People living in some of the largest U.S. cities and their surrounding areas face the highest ラーメンベット 入金ボーナス of contracting COVID-19 in the near future, according to anew set of online dashboardscreated by researchers in the ラーメンベット 禁止ゲーム of Engineering at The University of Texas at Austin.
The ラーメンベット 入金ボーナス analysis model used by the website examines more than 3,000 U.S. counties and features three dashboards that focus on aspects of community resilience: ラーメンベット 入金ボーナス, exposure and vulnerability. Counties are scored on 14 different variables across the three dashboards, accounting for socioeconomic circumstances, population density, transportation infrastructure and other important metrics for measuring the pandemic, such as available intensive care unit beds and the average number of new cases.
The researchers said the new model presents the most comprehensive look yet at the virus’s current and future spread across the U.S. Other models have mostly focused on the number of cases and deaths observed in an area to make predictions about trends, rather than look at a wider variety of ラーメンベット 入金ボーナス factors to understand where increased spread could occur.
“This information allows the public and decision-makers to have a better sense of the risk level of each ラーメンベット 入金ボーナス in terms of infection, fatality, vulnerability and exposure,” said Zhanmin Zhang, a professor in the Department of Civil, Architectural and Environmental Engineering who led the development of the dashboards. “Knowing the risks allows people to develop better insights and make more informed day-to-day decisions.”
The model is updated weekly, and it currently rates four counties as extreme for both risk of contracting the virus and dying from it: Los Angeles ラーメンベット 入金ボーナス, Miami-Dade ラーメンベット 入金ボーナス, Harris ラーメンベット 入金ボーナス (Houston) and Dallas ラーメンベット 入金ボーナス. Cook ラーメンベット 入金ボーナス, Ill. (Chicago) is the only other ラーメンベット 入金ボーナス to receive an extreme rating, and it is for infection risk, but not death risk.
Seven of the 10 most populous counties/metro areas in the U.S. rank in the top 10 for infection ラーメンベット 入金ボーナス, and six of them are in the top 10 for death ラーメンベット 入金ボーナス. See table below for COVID-19 Infection and Fatality ラーメンベット 入金ボーナス for the 25 Most Populous Counties/Metro Areas
“The chances of being exposed to the virus in these populous counties are higher because of the massive number of daily trips created by businesses and other major points of interest — such as supermarkets, parks and restaurants — from other regions, as well as the presence of major airport hubs and highway systems,” Zhang said. “In such high-density areas, enforcing social distancing measures is a challenge, further increasing the ラーメンベット 入金ボーナス of contracting the virus.”
The site provides snapshots of each ラーメンベット 入金ボーナス’s metrics, as well as changes over time. Local governments can use these tools to find counties with similar levels of risk and examine how effective their COVID containment measures have been.
“These indicators of impending risks can help officials make decisions on enforcement of COVID-19-related restrictions, such as social distancing norms, stay-at-home orders, use of masks and sanitizers, or closing down of public spaces and institutions,” Zhang said. “The infection and fatality ラーメンベット 入金ボーナス numbers are based on the combination of vulnerability and exposure factors.”
Infection vulnerability factors include the number of residents per square kilometer, the percentage of workers who use public transit, the share of the population that works in industries where remote working isn’t possible and the number of apartments and condos as a function of the overall housing stock.
Fatality vulnerability metrics include the percentage of the population over age 65, the number of ICU beds per 10,000 people, the share of adults with health problems, the number of people lacking health insurance coverage and the percentage of adults with limited English fluency — an indicator that people might have trouble accessing services.
Exposure variables include the presence of busy roads and highways that bring in travelers, 14-day averages of COVID cases, proximity to major airports, and a social distancing indicator using the number of “point of interest” visitors — people going to gathering places such as restaurants and bars, based on anonymized mobile data.
Visit the website and review the dashboards at covid19.caee.utexas.edu.
COVID-19 Infection and Fatality ラーメンベット 入金ボーナス for the 25 Most Populous Counties/Metro Areas
Population | ラーメンベット 入金ボーナス/Metro Area | State | Rank by Infection ラーメンベット 入金ボーナス | Rank by Fatality ラーメンベット 入金ボーナス |
---|---|---|---|---|
10,098,052 | Los Angeles ラーメンベット 入金ボーナス | CA | 1 | 1 |
8,443,713 | New York City | NY | 8 | 19 |
5,223,719 | Cook ラーメンベット 入金ボーナス | IL | 3 | 6 |
4,602,523 | Harris ラーメンベット 入金ボーナス | TX | 4 | 3 |
4,253,913 | Maricopa ラーメンベット 入金ボーナス | AZ | 12 | 9 |
3,302,833 | San Diego ラーメンベット 入金ボーナス | CA | 22 | 21 |
3,164,182 | Orange ラーメンベット 入金ボーナス | CA | 6 | 11 |
2,715,516 | Miami-Dade ラーメンベット 入金ボーナス | FL | 2 | 2 |
2,586,552 | Dallas ラーメンベット 入金ボーナス | TX | 5 | 4 |
2,383,2863 | Riverside ラーメンベット 入金ボーナス | CA | 18 | 12 |
2,163,257 | King ラーメンベット 入金ボーナス | WA | 34 | 62 |
2,141,574 | Clark ラーメンベット 入金ボーナス | NV | 10 | 7 |
2,135,413 | San Bernardino ラーメンベット 入金ボーナス | CA | 19 | 13 |
2,019,977 | Tarrant ラーメンベット 入金ボーナス | TX | 9 | 10 |
1,925,865 | Bexar ラーメンベット 入金ボーナス | TX | 65 | 34 |
1,922,200 | Santa Clara ラーメンベット 入金ボーナス | CA | 17 | 26 |
1,909,151 | Broward ラーメンベット 入金ボーナス | FL | 7 | 5 |
1,761,382 | Wayne ラーメンベット 入金ボーナス | MI | 41 | 59 |
1,643,700 | Alameda ラーメンベット 入金ボーナス | CA | 11 | 28 |
1,595,192 | Middlesex ラーメンベット 入金ボーナス | MA | 89 | 185 |
1,575,522 | Philadelphia ラーメンベット 入金ボーナス | PA | 15 | 66 |
1,510,023 | Sacramento ラーメンベット 入金ボーナス | CA | 41 | 35 |
1,487,901 | Suffolk ラーメンベット 入金ボーナス | NY | 115 | 147 |
1,446,277 | Palm Beach ラーメンベット 入金ボーナス | FL | 19 | 15 |
1,378,883 | Hillsborough ラーメンベット 入金ボーナス | FL | 27 | 21 |
Updated as of Aug. 16