG3rHAY3jwogcZBw9LCooic4gCCNBwSSQpdMQ+vWbP+pWd72qulX39at6/R79/c7p0+9V3br11X1V9d3lW55FMTwErm8Z/im29vXRl3F8fevwz79lyxa2ZZQZtFMnOwYGMmWoz9pv+Mv0vRi89CoGEmUHNwzflurM89g6Zx5bE3XVtw730F3XWnvsf4Y+v7D79Mxyg9vD2PLPb9/Ojix5Y2Eb+gcGeGHDhlT71hPWNFnnqQ1ayx9AXfCe7DL2XNv7+3k+eb0vX5oqD6Dee43z+iNZUvIWtF19U/jq2rZ5s7Nc/bnhfX39/fRn1dM/7DC2afMWVJAevcXvO4DnNm9mnOPeyZN5qD6lcvcDbN22LfPercWm/WrHnszGZ59LlRns72/4XkvIU9823Lbbgl62Z7XL5sYcIoO1WkrmwYSz3dZ5i1IyDwI7+sNu1Lbtfalz1bek5R8YGGBrX3jMsxs3oMYNJ6Zi9r4wYyYbt/VR72scAddffJHawIsM7tjheI4aw8yoC1bB5k3Uf7iGjf0vQOyad/T1QdCTvubtoVybNm6gvsWdZ6U+mG6vZpg1KyNFbAYtjWGNMU/Z/88AtwNHAE/bqSLs/6hT+SSwd+zwOcBTdvucjO0V4Vpz8LBJ9xnyD2U2c0w1TN8LFofLM5keqIA64fThL66pHJ90gnGb89efll0mLzgZJEwgW1iLUWroHGqf/bPLuLKuQTqHBKBOORNVFM01iyIP9Ohe8Al2Fy+fJO6D4bJiS8oyLSPLWLz4x2/O3e8Vw8ljdrTuuvbEtaamB+MjDedzlIxjVuSXASrLLLbBozvHlHWXxlwnQ2bJSY/92sDwSCmWgEudrEPP8I1/zpnSSbTLhJ0IXr+cnmu+EK4txJ+R2kD2GmB8WikvI1+bppVGrBy01pO01lOiz8AJwMPAGiAylzgX+Lb9vAY4S2s9QWs9l3Dh+T47BbVVa32k1loBb40dUx05FhPOcBRei8Aeaw5PW93n1yAhmAAAFY9JREFUcmzadfhmVpOmZBapJ3pwmTRzTT4L0k7fjmJRvMxqffdHuOa0m5ElZ3/9u8avDpdy7PVQDrFje25cg0pGFk0Wj8fiycLLis1jzcEV6K8or0U80kCR42WePD4m4YEaNgvNKh8p3uSLNkgrh/pvHoI/raduYxg1LBZPts9gbYD6Az/JlqUoykHDgvRApvWainJ7b/qzu/O369S2WTK1MnLYE/iJ1voh4D7gu8aYHwAfBZZprR8BltnvGGPWAgZYB/wAWGmMiVrgIuDzhIvUjwLfb0GufPLs8CNGauUCxTb2AM+EyqH+yNrs/fHzO5RDaaasQ+vzDrNPn5FDTDuoY95YLIvrwY8UlGvxNq/OZvBdkM5LoerlYOjhNFmq4YInRSEgIMcHoPHYwb7EzHj8xe86j0/SLK8RUOA2C43Xm0wOFZWNvYAHoxAbz2RMWhQo7IZzReTFnBp4MXvksPseANS3b3OPHObO9wtrUgIjXnMwxjwGpMI2GmM2Asc7jrkauDpj+wPAwekjKqAVayUfomOb9Vp1bZ/sUA5lUc+xE0/itLiJKYcFjp/Rx19iqJLWHQnz6y9SDh51xF9eWVFQk2V8TVlbxeul6jjnc5uGixyw0OvYgccegUNfPbyhYVrJpTRLUg5BMDzCyYyKW2DWG38BR1FPM0bQauKkYgv0onAq8Wtc/wQk/ZbiddRqTuWgese5AwaWzNjzkHauOXjMIcd/FKfTWLTm0KQfQoMssRvdpRy8Qhv4jBwc7ZGF86UeO/awVxXL4nrwXSkhh86fPG6EL9bCaaWEx/GxJ+fX0b89vR/KW695xZHFZSJ8pmNcZX7/v+H/iZNQM+dkl0n8NvUXEtObDfeI58ghy8z6qSeyj42z/okwfwVkByZ0eshn+PZstEYg8ZfypCmhyenOsZHDzPiyafxcie/J3n1SlnUPZsgVMyt3TSv1juuKaaXuxJWy2Cd4nM8isH04CsMUg9/C9/idssuUpRxcCdwz5Sru/Xo5CTmnjQqUwwiSxnjVky7Q+DWaC44TeFxPvL1aiOIbHPOGwjKF52koUzBy23mSe1+i7SaetiKnbsc9mgwDf3E64mj9z3/KkzBNVr6DokjE8ed559DwQy1YPCzXJ24huPbLDTGQ1N4OY4q8bG9hgezj4gx5SLsXpOv9faFzZhvyO4w95eBM6OCxYBqPdX/Qy7PLRC+KVkYOPlMwZc07Dk0r+SgSx1C32SiyIx05JM+zU4YjkQ+FIwePOnxGBfHFWWcvtsm2K8KVnzhOUS70OfvlyNIob0/SWiw+KnD1X+JJs05dkXZ4hHRolSKy2nfcuOx7aWhBOrauMmkK7D4N9bZ3DVfZ2xs6jzY8j573ZvJ3SPzOwaqPuOUazLFWeug+AOo//kH2/hIZe8rBGT4j9t1lBRN7OapdMuYMs86TRyvRX0saWqqjjod5L0MtW15Kfe4TxXvaLoVn/zuVQ+LrqzKXtlCvLYi+si1noRnSL+PM0CMeC+ytWA41lGliiBRbN3DijK4bEpx1fs7OxJRbsq54W7g6MPEXv69FUyHpNlJB4Bj1xT2RLbUaav8F6euBxNqRn3KoJ6e5kh2Z6Rk53YfkqhXPUrRhamkMKofoQ86aw0THsDrP9jiq/u5Qo9fv/69iWRw9zngv02kOWNLIQU3ZhZ7LP4aaOr24cCs3pE/vq3BxPGFL7lDiwTnvyBWl7oqpk32a7J52fC3I154/s0wTCqTZ3nSSyOqmYOpJTduzWJaIpKLv8Rg5xJ8vx/WnkiAV4XoeJmRMy/amrZUYrOWEVfcJPZIcOTQqB7X7Ho3+Flm/pce0UjsZe8ohIrXmEPvsmlf0WXNILtDl0YpV1KDHi7psq4Ym4zk1HuvhFxApH495c3XuJfkFZu2DOvO87GMPPaqg8uTIIa0clE9v0sckt5nQ61kvuqjIa04orieixzGt5FpsjZPIwZHqvDR8z75HG6bYns72d1WnvblQFBXvBPh0biIy/Byo1fziX3lanamF6SRH6sCYJV+Ocqh/7Xrqa3/ZuG+PGahTV6SPqZBWw2d0Ia6Q0jFvYtcD22xvpgCXg5sXPr34spVDK8osatOeHnf7bnk2/zwNmcHyFUjPB69zi1KkfJKDyqOPyy/vm+Uts0wTCiTvmic4POmzcEzZBFdeW5irWO06NdesUykFhx4Nv/ip1z1a7+/L3O4MFNlQKPbMHv7q7DJ5aw6DNeq1Gjx4b6gcfEaArpFOLAx88KmvZj/b0e+oguzfIF73k79v3HXFx1G77E7tO7faLdVPK4095eCz5uBAzZlL8LGboMhL1ZNUcvlmjt1n/zAwVV5vwr5Mgw99ZsTnaTxpCzb5f1of/s8bLm+zzkqbHfPmcY/yvNAWLRO7zhkzUTk9dgC1zBGapOyRQ25Y6OJqiF7Ek7KdutT4CcVTVwVtAeFook74qBWKVZTlLo/AY8E/0/va9tBrNbjjNuq3f9lu91g7cl2Qj1NkbHowU94c5V+4xlkBY085+Fgr5aCsF2Mp5JkMFskx72UE134FNSUntnsT0zRetDJySHqp5uEzZZaXU7lV4i+UIrNPQO3muCdacUjLKuPT/q7850BwyQeo/+wuVCv5AOLJrK6/PbvM0DUV/45q/qLCMsElqx07bHvkXY8to846f9hfJT6ttDEWe7WVmGo+1o6RxdJ4h8GLz3mmTg/Da7imBktk7K05+Pg5tEDwjivCDx49rLybQR3zRpTLoSwqk6cYIDZKKulnLqueInweklr+9EdLlOQtr4IApk5rnBtP0syidd49Gv3UR2QHcwRQiw8juGBV8fnyaIidVCC7x7SmOikjpWmSjPn78GDbHi4DEhi+Z3t6htdHHPkcfMLZqCNeV1jGOZ1YZFjgca8FF10efsjysC6ZsTdycIbPKOnFt/fc8H/e8LwnzHKV5x8QnP321mXJiXI6EtS8BaXUU3wiR7vMexk8aqPCv1jlyMHD7NaTnmu+6HeuvBdDMyOHqilrNBQV9TE+cJm1Dr3sc36joXA2GQ6JSQMTl+NdfPrqgIOyy8TXfIrCzDSpHNTRMZPtyOLJxzimRTrgbms3rjWHkqqP5tRdobaBYPWnnJY0pdKM97MHmc5KVeBYyAzeedXwl0pHDh4+DGXj0/vNfem6hsQl46MsfTLp+eIK707MUspHOTTkiI+lCY0vwLueWZ/nJ+bH4FxMLxo5JDuo+x7AjH+7p9EyL8vSqiLG4MjB/q/qGZo6DabvRfBmd89fzd4XNXvfigSIEfUuOqHH2QyOl4qKOxKVsebgk+O4auUQzYkffLi7zJBSqPjF74NPeyxcAvf+GDXLwzQ2h+Bzt+UrxOi+znOYG5qSy3AsHaw1ejI70+BaGfKCYOZ0BlOyOKacG/yblp9NcMqZoZd2/PmdOAl1zkrUfEdgxBIZe8phiMRNV5JlmBo3np6P3FBcsB0UhaPoVHwc/ApMLosIPnid+2H3CaoHqBUXUL/fEd/fE7XbVIIrPpkfsiJy9qvUQssTj2ml4OjjqS9+Ze6amFr6OupPPp5bj3M6aahAE8ohc+RQo/74I8PbXS/4qJfem5M/xEc52PtKJZIPNRBNnbo6SOMnoF57YvG5SmAMKgdXovr2hMFtKz4mkJ2Ij39GiyMHNWufnJ2J8MoOguNOgeNOaUkOADV3fn6B6MXjY/ZZ9W/d65HMimJjieC8y6i3Ou3kM630qE2VG1fy8amZ+DqDK2zOrrujTjjdGa4F8FQOVt4c5aAWLqH+6G874n3UZV3KEnD5OUTb98hP09hNBO/6EOrE090JgzoNGxEzz0pLvekt4Ycqe9GdpkyjaYicoHpqSZhjOx5VtFLy1kg88QrYmF9B+D9v5BC9ZOMjhGjBOBkyw5XwSimCM/4mv0PhY50YdUzzRg6RAmlTzoY8xtzIQR16dPgjJ3PS1stdvO0E1Jy5qL+a23I9wap/gokjjIDaBD3vTuWBSqHmHhg+YnuOIHe0Jy2/tMpm54mo409FLT3GWUQtWEzPjWuql2XiFNh7LsHp51R/riKiNTWfRfJ46Ao7cqh/6ysNRYK3rByxKCoIUKefg1rkMLuF4Wkpn3WUDoitNPaUw4yZ2WEwrCONOqogVMIYRB1Y7KjULtTCJQRXfCLX2atMgn/8bFvOk4dSCpUXKbWNqN5eej7w6dEWIyQr9HayyDVfoP7Q/aijjh3alhnMcuES1OyckYGPOG88I79A5ECbExpEzd4n7Pz4TFNVTMcoB631ScCngR7g88aYj7bz/GriZILPfrM41r2QSbDy/fm9+clTwvAYzWQ1c6DmHthyHd40E9BNaC/WM11lheW2qKnTUcc68ppHZc67jGCpw7mtRNRxJ0N9MF+eQ5aGz9KiQyuXp4iOmEPRWvcAnwHeACwEVmitq7fVSqDGje+8KYUuQS1Z6k4tCQRvDz071czWemftRrUaJluoDLXP/gQXvge14sLW6nHlyy4Z1TuO4MS/cIaaBztKXLIUlZz2HgU6ZeRwBPA7Y8xjAFrrrwPLgXWjKpVQGmrBYoJLr4KDDhltUYSXEM5orM1QFIZmjNIpymE28IfY9yeBpaMki1AR6uDRHyr7os67rLWQ6kJH03PjGuov7oCNz8jo0EGnKIesuZyUEbTW+gLgAgBjDNOmTcusrLe317mvExF5q2VE8p7sERCuIrqpfbtJVsiQd+as0RPGg9Fs305RDk8CcV/7OUAqRZQx5gYgcj+ub9iwIbOyadOm4drXiYi81SLyVkc3yQoiL8CsWX4KsVOUw/3AfK31XGA9cBZQnCdQEARBqISOsFYyxgwAFwN3AL8JNxlHcHVBEAShajpl5IAx5nvA90ZbDkEQBKFDRg6CIAhCZyHKQRAEQUghykEQBEFIIcpBEARBSKFaTrgxenSt4IIgCKNMYRC5rh05aK1/TniBqT+t9QbXvliZG1stU0YdY1XeEmVpWd42y/KSkrdd9263ydtJz1qyjH13FtK1yqGA5zzKfKeEMmXUAWNT3rJkKUPedsryUpO3XfduWWXG4rPmW6aRer3elX9nnHHGAyPZ14l/Iq/I263ydpOsIm9zdXbzyOGGEe7rRETeahF5q6ObZAWR17vObl6QFgRBECqim0cOgiAIQkV0TGylIrTWXwROAZ4xxhxstx0C/CswGXgcONsYs0VrPR64HjgcGAQuNcbcbY85DLgZ2JkwltOlxphSh08lyno3MBPot1WfYIx5pkxZ7Xn2Br4E7GVluMEY82mt9VTgG8B+VmZtjHnWHvM+4G1ADfg7Y8wddns72rdMee+m4jZuVl6t9R7AN4FXAjcbYy6O1VVp+5Ys6910XtsuAz4KjAd2AKuMMXfZujru3i2Q924qbN9uGjncDJyU2PZ54HJjzGLgdmCV3X4+gN2+DPik1jq61s8RJgyab/+SdXaSrBAqkSX2r3TFYBkALjPGHAQcCay0ObwvB35kjJkP/Mh+x+47C1hEeJ2ftXnAoT3tW6a8UH0bNyUv8DywGnh3Rl1Vt2+ZskLnte0G4FT7vJ0LfDlWV8fduwXyQoXt2zXKwRhzD7ApsXkBcI/9/EMgSt+1kLCBsQ32HHC41nomsIsx5me2R/Al4E2dKGvZMuVhjPmjMeYX9vNWwrDpswnzeN9ii93CcFstB75ujHnBGPN74HfAEW1s31LkLVuusuQ1xvQZY35C+OIdoh3tW5as7WIE8v7SGBMlElsL7KS1ntCp965L3rLlyqJrlIODh4HT7OczGM4m9xCwXGvdaxMIHWb3zSbMOhfxpN3WibJG3KS1flBrvVprraoWUmu9H/AK4F5gT2PMHyG8qYEZtlhWzu/ZjEL7tihvRNva2FNeF21t3xZljejktv1L4JfGmBfo3HvXJW9EZe3b7crhbwmHZT8HphDOyQF8kfDHfQD4FPBTwuFcVuO1y1yrWVkhHDIuBl5j/86pUkCt9WTg34F3GmO25BR1tWNb27cEeaGNbdyEvC7a1r4lyAod3LZa60XANcCFdlOn3rtR+aS8UHH7drVyMMb81hhzgjHmMOBW4FG7fcAY8/d2Hm45sBvwCOFLeE6sisxc1R0iK8aY9fb/VuBrVDgVorUeR3izftUYc5vd/LQdbkdTGtGcpivnd9vatyR529bGTcrroi3tW5KsHdu2Wus5hOt+bzXGPGo3d+q965K38vbtauWgtZ5h/wfAlYTWQGitJ2qtJ9nPy4ABY8w6O1zbqrU+0g7B3gp8uxNltdNM0+z2cYTWTw9XJJsCvgD8xhhzbWzXGsJFMOz/b8e2n2XnaucSLt7d1672LUvedrXxCOTNpB3tW5asndq2WuvdgO8C7zPG/HdUuFPvXZe87WjfbjJlvRU4BpimtX4S+AdgstZ6pS1yG3CT/TwDuENrPQisp3G4dRHD5mrft3+dKOsEu30c0APcCdxYtqyWV9nz/lpr/aDddgWhCZ3RWr8N+D/CtRKMMWu11gZYRzgFttIYU7PHVd6+ZclrlXI72rgpeQG01o8DuwDjtdZvIjRTXEf17VuKrMATdGbbXgwcAKzWWq+22yIT0I67d13yAn1U3L7iIS0IgiCk6OppJUEQBKEaRDkIgiAIKUQ5CIIgCClEOQiCIAgpRDkIgiAIKUQ5CEIFaK3Xaq2PGeGxda31ASWLJAhN0TV+DoLQTRhjFo22DILQCjJyEIQS0VpLh0t4SSA3siBYrKfv9YQerDOBbwEXGWOe11qfAnyYMBnLOuDtxphfxY77HHA2sMB6Xv8OOM8Yc6cOQyxfA2h7KgO8N4quqbVeBbyLMNDbldVfqSAUIyMHQWjkbOBEYB5wIHCl1vpQwui5FwJ7ECqQNboxrv4K4GRgN2PMQGOVvJ8wscsS4BDCAGlXAmitTyJMlLOMMObT66u5LEFoDhk5CEIj1xlj/gCgtb4a+BesQjDG3GvL3KK1voLwhf9ju+2fo+MyOBu4JMrUpbX+IKGCWU04mrjJGPOw3XcVoaIRhFFFlIMgNBJ/wT8BzAL2Bc7VWl8S2zfe7ss6LsksW1ey3mjfzxP7BGHUEeUgCI3E8z7sQxjT/w/A1caYq3OOy4tg+RShglmbqBfgjxnnFIRRR5SDIDSyUmv9H8B2wlDK3yAMsX671vpO4D5gImFI9ntsopUibiVcu7ifUIl8APiK3WcIUz1+CXicMLy7IIw6siAtCI18DfhP4DH792FjzAPA+cB1wLOElkh/3USdHyZMA/sr4NfAL+w2jDHfJ0wPe5et964yLkIQWkXyOQiCxZqknmeMuXO0ZRGE0UZGDoIgCEIKUQ6CIAhCCplWEgRBEFLIyEEQBEFIIcpBEARBSCHKQRAEQUghykEQBEFIIcpBEARBSCHKQRAEQUjx/42r2TDvK6hMAAAAAElFTkSuQmCC\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sorted_data['inc'].plot()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Le plot est un peu compliqué à lire avec tant de données. Zoomons donc sur les dernières années." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sorted_data['inc'][-200:].plot()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A première vue nous ne distinguons pas un pattern aussi clair que lors de l'analyse précédente sur le syndrome grippal." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Etude de l'incidence annuelle" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ " Nous choisissons le 1er septembre comme début de chaque période annuelle, et nous commençons l'analyse à la première année complète, c'est-à-dire en 1991." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "34" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "first_september_weeks = [pd.Period(pd.Timestamp(y, 9, 1), 'W')\n", "for y in range(1991, sorted_data.index[-1].year)]\n", "len(first_september_weeks)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Petit contrôle de cohérence pour vérifier que les périodes définies contiennent bien entre 51 et 52 semaines. " ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "1992 832939\n", "1993 643387\n", "1994 661409\n", "1995 652478\n", "1996 564901\n", "dtype: int64" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "year = []\n", "yearly_incidence = []\n", "for week1, week2 in zip(first_september_weeks[:-1], first_september_weeks[1:]):\n", " one_year = sorted_data['inc'][week1:week2-1]\n", " assert abs(len(one_year)-52) < 2\n", " yearly_incidence.append(one_year.sum())\n", " year.append(week2.year)\n", "yearly_incidence = pd.Series(data = yearly_incidence, index = year)\n", "yearly_incidence.head()" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "yearly_incidence.plot(style = '.')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "On a déjà une idée de quelles années ont eu l'incidence la plus forte. Et on peut aussi remarquer que l'incidence (reportée en tout cas) a été particulièrement faible en 2020, année de COVID et confinements..." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Regardons les plus fortes incidences :" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "2009 842373\n", "1992 832939\n", "2010 829911\n", "2016 782114\n", "2004 777388\n", "dtype: int64" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "yearly_incidence.sort_values(ascending = False)[0:5,]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Puis les plus faibles :" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "2020 221186\n", "2023 366227\n", "2021 376290\n", "2024 479258\n", "2002 516689\n", "dtype: int64" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "yearly_incidence.sort_values()[0:5,]" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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