The COVID-19 Pandemic and Rural America
Recent county-level evidence on the prevalence of COVID-19 and local unemployment rates, while no means a complete picture, provides indication of the spread of the virus and ensuing economic recession across America (see the note on data sources). This page will be updated monthly.
COVID-19 has spread to nearly every nation in the world, and to every State and nearly every county in the United States. The virus initially spread most rapidly to large metro areas, and most confirmed cases are still in metro areas with populations of at least 1 million. This is consistent with most of the U.S. population living in large metro areas. In per capita terms, the prevalence of COVID-19 cases has been greater in metro than in nonmetro areas until late October. The prevalence of COVID-19 cases is now greater and growing more rapidly in nonmetro areas than in metro areas. The share of all COVID-19 cases in nonmetro areas has been growing since late March, increasing from 3.6 percent on April 1 to 15.6 percent on December 7.
By December 7, the regions with the highest prevalence of COVID-19 cases included much of the Great Plains, the upper Midwest, and the Mountain West (especially the northern parts of these regions), and large parts of the South and Southwest. Recent growth in COVID-19 prevalence has been especially rapid in the northern Great Plains and parts of the Upper Midwest and the Mountain West. Less affected areas generally include much of the Northeast, the West Coast, and Hawaii—though many exceptions are evident in these regions.
Higher COVID-19 case rates have been observed in some subpopulations, such as people confined to prisons and nursing homes, students at some colleges and universities, and in some minority populations, including African Americans, Hispanics, and some American Indian populations, such as members of the Navajo Nation in the Southwest.
Higher COVID-19 prevalence is also associated with some industries. The Economic Research Service (ERS) classifies counties by economic type, based primarily on the dependence of employment and income on specific types of industries. Among nonmetro counties, the highest COVID-19 case rates are found in farming-dependent and manufacturing-dependent counties. The high prevalence of COVID-19 in manufacturing-dependent counties is due partly to higher COVID-19 case rates in meatpacking-dependent counties (those in which 20 percent or more of employment is in the meatpacking industry), almost all of which are manufacturing-dependent counties. Nonmetro and metro recreation counties have the lowest COVID-19 case rates.
After the beginning of the pandemic, U.S. unemployment surged to levels not seen since the Great Depression in the 1930s. In March, the unemployment rate began to rise. Monthly unemployment estimates reported by the Bureau of Labor Statistics (BLS) refer to the week that includes the 12th day of each calendar month. By the week including April 12, U.S. unemployment peaked at a seasonally adjusted rate of 14.7 percent. This surge resulted from government restrictions on non-essential economic activity, social distancing requirements, temporary closures of some facilities due to infection concerns, effects of illness on availability of some essential workers, and voluntary decisions by consumers to limit travel and other activities.
The unemployment rate began to decline after April as the Coronavirus Aid, Relief, and Economic Security (CARES) Act, other new Federal laws, and the Federal Reserve made trillions of dollars in funds available as part of efforts to address the recession; States relaxed restrictions put in place to control the pandemic; and consumers began to increase spending. By the week of November 12, the national unemployment rate had fallen to 6.7 percent.
Based on BLS estimates of county-level unemployment, the unemployment rate rose rapidly in both metro and nonmetro areas in March and April. The (not seasonally adjusted) rate reached almost 14.6 percent in metro areas and about 13.6 percent in nonmetro areas by the week of April 12. After April, the unemployment rate declined in both metro and nonmetro areas. By the week of September 12, the unemployment rate had fallen to 7.9 percent in metro areas and 6.0 percent in nonmetro areas. According to preliminary BLS estimates for October, the unemployment rate continued falling to 6.8 percent in metro areas and 5.3 percent in nonmetro areas by the week of October 12.
Note: These rates are not seasonally adjusted because the BLS county-level estimates of employment and unemployment are not seasonally adjusted.
Estimated unemployment rates in September varied substantially across counties in the United States, ranging from a low of 0.6 percent to a high of 23.2 percent. Generally, the highest unemployment rates were evident in the Northeast, Appalachia, and large parts of the Great Lakes region, the South, Midwest, Texas, Southwest, West Coast, Hawaii and Alaska. The lowest unemployment rates were evident in the Great Plains and much of the Mountain West, though high unemployment rates occurred in some counties in these regions as well.
The unemployment rate in September was higher in metro than in nonmetro counties for all county economic types. Farming-dependent counties had the lowest unemployment rate in both metro and nonmetro counties (4.4 percent in nonmetro and 4.7 percent in metro farming-dependent counties), and nonmetro manufacturing-dependent also had relatively low unemployment (5.5 percent). The highest unemployment rate occurred in metro mining-dependent counties (8.8 percent). Among nonmetro counties, the highest unemployment rates also occurred in mining-dependent counties (7.4 percent).
In general, nonmetro counties have lower unemployment rates than metro counties but higher prevalence and more rapid growth of COVID-19 cases per 100,000 residents. This inverse relationship appears to be most evident in farming-dependent and manufacturing-dependent nonmetro counties, which have the highest prevalence of COVID-19 but the lowest unemployment rates in the most recent data.
The county-level data on COVID-19 cases are from the Johns Hopkins University Center for Systems Science and Engineering (JHU-CSSE). The number of cases in each county are divided by the 2019 population of the county to compute case rates, using the 2019 U.S. Department of Commerce, Bureau of the Census population estimates. The JHU-CSSE case data are based on case reports provided by the U.S. Centers for Disease Control and Prevention (CDC) and by State and local health departments. Not all cases are assigned to specific counties in the JHU-CSSE data (1.6 percent of total cases were not assigned to specific counties on December 7); these cases are not included in the analysis of case rates by metro status or county economic types.
The county-level data on unemployment rates are from the BLS Local Area Unemployment Statistics (LAUS) program. These data are model-based estimates based mainly on the monthly Current Population Survey employment and unemployment estimates, and unemployment insurance claims data from State workforce agencies. The county estimates are controlled to sum to State-level estimates, which are controlled to sum to national estimates.
The LAUS estimates are considered preliminary in the first month after release, as additional information is incorporated into subsequent estimates. Significant changes in estimated county-level unemployment rates can occur between the initial preliminary estimate and subsequent revised estimates. For example, the maximum change in the unemployment rate for a single county between the preliminary estimate for March 2020 provided in the LAUS data released on April 29, 2020, and the revised estimate for March 2020 provided in the LAUS data released on June 5, 2020, is 1.94 percentage points. Across all counties, the mean difference in the March 2020 unemployment rate between the preliminary and revised estimate was -0.06 percentage points (i.e., the mean rate was 0.06 percentage points lower in the revised LAUS estimates), and the median difference was -0.08 percentage points.
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