{"id": 989111, "name": "Daily new estimated COVID-19 infections (Youyang Gu, Mean estimate)", "unit": "estimated infections", "createdAt": "2024-09-16T14:24:11.000Z", "updatedAt": "2026-07-27T11:26:56.000Z", "coverage": "", "timespan": "", "datasetId": 6721, "columnOrder": 0, "shortName": "yyg_infections__estimate_mean", "catalogPath": "grapher/covid/latest/infections_model/infections_model#yyg_infections__estimate_mean", "dimensions": {"years": {"values": [{"id": 53}, {"id": 54}, {"id": 55}, {"id": 56}, {"id": 57}, {"id": 58}, {"id": 59}, {"id": 60}, {"id": 61}, {"id": 62}, {"id": 63}, {"id": 64}, {"id": 65}, {"id": 66}, {"id": 67}, {"id": 68}, {"id": 69}, {"id": 70}, {"id": 71}, {"id": 72}, {"id": 73}, {"id": 74}, {"id": 75}, {"id": 76}, {"id": 77}, {"id": 78}, {"id": 79}, {"id": 80}, {"id": 81}, {"id": 82}, {"id": 83}, {"id": 84}, {"id": 85}, {"id": 86}, {"id": 87}, {"id": 88}, {"id": 89}, {"id": 90}, {"id": 91}, {"id": 92}, {"id": 93}, {"id": 94}, {"id": 95}, {"id": 96}, {"id": 97}, {"id": 98}, {"id": 99}, {"id": 100}, {"id": 101}, {"id": 102}, {"id": 103}, {"id": 104}, {"id": 105}, {"id": 106}, {"id": 107}, {"id": 108}, {"id": 109}, {"id": 110}, {"id": 111}, {"id": 112}, {"id": 113}, {"id": 114}, {"id": 115}, {"id": 116}, {"id": 117}, {"id": 118}, {"id": 119}, {"id": 120}, {"id": 121}, {"id": 122}, {"id": 123}, {"id": 124}, {"id": 125}, {"id": 126}, {"id": 127}, {"id": 128}, {"id": 129}, {"id": 130}, {"id": 131}, {"id": 132}, {"id": 133}, {"id": 134}, {"id": 135}, {"id": 136}, {"id": 137}, {"id": 138}, {"id": 139}, {"id": 140}, {"id": 141}, {"id": 142}, {"id": 143}, {"id": 144}, {"id": 145}, {"id": 146}, {"id": 147}, {"id": 148}, {"id": 149}, {"id": 150}, {"id": 151}, {"id": 152}, {"id": 153}, {"id": 154}, {"id": 155}, {"id": 156}, {"id": 157}, {"id": 158}, {"id": 159}, {"id": 160}, {"id": 161}, {"id": 162}, {"id": 163}, {"id": 164}, {"id": 165}, {"id": 166}, {"id": 167}, {"id": 168}, {"id": 169}, {"id": 170}, {"id": 171}, {"id": 172}, {"id": 173}, {"id": 174}, {"id": 175}, {"id": 176}, {"id": 177}, {"id": 178}, {"id": 179}, {"id": 180}, {"id": 181}, {"id": 182}, {"id": 183}, {"id": 184}, {"id": 185}, {"id": 186}, {"id": 187}, {"id": 188}, {"id": 189}, {"id": 190}, {"id": 191}, {"id": 192}, {"id": 193}, {"id": 194}, {"id": 195}, {"id": 196}, {"id": 197}, {"id": 198}, {"id": 199}, {"id": 200}, {"id": 201}, {"id": 202}, {"id": 203}, {"id": 204}, {"id": 205}, {"id": 206}, {"id": 207}, {"id": 208}, {"id": 209}, {"id": 210}, {"id": 211}, {"id": 212}, {"id": 213}, {"id": 214}, {"id": 215}, {"id": 216}, {"id": 217}, {"id": 218}, {"id": 219}, {"id": 220}, {"id": 221}, {"id": 222}, {"id": 223}, {"id": 224}, {"id": 225}, {"id": 226}, {"id": 227}, {"id": 228}, {"id": 229}, {"id": 230}, {"id": 231}, {"id": 232}, {"id": 233}, {"id": 234}, {"id": 235}, {"id": 236}, {"id": 237}, {"id": 238}, {"id": 239}, {"id": 240}, {"id": 241}, {"id": 242}, {"id": 243}, {"id": 244}, {"id": 245}, {"id": 246}, {"id": 247}, {"id": 248}, {"id": 249}, {"id": 250}, {"id": 251}, {"id": 252}, {"id": 253}, {"id": 254}, {"id": 255}, {"id": 256}, {"id": 257}, {"id": 258}, {"id": 259}, {"id": 260}, {"id": 261}, {"id": 262}, {"id": 263}, {"id": 264}, {"id": 265}, {"id": 266}, {"id": 267}, {"id": 268}, {"id": 269}, {"id": 270}, {"id": 271}, {"id": 272}, {"id": 273}, {"id": 274}, {"id": 275}, {"id": 276}, {"id": 277}, {"id": 278}, {"id": 279}, {"id": 280}, {"id": 281}, {"id": 282}, {"id": 283}, {"id": 49}, {"id": 50}, {"id": 51}, {"id": 52}, {"id": 42}, {"id": 43}, {"id": 44}, {"id": 45}, {"id": 46}, {"id": 47}, {"id": 48}, {"id": 0}, {"id": 1}, {"id": 2}, {"id": 3}, {"id": 4}, {"id": 5}, {"id": 6}, {"id": 7}, {"id": 8}, {"id": 9}, {"id": 10}, {"id": 11}, {"id": 12}, {"id": 13}, {"id": 14}, {"id": 15}, {"id": 16}, {"id": 17}, {"id": 18}, {"id": 19}, {"id": 20}, {"id": 21}, {"id": 22}, {"id": 23}, {"id": 24}, {"id": 25}, {"id": 26}, {"id": 27}, {"id": 28}, {"id": 29}, {"id": 30}, {"id": 31}, {"id": 32}, {"id": 33}, {"id": 34}, {"id": 35}, {"id": 36}, {"id": 37}, {"id": 38}, {"id": 39}, {"id": 40}, {"id": 41}]}, "entities": {"values": [{"id": 17, "name": "Algeria", "code": "DZA"}, {"id": 21, "name": "Argentina", "code": "ARG"}, {"id": 23, "name": "Australia", "code": "AUS"}, {"id": 24, "name": "Austria", "code": "AUT"}, {"id": 28, "name": "Bangladesh", "code": "BGD"}, {"id": 30, "name": "Belarus", "code": "BLR"}, {"id": 4, "name": "Belgium", "code": "BEL"}, {"id": 34, "name": "Bolivia", "code": "BOL"}, {"id": 37, "name": "Brazil", "code": "BRA"}, {"id": 39, "name": "Bulgaria", "code": "BGR"}, {"id": 44, "name": "Canada", "code": "CAN"}, {"id": 172, "name": "Chile", "code": "CHL"}, {"id": 171, "name": "China", "code": "CHN"}, {"id": 170, "name": "Colombia", "code": "COL"}, {"id": 165, "name": "Croatia", "code": "HRV"}, {"id": 164, "name": "Cuba", "code": "CUB"}, {"id": 163, "name": "Cyprus", "code": "CYP"}, {"id": 162, "name": "Czechia", "code": "CZE"}, {"id": 161, "name": "Denmark", "code": "DNK"}, {"id": 160, "name": "Dominican Republic", "code": "DOM"}, {"id": 201, "name": "Ecuador", "code": "ECU"}, {"id": 65, "name": "Egypt", "code": "EGY"}, {"id": 156, "name": "Estonia", "code": "EST"}, {"id": 155, "name": "Finland", "code": "FIN"}, {"id": 3, "name": "France", "code": "FRA"}, {"id": 6, "name": "Germany", "code": "DEU"}, {"id": 149, "name": "Greece", "code": "GRC"}, {"id": 139, "name": "Honduras", "code": "HND"}, {"id": 138, "name": "Hungary", "code": "HUN"}, {"id": 207, "name": "Iceland", "code": "ISL"}, {"id": 137, "name": "India", "code": "IND"}, {"id": 136, "name": "Indonesia", "code": "IDN"}, {"id": 135, "name": "Iran", "code": "IRN"}, {"id": 2, "name": "Ireland", "code": "IRL"}, {"id": 133, "name": "Israel", "code": "ISR"}, {"id": 8, "name": "Italy", "code": "ITA"}, {"id": 14, "name": "Japan", "code": "JPN"}, {"id": 208, "name": "Kuwait", "code": "KWT"}, {"id": 122, "name": "Latvia", "code": "LVA"}, {"id": 119, "name": "Lithuania", "code": "LTU"}, {"id": 210, "name": "Luxembourg", "code": "LUX"}, {"id": 116, "name": "Malaysia", "code": "MYS"}, {"id": 212, "name": "Malta", "code": "MLT"}, {"id": 113, "name": "Mexico", "code": "MEX"}, {"id": 111, "name": "Moldova", "code": "MDA"}, {"id": 110, "name": "Morocco", "code": "MAR"}, {"id": 5, "name": "Netherlands", "code": "NLD"}, {"id": 103, "name": "Nigeria", "code": "NGA"}, {"id": 102, "name": "Norway", "code": "NOR"}, {"id": 101, "name": "Pakistan", "code": "PAK"}, {"id": 100, "name": "Panama", "code": "PAN"}, {"id": 97, "name": "Peru", "code": "PER"}, {"id": 96, "name": "Philippines", "code": "PHL"}, {"id": 11, "name": "Poland", "code": "POL"}, {"id": 95, "name": "Portugal", "code": "PRT"}, {"id": 92, "name": "Romania", "code": "ROU"}, {"id": 12, "name": "Russia", "code": "RUS"}, {"id": 90, "name": "Saudi Arabia", "code": "SAU"}, {"id": 88, "name": "Serbia", "code": "SRB"}, {"id": 85, "name": "Slovakia", "code": "SVK"}, {"id": 83, "name": "Slovenia", "code": "SVN"}, {"id": 81, "name": "South Africa", "code": "ZAF"}, {"id": 127, "name": "South Korea", "code": "KOR"}, {"id": 9, "name": "Spain", "code": "ESP"}, {"id": 10, "name": "Sweden", "code": "SWE"}, {"id": 7, "name": "Switzerland", "code": "CHE"}, {"id": 70, "name": "Turkey", "code": "TUR"}, {"id": 67, "name": "Ukraine", "code": "UKR"}, {"id": 72, "name": "United Arab Emirates", "code": "ARE"}, {"id": 1, "name": "United Kingdom", "code": "GBR"}, {"id": 13, "name": "United States", "code": "USA"}]}}, "descriptionShort": "Mean estimates of the true number of COVID-19 infections Youyang Gu model.", "type": "int", "dataChecksum": "16549052774273599804", "metadataChecksum": "-5596329000590871604", "datasetName": "COVID-19, infection model estimates", "updatePeriodDays": 365, "datasetVersion": "latest", "nonRedistributable": false, "display": {"name": "Mean estimate", "unit": "estimated infections", "zeroDay": "2019-12-26", "timeInterval": "day", "numDecimalPlaces": 3}, "schemaVersion": 2, "presentation": {"titlePublic": "Daily new estimated COVID-19 infections (Youyang Gu, Mean estimate)", "topicTagsLinks": ["COVID-19"]}, "descriptionKey": "- The model combines a standard SEIR framework with a machine-learning layer that adjusts parameters to align with observed data, aiming for forecast accuracy.\n- Using reported deaths and an estimated infection fatality rate (IFR) to back-calculate infections can introduce uncertainty, especially if actual deaths are underreported.\n- The model assumes that IFR decreases over time (e.g., to 30% of its initial value) to reflect changing demographics of infection and improvements in treatment.\n- Although designed primarily for the United States, the model also provides estimates for other countries, where it may have reduced accuracy due to differing data quality and health-system factors.\n- Updates to the model ceased on 5 October 2020, so any emerging trends or subsequent changes in testing, transmission, or IFR are not reflected in its latest estimates.\n- For a full list of assumptions and limitations see [the model \"About\" page](https://covid19-projections.com/about/#assumptions).", "origins": [{"id": 1340, "title": "COVID-19 Projections Using Machine Learning", "description": "Comprehensive library of the recent updates but also all historical updates. If you are only interested in the last infections estimates made in March 2021, click here. See a list of all of our COVID-19 repositories below.", "producer": "Youyang Gu", "citationFull": "Russell, T. W., Hellewell, J., Abbott, S., Golding, N., Gibbs, H., Jarvis, C. I., van Zandvoort, K., CMMID COVID-19 working group, Flasche, S., Eggo, R. M., Edmunds, W. J., & Kucharski, A. J. (2020). Using a delay-adjusted case fatality ratio to estimate under-reporting. BMC Medicine. Retrieved from https://cmmid.github.io/topics/covid19/global_cfr_estimates.html.", "urlMain": "https://github.com/youyanggu/covid19_projections", "dateAccessed": "2020-10-06", "datePublished": "2020", "license": {"name": "CC BY 4.0"}}]}