{"componentChunkName":"component---node-modules-narative-gatsby-theme-novela-src-templates-article-template-tsx","path":"/implications-of-missing-data:-gaps-in-covid-19-data-by-race-and-ethnicity","result":{"data":{"allSite":{"edges":[{"node":{"siteMetadata":{"name":"MIT Civic Data Design Lab"}}}]}},"pageContext":{"article":{"id":"b4d90428-7351-5143-86d7-d3595a436a7d","slug":"/implications-of-missing-data:-gaps-in-covid-19-data-by-race-and-ethnicity","secret":false,"title":"Implications of Missing Data: Gaps in COVID-19 Data by Race & Ethnicity","author":"Chenab Navalkha","date":"June 5th, 2020","dateForSEO":"2020-06-05T00:00:00.000Z","timeToRead":2,"excerpt":"The COVID-19 pandemic has highlighted the importance of collecting and reporting data on health outcomes by race and ethnicity in order to…","canonical_url":null,"subscription":true,"body":"function _extends() { _extends = Object.assign || function (target) { for (var i = 1; i < arguments.length; i++) { var source = arguments[i]; for (var key in source) { if (Object.prototype.hasOwnProperty.call(source, key)) { target[key] = source[key]; } } } return target; }; return _extends.apply(this, arguments); }\n\nfunction _objectWithoutProperties(source, excluded) { if (source == null) return {}; var target = _objectWithoutPropertiesLoose(source, excluded); var key, i; if (Object.getOwnPropertySymbols) { var sourceSymbolKeys = Object.getOwnPropertySymbols(source); for (i = 0; i < sourceSymbolKeys.length; i++) { key = sourceSymbolKeys[i]; if (excluded.indexOf(key) >= 0) continue; if (!Object.prototype.propertyIsEnumerable.call(source, key)) continue; target[key] = source[key]; } } return target; }\n\nfunction _objectWithoutPropertiesLoose(source, excluded) { if (source == null) return {}; var target = {}; var sourceKeys = Object.keys(source); var key, i; for (i = 0; i < sourceKeys.length; i++) { key = sourceKeys[i]; if (excluded.indexOf(key) >= 0) continue; target[key] = source[key]; } return target; }\n\n/* @jsx mdx */\nvar _frontmatter = {\n  \"title\": \"Implications of Missing Data: Gaps in COVID-19 Data by Race & Ethnicity\",\n  \"author\": \"Chenab Navalkha\",\n  \"date\": \"2020-06-05T00:00:00.000Z\",\n  \"tags\": [\"Covid\", \"Health\", \"Mapping\"],\n  \"hero\": \"images/screen-shot-2020-05-22-at-10.08.27-am.png\"\n};\n\nvar makeShortcode = function makeShortcode(name) {\n  return function MDXDefaultShortcode(props) {\n    console.warn(\"Component \" + name + \" was not imported, exported, or provided by MDXProvider as global scope\");\n    return mdx(\"div\", props);\n  };\n};\n\nvar layoutProps = {\n  _frontmatter: _frontmatter\n};\nvar MDXLayout = \"wrapper\";\nreturn function MDXContent(_ref) {\n  var components = _ref.components,\n      props = _objectWithoutProperties(_ref, [\"components\"]);\n\n  return mdx(MDXLayout, _extends({}, layoutProps, props, {\n    components: components,\n    mdxType: \"MDXLayout\"\n  }), mdx(\"p\", null, \"The COVID-19 pandemic has highlighted the importance of collecting and reporting data on health outcomes by race and ethnicity in order to quantify the way in which the virus\\u2019s impacts fall along existing lines of health and structural inequity. Just this past week, the federal government \", mdx(\"a\", _extends({\n    parentName: \"p\"\n  }, {\n    \"href\": \"https://www.npr.org/sections/coronavirus-live-updates/2020/06/04/869815033/race-ethnicity-data-to-be-required-with-coronavirus-tests-in-u-s\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"announced\"), \" that it will require data on race and ethnicity to be collected for all COVID-19 tests.\"), mdx(\"p\", null, \"The push for these data sits within a broader conversation about the importance of collecting racial data that has been ongoing among those working toward \", mdx(\"a\", _extends({\n    parentName: \"p\"\n  }, {\n    \"href\": \"https://www.google.com/url?q=https://www.healthaffairs.org/do/10.1377/hblog20200507.469145/full/?utm_source%3DNewsletter%26utm_medium%3Demail%26utm_content%3DEye%2BOn%2BHealth%2BReform%253A%2BRisk%2BCorridors%252C%2BCOVID-19%252C%2BAnd%2BThe%2BACA%253B%2BCOVID-19%253A%2BFederal%2BFunding%2BFor%2BContact%2BTracing%253B%2BMedicaid%2BMCOs%2BAnd%2BPayment%2BReform%253B%2BInequity%26utm_campaign%3DHAT%2B5-11-20%26&sa=D&ust=1590158619227000&usg=AFQjCNGo8Ae6MN6_8xi21Iua4cbQU62_Yg\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"health equity\"), \" and to mitigate the negative impacts of the \", mdx(\"a\", _extends({\n    parentName: \"p\"\n  }, {\n    \"href\": \"https://www.google.com/url?q=https://patientengagementhit.com/news/social-determinants-of-health-comorbidities-sway-covid-19-severity&sa=D&ust=1590158619229000&usg=AFQjCNHUbDqYt4PiAPAbP4WYpvXRBwCHVg\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"\\u201Csocial determinants of health\\u201D\"), \" \\u2013 or the place-based conditions that impact the health of individuals and communities. \"), mdx(\"p\", null, \"Over the last month or so, \", mdx(\"a\", _extends({\n    parentName: \"p\"\n  }, {\n    \"href\": \"https://www.google.com/url?q=https://www.theatlantic.com/ideas/archive/2020/04/stop-looking-away-race-covid-19-victims/609250/&sa=D&ust=1590158619231000&usg=AFQjCNGvZda446O1AMbKQ8ZIARTVGGXPNw\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"more\"), \" and more articles have been published discussing the disparate impact of COVID-19 on \", mdx(\"a\", _extends({\n    parentName: \"p\"\n  }, {\n    \"href\": \"https://www.google.com/url?q=https://labblog.uofmhealth.org/rounds/racial-disparities-time-of-covid-19&sa=D&ust=1590158619228000&usg=AFQjCNHWT_KM3b_dszEG9VEUE-ItDnojJA\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"African American\"), \", \", mdx(\"a\", _extends({\n    parentName: \"p\"\n  }, {\n    \"href\": \"https://www.washingtonpost.com/national/coronavirus-navajo-nation-crisis/2020/05/11/b2a35c4e-91fe-11ea-a0bc-4e9ad4866d21_story.html\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"Indigenous\"), \", and \", mdx(\"a\", _extends({\n    parentName: \"p\"\n  }, {\n    \"href\": \"https://www.google.com/url?q=https://www.nytimes.com/2020/05/07/us/coronavirus-latinos-disparity.html&sa=D&ust=1590158619219000&usg=AFQjCNGB63MElzGWkmKzA6k6VgNhgCAgtA\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"Latinx\"), \" people. These articles bring to light the ways in which existing inequities \\u2013 both in terms of access to resources and healthcare, and resulting from historic processes of discrimination such as \", mdx(\"a\", _extends({\n    parentName: \"p\"\n  }, {\n    \"href\": \"https://www.npr.org/2017/05/03/526655831/a-forgotten-history-of-how-the-u-s-government-segregated-america\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"redlining\"), \" \\u2013 are manifesting in COVID-19 infection and mortality rates.\"), mdx(\"p\", null, \"This burgeoning discussion also has brought into clear focus the inconsistencies in how data on race and ethnicity are collected and shared at the state level. Some states have robust data on COVID-19 testing results and death rates that include granular information by race and ethnicity and have made these data easily accessible to the public. Other states are lagging behind. \"), mdx(\"p\", null, \"One of the clear principles among those working to mitigate health disparities is the need to collect and report race and ethnicity data in order to understand differences in health outcomes before we can determine how to intervene in order to mitigate these inequities.  \"), mdx(\"p\", null, \"Our lab decided to look into how states have been collecting and sharing data on COVID-19 testing and deaths by race. \", mdx(\"a\", _extends({\n    parentName: \"p\"\n  }, {\n    \"href\": \"https://www.google.com/url?q=https://covidtracking.com/race&sa=D&ust=1590158619219000&usg=AFQjCNESMUbMb9qT-r1q-f8XRMbXnNj73g\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"The COVID Tracking Project\"), \" recently teamed up with the Antiracist Research & Policy Center to aggregate race data by state and to highlight where the gaps are. (Check out their regularly updated racial data tracker \", mdx(\"a\", _extends({\n    parentName: \"p\"\n  }, {\n    \"href\": \"https://www.google.com/url?q=https://docs.google.com/spreadsheets/u/1/d/e/2PACX-1vTfUQPxkhP_CRcGmnnpUBihnTNZ9Z8pcizII4_sc2o2n3opOoAJdAM4CRTJBI339tou8LWnQrqbTMgH/pubhtml%23&sa=D&ust=1590158619220000&usg=AFQjCNEYWrNViMBob1DzXPfjotH7ablwGA\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"here\"), \".)\"), mdx(\"p\", null, \"Using their data, we created these maps that show the percent of missing data on race and ethnicity among those who have tested positive for COVID-19, by state. The darker colors indicate states where the race and ethnicity of those who have tested positive for COVID-19 is least known.\"), mdx(\"iframe\", {\n    id: \"carto\",\n    title: \"Carto Map\",\n    src: \"https://mit.carto.com/u/chenab/builder/760496a1-4886-40c3-be1c-73ae28cfb2b9/embed\",\n    width: \"100%\",\n    height: \"520\",\n    allow: \"\"\n  }), mdx(\"p\", null, mdx(\"em\", {\n    parentName: \"p\"\n  }, \"(Data pulled June 4, 2020 from \", mdx(\"a\", _extends({\n    parentName: \"em\"\n  }, {\n    \"href\": \"https://covidtracking.com/race\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"https://covidtracking.com/race\"), \")\")), mdx(\"iframe\", {\n    id: \"carto-2\",\n    title: \"Carto Map Ethnicity\",\n    src: \"https://mit.carto.com/u/chenab/builder/03122e0c-35fb-4950-be0c-00af2281175c/embed\",\n    width: \"100%\",\n    height: \"520\",\n    allow: \"\"\n  }), mdx(\"p\", null, mdx(\"em\", {\n    parentName: \"p\"\n  }, \"(Data pulled June 4, 2020 from \", mdx(\"a\", _extends({\n    parentName: \"em\"\n  }, {\n    \"href\": \"https://covidtracking.com/race\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"https://covidtracking.com/race\"), \")\")), mdx(\"p\", null, \"It\\u2019s important to note, though, that even where testing data and outcomes are reported by race and ethnicity, an outstanding question remains of who is and isn\\u2019t being tested. Even the most \\u201Ccomplete\\u201D datasets don\\u2019t answer this more fundamental question. Though the federal government\\u2019s new requirement is vital to filling gaps in the data, this question of who is and isn\\u2019t tested will persist until testing becomes more ubiquitous.\"), mdx(\"p\", null, \"Understanding where these data are missing is, of course, just one piece of the larger conversation about how the structural features of our society have left some communities more vulnerable to the pandemic than others. If you\\u2019re interested, \", mdx(\"a\", _extends({\n    parentName: \"p\"\n  }, {\n    \"href\": \"https://www.google.com/url?q=https://www.healthaffairs.org/do/10.1377/hblog20200507.469145/full/?utm_source%3DNewsletter%26utm_medium%3Demail%26utm_content%3DEye%2BOn%2BHealth%2BReform%253A%2BRisk%2BCorridors%252C%2BCOVID-19%252C%2BAnd%2BThe%2BACA%253B%2BCOVID-19%253A%2BFederal%2BFunding%2BFor%2BContact%2BTracing%253B%2BMedicaid%2BMCOs%2BAnd%2BPayment%2BReform%253B%2BInequity%26utm_campaign%3DHAT%2B5-11-20%26&sa=D&ust=1590158619230000&usg=AFQjCNE3I8JdtgTHBTX5Z4m1lHlh8LGnBQ\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"here\"), \" is a great piece that delves into how inequity is playing a role as a \\u201Cpre-existing condition\\u201D in our current healthcare system.\"));\n}\n;\nMDXContent.isMDXComponent = 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The graph above shows the changes of test per capita and percentage of positive tests returned. The size of the circle indicate the…","canonical_url":null,"subscription":true,"body":"function _extends() { _extends = Object.assign || function (target) { for (var i = 1; i < arguments.length; i++) { var source = arguments[i]; for (var key in source) { if (Object.prototype.hasOwnProperty.call(source, key)) { target[key] = source[key]; } } } return target; }; return _extends.apply(this, arguments); }\n\nfunction _objectWithoutProperties(source, excluded) { if (source == null) return {}; var target = _objectWithoutPropertiesLoose(source, excluded); var key, i; if (Object.getOwnPropertySymbols) { var sourceSymbolKeys = Object.getOwnPropertySymbols(source); for (i = 0; i < sourceSymbolKeys.length; i++) { key = sourceSymbolKeys[i]; if (excluded.indexOf(key) >= 0) continue; if (!Object.prototype.propertyIsEnumerable.call(source, key)) continue; target[key] = source[key]; } } return target; }\n\nfunction _objectWithoutPropertiesLoose(source, excluded) { if (source == null) return {}; var target = {}; var sourceKeys = Object.keys(source); var key, i; for (i = 0; i < sourceKeys.length; i++) { key = sourceKeys[i]; if (excluded.indexOf(key) >= 0) continue; target[key] = source[key]; } return target; }\n\n/* @jsx mdx */\nvar _frontmatter = {\n  \"title\": \"Covid-19 Tests and Inequality\",\n  \"author\": \"Zhuangyuan (Yuan) Fan\",\n  \"date\": \"2020-05-29T00:00:00.000Z\",\n  \"tags\": [\"General\", \"Covid\"],\n  \"hero\": \"images/image1-01.jpg\"\n};\n\nvar makeShortcode = function makeShortcode(name) {\n  return function MDXDefaultShortcode(props) {\n    console.warn(\"Component \" + name + \" was not imported, exported, or provided by MDXProvider as global scope\");\n    return mdx(\"div\", props);\n  };\n};\n\nvar layoutProps = {\n  _frontmatter: _frontmatter\n};\nvar MDXLayout = \"wrapper\";\nreturn function MDXContent(_ref) {\n  var components = _ref.components,\n      props = _objectWithoutProperties(_ref, [\"components\"]);\n\n  return mdx(MDXLayout, _extends({}, layoutProps, props, {\n    components: components,\n    mdxType: \"MDXLayout\"\n  }), mdx(\"p\", null, mdx(\"em\", {\n    parentName: \"p\"\n  }, \"Chart 1. The graph above shows the changes of test per capita and percentage of positive tests returned. The size of the circle indicate the median household income\")), mdx(\"h2\", {\n    \"id\": \"introduction\"\n  }, \"Introduction\"), mdx(\"p\", null, mdx(\"a\", _extends({\n    parentName: \"p\"\n  }, {\n    \"href\": \"https://www.newyorker.com/magazine/2020/05/04/seattles-leaders-let-scientists-take-the-lead-new-yorks-did-not\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"New York City was slow to respond to COVID-19.\"), \" It took the city officials over a month to shift adequate testing resources to areas that were suffering most: New York\\u2019s low-income and disproportionately minority neighborhoods and households. \"), mdx(\"p\", null, \"Many journalists and civil society actors have begun to raise alarm at what is proving to be an economic and social disparity in our governments\\u2019 response. 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\"/static/d854378ad53ac6214d29861cb9253466/09625/image4.webp 3000w\"],\n    \"sizes\": \"(max-width: 3000px) 100vw, 3000px\",\n    \"type\": \"image/webp\"\n  })), \"\\n        \", mdx(\"source\", _extends({\n    parentName: \"picture\"\n  }, {\n    \"srcSet\": [\"/static/d854378ad53ac6214d29861cb9253466/412e4/image4.png 2500w\", \"/static/d854378ad53ac6214d29861cb9253466/22748/image4.png 3000w\"],\n    \"sizes\": \"(max-width: 3000px) 100vw, 3000px\",\n    \"type\": \"image/png\"\n  })), \"\\n        \", mdx(\"img\", _extends({\n    parentName: \"picture\"\n  }, {\n    \"className\": \"gatsby-resp-image-image\",\n    \"src\": \"/static/d854378ad53ac6214d29861cb9253466/22748/image4.png\",\n    \"alt\": \"image4\",\n    \"title\": \"New York City Median Household Income and Test Per Capita \",\n    \"loading\": \"lazy\",\n    \"style\": {\n      \"width\": \"100%\",\n      \"height\": \"100%\",\n      \"margin\": \"0\",\n      \"verticalAlign\": \"middle\",\n      \"position\": \"absolute\",\n      \"top\": \"0\",\n      \"left\": \"0\"\n    }\n  })), \"\\n      \"), \"\\n    \")), mdx(\"p\", null, \"Second, to go one step further we divided the median household income and the testing rate per capita into quintiles. We assigned each quintile a score from 1 to 5: 1 representing the lowest quintile and 5 representing the highest quintile. We then add the testing rate per capita score with the household income score created a map that illuminates where there is disparity between income and testing. A score of 10 represents the highest income and  testing rates, while a score of 2 represents lowest income and testing rates. In the map (Graph 4.1) we can see the extreme color of blue and red diminishing between early April and early May. However, there are still places that remain at score 2.\"), mdx(\"p\", null, \"If we plot positive returns per test rate (at zip code level) by quintile against the test per capita by quintile (Graph 4.2), we show a map with dark red indicating very high likelihood of getting a positive return per test but the overall tests per capita remain low. The blue color indicates the zip code has a very positive per test rate but high test per capita rate. These maps uncover the fact that even with the trend reversing, we still have many zip codes that are left behind. For example, as of May 4th, Flushing in Queens (11355) has a positive cases per test rate as high as 46.7% but their overall test per capita is less than 3%. On the contrary, Staten Island (10305) has a positive cases per test rate at 36.9% and its overall test per capita rate is around 7.2%. \"), mdx(\"p\", null, mdx(\"span\", _extends({\n    parentName: \"p\"\n  }, {\n    \"className\": \"gatsby-resp-image-wrapper\",\n    \"style\": {\n      \"position\": \"relative\",\n      \"display\": \"block\",\n      \"marginLeft\": \"auto\",\n      \"marginRight\": \"auto\",\n      \"maxWidth\": \"1574px\"\n    }\n  }), \"\\n      \", mdx(\"span\", _extends({\n    parentName: \"span\"\n  }, {\n    \"className\": \"gatsby-resp-image-background-image\",\n    \"style\": {\n      \"paddingBottom\": \"58.83100381194409%\",\n      \"position\": \"relative\",\n      \"bottom\": \"0\",\n      \"left\": \"0\",\n      \"backgroundImage\": 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     \"backgroundSize\": \"cover\",\n      \"display\": \"block\"\n    }\n  })), \"\\n  \", mdx(\"picture\", {\n    parentName: \"span\"\n  }, \"\\n        \", mdx(\"source\", _extends({\n    parentName: \"picture\"\n  }, {\n    \"srcSet\": [\"/static/8f267b3f473b3a575e179b2b67d2afff/62d33/mapforweb2.webp 1574w\"],\n    \"sizes\": \"(max-width: 1574px) 100vw, 1574px\",\n    \"type\": \"image/webp\"\n  })), \"\\n        \", mdx(\"source\", _extends({\n    parentName: \"picture\"\n  }, {\n    \"srcSet\": [\"/static/8f267b3f473b3a575e179b2b67d2afff/2c1f1/mapforweb2.png 1574w\"],\n    \"sizes\": \"(max-width: 1574px) 100vw, 1574px\",\n    \"type\": \"image/png\"\n  })), \"\\n        \", mdx(\"img\", _extends({\n    parentName: \"picture\"\n  }, {\n    \"className\": \"gatsby-resp-image-image\",\n    \"src\": \"/static/8f267b3f473b3a575e179b2b67d2afff/2c1f1/mapforweb2.png\",\n    \"alt\": \"mapforweb2\",\n    \"title\": \"Positive per test rate vs. Test per capita\",\n    \"loading\": \"lazy\",\n    \"style\": {\n      \"width\": \"100%\",\n      \"height\": \"100%\",\n      \"margin\": \"0\",\n      \"verticalAlign\": \"middle\",\n      \"position\": \"absolute\",\n      \"top\": \"0\",\n      \"left\": \"0\"\n    }\n  })), \"\\n      \"), \"\\n    \")), mdx(\"p\", null, \"There are potentially many factors that contributed to New York\\u2019s decisions on where to allocation COVID19 resources. It could be because her healthcare system is just simply responding to the number of confirmed cases. Whatever the reason, we all have an obligation to understand and learn from these failings in order to better inform more equitable designs and plans. Many of us don\\u2019t have the luxury of time. So it is left to our planners, policy-makers, and public health officials to ensure that we make the very best of it. To know and never doubt that income should never dictate the acquisition of something so priceless - a life well lived\"), mdx(\"h2\", {\n    \"id\": \"reference\"\n  }, \"Reference:\"), mdx(\"p\", null, \"[\", \"1] Borjas, G. J. (2020).\", mdx(\"em\", {\n    parentName: \"p\"\n  }, \"Demographic determinants of testing incidence and COVID-19 infections in New York City neighborhoods\"), \"(No. w26952). National Bureau of Economic Research.\"), mdx(\"p\", null, \"[\", \"2] Schmitt-Groh\\xE9, S., Teoh, K., & Uribe, M. (2020).\", mdx(\"em\", {\n    parentName: \"p\"\n  }, \"Covid-19: Testing Inequality in New York City\"), \"(No. w27019). National Bureau of Economic Research.\"));\n}\n;\nMDXContent.isMDXComponent = 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Here is a survey of professional guidance on this topic.","canonical_url":null,"subscription":true,"body":"function _extends() { _extends = Object.assign || function (target) { for (var i = 1; i < arguments.length; i++) { var source = arguments[i]; for (var key in source) { if (Object.prototype.hasOwnProperty.call(source, key)) { target[key] = source[key]; } } } return target; }; return _extends.apply(this, arguments); }\n\nfunction _objectWithoutProperties(source, excluded) { if (source == null) return {}; var target = _objectWithoutPropertiesLoose(source, excluded); var key, i; if (Object.getOwnPropertySymbols) { var sourceSymbolKeys = Object.getOwnPropertySymbols(source); for (i = 0; i < sourceSymbolKeys.length; i++) { key = sourceSymbolKeys[i]; if (excluded.indexOf(key) >= 0) continue; if (!Object.prototype.propertyIsEnumerable.call(source, key)) continue; target[key] = source[key]; } } return target; }\n\nfunction _objectWithoutPropertiesLoose(source, excluded) { if (source == null) return {}; var target = {}; var sourceKeys = Object.keys(source); var key, i; for (i = 0; i < sourceKeys.length; i++) { key = sourceKeys[i]; if (excluded.indexOf(key) >= 0) continue; target[key] = source[key]; } return target; }\n\n/* @jsx mdx */\nvar _frontmatter = {\n  \"title\": \"Creating Best Practices for Visualizing Covid Data\",\n  \"author\": \"Griffin Kantz\",\n  \"date\": \"2020-05-21T00:00:00.000Z\",\n  \"excerpt\": \"The global importance of the SARS-CoV-2/COVID-19 pandemic, and the salience of eye-catching data visualizations in these times, necessitate a profoundly judicious use of data variables and normalizations. Here is a survey of professional guidance on this topic.\",\n  \"tags\": [\"Covid\", \"Data\", \"Visualization\"],\n  \"hero\": \"images/blog_griffin-k_responsible-covid-data-visualization_header.png\"\n};\n\nvar makeShortcode = function makeShortcode(name) {\n  return function MDXDefaultShortcode(props) {\n    console.warn(\"Component \" + name + \" was not imported, exported, or provided by MDXProvider as global scope\");\n    return mdx(\"div\", props);\n  };\n};\n\nvar layoutProps = {\n  _frontmatter: _frontmatter\n};\nvar MDXLayout = \"wrapper\";\nreturn function MDXContent(_ref) {\n  var components = _ref.components,\n      props = _objectWithoutProperties(_ref, [\"components\"]);\n\n  return mdx(MDXLayout, _extends({}, layoutProps, props, {\n    components: components,\n    mdxType: \"MDXLayout\"\n  }), mdx(\"p\", null, \"The global importance of the SARS-CoV-2/COVID-19 pandemic, and the salience of eye-catching data visualizations in these times, necessitate a profoundly judicious use of data variables and normalizations. 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     \"backgroundSize\": \"cover\",\n      \"display\": \"block\"\n    }\n  })), \"\\n  \", mdx(\"picture\", {\n    parentName: \"span\"\n  }, \"\\n        \", mdx(\"source\", _extends({\n    parentName: \"picture\"\n  }, {\n    \"srcSet\": [\"/static/aaa42fa7f634e3b8184b58478608815f/909b8/screen-shot-2020-05-19-at-6.44.47-am.webp 1328w\"],\n    \"sizes\": \"(max-width: 1328px) 100vw, 1328px\",\n    \"type\": \"image/webp\"\n  })), \"\\n        \", mdx(\"source\", _extends({\n    parentName: \"picture\"\n  }, {\n    \"srcSet\": [\"/static/aaa42fa7f634e3b8184b58478608815f/fa900/screen-shot-2020-05-19-at-6.44.47-am.png 1328w\"],\n    \"sizes\": \"(max-width: 1328px) 100vw, 1328px\",\n    \"type\": \"image/png\"\n  })), \"\\n        \", mdx(\"img\", _extends({\n    parentName: \"picture\"\n  }, {\n    \"className\": \"gatsby-resp-image-image\",\n    \"src\": \"/static/aaa42fa7f634e3b8184b58478608815f/fa900/screen-shot-2020-05-19-at-6.44.47-am.png\",\n    \"alt\": \"Tweet by Ferris Jabr: \\\"Following numerous critiques, the most inaccurate tweet in the original viral thread disappeared/was probably deleted without explanation or follow-up correction. For transparency and posterity, this is what it looked like.  The info in the pictured tweet is unequivocally wrong\\\" [image of tweet by Dr. Eric Feigl Ding: \\\"SUMMARY: So what does this mean for the world??? We are now faced with the most virulent virus epidemic the world has ever seen. An R0=3.8 means that it exceeds SARS's modest 0.49 viral attack rate by 7.75x -- almost 8 fold! A virus that spreads 8 times faster than SARS...\\\"]\",\n    \"title\": \"tweet4\",\n    \"loading\": \"lazy\",\n    \"style\": {\n      \"width\": \"100%\",\n      \"height\": \"100%\",\n      \"margin\": \"0\",\n      \"verticalAlign\": \"middle\",\n      \"position\": \"absolute\",\n      \"top\": \"0\",\n      \"left\": \"0\"\n    }\n  })), \"\\n      \"), \"\\n    \")), mdx(\"p\", null, \"Even among infectious disease experts, consensus on the best practices for modeling the incoming data would adapt over time (\", mdx(\"a\", _extends({\n    parentName: \"p\"\n  }, {\n    \"href\": \"https://twitter.com/neil_ferguson/status/1243294815200124928\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"thread\"), \"):\"), mdx(\"p\", null, mdx(\"span\", _extends({\n    parentName: \"p\"\n  }, {\n    \"className\": \"gatsby-resp-image-wrapper\",\n    \"style\": {\n      \"position\": \"relative\",\n      \"display\": \"block\",\n      \"marginLeft\": \"auto\",\n      \"marginRight\": \"auto\",\n      \"maxWidth\": \"1324px\"\n    }\n  }), \"\\n      \", mdx(\"span\", _extends({\n    parentName: \"span\"\n  }, {\n    \"className\": \"gatsby-resp-image-background-image\",\n    \"style\": {\n      \"paddingBottom\": \"52.87009063444109%\",\n      \"position\": \"relative\",\n      \"bottom\": \"0\",\n      \"left\": \"0\",\n      \"backgroundImage\": \"url('data:image/png;base64,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')\",\n      \"backgroundSize\": \"cover\",\n      \"display\": \"block\"\n    }\n  })), \"\\n  \", mdx(\"picture\", {\n    parentName: \"span\"\n  }, \"\\n        \", mdx(\"source\", _extends({\n    parentName: \"picture\"\n  }, {\n    \"srcSet\": [\"/static/3d8969f7f0e3203a38c7436bd7f5772c/33b3d/screen-shot-2020-05-19-at-6.45.02-am.webp 1324w\"],\n    \"sizes\": \"(max-width: 1324px) 100vw, 1324px\",\n    \"type\": \"image/webp\"\n  })), \"\\n        \", mdx(\"source\", _extends({\n    parentName: \"picture\"\n  }, {\n    \"srcSet\": [\"/static/3d8969f7f0e3203a38c7436bd7f5772c/b58f7/screen-shot-2020-05-19-at-6.45.02-am.png 1324w\"],\n    \"sizes\": \"(max-width: 1324px) 100vw, 1324px\",\n    \"type\": \"image/png\"\n  })), \"\\n        \", mdx(\"img\", _extends({\n    parentName: \"picture\"\n  }, {\n    \"className\": \"gatsby-resp-image-image\",\n    \"src\": \"/static/3d8969f7f0e3203a38c7436bd7f5772c/b58f7/screen-shot-2020-05-19-at-6.45.02-am.png\",\n    \"alt\": \"Tweet by neil_ferguson: \\\"1/4 - I think it would be helpful if I cleared up some confusion that has emerged in recent days. Some have interpreted my evidence to a UK parliamentary committee as indicating we have substantially revised our assessments of the potential mortality impact of COVID-19.\\\"\",\n    \"title\": \"tweet5\",\n    \"loading\": \"lazy\",\n    \"style\": {\n      \"width\": \"100%\",\n      \"height\": \"100%\",\n      \"margin\": \"0\",\n      \"verticalAlign\": \"middle\",\n      \"position\": \"absolute\",\n      \"top\": \"0\",\n      \"left\": \"0\"\n    }\n  })), \"\\n      \"), \"\\n    \")), mdx(\"p\", null, \"All these epistemological limitations fit under the umbrella of the \", mdx(\"a\", _extends({\n    parentName: \"p\"\n  }, {\n    \"href\": \"https://en.wikipedia.org/wiki/Dunning%E2%80%93Kruger_effect\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"Dunning-Kruger effect\"), \":\"), mdx(\"p\", null, mdx(\"span\", _extends({\n    parentName: \"p\"\n  }, {\n    \"className\": \"gatsby-resp-image-wrapper\",\n    \"style\": {\n      \"position\": \"relative\",\n      \"display\": \"block\",\n      \"marginLeft\": \"auto\",\n      \"marginRight\": \"auto\",\n      \"maxWidth\": \"800px\"\n    }\n  }), \"\\n      \", mdx(\"span\", _extends({\n    parentName: \"span\"\n  }, {\n    \"className\": \"gatsby-resp-image-background-image\",\n    \"style\": {\n      \"paddingBottom\": \"71.74999999999999%\",\n      \"position\": \"relative\",\n      \"bottom\": \"0\",\n      \"left\": \"0\",\n      \"backgroundImage\": \"url('data:image/jpeg;base64,/9j/2wBDABALDA4MChAODQ4SERATGCgaGBYWGDEjJR0oOjM9PDkzODdASFxOQERXRTc4UG1RV19iZ2hnPk1xeXBkeFxlZ2P/2wBDARESEhgVGC8aGi9jQjhCY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2P/wgARCAAOABQDASIAAhEBAxEB/8QAFwABAAMAAAAAAAAAAAAAAAAAAAECBf/EABQBAQAAAAAAAAAAAAAAAAAAAAD/2gAMAwEAAhADEAAAAdxYEj//xAAXEAEAAwAAAAAAAAAAAAAAAAAQABEh/9oACAEBAAEFApbp/8QAFBEBAAAAAAAAAAAAAAAAAAAAEP/aAAgBAwEBPwE//8QAFBEBAAAAAAAAAAAAAAAAAAAAEP/aAAgBAgEBPwE//8QAFBABAAAAAAAAAAAAAAAAAAAAIP/aAAgBAQAGPwJf/8QAHBAAAgICAwAAAAAAAAAAAAAAABEBIRAxQWGB/9oACAEBAAE/IX2ikbgh8is8Y//aAAwDAQACAAMAAAAQ4w//xAAUEQEAAAAAAAAAAAAAAAAAAAAQ/9oACAEDAQE/ED//xAAUEQEAAAAAAAAAAAAAAAAAAAAQ/9oACAECAQE/ED//xAAdEAEAAgICAwAAAAAAAAAAAAABABEhMUFhUXGB/9oACAEBAAE/EG1r4MvcBka9YY0afI7rfUC2cOoXyz//2Q==')\",\n      \"backgroundSize\": \"cover\",\n      \"display\": \"block\"\n    }\n  })), \"\\n  \", mdx(\"picture\", {\n    parentName: \"span\"\n  }, \"\\n        \", mdx(\"source\", _extends({\n    parentName: \"picture\"\n  }, {\n    \"srcSet\": [\"/static/658e085757182365014640f9cc50c084/8d2ea/image1.webp 800w\"],\n    \"sizes\": \"(max-width: 800px) 100vw, 800px\",\n    \"type\": \"image/webp\"\n  })), \"\\n        \", mdx(\"source\", _extends({\n    parentName: \"picture\"\n  }, {\n    \"srcSet\": [\"/static/658e085757182365014640f9cc50c084/c60e9/image1.jpg 800w\"],\n    \"sizes\": \"(max-width: 800px) 100vw, 800px\",\n    \"type\": \"image/jpeg\"\n  })), \"\\n        \", mdx(\"img\", _extends({\n    parentName: \"picture\"\n  }, {\n    \"className\": \"gatsby-resp-image-image\",\n    \"src\": \"/static/658e085757182365014640f9cc50c084/c60e9/image1.jpg\",\n    \"alt\": \"Dunning-Kruger Effect. Diagram showing relationship between knowledge in field and confidence.\",\n    \"title\": \"Dunning-Kruger\",\n    \"loading\": \"lazy\",\n    \"style\": {\n      \"width\": \"100%\",\n      \"height\": \"100%\",\n      \"margin\": \"0\",\n      \"verticalAlign\": \"middle\",\n      \"position\": \"absolute\",\n      \"top\": \"0\",\n      \"left\": \"0\"\n    }\n  })), \"\\n      \"), \"\\n    \")), mdx(\"p\", null, mdx(\"em\", {\n    parentName: \"p\"\n  }, \"Original creator of this diagram unknown.\")), mdx(\"p\", null, \"Following this evolving consensus on best practices, we can often observe improvements over time in some of the COVID data visualizations which have managed to reach a wider audience, and these revisions are instructive.\"), mdx(\"p\", null, \"For example, \", mdx(\"a\", _extends({\n    parentName: \"p\"\n  }, {\n    \"href\": \"https://covidactnow.org/\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"covidactnow.org\"), \" has added models of the infection growth rate (with confidence intervals) and the positive test rate to its forecasts of state-by-state hospital capacity, which were more simplistic \", mdx(\"a\", _extends({\n    parentName: \"p\"\n  }, {\n    \"href\": \"https://web.archive.org/web/20200327060650/http:/www.covidactnow.org/state/NY\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"in the site\\u2019s first few weeks\"), \".\"), mdx(\"p\", null, \"The \", mdx(\"a\", _extends({\n    parentName: \"p\"\n  }, {\n    \"href\": \"http://91-divoc.com/pages/covid-visualization/\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"interactive COVID tool at 91-divoc.com\"), \" was already making the best of multiple approaches upon its debut, showing gross and per-capita case counts by country and region, and allowing users to toggle between linear and logarithmic scales on the y-axis. Like other popular COVID tools, 91-divoc brackets the x-axes of its graphs around early quantitative thresholds such as \", mdx(\"em\", {\n    parentName: \"p\"\n  }, \"days since 100 cases\"), \", and by late April had shifted its default view from total cases to one-week trailing averages of new cases to better illustrate flattening growth. In mid-April the site added forecast trendlines for countries, but days later opted to truncate those forecasts to seven days forward so as to \\u201Cavoid extreme extrapolation\\u201D. Peruse 91-divoc\\u2019s change log \", mdx(\"a\", _extends({\n    parentName: \"p\"\n  }, {\n    \"href\": \"http://91-divoc.com/pages/covid-visualization/changes.html\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"here\"), \".\"), mdx(\"p\", null, \"The most important prevailing debates on best practices for COVID data visualization concern the proper selection of variables and denominators.\"), mdx(\"p\", null, \"The modeler\\u2019s choice between gross counts and per-capita normalizations depends on the purpose of their model. Gross counts accurately measure the growth of local outbreaks, whereas per-capita rates better depict the burden on a nation/region\\u2019s healthcare system and policymaking apparatus. Some sentiments in favor of per-capita normalizations are \", mdx(\"a\", _extends({\n    parentName: \"p\"\n  }, {\n    \"href\": \"https://twitter.com/NateSilver538/status/1245132431818178561\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"quite inflexble\"), \", but perhaps wrongly so. Observe the linear graph of cases by country captured on March 25 from 91-divoc\\u2019s tool:\"), mdx(\"p\", null, mdx(\"span\", _extends({\n    parentName: \"p\"\n  }, {\n    \"className\": \"gatsby-resp-image-wrapper\",\n    \"style\": {\n      \"position\": \"relative\",\n      \"display\": \"block\",\n      \"marginLeft\": \"auto\",\n      \"marginRight\": \"auto\",\n      \"maxWidth\": \"960px\"\n    }\n  }), \"\\n      \", mdx(\"span\", _extends({\n    parentName: \"span\"\n  }, {\n    \"className\": \"gatsby-resp-image-background-image\",\n    \"style\": {\n      \"paddingBottom\": \"55.104166666666664%\",\n      \"position\": \"relative\",\n      \"bottom\": \"0\",\n      \"left\": \"0\",\n      \"backgroundImage\": 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\"picture\"\n  }, {\n    \"srcSet\": [\"/static/46ecf1d1e90e59fe79421cb3eb716699/6c7d1/image2.webp 960w\"],\n    \"sizes\": \"(max-width: 960px) 100vw, 960px\",\n    \"type\": \"image/webp\"\n  })), \"\\n        \", mdx(\"source\", _extends({\n    parentName: \"picture\"\n  }, {\n    \"srcSet\": [\"/static/46ecf1d1e90e59fe79421cb3eb716699/1fe05/image2.jpg 960w\"],\n    \"sizes\": \"(max-width: 960px) 100vw, 960px\",\n    \"type\": \"image/jpeg\"\n  })), \"\\n        \", mdx(\"img\", _extends({\n    parentName: \"picture\"\n  }, {\n    \"className\": \"gatsby-resp-image-image\",\n    \"src\": \"/static/46ecf1d1e90e59fe79421cb3eb716699/1fe05/image2.jpg\",\n    \"alt\": \"COVID-19 Cases by Country from 91-divoc.com, captured on March 25, 2020.\",\n    \"title\": \"COVID-19 Cases by Country from 91-divoc.com, captured on March 25, 2020.\",\n    \"loading\": \"lazy\",\n    \"style\": {\n      \"width\": \"100%\",\n      \"height\": \"100%\",\n      \"margin\": \"0\",\n      \"verticalAlign\": \"middle\",\n      \"position\": \"absolute\",\n      \"top\": \"0\",\n      \"left\": \"0\"\n    }\n  })), \"\\n      \"), \"\\n    \")), mdx(\"p\", null, \"Now observe the linear graph of cases per capita, captured on the same day from the same tool:\"), mdx(\"p\", null, mdx(\"span\", _extends({\n    parentName: \"p\"\n  }, {\n    \"className\": \"gatsby-resp-image-wrapper\",\n    \"style\": {\n      \"position\": \"relative\",\n      \"display\": \"block\",\n      \"marginLeft\": \"auto\",\n      \"marginRight\": \"auto\",\n      \"maxWidth\": \"960px\"\n    }\n  }), \"\\n      \", mdx(\"span\", _extends({\n    parentName: \"span\"\n  }, {\n    \"className\": \"gatsby-resp-image-background-image\",\n    \"style\": {\n      \"paddingBottom\": \"55.208333333333336%\",\n      \"position\": \"relative\",\n      \"bottom\": \"0\",\n      \"left\": \"0\",\n      \"backgroundImage\": 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\"picture\"\n  }, {\n    \"srcSet\": [\"/static/0d552191a3e2c10067d053bce86032a9/6c7d1/image3.webp 960w\"],\n    \"sizes\": \"(max-width: 960px) 100vw, 960px\",\n    \"type\": \"image/webp\"\n  })), \"\\n        \", mdx(\"source\", _extends({\n    parentName: \"picture\"\n  }, {\n    \"srcSet\": [\"/static/0d552191a3e2c10067d053bce86032a9/1fe05/image3.jpg 960w\"],\n    \"sizes\": \"(max-width: 960px) 100vw, 960px\",\n    \"type\": \"image/jpeg\"\n  })), \"\\n        \", mdx(\"img\", _extends({\n    parentName: \"picture\"\n  }, {\n    \"className\": \"gatsby-resp-image-image\",\n    \"src\": \"/static/0d552191a3e2c10067d053bce86032a9/1fe05/image3.jpg\",\n    \"alt\": \"COVID-19 Cases per Capita by Country from 91-divoc.com, captured on March 25, 2020.\",\n    \"title\": \"COVID-19 Cases per Capita by Country from 91-divoc.com, captured on March 25, 2020.\",\n    \"loading\": \"lazy\",\n    \"style\": {\n      \"width\": \"100%\",\n      \"height\": \"100%\",\n      \"margin\": \"0\",\n      \"verticalAlign\": \"middle\",\n      \"position\": \"absolute\",\n      \"top\": \"0\",\n      \"left\": \"0\"\n    }\n  })), \"\\n      \"), \"\\n    \")), mdx(\"p\", null, \"It would seem here that the Vatican City is careening towards anarchy at an unprecedented rate\\u2014an incorrect implication emerging from our choice of scale and normalization.\"), mdx(\"p\", null, \"Here John Burn-Murdoch, whose graphs for the \", mdx(\"em\", {\n    parentName: \"p\"\n  }, \"Financial Times\"), \" have earned praise, makes his team\\u2019s case against using per-capita rates in graphs (\", mdx(\"a\", _extends({\n    parentName: \"p\"\n  }, {\n    \"href\": \"https://twitter.com/jburnmurdoch/status/1249445458264698880?ref_src=twsrc%5Etfw\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"link\"), \"):\"), mdx(\"p\", null, mdx(\"span\", _extends({\n    parentName: \"p\"\n  }, {\n    \"className\": \"gatsby-resp-image-wrapper\",\n    \"style\": {\n      \"position\": 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     \"backgroundSize\": \"cover\",\n      \"display\": \"block\"\n    }\n  })), \"\\n  \", mdx(\"picture\", {\n    parentName: \"span\"\n  }, \"\\n        \", mdx(\"source\", _extends({\n    parentName: \"picture\"\n  }, {\n    \"srcSet\": [\"/static/9d60f9c11fb960caa002786bff6b6a4c/3bde5/screen-shot-2020-05-19-at-6.48.50-am.webp 506w\"],\n    \"sizes\": \"(max-width: 506px) 100vw, 506px\",\n    \"type\": \"image/webp\"\n  })), \"\\n        \", mdx(\"source\", _extends({\n    parentName: \"picture\"\n  }, {\n    \"srcSet\": [\"/static/9d60f9c11fb960caa002786bff6b6a4c/30942/screen-shot-2020-05-19-at-6.48.50-am.png 506w\"],\n    \"sizes\": \"(max-width: 506px) 100vw, 506px\",\n    \"type\": \"image/png\"\n  })), \"\\n        \", mdx(\"img\", _extends({\n    parentName: \"picture\"\n  }, {\n    \"className\": \"gatsby-resp-image-image\",\n    \"src\": \"/static/9d60f9c11fb960caa002786bff6b6a4c/30942/screen-shot-2020-05-19-at-6.48.50-am.png\",\n    \"alt\": \"Tweets by John Burn-Murdoch: \\\"Here’s a video where I explain why we’re using log scales, showing absolute numbers instead of per capita, and much more: [video link: 'Everything you need to know about that pink graph mapping coronavirus death rates by country by @jburnmurdoch'] And a chart showing why we're using absolute numbers rather than population-adjusted rates: [linked tweet: 'A quick chart for those who keep asking for per-capita adjustment:  Here’s population vs total death toll one week after 10th death.  No relationship.  As I’ve been saying, population does not affect pace of spread. All per-capita figures do is make smaller countries look worse.'] [scatter plot chart with trendline] \\\"\",\n    \"title\": \"tweet05\",\n    \"loading\": \"lazy\",\n    \"style\": {\n      \"width\": \"100%\",\n      \"height\": \"100%\",\n      \"margin\": \"0\",\n      \"verticalAlign\": \"middle\",\n      \"position\": \"absolute\",\n      \"top\": \"0\",\n      \"left\": \"0\"\n    }\n  })), \"\\n      \"), \"\\n    \")), mdx(\"p\", null, \"In the \", mdx(\"a\", _extends({\n    parentName: \"p\"\n  }, {\n    \"href\": \"https://twitter.com/CT_Bergstrom/status/1249930293928030209\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"thread below\"), \", Carl T. Bergstrom of the University of Washington explains how per-capita rates \", mdx(\"em\", {\n    parentName: \"p\"\n  }, \"can\"), \" be responsibly compared between countries if the curves are left-aligned to starting positions of a given fractional infection rate. However, he also advises that per-capita comparisons between regions are preferable to those between countries.\"), mdx(\"p\", null, mdx(\"span\", _extends({\n    parentName: \"p\"\n  }, {\n    \"className\": \"gatsby-resp-image-wrapper\",\n    \"style\": {\n      \"position\": \"relative\",\n      \"display\": \"block\",\n      \"marginLeft\": \"auto\",\n      \"marginRight\": \"auto\",\n      \"maxWidth\": \"1346px\"\n    }\n  }), \"\\n      \", mdx(\"span\", _extends({\n    parentName: \"span\"\n  }, {\n    \"className\": \"gatsby-resp-image-background-image\",\n    \"style\": {\n      \"paddingBottom\": \"62.704309063893014%\",\n      \"position\": \"relative\",\n      \"bottom\": \"0\",\n      \"left\": \"0\",\n      \"backgroundImage\": \"url('data:image/png;base64,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')\",\n      \"backgroundSize\": \"cover\",\n      \"display\": \"block\"\n    }\n  })), \"\\n  \", mdx(\"picture\", {\n    parentName: \"span\"\n  }, \"\\n        \", mdx(\"source\", _extends({\n    parentName: \"picture\"\n  }, {\n    \"srcSet\": [\"/static/3f8f0179165a2e9a980f52c1b3c9d7af/8170e/screen-shot-2020-05-19-at-6.50.42-am.webp 1346w\"],\n    \"sizes\": \"(max-width: 1346px) 100vw, 1346px\",\n    \"type\": \"image/webp\"\n  })), \"\\n        \", mdx(\"source\", _extends({\n    parentName: \"picture\"\n  }, {\n    \"srcSet\": [\"/static/3f8f0179165a2e9a980f52c1b3c9d7af/4eb26/screen-shot-2020-05-19-at-6.50.42-am.png 1346w\"],\n    \"sizes\": \"(max-width: 1346px) 100vw, 1346px\",\n    \"type\": \"image/png\"\n  })), \"\\n        \", mdx(\"img\", _extends({\n    parentName: \"picture\"\n  }, {\n    \"className\": \"gatsby-resp-image-image\",\n    \"src\": \"/static/3f8f0179165a2e9a980f52c1b3c9d7af/4eb26/screen-shot-2020-05-19-at-6.50.42-am.png\",\n    \"alt\": \"Tweet by Carl T. Bergstrom: \\\"1. When plotting epidemic curves or death totals, should we divide by population size? Here on twitter this question has generated a lot more heat than light.   The answer is a bit subtle and so while I’ve tweeted about this before I want to address it in more detail.\\\"\",\n    \"title\": \"tweet06\",\n    \"loading\": \"lazy\",\n    \"style\": {\n      \"width\": \"100%\",\n      \"height\": \"100%\",\n      \"margin\": \"0\",\n      \"verticalAlign\": \"middle\",\n      \"position\": \"absolute\",\n      \"top\": \"0\",\n      \"left\": \"0\"\n    }\n  })), \"\\n      \"), \"\\n    \")), mdx(\"p\", null, \"There is also volatile disagreement on the proper selection of variables. Many sources, \", mdx(\"a\", _extends({\n    parentName: \"p\"\n  }, {\n    \"href\": \"https://fivethirtyeight.com/features/coronavirus-case-counts-are-meaningless/\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), mdx(\"em\", {\n    parentName: \"a\"\n  }, \"FiveThirtyEight\"), \" among them\"), \", point out the futility of using reported case counts from governments (of inconsistent trustworthiness) using inconsistent testing methods. Burn-Murdoch\\u2019s detractors critique his visuals\\u2019 acceptance of China\\u2019s published counts at face value. \", mdx(\"a\", _extends({\n    parentName: \"p\"\n  }, {\n    \"href\": \"https://blog.datawrapper.de/coronaviruscharts/\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"Datawrapper\"), \" recommends avoiding this problem by instead using confirmed death counts, which are harder to misreport but still imperfect since COVID can be an indirect cause of death.\"), mdx(\"p\", null, \"What are some general best practices and precautions for analyzing and visualizing COVID data? Here are some excellent sources addressing this question.\"), mdx(\"ul\", null, mdx(\"li\", {\n    parentName: \"ul\"\n  }, mdx(\"strong\", {\n    parentName: \"li\"\n  }, mdx(\"a\", _extends({\n    parentName: \"strong\"\n  }, {\n    \"href\": \"https://www.tableau.com/about/blog/2020/3/ten-considerations-you-create-another-chart-about-covid-19\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"10 considerations before you create another chart about COVID-19\")), \" (03/13/20) by Amanda Makulec, Operations Director for the Data Visualization Societ\", mdx(\"a\", _extends({\n    parentName: \"li\"\n  }, {\n    \"href\": \"http://news.mit.edu/2020/catherine-dignazio-visualizing-covid-19-data-0414\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  })), \"y\"), mdx(\"li\", {\n    parentName: \"ul\"\n  }, mdx(\"strong\", {\n    parentName: \"li\"\n  }, mdx(\"a\", _extends({\n    parentName: \"strong\"\n  }, {\n    \"href\": \"http://news.mit.edu/2020/catherine-dignazio-visualizing-covid-19-data-0414\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"3 Questions: Catherine D\\u2019Ignazio on visualizing COVID-19 data\")), \" (04/13/20) profiling MIT assistant professor D\\u2019Ignazio;\", mdx(\"a\", _extends({\n    parentName: \"li\"\n  }, {\n    \"href\": \"https://www.esri.com/arcgis-blog/products/product/mapping/mapping-coronavirus-responsibly/\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }))), mdx(\"li\", {\n    parentName: \"ul\"\n  }, mdx(\"strong\", {\n    parentName: \"li\"\n  }, mdx(\"a\", _extends({\n    parentName: \"strong\"\n  }, {\n    \"href\": \"https://www.esri.com/arcgis-blog/products/product/mapping/mapping-coronavirus-responsibly/\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"Mapping coronavirus, responsibly\")), \" (02/25/20) by Kenneth Field for ESRI;\"), mdx(\"li\", {\n    parentName: \"ul\"\n  }, mdx(\"strong\", {\n    parentName: \"li\"\n  }, mdx(\"a\", _extends({\n    parentName: \"strong\"\n  }, {\n    \"href\": \"https://fivethirtyeight.com/features/why-its-so-freaking-hard-to-make-a-good-covid-19-model/\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"Why It\\u2019s So Freaking Hard to Make a Good COVID-19 Model\")), \" (03/31/20) by Maggie Koerth, Laura Bronner, and Jasmine Mithani for \", mdx(\"em\", {\n    parentName: \"li\"\n  }, \"FiveThirtyEight\"), \";\"), mdx(\"li\", {\n    parentName: \"ul\"\n  }, \"Once again, \", mdx(\"a\", _extends({\n    parentName: \"li\"\n  }, {\n    \"href\": \"https://twitter.com/EvanMPeck/status/1235568532840120321\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"this Twitter thread\"), \" by Evan M. Peck of Bucknell University.\")), mdx(\"p\", null, \"For trustworthy visualizations, explore \", mdx(\"a\", _extends({\n    parentName: \"p\"\n  }, {\n    \"href\": \"https://www.tableau.com/about/blog/2020/4/most-interesting-data-vizzes-covid-19-weve-seen-media-so-far\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"these gems selected by Tableau\"), \" or the\", mdx(\"a\", _extends({\n    parentName: \"p\"\n  }, {\n    \"href\": \"https://blog.datawrapper.de/coronaviruscharts/\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \" charts featured by Datawrapper\"), \".\"), mdx(\"p\", null, \"The COVID-19 pandemic has underscored the importance of informed epidemiological data analysis. Often, the niche expertise required for this analysis can be a hazard \", mdx(\"a\", _extends({\n    parentName: \"p\"\n  }, {\n    \"href\": \"https://twitter.com/ferrisjabr/status/1221146622341443584\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"even to credentialed experts\"), \". The democratic, collaborative nature of public forum data science can help us meet the demands of this vexing global problem. But, this does not suggest that every individual or team reporting on COVID has an equal claim to accuracy; rather, it implies that the analysis challenges are larger than any one mind can confidently answer.\"));\n}\n;\nMDXContent.isMDXComponent = 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