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37 results for “synthetic populations”
Synthetic population for IND_PUNJAB
<p><strong>Synthetic populations for regions of the World (SPW) | Punjab</strong></p><p><strong>Dataset information</strong></p><p>A synthetic population of a region as provided here, captures the people of the region with selected demographic attributes, their organization into households, their assigned activities for a day, the locations where the activities take place and thus where interactions among population members happen (e.g., spread of epidemics).</p> <p><strong>License</strong></p><p><a href="https://creativecommons.org/licenses/by/4.0/">CC-BY-4.0</a></p> <p><strong>Acknowledgment</strong></p><p>This project was supported by the National Science Foundation under the NSF RAPID: COVID-19 Response Support: Building Synthetic Multi-scale Networks (PI: Madhav Marathe, Co-PIs: Henning Mortveit, Srinivasan Venkatramanan; Fund Number: OAC-2027541).</p> <p><strong>Contact information</strong></p><p>Henning.Mortveit@virginia.edu</p> <p><strong>Identifiers</strong></p><table> <thead><tr> <th></th> <th></th> </tr> </thead> <tbody> <tr> <td>Region name</td> <td>Punjab</td> </tr> <tr> <td>Region ID</td> <td>ind_140001934</td> </tr> <tr> <td>Model</td> <td>coarse</td> </tr> <tr> <td>Version</td> <td>0_9_0</td> </tr> </tbody> </table> <p><strong>Statistics</strong></p><table> <thead><tr> <th>Name</th> <th>Value</th> </tr> </thead> <tbody> <tr> <td>Population</td> <td>27875875</td> </tr> <tr> <td>Average age</td> <td>30.2</td> </tr> <tr> <td>Households</td> <td>6337346</td> </tr> <tr> <td>Average household size</td> <td>4.4</td> </tr> <tr> <td>Residence locations</td> <td>6337346</td> </tr> <tr> <td>Activity locations</td> <td>1608398</td> </tr> <tr> <td>Average number of activities</td> <td>5.5</td> </tr> <tr> <td>Average travel distance</td> <td>101.9</td> </tr> </tbody> </table> <p><strong>Sources</strong></p><table> <thead><tr> <th>Description</th> <th>Name</th> <th>Version</th> <th>Url</th> </tr> </thead> <tbody> <tr> <td>Activity template data</td> <td>World Bank</td> <td>2021</td> <td><a href="https://data.worldbank.org">https://data.worldbank.org</a></td> </tr> <tr> <td>Administrative boundaries</td> <td>ADCW</td> <td>7.6</td> <td><a href="https://www.adci.com/adc-worldmap">https://www.adci.com/adc-worldmap</a></td> </tr> <tr> <td>Curated POIs based on OSM</td> <td>SLIPO/OSM POIs</td> <td></td> <td><a href="http://slipo.eu/?p=1551">http://slipo.eu/?p=1551</a> <a href="https://www.openstreetmap.org/">https://www.openstreetmap.org/</a></td> </tr> <tr> <td>Household data</td> <td>DHS</td> <td></td> <td><a href="https://dhsprogram.com">https://dhsprogram.com</a></td> </tr> <tr> <td>Population count with demographic attributes</td> <td>GPW</td> <td>v4.11</td> <td><a href="https://sedac.ciesin.columbia.edu/data/set/gpw-v4-admin-unit-center-points-population-estimates-rev11">https://sedac.ciesin.columbia.edu/data/set/gpw-v4-admin-unit-center-points-population-estimates-rev11</a></td> </tr> </tbody> </table> <p><strong>Files description</strong></p><p><strong>Base data files (ind_140001934_data_v_0_9.zip)</strong></p><table> <thead><tr> <th>Filename</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td><code>ind_140001934_person_v_0_9.csv</code></td> <td>Data for each person including attributes such as age, gender, and household ID.</td> </tr> <tr> <td><code>ind_140001934_household_v_0_9.csv</code></td> <td>Data at household level.</td> </tr> <tr> <td><code>ind_140001934_residence_locations_v_0_9.csv</code></td> <td>Data about residence locations</td> </tr> <tr> <td><code>ind_140001934_activity_locations_v_0_9.csv</code></td> <td>Data about activity locations, including what activity types are supported at these locations</td> </tr> <tr> <td><code>ind_140001934_activity_location_assignment_v_0_9.csv</code></td> <td>For each person and for each of their activities, this file specifies the location where the activity takes place</td> </tr> </tbody> </table> <p><strong>Derived data files</strong></p><table> <thead><tr> <th>Filename</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td><code>ind_140001934_contact_matrix_v_0_9.csv</code></td> <td>A POLYMOD-type contact matrix constructed from a network representation of the location assignment data and a within-location contact model.</td> </tr> </tbody> </table> <p><strong>Validation and measures files</strong></p><table> <thead><tr> <th>Filename</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td><code>ind_140001934_household_grouping_validation_v_0_9.pdf</code></td> <td>Validation plots for household construction</td> </tr> <tr> <td><code>ind_140001934_activity_durations_{adult,child}_v_0_9.pdf</code></td> <td>Comparison of time spent on generated activities with survey data</td> </tr> <tr> <td><code>ind_140001934_activity_patterns_{adult,child}_v_0_9.pdf</code></td> <td>Comparison of generated activity patterns by the time of day with survey data</td> </tr> <tr> <td><code>ind_140001934_location_construction_0_9.pdf</code></td> <td>Validation plots for location construction</td> </tr> <tr> <td><code>ind_140001934_location_assignement_0_9.pdf</code></td> <td>Validation plots for location assignment, including travel distribution plots</td> </tr> <tr> <td><code>ind_140001934_ind_140001934_ver_0_9_0_avg_travel_distance.pdf</code></td> <td>Choropleth map visualizing average travel distance</td> </tr> <tr> <td><code>ind_140001934_ind_140001934_ver_0_9_0_travel_distr_combined.pdf</code></td> <td>Travel distance distribution</td> </tr> <tr> <td><code>ind_140001934_ind_140001934_ver_0_9_0_num_activity_loc.pdf</code></td> <td>Choropleth map visualizing number of activity locations</td> </tr> <tr> <td><code>ind_140001934_ind_140001934_ver_0_9_0_avg_age.pdf</code></td> <td>Choropleth map visualizing average age</td> </tr> <tr> <td><code>ind_140001934_ind_140001934_ver_0_9_0_pop_density_per_sqkm.pdf</code></td> <td>Choropleth map visualizing population density</td> </tr> <tr> <td><code>ind_140001934_ind_140001934_ver_0_9_0_pop_size.pdf</code></td> <td>Choropleth map visualizing population size</td> </tr> </tbody> </table>
Synthetic population for USA_VIRGINIA
<p><strong>Synthetic populations for regions of the World (SPW) | Virginia</strong></p><p><strong>Dataset information</strong></p><p>A synthetic population of a region as provided here, captures the people of the region with selected demographic attributes, their organization into households, their assigned activities for a day, the locations where the activities take place and thus where interactions among population members happen (e.g., spread of epidemics).</p> <p><strong>License</strong></p><p><a href="https://creativecommons.org/licenses/by/4.0/">CC-BY-4.0</a></p> <p><strong>Acknowledgment</strong></p><p>This project was supported by the National Science Foundation under the NSF RAPID: COVID-19 Response Support: Building Synthetic Multi-scale Networks (PI: Madhav Marathe, Co-PIs: Henning Mortveit, Srinivasan Venkatramanan; Fund Number: OAC-2027541).</p> <p><strong>Contact information</strong></p><p>Henning.Mortveit@virginia.edu</p> <p><strong>Identifiers</strong></p><table> <thead><tr> <th></th> <th></th> </tr> </thead> <tbody> <tr> <td>Region name</td> <td>Virginia</td> </tr> <tr> <td>Region ID</td> <td>usa_140002905</td> </tr> <tr> <td>Model</td> <td>coarse</td> </tr> <tr> <td>Version</td> <td>0_9_0</td> </tr> </tbody> </table> <p><strong>Statistics</strong></p><table> <thead><tr> <th>Name</th> <th>Value</th> </tr> </thead> <tbody> <tr> <td>Population</td> <td>7908211</td> </tr> <tr> <td>Average age</td> <td>37.3</td> </tr> <tr> <td>Households</td> <td>3206012</td> </tr> <tr> <td>Average household size</td> <td>2.5</td> </tr> <tr> <td>Residence locations</td> <td>3206012</td> </tr> <tr> <td>Activity locations</td> <td>729228</td> </tr> <tr> <td>Average number of activities</td> <td>5.7</td> </tr> <tr> <td>Average travel distance</td> <td>43.5</td> </tr> </tbody> </table> <p><strong>Sources</strong></p><table> <thead><tr> <th>Description</th> <th>Name</th> <th>Version</th> <th>Url</th> </tr> </thead> <tbody> <tr> <td>Activity template data</td> <td>World Bank</td> <td>2021</td> <td><a href="https://data.worldbank.org">https://data.worldbank.org</a></td> </tr> <tr> <td>Administrative boundaries</td> <td>ADCW</td> <td>7.6</td> <td><a href="https://www.adci.com/adc-worldmap">https://www.adci.com/adc-worldmap</a></td> </tr> <tr> <td>Curated POIs based on OSM</td> <td>SLIPO/OSM POIs</td> <td></td> <td><a href="http://slipo.eu/?p=1551">http://slipo.eu/?p=1551</a> <a href="https://www.openstreetmap.org/">https://www.openstreetmap.org/</a></td> </tr> <tr> <td>Household data</td> <td>IPUMS</td> <td></td> <td><a href="https://international.ipums.org/international">https://international.ipums.org/international</a></td> </tr> <tr> <td>Population count with demographic attributes</td> <td>GPW</td> <td>v4.11</td> <td><a href="https://sedac.ciesin.columbia.edu/data/set/gpw-v4-admin-unit-center-points-population-estimates-rev11">https://sedac.ciesin.columbia.edu/data/set/gpw-v4-admin-unit-center-points-population-estimates-rev11</a></td> </tr> </tbody> </table> <p><strong>Files description</strong></p><p><strong>Base data files (usa_140002905_data_v_0_9.zip)</strong></p><table> <thead><tr> <th>Filename</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td><code>usa_140002905_person_v_0_9.csv</code></td> <td>Data for each person including attributes such as age, gender, and household ID.</td> </tr> <tr> <td><code>usa_140002905_household_v_0_9.csv</code></td> <td>Data at household level.</td> </tr> <tr> <td><code>usa_140002905_residence_locations_v_0_9.csv</code></td> <td>Data about residence locations</td> </tr> <tr> <td><code>usa_140002905_activity_locations_v_0_9.csv</code></td> <td>Data about activity locations, including what activity types are supported at these locations</td> </tr> <tr> <td><code>usa_140002905_activity_location_assignment_v_0_9.csv</code></td> <td>For each person and for each of their activities, this file specifies the location where the activity takes place</td> </tr> </tbody> </table> <p><strong>Derived data files</strong></p><table> <thead><tr> <th>Filename</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td><code>usa_140002905_contact_matrix_v_0_9.csv</code></td> <td>A POLYMOD-type contact matrix constructed from a network representation of the location assignment data and a within-location contact model.</td> </tr> </tbody> </table> <p><strong>Validation and measures files</strong></p><table> <thead><tr> <th>Filename</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td><code>usa_140002905_household_grouping_validation_v_0_9.pdf</code></td> <td>Validation plots for household construction</td> </tr> <tr> <td><code>usa_140002905_activity_durations_{adult,child}_v_0_9.pdf</code></td> <td>Comparison of time spent on generated activities with survey data</td> </tr> <tr> <td><code>usa_140002905_activity_patterns_{adult,child}_v_0_9.pdf</code></td> <td>Comparison of generated activity patterns by the time of day with survey data</td> </tr> <tr> <td><code>usa_140002905_location_construction_0_9.pdf</code></td> <td>Validation plots for location construction</td> </tr> <tr> <td><code>usa_140002905_location_assignement_0_9.pdf</code></td> <td>Validation plots for location assignment, including travel distribution plots</td> </tr> <tr> <td><code>usa_140002905_usa_140002905_ver_0_9_0_avg_travel_distance.pdf</code></td> <td>Choropleth map visualizing average travel distance</td> </tr> <tr> <td><code>usa_140002905_usa_140002905_ver_0_9_0_travel_distr_combined.pdf</code></td> <td>Travel distance distribution</td> </tr> <tr> <td><code>usa_140002905_usa_140002905_ver_0_9_0_num_activity_loc.pdf</code></td> <td>Choropleth map visualizing number of activity locations</td> </tr> <tr> <td><code>usa_140002905_usa_140002905_ver_0_9_0_avg_age.pdf</code></td> <td>Choropleth map visualizing average age</td> </tr> <tr> <td><code>usa_140002905_usa_140002905_ver_0_9_0_pop_density_per_sqkm.pdf</code></td> <td>Choropleth map visualizing population density</td> </tr> <tr> <td><code>usa_140002905_usa_140002905_ver_0_9_0_pop_size.pdf</code></td> <td>Choropleth map visualizing population size</td> </tr> </tbody> </table>
New York State Synthetic Population
<p><span>The synthetic population includes nearly 20 million individuals and 7.5 million households in the whole New York State using the PUMS from 2021 5-year ACS. The marginals obtained from the synthetic population well matches the census marginals. When coming to attribute combinations, the synthetic population can still generally follow what the input sample depict. In addition, the synthetic population reconstructs the associations among household members that the input sample shows.</span></p> <p><span>We propose a population synthesis framework that involves both the deterministic model and ciDATGAN to generate households and corresponding personal synthetic populations. The framework is illustrated in the figure below.</span></p> <p><span></span></p> <p> </p> <p><span>A wide range of socio-demographic variables are included, and the variables selected for this study can be found in Table 1. We aggregate categories of some attributes deemed too granular, such as age and working industry (NAICS). To capture potential spatial heterogeneity of the population between New York City (NYC) and non-NYC regions, we separate PUMS by filtering regions within and outside of NYC using the Public Use Microdata Areas (PUMAs). </span></p> <p><span>Because NYC is the most densely populated region in the US with high population diversity, we want higher population resolutions. Therefore, we further assign the NYC specific PUMS from PUMA level to Census Tract (CT) levels by using Popgen.</span></p> <p><span>Table 1. Selected attributes of input samples</span></p> <div> <table> <tbody> <tr> <td> </td> <td> <p><em><span>Non-NYC region attribute (label name)</span></em></p> </td> <td> <p><em><span>No. of values (range if continuous)</span></em></p> </td> <td> <p><em><span>NYC region attribute (label name)</span></em></p> </td> <td> <p><em><span>No. of values</span></em></p> </td> </tr> <tr> <td> <p><em><span>Household attribute</span></em></p> </td> <td> <p><span>Residence area (PUMA)</span></p> </td> <td> <p><span>90</span></p> </td> <td> <p><span>Residence area (CT)</span></p> </td> <td> <p><span>2313</span></p> </td> </tr> <tr> <td> <p><span>Income level (HINCP)</span></p> </td> <td> <p><span>9</span></p> </td> <td> <p><span>Income level (HINCP)</span></p> </td> <td> <p><span>9</span></p> </td> </tr> <tr> <td> <p><span>Vehicle ownership (VEH)</span></p> </td> <td> <p><span>4</span></p> </td> <td> <p><span>Vehicle ownership (VEH)</span></p> </td> <td> <p><span>4</span></p> </td> </tr> <tr> <td> <p><em><span>Personal attribute</span></em></p> </td> <td> <p><span>Age (AGEP)</span></p> </td> <td> <p><span>7</span></p> </td> <td> <p><span>Age (AGEP)</span></p> </td> <td> <p><span>7</span></p> </td> </tr> <tr> <td> <p><span>English proficiency (ENG)</span></p> </td> <td> <p><span>5</span></p> </td> <td> <p><span>English proficiency (ENG)</span></p> </td> <td> <p><span>5</span></p> </td> </tr> <tr> <td> <p><span>Commute trip length (JWMNP)</span></p> </td> <td> <p><span>0-140 min</span></p> </td> <td> <p><span>Gender (SEX)</span></p> </td> <td> <p><span>2</span></p> </td> </tr> <tr> <td> <p><span>Commute mode (JWTRNS)</span></p> </td> <td> <p><span>13</span></p> </td> <td> <p><span>Disability (DIS)</span></p> </td> <td> <p><span>2</span></p> </td> </tr> <tr> <td> <p><span>School status (SCH)</span></p> </td> <td> <p><span>3</span></p> </td> <td> <p><span>Working industry (NAICSP)</span></p> </td> <td> <p><span>2</span></p> </td> </tr> <tr> <td> <p><span>Gender (SEX)</span></p> </td> <td> <p><span>2</span></p> </td> <td> <p><span>Race white/non-white (RACWHT)</span></p> </td> <td> <p><span>2</span></p> </td> </tr> <tr> <td> <p><span>Disability (DIS)</span></p> </td> <td> <p><span>2</span></p> </td> <td> </td> <td> </td> </tr> <tr> <td> <p><span>Working industry (NAICSP)</span></p> </td> <td> <p><span>20</span></p> </td> <td> </td> <td> </td> </tr> <tr> <td> <p><span>Race white/non-white (RACWHT)</span></p> </td> <td> <p><span>2</span></p> </td> <td> </td> <td> </td> </tr> </tbody> </table> <p> </p> </div>
Crossing design shapes patterns of genetic variation in synthetic recombinant populations of Saccharomyces cerevisiae
<p>"Synthetic recombinant" populations have emerged as a useful tool for dissecting the genetics of complex traits. They can be used to derive inbred lines for fine QTL mapping, or the populations themselves can be sampled for experimental evolution. In latter application, investigators generally value maximizing genetic variation in constructed populations. This is because in evolution experiments initiated from such populations, adaptation is primarily fueled by standing genetic variation. Despite this reality, little has been done to systematically evaluate how different methods of constructing synthetic populations shape initial patterns of variation. Here we seek to address this issue by comparing outcomes in synthetic recombinant <i>Saccharomyces cerevisiae</i> populations<i> </i>created using one of two strategies: pairwise crossing of isogenic strains or simple mixing of strains in equal proportion. We also explore the impact of the varying the number of parental strains. We find that more genetic variation is initially present and maintained when population construction includes a round of pairwise crossing. As perhaps expected, we also observe that increasing the number of parental strains typically increases genetic diversity. In summary, we suggest that when constructing populations for use in evolution experiments, simply mixing founder strains in equal proportion may limit the adaptive potential.</p>
Crossing design shapes patterns of genetic variation in synthetic recombinant populations of Saccharomyces cerevisiae
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Synthetic population data for Belgium for STRIDE
<p>This repository contains population files with 11 million individuals for Belgium we used to explore the impact of contact tracing and household bubbles on Belgian deconfinement strategies after the COVID-19 related lockdown in 2020 (Willem et al 2021) and universal testing strategies for COVID-19 mitigation (Libin et al 2021).</p> <p>We created census-based synthetic populations for Belgium consisting of individuals that are part of “contact pools”, representing a household, school-class, workplace, or community.</p> <p>References:</p> <p>Willem L, Abrams S, Libin JK P, Petrof O, Coletti P, Kuylen E, Møgelmose S, Wambua J, Herzog S A, Faes C, SIMID COVID19 team, Beutels P, Hens N: The impact of contact tracing and household bubbles on deconfinement strategies for COVID-19. Nature Communications <strong>12, </strong>1524 (2021) (<a href="https://doi.org/10.1038/s41467-021-21747-7">https://doi.org/10.1038/s41467-021-21747-7</a>).</p> <p>Libin JK P, Willem L, Verstraeten T, Torneri A, Vanderlocht J, Hens N. Assessing the feasibility and effectiveness of household-pooled universal testing to control COVID-19 epidemics. PLoS Computational Biology 17(3): e1008688 (2021) (<a href="https://doi.org/10.1371/journal.pcbi.1008688">https://doi.org/10.1371/journal.pcbi.1008688</a>)</p>
Synthetic population housing and person records for the United States
<p>The synthetic population was generated from the 2010-2014 ACS PUMS housing and person files.</p> <p> United States Department of Commerce. Bureau of the Census. (2017-03-06).<br> American Community Survey 2010-2014 ACS 5-Year PUMS File [Data set].<br> Ann Arbor, MI: Inter-university Consortium of Political and Social<br> Research [distributor]. http://doi.org/10.3886/E100486V1</p> <p><strong>Outputs</strong></p> <p>There are 17 housing files<br> - repHus0.csv, repHus1.csv, ... repHus16.csv<br> and 32 person files<br> - rep_recode_ACSpus0.csv, rep_recode_ACSpus1.csv, ... rep_recode_ACSpus31.csv.</p> <p> </p> <p>Files are split to be roughly equal in size. The files contain data for the entire country. Files are not split along any demographic characteristic. The person files and housing files must be concatenated to form a complete person file and a complete housing file, respectively.</p> <p>If desired, person and housing records should be merged on 'id'. Variable description is below.</p> <p><strong>Data Dictionary</strong><br> See [2010-2014 ACS PUMS data dictionary](http://doi.org/10.3886/E100486V1). All variables from the ACS PUMS housing files are present in the synthetic housing files and all variables from the ACS PUMS person files are present in the synthetic person files. Variables have not been modified in any way. Theoretically, variables like `person weight` no longer have any use in the synthetic population.</p> <p> </p> <p>See README.md for more details.</p>
Dataset in csv format containing labor force data in a synthetic population
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Synthetic population for GIN
<p>Synthetic population for GIN. </p>
Development of a synthetic vulnerable population for four major metropolitan regions in Canada
<p>Code and source data to generate a synthetic population of potentially vulnerable individuals at the DA levels for four canadian metropolitan regions (Calgary, Montreal, Toronto, Vancouver). The repository also includes the results and code to analyse them.</p> <p>It is shared as a complementary material for the article "<em>A synthetic vulnerable population dataset for fine scale geographical equity analysis and policy assessment in urban projects."</em>. (submitted), Jérémy Gelb, Philippe Apparicio, Hamzeh Alizadeh</p>
Dataset in R format, containing labor force data for a synthetic population
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Synthetic population for SWE
<p><strong>Synthetic populations for regions of the World (SPW) | Sweden</strong></p><p><strong>Dataset information</strong></p><p>A synthetic population of a region as provided here, captures the people of the region with selected demographic attributes, their organization into households, their assigned activities for a day, the locations where the activities take place and thus where interactions among population members happen (e.g., spread of epidemics).</p> <p><strong>License</strong></p><p><a href="https://creativecommons.org/licenses/by/4.0/">CC-BY-4.0</a></p> <p><strong>Acknowledgment</strong></p><p>This project was supported by the National Science Foundation under the NSF RAPID: COVID-19 Response Support: Building Synthetic Multi-scale Networks (PI: Madhav Marathe, Co-PIs: Henning Mortveit, Srinivasan Venkatramanan; Fund Number: OAC-2027541).</p> <p><strong>Contact information</strong></p><p>Henning.Mortveit@virginia.edu</p> <p><strong>Identifiers</strong></p><table> <thead><tr> <th></th> <th></th> </tr> </thead> <tbody> <tr> <td>Region name</td> <td>Sweden</td> </tr> <tr> <td>Region ID</td> <td>swe</td> </tr> <tr> <td>Model</td> <td>coarse</td> </tr> <tr> <td>Version</td> <td>0_9_0</td> </tr> </tbody> </table> <p><strong>Statistics</strong></p><table> <thead><tr> <th>Name</th> <th>Value</th> </tr> </thead> <tbody> <tr> <td>Population</td> <td>9143037.0</td> </tr> <tr> <td>Average age</td> <td>40.8</td> </tr> <tr> <td>Households</td> <td>3820873.0</td> </tr> <tr> <td>Average household size</td> <td>2.4</td> </tr> <tr> <td>Residence locations</td> <td>3820873.0</td> </tr> <tr> <td>Activity locations</td> <td>1440586.0</td> </tr> <tr> <td>Average number of activities</td> <td>5.8</td> </tr> <tr> <td>Average travel distance</td> <td>49.3</td> </tr> </tbody> </table> <p><strong>Sources</strong></p><table> <thead><tr> <th>Description</th> <th>Name</th> <th>Version</th> <th>Url</th> </tr> </thead> <tbody> <tr> <td>Activity template data</td> <td>World Bank</td> <td>2021</td> <td><a href="https://data.worldbank.org">https://data.worldbank.org</a></td> </tr> <tr> <td>Administrative boundaries</td> <td>ADCW</td> <td>7.6</td> <td><a href="https://www.adci.com/adc-worldmap">https://www.adci.com/adc-worldmap</a></td> </tr> <tr> <td>Curated POIs based on OSM</td> <td>SLIPO/OSM POIs</td> <td></td> <td><a href="http://slipo.eu/?p=1551">http://slipo.eu/?p=1551</a> <a href="https://www.openstreetmap.org/">https://www.openstreetmap.org/</a></td> </tr> <tr> <td>Population count with demographic attributes</td> <td>GPW</td> <td>v4.11</td> <td><a href="https://sedac.ciesin.columbia.edu/data/set/gpw-v4-admin-unit-center-points-population-estimates-rev11">https://sedac.ciesin.columbia.edu/data/set/gpw-v4-admin-unit-center-points-population-estimates-rev11</a></td> </tr> </tbody> </table> <p><strong>Files description</strong></p><p><strong>Base data files (swe_data_v_0_9.zip)</strong></p><table> <thead><tr> <th>Filename</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td><code>swe_person_v_0_9.csv</code></td> <td>Data for each person including attributes such as age, gender, and household ID.</td> </tr> <tr> <td><code>swe_household_v_0_9.csv</code></td> <td>Data at household level.</td> </tr> <tr> <td><code>swe_residence_locations_v_0_9.csv</code></td> <td>Data about residence locations</td> </tr> <tr> <td><code>swe_activity_locations_v_0_9.csv</code></td> <td>Data about activity locations, including what activity types are supported at these locations</td> </tr> <tr> <td><code>swe_activity_location_assignment_v_0_9.csv</code></td> <td>For each person and for each of their activities, this file specifies the location where the activity takes place</td> </tr> </tbody> </table> <p><strong>Derived data files</strong></p><table> <thead><tr> <th>Filename</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td><code>swe_contact_matrix_v_0_9.csv</code></td> <td>A POLYMOD-type contact matrix constructed from a network representation of the location assignment data and a within-location contact model.</td> </tr> </tbody> </table> <p><strong>Validation and measures files</strong></p><table> <thead><tr> <th>Filename</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td><code>swe_household_grouping_validation_v_0_9.pdf</code></td> <td>Validation plots for household construction</td> </tr> <tr> <td><code>swe_activity_durations_{adult,child}_v_0_9.pdf</code></td> <td>Comparison of time spent on generated activities with survey data</td> </tr> <tr> <td><code>swe_activity_patterns_{adult,child}_v_0_9.pdf</code></td> <td>Comparison of generated activity patterns by the time of day with survey data</td> </tr> <tr> <td><code>swe_location_construction_0_9.pdf</code></td> <td>Validation plots for location construction</td> </tr> <tr> <td><code>swe_location_assignement_0_9.pdf</code></td> <td>Validation plots for location assignment, including travel distribution plots</td> </tr> <tr> <td><code>swe_swe_ver_0_9_0_avg_travel_distance.pdf</code></td> <td>Choropleth map visualizing average travel distance</td> </tr> <tr> <td><code>swe_swe_ver_0_9_0_travel_distr_combined.pdf</code></td> <td>Travel distance distribution</td> </tr> <tr> <td><code>swe_swe_ver_0_9_0_num_activity_loc.pdf</code></td> <td>Choropleth map visualizing number of activity locations</td> </tr> <tr> <td><code>swe_swe_ver_0_9_0_avg_age.pdf</code></td> <td>Choropleth map visualizing average age</td> </tr> <tr> <td><code>swe_swe_ver_0_9_0_pop_density_per_sqkm.pdf</code></td> <td>Choropleth map visualizing population density</td> </tr> <tr> <td><code>swe_swe_ver_0_9_0_pop_size.pdf</code></td> <td>Choropleth map visualizing population size</td> </tr> </tbody> </table>
Synthetic population for ESP
<p><strong>Synthetic populations for regions of the World (SPW) | Spain</strong></p><p><strong>Dataset information</strong></p><p>A synthetic population of a region as provided here, captures the people of the region with selected demographic attributes, their organization into households, their assigned activities for a day, the locations where the activities take place and thus where interactions among population members happen (e.g., spread of epidemics).</p> <p><strong>License</strong></p><p><a href="https://creativecommons.org/licenses/by/4.0/">CC-BY-4.0</a></p> <p><strong>Acknowledgment</strong></p><p>This project was supported by the National Science Foundation under the NSF RAPID: COVID-19 Response Support: Building Synthetic Multi-scale Networks (PI: Madhav Marathe, Co-PIs: Henning Mortveit, Srinivasan Venkatramanan; Fund Number: OAC-2027541).</p> <p><strong>Contact information</strong></p><p>Henning.Mortveit@virginia.edu</p> <p><strong>Identifiers</strong></p><table> <thead><tr> <th></th> <th></th> </tr> </thead> <tbody> <tr> <td>Region name</td> <td>Spain</td> </tr> <tr> <td>Region ID</td> <td>esp</td> </tr> <tr> <td>Model</td> <td>coarse</td> </tr> <tr> <td>Version</td> <td>0_9_0</td> </tr> </tbody> </table> <p><strong>Statistics</strong></p><table> <thead><tr> <th>Name</th> <th>Value</th> </tr> </thead> <tbody> <tr> <td>Population</td> <td>45639013.0</td> </tr> <tr> <td>Average age</td> <td>41.1</td> </tr> <tr> <td>Households</td> <td>17918332.0</td> </tr> <tr> <td>Average household size</td> <td>2.6</td> </tr> <tr> <td>Residence locations</td> <td>17918332.0</td> </tr> <tr> <td>Activity locations</td> <td>5782846.0</td> </tr> <tr> <td>Average number of activities</td> <td>5.6</td> </tr> <tr> <td>Average travel distance</td> <td>130.4</td> </tr> </tbody> </table> <p><strong>Sources</strong></p><table> <thead><tr> <th>Description</th> <th>Name</th> <th>Version</th> <th>Url</th> </tr> </thead> <tbody> <tr> <td>Activity template data</td> <td>World Bank</td> <td>2021</td> <td><a href="https://data.worldbank.org">https://data.worldbank.org</a></td> </tr> <tr> <td>Administrative boundaries</td> <td>ADCW</td> <td>7.6</td> <td><a href="https://www.adci.com/adc-worldmap">https://www.adci.com/adc-worldmap</a></td> </tr> <tr> <td>Curated POIs based on OSM</td> <td>SLIPO/OSM POIs</td> <td></td> <td><a href="http://slipo.eu/?p=1551">http://slipo.eu/?p=1551</a> <a href="https://www.openstreetmap.org/">https://www.openstreetmap.org/</a></td> </tr> <tr> <td>Household data</td> <td>IPUMS</td> <td></td> <td><a href="https://international.ipums.org/international">https://international.ipums.org/international</a></td> </tr> <tr> <td>Population count with demographic attributes</td> <td>GPW</td> <td>v4.11</td> <td><a href="https://sedac.ciesin.columbia.edu/data/set/gpw-v4-admin-unit-center-points-population-estimates-rev11">https://sedac.ciesin.columbia.edu/data/set/gpw-v4-admin-unit-center-points-population-estimates-rev11</a></td> </tr> </tbody> </table> <p><strong>Files description</strong></p><p><strong>Base data files (esp_data_v_0_9.zip)</strong></p><table> <thead><tr> <th>Filename</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td><code>esp_person_v_0_9.csv</code></td> <td>Data for each person including attributes such as age, gender, and household ID.</td> </tr> <tr> <td><code>esp_household_v_0_9.csv</code></td> <td>Data at household level.</td> </tr> <tr> <td><code>esp_residence_locations_v_0_9.csv</code></td> <td>Data about residence locations</td> </tr> <tr> <td><code>esp_activity_locations_v_0_9.csv</code></td> <td>Data about activity locations, including what activity types are supported at these locations</td> </tr> <tr> <td><code>esp_activity_location_assignment_v_0_9.csv</code></td> <td>For each person and for each of their activities, this file specifies the location where the activity takes place</td> </tr> </tbody> </table> <p><strong>Derived data files</strong></p><table> <thead><tr> <th>Filename</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td><code>esp_contact_matrix_v_0_9.csv</code></td> <td>A POLYMOD-type contact matrix constructed from a network representation of the location assignment data and a within-location contact model.</td> </tr> </tbody> </table> <p><strong>Validation and measures files</strong></p><table> <thead><tr> <th>Filename</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td><code>esp_household_grouping_validation_v_0_9.pdf</code></td> <td>Validation plots for household construction</td> </tr> <tr> <td><code>esp_activity_durations_{adult,child}_v_0_9.pdf</code></td> <td>Comparison of time spent on generated activities with survey data</td> </tr> <tr> <td><code>esp_activity_patterns_{adult,child}_v_0_9.pdf</code></td> <td>Comparison of generated activity patterns by the time of day with survey data</td> </tr> <tr> <td><code>esp_location_construction_0_9.pdf</code></td> <td>Validation plots for location construction</td> </tr> <tr> <td><code>esp_location_assignement_0_9.pdf</code></td> <td>Validation plots for location assignment, including travel distribution plots</td> </tr> <tr> <td><code>esp_esp_ver_0_9_0_avg_travel_distance.pdf</code></td> <td>Choropleth map visualizing average travel distance</td> </tr> <tr> <td><code>esp_esp_ver_0_9_0_travel_distr_combined.pdf</code></td> <td>Travel distance distribution</td> </tr> <tr> <td><code>esp_esp_ver_0_9_0_num_activity_loc.pdf</code></td> <td>Choropleth map visualizing number of activity locations</td> </tr> <tr> <td><code>esp_esp_ver_0_9_0_avg_age.pdf</code></td> <td>Choropleth map visualizing average age</td> </tr> <tr> <td><code>esp_esp_ver_0_9_0_pop_density_per_sqkm.pdf</code></td> <td>Choropleth map visualizing population density</td> </tr> <tr> <td><code>esp_esp_ver_0_9_0_pop_size.pdf</code></td> <td>Choropleth map visualizing population size</td> </tr> </tbody> </table>
Synthetic population for DNK
<p><strong>Synthetic populations for regions of the World (SPW) | Denmark</strong></p><p><strong>Dataset information</strong></p><p>A synthetic population of a region as provided here, captures the people of the region with selected demographic attributes, their organization into households, their assigned activities for a day, the locations where the activities take place and thus where interactions among population members happen (e.g., spread of epidemics).</p> <p><strong>License</strong></p><p><a href="https://creativecommons.org/licenses/by/4.0/">CC-BY-4.0</a></p> <p><strong>Acknowledgment</strong></p><p>This project was supported by the National Science Foundation under the NSF RAPID: COVID-19 Response Support: Building Synthetic Multi-scale Networks (PI: Madhav Marathe, Co-PIs: Henning Mortveit, Srinivasan Venkatramanan; Fund Number: OAC-2027541).</p> <p><strong>Contact information</strong></p><p>Henning.Mortveit@virginia.edu</p> <p><strong>Identifiers</strong></p><table> <thead><tr> <th></th> <th></th> </tr> </thead> <tbody> <tr> <td>Region name</td> <td>Denmark</td> </tr> <tr> <td>Region ID</td> <td>dnk</td> </tr> <tr> <td>Model</td> <td>coarse</td> </tr> <tr> <td>Version</td> <td>0_9_0</td> </tr> </tbody> </table> <p><strong>Statistics</strong></p><table> <thead><tr> <th>Name</th> <th>Value</th> </tr> </thead> <tbody> <tr> <td>Population</td> <td>5408229.0</td> </tr> <tr> <td>Average age</td> <td>39.8</td> </tr> <tr> <td>Households</td> <td>2320319.0</td> </tr> <tr> <td>Average household size</td> <td>2.3</td> </tr> <tr> <td>Residence locations</td> <td>2320319.0</td> </tr> <tr> <td>Activity locations</td> <td>766137.0</td> </tr> <tr> <td>Average number of activities</td> <td>5.7</td> </tr> <tr> <td>Average travel distance</td> <td>34.4</td> </tr> </tbody> </table> <p><strong>Sources</strong></p><table> <thead><tr> <th>Description</th> <th>Name</th> <th>Version</th> <th>Url</th> </tr> </thead> <tbody> <tr> <td>Activity template data</td> <td>World Bank</td> <td>2021</td> <td><a href="https://data.worldbank.org">https://data.worldbank.org</a></td> </tr> <tr> <td>Administrative boundaries</td> <td>ADCW</td> <td>7.6</td> <td><a href="https://www.adci.com/adc-worldmap">https://www.adci.com/adc-worldmap</a></td> </tr> <tr> <td>Curated POIs based on OSM</td> <td>SLIPO/OSM POIs</td> <td></td> <td><a href="http://slipo.eu/?p=1551">http://slipo.eu/?p=1551</a> <a href="https://www.openstreetmap.org/">https://www.openstreetmap.org/</a></td> </tr> <tr> <td>Population count with demographic attributes</td> <td>GPW</td> <td>v4.11</td> <td><a href="https://sedac.ciesin.columbia.edu/data/set/gpw-v4-admin-unit-center-points-population-estimates-rev11">https://sedac.ciesin.columbia.edu/data/set/gpw-v4-admin-unit-center-points-population-estimates-rev11</a></td> </tr> </tbody> </table> <p><strong>Files description</strong></p><p><strong>Base data files (dnk_data_v_0_9.zip)</strong></p><table> <thead><tr> <th>Filename</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td><code>dnk_person_v_0_9.csv</code></td> <td>Data for each person including attributes such as age, gender, and household ID.</td> </tr> <tr> <td><code>dnk_household_v_0_9.csv</code></td> <td>Data at household level.</td> </tr> <tr> <td><code>dnk_residence_locations_v_0_9.csv</code></td> <td>Data about residence locations</td> </tr> <tr> <td><code>dnk_activity_locations_v_0_9.csv</code></td> <td>Data about activity locations, including what activity types are supported at these locations</td> </tr> <tr> <td><code>dnk_activity_location_assignment_v_0_9.csv</code></td> <td>For each person and for each of their activities, this file specifies the location where the activity takes place</td> </tr> </tbody> </table> <p><strong>Derived data files</strong></p><table> <thead><tr> <th>Filename</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td><code>dnk_contact_matrix_v_0_9.csv</code></td> <td>A POLYMOD-type contact matrix constructed from a network representation of the location assignment data and a within-location contact model.</td> </tr> </tbody> </table> <p><strong>Validation and measures files</strong></p><table> <thead><tr> <th>Filename</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td><code>dnk_household_grouping_validation_v_0_9.pdf</code></td> <td>Validation plots for household construction</td> </tr> <tr> <td><code>dnk_activity_durations_{adult,child}_v_0_9.pdf</code></td> <td>Comparison of time spent on generated activities with survey data</td> </tr> <tr> <td><code>dnk_activity_patterns_{adult,child}_v_0_9.pdf</code></td> <td>Comparison of generated activity patterns by the time of day with survey data</td> </tr> <tr> <td><code>dnk_location_construction_0_9.pdf</code></td> <td>Validation plots for location construction</td> </tr> <tr> <td><code>dnk_location_assignement_0_9.pdf</code></td> <td>Validation plots for location assignment, including travel distribution plots</td> </tr> <tr> <td><code>dnk_dnk_ver_0_9_0_avg_travel_distance.pdf</code></td> <td>Choropleth map visualizing average travel distance</td> </tr> <tr> <td><code>dnk_dnk_ver_0_9_0_travel_distr_combined.pdf</code></td> <td>Travel distance distribution</td> </tr> <tr> <td><code>dnk_dnk_ver_0_9_0_num_activity_loc.pdf</code></td> <td>Choropleth map visualizing number of activity locations</td> </tr> <tr> <td><code>dnk_dnk_ver_0_9_0_avg_age.pdf</code></td> <td>Choropleth map visualizing average age</td> </tr> <tr> <td><code>dnk_dnk_ver_0_9_0_pop_density_per_sqkm.pdf</code></td> <td>Choropleth map visualizing population density</td> </tr> <tr> <td><code>dnk_dnk_ver_0_9_0_pop_size.pdf</code></td> <td>Choropleth map visualizing population size</td> </tr> </tbody> </table>
Synthetic population for IND_MANIPUR
<p><strong>Synthetic populations for regions of the World (SPW) | Manipur</strong></p><p><strong>Dataset information</strong></p><p>A synthetic population of a region as provided here, captures the people of the region with selected demographic attributes, their organization into households, their assigned activities for a day, the locations where the activities take place and thus where interactions among population members happen (e.g., spread of epidemics).</p> <p><strong>License</strong></p><p><a href="https://creativecommons.org/licenses/by/4.0/">CC-BY-4.0</a></p> <p><strong>Acknowledgment</strong></p><p>This project was supported by the National Science Foundation under the NSF RAPID: COVID-19 Response Support: Building Synthetic Multi-scale Networks (PI: Madhav Marathe, Co-PIs: Henning Mortveit, Srinivasan Venkatramanan; Fund Number: OAC-2027541).</p> <p><strong>Contact information</strong></p><p>Henning.Mortveit@virginia.edu</p> <p><strong>Identifiers</strong></p><table> <thead><tr> <th></th> <th></th> </tr> </thead> <tbody> <tr> <td>Region name</td> <td>Manipur</td> </tr> <tr> <td>Region ID</td> <td>ind_140001942</td> </tr> <tr> <td>Model</td> <td>coarse</td> </tr> <tr> <td>Version</td> <td>0_9_0</td> </tr> </tbody> </table> <p><strong>Statistics</strong></p><table> <thead><tr> <th>Name</th> <th>Value</th> </tr> </thead> <tbody> <tr> <td>Population</td> <td>2796700</td> </tr> <tr> <td>Average age</td> <td>27.5</td> </tr> <tr> <td>Households</td> <td>635806</td> </tr> <tr> <td>Average household size</td> <td>4.4</td> </tr> <tr> <td>Residence locations</td> <td>635806</td> </tr> <tr> <td>Activity locations</td> <td>192709</td> </tr> <tr> <td>Average number of activities</td> <td>5.5</td> </tr> <tr> <td>Average travel distance</td> <td>78.3</td> </tr> </tbody> </table> <p><strong>Sources</strong></p><table> <thead><tr> <th>Description</th> <th>Name</th> <th>Version</th> <th>Url</th> </tr> </thead> <tbody> <tr> <td>Activity template data</td> <td>World Bank</td> <td>2021</td> <td><a href="https://data.worldbank.org">https://data.worldbank.org</a></td> </tr> <tr> <td>Administrative boundaries</td> <td>ADCW</td> <td>7.6</td> <td><a href="https://www.adci.com/adc-worldmap">https://www.adci.com/adc-worldmap</a></td> </tr> <tr> <td>Curated POIs based on OSM</td> <td>SLIPO/OSM POIs</td> <td></td> <td><a href="http://slipo.eu/?p=1551">http://slipo.eu/?p=1551</a> <a href="https://www.openstreetmap.org/">https://www.openstreetmap.org/</a></td> </tr> <tr> <td>Household data</td> <td>DHS</td> <td></td> <td><a href="https://dhsprogram.com">https://dhsprogram.com</a></td> </tr> <tr> <td>Population count with demographic attributes</td> <td>GPW</td> <td>v4.11</td> <td><a href="https://sedac.ciesin.columbia.edu/data/set/gpw-v4-admin-unit-center-points-population-estimates-rev11">https://sedac.ciesin.columbia.edu/data/set/gpw-v4-admin-unit-center-points-population-estimates-rev11</a></td> </tr> </tbody> </table> <p><strong>Files description</strong></p><p><strong>Base data files (ind_140001942_data_v_0_9.zip)</strong></p><table> <thead><tr> <th>Filename</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td><code>ind_140001942_person_v_0_9.csv</code></td> <td>Data for each person including attributes such as age, gender, and household ID.</td> </tr> <tr> <td><code>ind_140001942_household_v_0_9.csv</code></td> <td>Data at household level.</td> </tr> <tr> <td><code>ind_140001942_residence_locations_v_0_9.csv</code></td> <td>Data about residence locations</td> </tr> <tr> <td><code>ind_140001942_activity_locations_v_0_9.csv</code></td> <td>Data about activity locations, including what activity types are supported at these locations</td> </tr> <tr> <td><code>ind_140001942_activity_location_assignment_v_0_9.csv</code></td> <td>For each person and for each of their activities, this file specifies the location where the activity takes place</td> </tr> </tbody> </table> <p><strong>Derived data files</strong></p><table> <thead><tr> <th>Filename</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td><code>ind_140001942_contact_matrix_v_0_9.csv</code></td> <td>A POLYMOD-type contact matrix constructed from a network representation of the location assignment data and a within-location contact model.</td> </tr> </tbody> </table> <p><strong>Validation and measures files</strong></p><table> <thead><tr> <th>Filename</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td><code>ind_140001942_household_grouping_validation_v_0_9.pdf</code></td> <td>Validation plots for household construction</td> </tr> <tr> <td><code>ind_140001942_activity_durations_{adult,child}_v_0_9.pdf</code></td> <td>Comparison of time spent on generated activities with survey data</td> </tr> <tr> <td><code>ind_140001942_activity_patterns_{adult,child}_v_0_9.pdf</code></td> <td>Comparison of generated activity patterns by the time of day with survey data</td> </tr> <tr> <td><code>ind_140001942_location_construction_0_9.pdf</code></td> <td>Validation plots for location construction</td> </tr> <tr> <td><code>ind_140001942_location_assignement_0_9.pdf</code></td> <td>Validation plots for location assignment, including travel distribution plots</td> </tr> <tr> <td><code>ind_140001942_ind_140001942_ver_0_9_0_avg_travel_distance.pdf</code></td> <td>Choropleth map visualizing average travel distance</td> </tr> <tr> <td><code>ind_140001942_ind_140001942_ver_0_9_0_travel_distr_combined.pdf</code></td> <td>Travel distance distribution</td> </tr> <tr> <td><code>ind_140001942_ind_140001942_ver_0_9_0_num_activity_loc.pdf</code></td> <td>Choropleth map visualizing number of activity locations</td> </tr> <tr> <td><code>ind_140001942_ind_140001942_ver_0_9_0_avg_age.pdf</code></td> <td>Choropleth map visualizing average age</td> </tr> <tr> <td><code>ind_140001942_ind_140001942_ver_0_9_0_pop_density_per_sqkm.pdf</code></td> <td>Choropleth map visualizing population density</td> </tr> <tr> <td><code>ind_140001942_ind_140001942_ver_0_9_0_pop_size.pdf</code></td> <td>Choropleth map visualizing population size</td> </tr> </tbody> </table>
Synthetic population – Democratization of electric vehicle charging infrastructure
Open the record for dataset details and reuse information.
Efficient detection and purification of cell populations using synthetic microRNA switches
GEO Series GSE60633. Homo sapiens. 43 samples. Type: Expression profiling by array; Non-coding RNA profiling by array.
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