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Figure 1.  Cumulative Coronavirus Disease 2019 (COVID-19) Cases per 10 000 Residents in Iowa and Illinois Border Counties
Cumulative Coronavirus Disease 2019 (COVID-19) Cases per 10 000 Residents in Iowa and Illinois Border Counties

The vertical line represents the date on which the stay-at-home order took effect in Illinois.

Figure 2.  Statewide Cumulative Coronavirus Disease 2019 Tests per 10 000 Residents in Iowa and Illinois
Statewide Cumulative Coronavirus Disease 2019 Tests per 10 000 Residents in Iowa and Illinois

The vertical line represents the date on which the stay-at-home order took effect in Illinois.

Table 1.  Difference-in-Differences Estimates of COVID-19 Cases Comparing Border Counties in Iowa With Those in Illinois Before and After the Stay-at-Home Order Was Issued in Illinoisa
Difference-in-Differences Estimates of COVID-19 Cases Comparing Border Counties in Iowa With Those in Illinois Before and After the Stay-at-Home Order Was Issued in Illinoisa
Table 2.  Sensitivity Analysis of Difference-in-Differences Estimates of COVID-19 Cases Comparing Border Counties in Iowa With Those in Illinois Before and After the Stay-at-Home Order Was Issued in Illinoisa
Sensitivity Analysis of Difference-in-Differences Estimates of COVID-19 Cases Comparing Border Counties in Iowa With Those in Illinois Before and After the Stay-at-Home Order Was Issued in Illinoisa
Audio Editors' Summary (14:42)
1.
Office of the Governor of Iowa. Gov. Reynolds signs new proclamation continuing State Public Health Emergency Declaration, ordering additional closures. Published April 6, 2020. Accessed April 20, 2020. https://governor.iowa.gov/press-release/gov-reynolds-signs-new-proclamation-continuing-state-public-health-emergency-3
2.
Rodriguez  B. Iowa Board of Medicine, physicians' group ask Gov. Kim Reynolds to issue mandatory order for Iowans to stay home during outbreak. Des Moines Register. Published April 3, 2020. Accessed April 20, 2020. https://www.desmoinesregister.com/story/news/health/2020/04/03/coronavirus-board-medicine-recommends-iowa-governor-issue-mandatory-shelter-place/2940467001/
3.
Coltrain  N. Gov. Kim Reynolds: Iowa is already under 'equivalent' of stay-at-home order to fight coronavirus. Des Moines Register. Published March 25, 2020. Accessed May 9, 2020. https://www.desmoinesregister.com/story/news/health/2020/03/25/iowa-gov-kim-reynolds-holds-daily-covid-19-briefing-wednesday-march-25-coronavirus/5077077002/
4.
State of Illinois. Executive orders related to COVID-19. Accessed April 20, 2020. https://www2.illinois.gov/sites/coronavirus/Resources/Pages/ExecutiveOrders.aspx
5.
GitHub. An ongoing repository of data on coronavirus cases and deaths in the U.S. Accessed April 28, 2020. https://github.com/nytimes/covid-19-data
6.
US Census Bureau. SAIPE state and county estimates for 2018. Published December 2019. Accessed May 5, 2020. https://www.census.gov/data/datasets/2018/demo/saipe/2018-state-and-county.html
7.
The COVID Tracking Project. About us. Accessed April 28, 2020. https://covidtracking.com/about-project
8.
US Census Bureau. Population, population change, and estimated components of population change: April 1, 2010, to July 1, 2019 (CO-EST2019-alldata). Accessed April 20, 2020. https://www.census.gov/data/datasets/time-series/demo/popest/2010s-counties-total.html#par_textimage_70769902
9.
US Census Bureau. USA Counties Land Area. Published October 2011. Accessed April 20, 2020. https://www.census.gov/library/publications/2011/compendia/usa-counties-2011.html#LND
10.
Friedson  AI, McNichols  D, Sabia  JJ, Dave  D. Did California’s shelter-in-place order work? early coronavirus-related public health benefits. National Bureau of Economic Research Working Paper Series, No. 26992. Published April 2020. Accessed May 11, 2020. https://www.nber.org/papers/w26992.pdf
11.
Iowa Department of Public Health. Novel coronavirus—press release archive. Accessed May 9, 2020. https://idph.iowa.gov/Emerging-Health-Issues/Novel-Coronavirus/Press-Release-Archive
12.
Eller  D. COVID-19 outbreak halts production at Tyson pork processing plant in eastern Iowa. Des Moines Register. Published April 6, 2020. Accessed April 20, 2020. https://www.desmoinesregister.com/story/money/agriculture/2020/04/06/covid-19-outbreak-halts-production-east-iowa-pork-processing-plant/2955922001/
6 Comments for this article
EXPAND ALL
Interstate Economic Activity
Pranav Puri, BA | Mayo Clinic
One limitation I see in this article is that the authors do not account for significant interstate economic activity. Rock Island County and Scott County comprise the Quad Cities, an effectively contiguous economic region. There was no shutdown of interstate travel, so this maybe an important confounding factor. Thousands of people live in Illinois but work in Iowa. Similarly, many residents of Illinois cross the river to Iowa for restaurants and shopping.
CONFLICT OF INTEREST: None Reported
Cost of fewer cases
Judith Nowak, MD | George Washington University Medical Center
At the risk of being attacked as heartless, were 217 less cases worth the costs of a shutdown?
CONFLICT OF INTEREST: None Reported
Relevance
Michael Plunkett, MD MBA | Primary care
Agree with their conclusion,”more research is needed.”

So 500 more Corona cases in 1 month out of a population of ~500,000 attributed to lack of a stay at home order.

Interesting but not impressive.
CONFLICT OF INTEREST: None Reported
Death rates and ICU occupancy
Manoel Luiz Neto, MPH | Hospital de Base do Distrito Federal
Interesting paper. Although the number of cases was higher at Iowa, Illinois have almost 10 times more deaths than Iowa.

The severity of cases should be compared probably in another study.
CONFLICT OF INTEREST: None Reported
Failure of Intellectual Honesty
Darrell Lewis, MA, BS | former Iowa Hospital Board Member
This study compares the 7 counties in Illinois to the 8 counties in Iowa along their Mississippi River; the authors conclude that Illinois has been more successful than Iowa in their COVID-19 mitigation efforts; I disagree with this claim.

The seven Illinois counties are primarily rural. Five of the seven have a population less than 25,000. By comparison, the Iowa counties are urban in nature. Six of the Eight Iowa counties have a population of more than 25,000. Drawing conclusion from geographic areas so substantially disparate in their basic nature would be ill advised.

On the Iowa side, you have several of Iowa largest cities including Davenport, Dubuque, Clinton, Bettendorf, Burlington, Fort Madison, Keokuk and Muscatine. On the Illinois side, the only cities of size are Rock Island, Moline and East Moline.

Looking specifically at the Quad Cities, the differences appear minimal. In Iowa, the Quad Cities includes primarily Scott County with 172,000 people (Davenport and Bettendorf). In Illinois, it’s Rock Island County with 145,000 people (Rock Island, Moline and East Moline).

To date, Rock Island County has 600 cases with 21 deaths. The more populous Scott County in Iowa has only 286 cases with 8 deaths. So the facts are when we actually compare counties that are comparable Iowa outperforms Illinois by a factor of two to one.

The remaining six Illinois counties have a total population of 133,000, while the seven Iowa counties across the river have a population of 289,000. In Iowa, this includes the cities of Dubuque, Clinton, Muscatine, Burlington, Ft. Madison and Keokuk. There are no cities of similar size on the Illinois side.

So while those Iowa counties do have more cases, well over half the cases can be attributed to the packing plant in Columbus Junction, Iowa. Stay at home orders have no relevance to packing plant COVID spread and therefore should not be considered.
CONFLICT OF INTEREST: None Reported
READ MORE
A Rush to Publish: A Case Study On How To Perform Poor Case Studies
Ron Bremner, PhD | Member IEEE
This study is flawed, as the researchers may have lacked some information, but certainly discounted information which they did have. In their ‘Results’ section, they state that ‘The estimates indicate excess cases in the border Iowa counties by as many as 217 cases after 1 month without a stay-at-home order.’

The paper states that the ‘trends of cumulative COVID-19 cases per 10,000 residents for the Iowa and Illinois border counties were comparable before the Illinois stay-at-home order’, which was the start of the time period for this study. As mentioned, the authors stated that a stay-at-home order could have
resulted in 217 fewer cases.

Later in the paper, they mention that there was an outbreak in a meat packing plant in Louisa County, one of the Iowa counties in the study, and that this outbreak occurred on April 6, early in the study period. They do not, however, look at the impact of that outbreak on their statistics, nor do they mention the number of meat-packing employees who tested positive, and that these employees would have continued to work, regardless of a stay-at-home order. On May 5, it was reported that 221 employees had tested positive.

The fact that the statistics showed 217 fewer cases could have occurred, and that 221 employees at a facility which would have remained open (regardless of a stay-at-home order) should have been considered. Further analysis could have compared the Iowa counties in their study with each other. The highest number of cases occurred in Louisa County, with 334 cases as of 25 May (after their study), and a rate of 2.99%. (I use the rate after the study, as it is what I had available the day this was written). The second highest rate in the Iowa counties studied was Muscatine County, which is two miles from the meat packing plant. Their rate was 1.27%, with 542 cases. These two counties account for less than 12% of the population, but 52% of the COVID cases in the Iowa counties.

The Iowa county in the study with the next highest incidence of COVID is Dubuque County, at 0.33%. The disparity between the 2.99% and the 0.33% should have been another significant red flag to the authors of the study.

The authors also note that there is a difference in population density between the counties studied, but this and other factors were not taken into account, simply mentioned.

The authors mention that the state of Illinois had a higher testing rate than the state of Iowa, but do not mention that the incidence statewide for Illinois is also higher than for Iowa. The assumption or inference is that the higher testing rate in Illinois would pertain to the counties studied. However, a higher incidence rate in Illinois outside of those 8 counties would likely result in a higher testing rate outside of those counties.
CONFLICT OF INTEREST: None Reported
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Original Investigation
Public Health
May 15, 2020

Comparison of Estimated Rates of Coronavirus Disease 2019 (COVID-19) in Border Counties in Iowa Without a Stay-at-Home Order and Border Counties in Illinois With a Stay-at-Home Order

Author Affiliations
  • 1Department of Health Management and Policy, The University of Iowa, Iowa City
  • 2Department of Economics, The University of Iowa, Iowa City
  • 3Department of Preventive and Community Dentistry, The University of Iowa, Iowa City
  • 4Public Policy Center, The University of Iowa, Iowa City
  • 5National Bureau of Economic Research, Cambridge, Massachusetts
JAMA Netw Open. 2020;3(5):e2011102. doi:10.1001/jamanetworkopen.2020.11102
Key Points

Question  Was the stay-at-home order in Illinois associated with different rates of coronavirus disease 2019 (COVID-19) compared with Iowa, which did not issue a stay-at-home order?

Findings  This cross-sectional study of border counties in Iowa and Illinois used difference-in-differences design and found an increase in estimated rates of COVID-19 cases per 10 000 residents in the border counties in Iowa compared with the border counties in Illinois after a stay-at-home order was implemented in Illinois but not in Iowa.

Meaning  The results of this study suggest that issuing a stay-at-home order in Iowa may have helped limit the spread of COVID-19 cases in that state.

Abstract

Importance  Iowa is 1 of 5 states in the US that have not issued a stay-at-home order during the coronavirus disease 2019 (COVID-19) pandemic. There is no empirical evidence on whether issuing a stay-at-home order in Iowa could have been associated with a reduced rate of COVID-19 infections in the state.

Objective  To compare COVID-19 cases in border counties in Iowa, which did not issue a stay-at-home order, with cases in border counties in Illinois, which did issue a stay-at-home order.

Design, Setting, and Participants  This cross-sectional study with a difference-in-differences design compared daily changes in COVID-19 cases per 10 000 residents in 8 Iowa counties bordering Illinois with those in the 7 Illinois counties bordering Iowa before and after Illinois issued a stay-at-home order on March 21, 2020. Additional sensitivity analyses were conducted to account for differences in timing of closing schools and nonessential businesses between the 2 states and differential trends in COVID-19 cases by county population density and poverty rates.

Exposures  Issuing a stay-at-home order.

Main Outcomes and Measures  Comparison of cumulative cases of COVID-19 per 10 000 residents in border counties in Iowa and Illinois.

Results  The total populations were 462 445 in the Iowa border counties and 272 385 in the Illinois border counties. Population density was higher in the Iowa counties (114.2 people per square mile) than in the Illinois counties (78.2 people per square mile). Trends of cumulative COVID-19 cases per 10 000 residents for the Iowa and Illinois border counties were comparable before the Illinois stay-at-home order, which went into effect at 5:00 pm on March 21 (March 15 to March 21: 0.024 per 10 000 residents vs 0.026 per 10 000 residents). After that, cases increased more quickly in Iowa and more slowly in Illinois. Within 10, 20, and 30 days after the enactment of the stay-at-home order in Illinois, the difference in cases was −0.51 per 10 000 residents (SE, 0.09; 95% CI, −0.69 to −0.32; P < .001), −1.15 per 10 000 residents (SE, 0.49; 95% CI, −2.12 to −0.18; P = .02), and −4.71 per 10 000 residents (SE, 1.99; 95% CI, −8.64 to −0.78; P = .02), respectively. The estimates indicate excess cases in the border Iowa counties by as many as 217 cases after 1 month without a stay-at-home order. This estimate of excess cases represents 30.4% of the 716 total cases in those Iowa counties by that date. Sensitivity analyses addressing differences in timing of closing schools and nonessential businesses and differences in county population density and poverty rates between the 2 states supported these findings.

Conclusions and Relevance  This cross-sectional study with a difference-in-differences design found an increase in estimated rates of COVID-19 cases per 10 000 residents in the border counties in Iowa compared with the border counties in Illinois following a stay-at-home order that was implemented in Illinois but not in Iowa.

Introduction

Iowa is 1 of 5 states that have not issued stay-at-home orders for the coronavirus disease 2019 (COVID-19) pandemic. The state has issued a series of orders, including banning large gatherings and closing bars and restaurant dining on March 17, 2020; closing some nonessential businesses (eg, dental offices, clothing stores, barbershops, massage therapy, medical spas) on March 26, 2020; closing all primary and secondary schools (recommended on March 15, 2020) on April 2, 2020; and closing additional businesses (eg, malls, nongrocery stores, museums, libraries, social clubs) on April 6, 2020.1

Multiple constituents have petitioned Iowa’s governor to issue a stay-at-home order (including the Iowa Board of Medicine).2 However, the governor has indicated that the existing restrictions are essentially equivalent to stay-at-home orders in other states.3 There is no empirical evidence on whether issuing a stay-at-home order in Iowa could have been associated with a reduced rate of COVID-19 infections in the state. Illinois, which borders Iowa, issued a stay-at-home order effective on the evening of March 21, 2020.4 The order also closed all nonessential businesses in that state. Using a cross-sectional study with difference-in-differences design, we compared the cases of COVID-19 in border counties in Iowa and Illinois.

Methods

This cross-sectional study used a difference-in-differences design to compare daily changes in COVID-19 cases per 10 000 residents in 8 Iowa counties bordering Illinois (ie, Clinton, Des Moines, Dubuque, Jackson, Lee, Louisa, Muscatine, and Scott) with those in 7 Illinois counties bordering Iowa (ie, Carroll, Hancock, Henderson, Jo Daviess, Mercer, Rock Island, and Whiteside) before and after Illinois issued a stay-at-home order on March 21, 2020. County-level COVID-19 data come from a repository of state and local health agency reports.5 The difference-in-differences design assumes similarity of COVID-19 trends across the border if Iowa and Illinois had issued similar orders. We evaluated this assumption by comparing COVID-19 trends before enacting the order. The study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for cross-sectional studies. Per the Common Rule, institutional review board review was not required for this study, which used deidentified, publicly available data.

Statistical Analyses

We estimated the following difference-in-differences regression using daily county-level COVID-19 data: Casesct = α + β1StayHomec × Postt + θc + ωt + ϵct, in which β1 is the difference-in-differences estimate, representing the pre-post stay-at-home order differential change in COVID-19 cases per 10 000 residents (Cases) between Iowa and Illinois, c indicates a specific county, and t indicates a specific day. The pre-period is from March 15 (when the first case was reported in those counties) to March 21. We performed a t test to test whether the β1 equaled 0 at a significance level of P < .05. We estimated this model separately for 6 post-periods (each 5 days) from March 22 (the first full day with a stay-at-home order in Illinois) until April 20. County-specific fixed effects (θc) captured county time-invariant differences, such as population density and demographic and socioeconomic characteristics, which should not change during the short study period. Day fixed effects (ωt) captured daily changes in COVID-19 spread shared between Iowa and Illinois. The regression was estimated via least squares weighted by 2019 county population. We tested for homoscedasticity using a Breusch-Pagan test; the test rejected homoscedasticity at P < .001. Therefore, we estimated heteroscedasticity-robust standard errors.

We also performed 2 sensitivity analyses. The first sensitivity analysis accounted for differences in the timing of closing schools and nonessential businesses between the 2 states. We reestimated the regressions adding 2 state-level time-varying indicators as covariates, as follows: (1) whether the state had issued an order for closing primary and secondary schools by that day (issued on April 2 in Iowa and March 17 in Illinois) and (2) whether the state had issued an order to close nonessential businesses (the first order in Iowa was on March 26; in Illinois, closure of nonessential businesses was part of the stay-at-home order, so it was assigned the same date). The second sensitivity analysis examined whether there were differential trends in COVID-19 cases by county population density and poverty rates, reported by census data,6 that may have confounded the difference-in-differences estimates. For this analysis, we added an interaction between the county population density and the post-period indicator (post) and another interaction between the county poverty rate and post to each regression.

To address testing rate differences between the counties in Iowa vs Illinois, we examined daily state level testing data from the COVID Tracking Project to determine total tests per 10 000 residents in Iowa and Illinois.7 Data analyses were conducted with Stata/SE version 16.0 (StataCorp). Statistical significance was set at P < .05, and all tests were 2-tailed.

Results

The total population (based on 2019 census estimates) in the 8 Iowa border counties was 462 445; the total population in the 7 Illinois border counties was 272 385.8 Population density was higher in the Iowa counties (114.2 people per square mile) vs the Illinois counties (78.2 people per square mile).8,9 The population poverty rate was slightly higher in the Iowa counties (12.1% vs 10.8%).6

Figure 1 shows daily cumulative COVID-19 cases per 10 000 residents for the Iowa and Illinois border counties. Trends were comparable before the Illinois stay-at-home order became effective, supporting the difference-in-differences design. From March 15 to March 21 (on the evening of which the stay-at-home order became effective in Illinois), the average daily cases per 10 000 residents was 0.024 in the Iowa counties and 0.026 in the Illinois counties. After that, cases increased more quickly in Iowa. The difference-in-differences regression estimates also indicated a slower increase in COVID-19 cases in Illinois (Table 1). Within 10, 20, and 30 days after the enactment of the stay-at home order in Illinois, the difference in cases was −0.51 per 10 000 residents (SE, 0.09; 95% CI, −0.69 to −0.32; P < .001), −1.15 per 10 000 residents (SE, 0.49; 95% CI, −2.12 to −0.18; P = .02), and −4.71 per 10 000 residents (SE, 1.99; 95% CI, −8.64 to −0.78; P = .02), respectively. The estimates indicate excess cases in the border Iowa counties by as many as 217 after 1 month without a stay-at-home order. This estimate of excess cases represents 30.4% of the 716 total cases in those Iowa counties by that date.

In the first sensitivity analysis accounting for differences in the timing of closing schools and nonessential businesses between the 2 states, the difference-in-differences estimates for the stay-at-home order were similar, although not statistically significant at 20 and 30 days (eg, difference in COVID-19 cases per 10 000 residents in Illinois at 10 days, −0.51; SE, 0.10; 95% CI, −0.71 to −0.31; P < .001; 20 days, −1.18; SE, 0.61; 95% CI, −2.39 to 0.04; P = .06; 30 days, −4.73; SE, 2.57; 95% CI, −9.81 to 0.35; P = .07) (Table 2). In the second sensitivity analysis examining whether there were differential trends in COVID-19 cases by county population density and poverty rates that may have confounded the difference-in-differences estimates, the difference-in-differences estimates were robust to adding these covariates (eg, difference in COVID-19 cases per 10 000 residents in Illinois at 10 days, −0.50; SE, 0.10; 95% CI, −0.70 to −0.30; P < .001; 20 days, −1.13; SE, 0.53; 95% CI, −2.18 to −0.77; P = .04; 30 days, −4.80; SE, 2.517; 95% CI, −9.09 to −0.52; P = .03) (Table 2).

Illinois had a greater increase in tests per 10 000 residents following the stay-at-home order. Both states started with a similar testing rate, but the testing rate in Illinois increased after the stay-at-home order at a faster rate than in Iowa (10 days, 28 vs 23 tests per 10 000 residents; 20 days, 69 vs 51 tests per 10 000 residents; 30 days, 117 vs 82 tests per 10 000 residents) (Figure 2).

Discussion

This cross-sectional study with difference-in-differences design found an increase in estimated rates of COVID-19 cases per 10 000 residents in the border counties in Iowa compared with the border counties in Illinois following a stay-at-home order that was implemented in Illinois but not in Iowa. The estimates indicated as many as 217 excess cases in Iowa after 1 month without a stay-at-home order. Our findings are also consistent with recent evidence from California,10 where a statewide stay-at-home order was associated with reduced COVID-19 cases by 125.5 to 219.7 per 100 000 residents by April 20. Our findings suggest that issuing a stay-at-home order in Iowa while daily cases continued to increase may have helped limit the number of cases.

In the last 2 days of the study period (ie, April 19-20), Iowa began announcing an increase in cases from surveillance testing following outbreaks in meat-processing facilities, including 1 facility in Louisa County.11 That outbreak appears to have been first reported on April 6.12 As described earlier, there was a trend of more cases in Iowa before April 6 and the trend increased during most of the study period. Therefore, the surveillance testing reported toward the end of the study period does not appear to explain the whole trend. Meat-processing plants would not be closed during a stay-at-home order because they are considered essential businesses. Whether stay-at-home orders could modify the likelihood of such outbreaks (through initial cases) and their subsequent effects on community spread is unknown and is an important question for future research, given the outbreaks reported in multiple meat-processing facilities in Iowa and other states.

Limitations

This study has limitations. Findings should be interpreted cautiously considering that possible differences in COVID-19 testing across the border may confound the difference-in-differences estimates. For example, Illinois had a greater increase in tests per 10 000 residents after the stay-at-home order (Figure 2). If state-level testing rates are representative of these counties, this would suggest that Iowa’s testing rate was not higher during this period, and therefore the difference in testing would not explain the observed difference in rates per capita after the stay-at-home order. However, county-level testing trends may be different from state trends and may still confound the difference-in-differences estimates. As noted earlier, a meat-packing facility in Iowa had an outbreak, which increased surveillance. Whether stay-at-home orders affect the likelihood of such outbreaks and their spillovers into the community is an open question for future research.

Conclusions

This cross-sectional study of counties along the border of Iowa and Illinois provides early evidence suggesting that issuing a stay-at-home order in Iowa while daily cases continued to increase may have helped limit the spread of COVID-19 cases in Iowa. Further research is needed to examine the effects of stay-at-home orders in other areas and potential heterogeneity by population and contextual factors.

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Article Information

Accepted for Publication: May 11, 2020.

Published: May 15, 2020. doi:10.1001/jamanetworkopen.2020.11102

Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2020 Lyu W et al. JAMA Network Open.

Corresponding Author: George L. Wehby, PhD, Department of Health Management and Policy, The University of Iowa, 145 N Riverside Dr, 100 College of Public Health Bldg, Room N250, Iowa City, IA 52242 (george-wehby@uiowa.edu).

Author Contributions: Mr Lyu and Dr Wehby had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Wehby.

Acquisition, analysis, or interpretation of data: Both authors.

Drafting of the manuscript: Both authors.

Critical revision of the manuscript for important intellectual content: Wehby.

Statistical analysis: Both authors.

Administrative, technical, or material support: Lyu.

Supervision: Wehby.

Conflict of Interest Disclosures: None reported.

References
1.
Office of the Governor of Iowa. Gov. Reynolds signs new proclamation continuing State Public Health Emergency Declaration, ordering additional closures. Published April 6, 2020. Accessed April 20, 2020. https://governor.iowa.gov/press-release/gov-reynolds-signs-new-proclamation-continuing-state-public-health-emergency-3
2.
Rodriguez  B. Iowa Board of Medicine, physicians' group ask Gov. Kim Reynolds to issue mandatory order for Iowans to stay home during outbreak. Des Moines Register. Published April 3, 2020. Accessed April 20, 2020. https://www.desmoinesregister.com/story/news/health/2020/04/03/coronavirus-board-medicine-recommends-iowa-governor-issue-mandatory-shelter-place/2940467001/
3.
Coltrain  N. Gov. Kim Reynolds: Iowa is already under 'equivalent' of stay-at-home order to fight coronavirus. Des Moines Register. Published March 25, 2020. Accessed May 9, 2020. https://www.desmoinesregister.com/story/news/health/2020/03/25/iowa-gov-kim-reynolds-holds-daily-covid-19-briefing-wednesday-march-25-coronavirus/5077077002/
4.
State of Illinois. Executive orders related to COVID-19. Accessed April 20, 2020. https://www2.illinois.gov/sites/coronavirus/Resources/Pages/ExecutiveOrders.aspx
5.
GitHub. An ongoing repository of data on coronavirus cases and deaths in the U.S. Accessed April 28, 2020. https://github.com/nytimes/covid-19-data
6.
US Census Bureau. SAIPE state and county estimates for 2018. Published December 2019. Accessed May 5, 2020. https://www.census.gov/data/datasets/2018/demo/saipe/2018-state-and-county.html
7.
The COVID Tracking Project. About us. Accessed April 28, 2020. https://covidtracking.com/about-project
8.
US Census Bureau. Population, population change, and estimated components of population change: April 1, 2010, to July 1, 2019 (CO-EST2019-alldata). Accessed April 20, 2020. https://www.census.gov/data/datasets/time-series/demo/popest/2010s-counties-total.html#par_textimage_70769902
9.
US Census Bureau. USA Counties Land Area. Published October 2011. Accessed April 20, 2020. https://www.census.gov/library/publications/2011/compendia/usa-counties-2011.html#LND
10.
Friedson  AI, McNichols  D, Sabia  JJ, Dave  D. Did California’s shelter-in-place order work? early coronavirus-related public health benefits. National Bureau of Economic Research Working Paper Series, No. 26992. Published April 2020. Accessed May 11, 2020. https://www.nber.org/papers/w26992.pdf
11.
Iowa Department of Public Health. Novel coronavirus—press release archive. Accessed May 9, 2020. https://idph.iowa.gov/Emerging-Health-Issues/Novel-Coronavirus/Press-Release-Archive
12.
Eller  D. COVID-19 outbreak halts production at Tyson pork processing plant in eastern Iowa. Des Moines Register. Published April 6, 2020. Accessed April 20, 2020. https://www.desmoinesregister.com/story/money/agriculture/2020/04/06/covid-19-outbreak-halts-production-east-iowa-pork-processing-plant/2955922001/
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