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. 2025 Oct 1;25:3257. doi: 10.1186/s12889-025-24530-1

Disparities in COVID-19 mortality in the United States, 2020–2023

Zain ul Abidin 1, Joseph Thirumalareddy 2, Jaya S Gupta 2, Ali Bin Abdul Jabbar 2,✉
PMCID: PMC12487207  PMID: 41034766

Abstract

Background

The COVID-19 pandemic disproportionately affected various demographics and regions in the United States. Understanding disparities in COVID-19 mortality is essential for promoting health equity and guiding future responses.

Objective

To examine demographic and regional disparities in age-adjusted and proportionate COVID-19 mortality in the US from 2020 to 2023.

Design, setting, and participants

In this repeated cross-sectional study, data from the Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research (CDC WONDER) multiple causes of death database were used to analyze death certificates from 2020 to 2023 for COVID-19-related mortality among persons aged ≥ 15 years in the U.S.

Main outcome measures

Age-adjusted mortality rate (AAMR) per 100,000 persons, Rate ratio (with 95% CI), and proportionate mortality of COVID-19, calculated using descriptive statistics.

Results

From 2020 to 2023, 1,167,362 (8.91%) of 13,098,787 total deaths in the U.S. were attributed to COVID-19. The AAMR peaked in 2021 at 147.0 (95% CI: 146.6–147.5) per 100,000, with 13.45% of all deaths related to COVID-19, decreasing to 23.1 (2.49%) by 2023. Males exhibited a 1.56-fold higher AAMR than females. Non-Hispanic (NH) American Indian/Alaska Native experienced the highest cumulative AAMR (154), followed by NH Native Hawaiian/Pacific Islander (124.2) and NH African American (123.9) populations. Hispanics had the highest proportionate mortality, with COVID-19 contributing to 23.55% of all deaths in 2021. The oldest age group (≥ 75 years) had the highest cumulative AAMR, 71.6 times higher compared to the youngest group (15–44 years), whereas the highest proportionate mortality was seen in middle-aged adults (45–74 years). Regionally, the Southern U.S. census region recorded the highest cumulative and annual AAMR, except for the Northeast, in 2020.

Conclusion

From 2020 to 2023, males, older adults, and racial/ethnic minority groups, notably NH AI/AN, NH NH/PI, NH African American, and Hispanic populations, experienced higher COVID-19 mortality. Regionally, the Southern U.S. Census region had the highest COVID-19 mortality, except for the Northeast, in 2020. These disparities underscore the importance of implementing equitable public health strategies and ensuring preparedness for future health crises.

Clinical trial number

Not applicable

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-025-24530-1.

Keywords: COVID-19, Mortality, United states of america, Disparities, Regional disparities, Demographic disparities

Introduction

The COVID-19 pandemic has had a profound impact on global health, with more than 6.9 million deaths reported worldwide as of January 2025 [1]. The United States (U.S.) has reported over 1.1 million deaths, accounting for approximately 16% of global mortality, despite having only 4% of the world’s population [2]. COVID-19 mortality has significantly varied between different demographics and regions, highlighting the unequal burden of the pandemic across the world and within nations [3]. Globally, COVID-19 mortality rates have varied based on healthcare infrastructure, public health responses, and access to vaccination, with high-income nations generally reporting lower mortality rates than low- and middle-income countries [4–7]. However, even among high-income nations, the U.S. experienced disproportionately higher COVID-19 mortality compared to countries such as Canada, Germany, and Australia, primarily due to variations in public health responses, healthcare access, vaccination uptake, and underlying health disparities [2, 8].

In the U.S., overall mortality rates have shown sharp variations based on demographics such as age, sex, race, ethnicity, and geographic region [9, 10]. Analyzing these disparities offers insight into the unequal burden of COVID-19 mortality and underscores the need for ongoing monitoring of mortality trends to inform public health interventions and promote health equity [11, 12]. While prior U.S.-based studies have identified early disparities in COVID-19 mortality, most analyses have focused on earlier periods of the pandemic (2020–2021), lacking comprehensive updated data through 2023. Additionally, earlier studies have typically focused exclusively on age-adjusted mortality without considering proportionate mortality separately. Thus, current literature provides insufficient comprehensive data on contemporary trends in disparities in COVID-19 mortality across demographic and geographic subgroups.

Therefore, this study aims to address these gaps by analyzing demographic and regional disparities in COVID-19 mortality in the United States from 2020 to 2023, providing a comprehensive overview of both age-adjusted and proportionate mortality measures across population groups.

Methods

Study design and data source

In this repeated cross-sectional study, Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research (CDC WONDER), available at https://wonder.cdc.gov/, was used to identify COVID-19 mortality in the US population aged ≥ 15 years [13]. This age threshold was used to focus on adult population, and because deaths from COVID-19 were rare for ages < 15 and CDC WONDER provides data stratified by 10-year age group. The Multiple Cause-of-Death Public Use Records of death certificates were used to extract COVID-19 as an underlying or contributing cause on nationwide death certificate records [14]. We extracted data regarding COVID-19-related deaths and population sizes from 2020 to 2023 using the International Classification of Diseases (ICD), 10th Revision, Clinical Modification code U07.1 [15]. Approval from the Institutional Review Board was not required since CDC WONDER includes publicly accessible, anonymized data.

Study population

Data were extracted for COVID-19 and all-cause mortality analysis based on biological sex, race/ethnicity, age groups, region, and state. Sex is categorized as men and women, preserving the categorizations used by CDC WONDER for gender as male and female. Race/ethnicity groups were divided into non-Hispanic (NH) white, NH Black or African American, NH Asian, NH Native Hawaiian or Pacific Islander (NH NH/PI), NH American Indian or Alaska Native (NH AI/AN), and Hispanic or Latino based on what was listed on the patient’s death certificate. Age groups were divided into young (15–44), middle-aged (45–74), and elderly (≥ 75). Regions were classified into Northeast, Midwest, South, and West according to the Census Bureau definitions.

Statistical analysis

COVID-19 and all-cause age-adjusted mortality rates (AAMR) per 100,000 were calculated direct standardization to the 2000 U.S. Standard population as provided by CDC WONDER using the formula in supplement Table 1 [16]. Cumulative AAMRs for the January 1, 2020 to December 31, 2023 period, as well as annual AAMRs for calendar years 2020, 2021, 2022, and 2023, were calculated with their calculated 95% CI by sampling normal distributions based on the underlying AAMRs and their standard errors, defining the CI as the 2.5 and 97.5 percentiles of calculations based on those samples. Statistical significance between groups was designated as a 95% CI that did not overlap. Rate Ratios of cumulative AAMRs were calculated for each group using the lowest AAMR in each category (sex, race, age group, and region) as a reference group for comparison, i.e., females for sex, NH Asian for race, young adults (15–44 years) for age groups, and West for regions were used as the reference groups. Similarly, data for all-cause deaths were extracted to calculate the proportionate mortality of COVID-19 as a percentage of all-cause mortality annually and cumulatively for 2020–2023. While AAMRs provide a comparison of the absolute burden of mortality, proportionate mortality gives a perspective of the relative burden of mortality for each subgroup. Both AAMR and proportionate mortality were analyzed for comparison in this study, as COVID-19-related AAMR may be higher in a subgroup due to higher all-cause mortality. A discrepancy between AAMR and proportionate mortality, therefore, may provide valuable insight into subgroups that had a higher relative burden of COVID-19-related mortality compared to their all-cause mortality. We followed the RECORD reporting guidelines. The study was exempt from institutional review board approval because the CDC WONDER database contains anonymized, publicly available data [14, 17].

Table 1.

Annual and cumulative AAMR per 100,000 for 2020–2023, the ratio of cumulative AAMR compared to reference subgroups (subgroups with the lowest cumulative AAMR are used as the reference for each category), and number of COVID-19 deaths: overall and stratified by sex, race/ethnicity, age groups, and regions. AAMR: Age-Adjusted mortality rate; NH: non-Hispanics; AI/AN: American Indian or Alaska native; NH/PI: native Hawaiian or other Pacific Islander

Category 2020 AAMR
(95% CI)		 2021 AAMR
(95% CI)		 2022 AAMR
(95% CI)		 2023 AAMR
(95% CI)		 Cumulative
2020–2023
AAMR (95% CI)		 2020–2023 AAMR Ratio compared to the reference group Number of COVID-19-related deaths
(2020–2023)
Overall 118.6 (118.2–119) 147 (146.6-147.5) 74.4 (74.1–74.7) 23.1 (23.0-23.3) 90.2 (90.0-90.3) - 1,167,362
Sex
 Female 94 (93.6–94.5) 116.7 (116.2-117.2) 60.1 (59.7–60.5) 19.5 (19.3–19.8) 72.2 (72-72.4) Reference 527,525
 Male 148.8 (148.2-149.5) 183.8 (183.1-184.5) 93.6 (93.1–94.1) 28.1 (27.8–28.4) 112.6 (112.3-112.8) 1.56 (1.56–1.56) 639,837
Race/ethnicity
 NH AI/AN 242.9 (235.7-250.1) 256.6 (249.3-263.9) 105.6 (101-110.2) 23.3 (21.1–25.4) 154 (151.2-156.8) 2.82 (2.79–2.84) 12,247
 NH Asian 85.5 (84.1–87) 84.8 (83.3–86.2) 40.5 (39.6–41.5) 13.6 (13-14.1) 54.7 (54.1–55.2) Reference 36,394
 NH Black or African American 197 (195.4-198.6) 192.4 (190.9–194) 89.9 (88.8–91) 21.4 (20.9–21.9) 123.9 (123.3-124.5) 2.27 (2.26–2.28) 158,666
 NH NH/PI 156.4 (144.3-168.5) 255.1 (240-270.1) 80.9 (72.5–89.3) 17.3 (13.7–21.7) 124.2 (119.1-129.4) 2.27 (2.20–2.34) 2313
 NH White 94.3 (93.9–94.7) 133.6 (133.1-134.1) 74.3 (74-74.7) 24.9 (24.7–25.1) 81.5 (81.3–81.7) 1.49 (1.48–1.50) 778,006
 Hispanics 209.8 (208.2-211.4) 205.7 (204.1-207.2) 73.9 (72.9–74.8) 16.4 (16-16.9) 123.2 (122.6-123.8) 2.25 (2.24–2.27) 172,174
Age groups
 Young (15–44) 8.2 (8-8.3) 20.9 (20.7–21.2) 6.6 (6.4–6.7) 1.1 (1.1–1.2) 9.2 (9.1–9.2) Reference 45,819
 Middle Age (45–74) 111.3 (110.8-111.9) 177.1 (176.4-177.9) 72.4 (71.9–72.9) 15.4 (15.1–15.6) 93.9 (93.6–94.1) 10.25 (10.18–10.31) 493,136
 Elderly (≥ 75) 952.4 (948.5-956.3) 916.1 (912.1–920) 575.3 (572.3-578.3) 219.5 (217.6-221.4) 659 (657.4-660.6) 71.95 (71.47–72.44) 628,407
Regions
 Northeast 156.7 (155.7-157.7) 113.3 (112.4-114.2) 69.9 (69.2–70.5) 23 (22.6–23.4) 90.2 (89.8–90.6) 1.17 (1.17–1.17)  218,942
 Midwest 126.2 (125.3–127) 133.8 (132.9-134.7) 78.7 (78-79.3) 24 (23.6–24.4) 90.4 (90-90.7) 1.17 (1.17–1.17) 248,719
 South 112.1 (111.5-112.7) 175.8 (175-176.5) 80 (79.5–80.5) 24.6 (24.3–24.9) 97.2 (96.9–97.5) 1.26 (1.26–1.26) 474,877
 West 89.5 (88.9–90.2) 137.6 (136.7-138.5) 64.4 (63.8–64.9) 19.9 (19.6–20.2) 77.2 (76.9–77.5) Reference 224,824
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Results

Overall

From 2020 to 2023, there were a total of 13,098,787 deaths, out of which 1,167,362 (8.91%) were related to COVID-19. The highest annual number of COVID-19 deaths was recorded in 2021. Specifically, COVID-19 deaths numbered 384,386 in 2020, peaked at 461,772 in 2021, and subsequently declined to 244,990 in 2022 and 76,214 in 2023. Correspondingly, the COVID-19-related AAMR per 100,000 persona increased from 118.6 (95% CI: 118.2–119.0) in 2020 to 147.0 (95% CI: 146.6–147.5) in 2021, before declining to 74.4 (95% CI: 74.1–74.7) in 2022 and 23.12 (95% CI: 22.96–23.29) in 2023, with a cumulative COVID-19-related AAMR of 90.17 (95% CI: 90.01–90.34) (Table 1; Figs. 1a and 2a). Similarly, the proportionate mortality (% of total deaths related to COVID-19) was highest in 2021 (13.45%), followed by 2020 (11.46%), 2022 (7.54%), and 2023 (2.49%) (Table 2; Figs. 1b and 2b).

Fig. 1.

Fig. 1

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Cumulative age-adjusted (a) and proportionate (b) COVID-19 mortality for 2020–2023: overall and stratified by sex, race/ethnicity, age groups, and census regions. AAMR: Age-Adjusted Mortality Rate; NH: non-Hispanics; AI/AN: American Indian or Alaska Native; NH/PI: Native Hawaiian or Other Pacific Islander; NH Black: non-Hispanics Black or African American

Fig. 2.

Fig. 2

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Annual age-adjusted (a) and proportionate (b) COVID-19 mortality rate for 2020–2023: overall and stratified by sex, race/ethnicity, age groups, and census regions. AAMR: Age-Adjusted Mortality Rate; NH: non-Hispanics; AI/AN: American Indian or Alaska Native; NH/PI: Native Hawaiian or Other Pacific Islander; NH Black: non-Hispanics Black or African American

Table 2.

Annual and cumulative proportionate COVID-19 mortality – percentage of all deaths which were contributed by COVID-19 (%): overall and stratified by sex, race/ethnicity, age groups, and regions

Proportionate COVID-19 mortality – percentage of all deaths which were related to COVID-19 infection (%)
Category 2020 2021 2022 2023 Cumulative 2020–2023
Overall 11.46 13.45 7.54 2.49 8.91
Sex
 Female 10.98 12.55 7.26 2.53 8.48
 Male 11.90 14.23 7.80 2.45 9.30
Race/ethnicity
 NH AI/AN 18.92 18.95 9.10 2.26 12.87
 NH Asian 14.96 14.97 7.73 2.74 10.24
 NH Black or African American 13.91 14.01 7.11 1.79 9.54
 NH NH/PI 15.84 22.85 8.40 1.87 12.67
 NH White 9.41 12.00 7.40 2.65 7.99
 Hispanics 23.05 23.55 9.32 2.12 15.25
Age groups
 Young (15–44) 4.67 10.63 3.74 0.71 5.17
 Middle Age (45–74) 11.15 16.21 7.58 1.81 9.55
 Elderly (≥ 75) 12.47 11.62 7.99 3.18 8.92
Regions
 Northeast 15.64 11.88 7.88 2.77 9.82
 Midwest 11.58 11.90 7.58 2.46 8.55
 South 10.34 14.73 7.62 2.48 9.00
 West 9.73 13.78 7.07 2.31 8.38
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NH Non-Hispanics, AI/AN American Indian or Alaska Native, NH/PI Native Hawaiian or Other Pacific Islander

Sex stratified

Males consistently exhibited higher COVID-19 mortality rates compared to females throughout the study period (2020–2023). Among males, there were 639,837 COVID-19 deaths (54.8%), compared to 527,525 deaths (45.2%) among females (Table 1). The cumulative COVID-19-related AAMR per 100,000 was 112.6 (95% CI: 112.3–112.8) among males, which was 1.56 times higher than that among females (72.2, 95% CI: 72.0–72.4). Annually, males had higher AAMRs than females: 148.8 vs. 94.0 in 2020, 183.8 vs. 116.7 in 2021, 93.6 vs. 60.1 in 2022, and 28.1 vs. 19.5 in 2023. The annual mortality trends for men and women mirrored the overall trend, peaking in 2021, followed by declines in subsequent years (Table 1; Fig. 2a). Similarly, proportionate mortality peaked in 2021, with COVID-19 being reported in 14.23% males and 12.55% females, declining thereafter (Table 2; Fig. 2b).

Race stratified

COVID-19-related mortality rates were notably higher among NH AI/AN, NH NH/PI, NH African American, and Hispanic populations, compared to NH Asian and NH White populations. Specifically, NH-AI/AN individuals experienced the highest cumulative COVID-19-related AAMR per 100,000 (154, 95% CI: 151.2–156.8), followed by NH NH/PI (124.2, 95% CI: 119.1–129.2), NH African Americans (123.9, 95% CI: 123.3–124.5) and Hispanics (123.2, 95% CI: 122.6-123.8. In contrast, NH Asians had the lowest cumulative AAMR (54.7; 95% CI: 54.1–55.2), followed by NH White individuals (81.5; 95% CI: 81.3–81.5) (Table 1; Fig. 1a). Cumulative AAMR for NH-AI/AN was 2.82 times higher than that of NH Asians (Table 1). The cumulative proportionate mortality was highest among Hispanic individuals (15.25%), reaching as high as 23.05% and 23.55% in 2020 and 2021. This was followed by Non-Hispanic AI/AN (12.87%), NH NH/PI (12.67%), NH Asians (10.24%), NH African Americans (9.54%), and the lowest among NH White individuals (7.99%) (Table 2; Figs. 1b and 2b).

Age group stratified

Elderly (≥ 75 years) had markedly higher cumulative COVID-19-related AAMRs compared to younger age groups. Specifically, the cumulative AAMR for older adults was 659.0 per 100,000 (95% CI: 657.4–660.6), which was approximately 71.6 times higher compared to younger adults aged 15–44 years (9.2; 95% CI: 9.1–9.2). Middle-aged adults (45–74 years) had a cumulative AAMR of 93.9 per 100,000 (95% CI: 93.6–94.1), approximately 10.2 times higher than younger adults (Table 1; Fig. 1a). However, the cumulative proportionate mortality was highest among middle-aged adults (9.55%), primarily driven by a peak of 16.21% in 2021 (Table 2; Figs. 1b and 2b).

Census region stratified

Across U.S. Census regions, the highest cumulative proportionate mortality from COVID-19 was observed in the Northeast (9.82%), followed closely by the South (9.00%), the Midwest (8.55%), and the West (8.38%). In 2020, the Northeast reported the highest regional proportionate mortality at 15.64%. However, from 2021 onwards, the South recorded the highest proportionate mortality (14.73% in 2021) (Table 2; Fig. 1b). The cumulative AAMR was highest in the South (97.2, 95% CI: 96.9–97.5), followed by the Midwest at (90.4, 95% CI: 90.0–90.7), the Northeast at (90.2, 5% CI: 89.8–90.6), and the West (77.2, 95% CI: 76.9–77.5) (Table 1; Fig. 1a). The cumulative AAMR of the South census region was 1.26 higher than that of the West census region (Table 1).

State-level differences

Noteworthy state-level variations in cumulative COVID-19 AAMRs were observed, with southern states notably recording higher rates. Specifically, Mississippi (135.4; 95% CI: 133.2–137.6), Oklahoma (135.2; 95% CI: 133.3–137.1), and Kentucky (119.2; 95% CI: 117.6–120.9) had the highest cumulative AAMRs. Except for 2020, when the Northeast states of New Jersey (196.3; 95% CI: 193.3–199.2) and New York (191.6; 95% CI: 189.6–193.5) had the highest rates, Southern states consistently reported the highest annual AAMRs. Oklahoma (233.1; 95% CI: 228.0–238.2) had the highest Rate in 2021, whereas Kentucky led in both 2022 (129.8; 95% CI: 126.4–133.2) and 2023 (43.5; 95% CI: 41.5–45.5). Conversely, Hawaii reported the lowest cumulative AAMR (31.7; 95% CI: 30.3–33.1), followed by Vermont (38.9; 95% CI: 36.5–41.2) (Table 1; Fig. 3).

Fig. 3.

Fig. 3

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Cumulative state-level age-adjusted mortality Rate per 100,000 related to COVID-19 for 2020–2023

Discussion

Our analysis provides a comprehensive contemporary analysis of disparities in age-adjusted and proportionate mortality related to COVID-19 infection from the finalized available mortality data of all deaths in the US, yielding several interesting findings. Males had 56% higher AAMR compared to females. NH Asians had the lowest AAMR, whereas NH AI/AN, NH NH/PI, NH African Americans, and Hispanics had more than twice the AAMR of NH Asians. Middle-aged people (45–74) had 10 times, and the older population (≥ 75) had as much as 72 times higher AAMR compared to the young population (15–44). The West region had the lowest AAMR among census regions. In contrast, the Southern US census region and its states (Mississippi, Oklahoma, and Kentucky) had the highest cumulative and annual AAMR, except for 2020, when the Northeastern US had the highest AAMR.

Several behavioral and social determinants may help explain higher COVID-19 mortality among males compared to females. Males have a higher prevalence of preexisting conditions like cardiovascular disease, hypertension, and diabetes, which are risk factors for severe COVID-19 outcomes [18–20]. In addition, men were reported to be less likely to adopt preventive behaviors (e.g., handwashing, mask use, physical distancing), which may have increased exposure risk [21, 22]. Occupational exposures may have also contributed: males are overrepresented in higherrisk jobs (e.g., construction, manufacturing, transportation) that often do not allow remote work, which potentially increased the likelihood of viral transmission[23]. Higher smoking prevalence among males has been associated with increased COVID-19 severity and mortality due to its negative impact on lung function and immune response [24, 25]. Additionally, studies show that males were less likely to seek healthcare early in the course of illness, which may have led to delayed treatment and worse outcomes [26].

In addition to behavioral and social factors, biological differences have been hypothesized to contribute to disparities in COVID-19 outcomes between males and females. Biologically, males have been reported to express higher levels of Angiotensin-converting enzyme 2 (ACE2), the receptor through which SARS-CoV-2 enters cells, potentially increasing their susceptibility to severe infection, though this relationship remains unclear [10]. Furthermore, differences in immune response between males and females play a key role; females generally have stronger innate and adaptive immune responses due to the effects of estrogen and the presence of two X chromosomes, which enhance antiviral defense mechanisms. Males, on the other hand, more often exhibit dysregulated immune response, including higher levels of pro-inflammatory cytokines, and this may have contributed to the higher incidence of severe disease and mortality observed among them [27].

The findings of this study highlight the disproportionate impact of COVID-19 on NH AI/AN, NH NH/PI, NH African American, and Hispanic populations, consistent with existing literature [28, 29]. These disparities may be explained by several socioeconomic and structural factors, including higher poverty rates and lower insurance coverage, which likely limit timely healthcare access and treatment [30, 31]. Individuals from these groups are more frequently employed in essential, frontline occupations that involved higher risks of COVID-19 exposure, and often live in multigenerational or densely populated households, which potentially further increased their exposure risk [32]. Many of these jobs are characterized by low wages and limited financial resources, and this may have further exacerbated their vulnerabilities [33]. Geographical disparities may also have contributed; these communities are primarily located in rural areas where healthcare facilities are underfunded, which potentially hindered effective management of COVID-19 cases [34]. Moreover, higher prevalence of comorbid conditions (e.g., hypertension, diabetes) in these populations may have elevated COVID-19 mortality risk [35]. Additionally, historical injustices and systemic racism may have reduced healthcare utilization by contributing to medical mistrust and lower adherence to public health guidelines [36].

Our findings also reveal patterns specific to the Hispanic population. Historically, despite socioeconomic disadvantages, Hispanic individuals in the U.S. have demonstrated lower all-cause mortality compared to NH White populations, a phenomenon termed the ‘Hispanic Mortality Paradox’ [37]. However, this paradox appeared to diminish during the COVID-19 pandemic in our Analysis, as Hispanic individuals experienced approximately 1.5-fold higher cumulative AAMR than NH White populations, along with the highest proportionate mortality among all racial and ethnic groups. This attenuation of the paradox may reflect increased exposure risk from essential employment, lower early vaccination rates, socioeconomic instability, and barriers to timely healthcare access in the Hispanic community during the pandemic [32, 38, 39].

In contrast, AAMR was lowest for NH Asians, followed by NH Whites. These relatively lower mortality rates may be associated with higher socioeconomic status, including greater healthcare coverage, financial stability, and timely access to medical interventions [40]. Both NH Asians and NH Whites had higher COVID-19 vaccination rates compared to NH African Americans [41]. Additionally, prior research suggests that NH Asian communities had higher adherence to preventive measures like mask-wearing and social distancing, potentially reducing viral transmission [42, 43]. NH Asian and NH White individuals also have lower prevalence of obesity and other chronic comorbidities, which are strongly associated with severe COVID-19 outcomes [44, 45]. Lower rates of smoking and alcohol consumption among NH Asians have been previously reported and could plausibly contribute to their lower mortality risk [46–49].

The elderly population experienced markedly higher cumulative AAMRs compared to younger populations, consistent with previously reported age gradients in COVID-19 mortality [50]. In a prior study, mortality Rates among individuals under 50 years were generally below 1%, compared to approximately 30% for individuals aged over 80 years [51]. This exponential increase in mortality with age is consistent with the known increased burden of chronic diseases (such as cardiovascular conditions and diabetes), natural decline in pulmonary function, and reduced immune system responsiveness in older populations [52–56]. Additionally, chronic low-grade inflammation, “inflammaging,” predisposes older adults to exaggerated immune responses, such as cytokine storms, which can cause multi-organ failure and increase mortality [57]. Additionally, older adults residing in long-term care or nursing facilities likely faced higher exposure risks due to congregate living settings, which may have facilitated the rapid spread of COVID-19 [58, 59].

Interestingly, while the AAMR for COVID-19 was highest among the elderly population, the proportion of deaths attributed to COVID-19 was lower in this group than in the middle-aged population in 2021. The lower proportionate mortality among the older age group may reflect their higher baseline mortality from other chronic conditions, meaning that COVID-19 represented a relatively smaller share of total deaths despite higher absolute mortality rates [60–62]. In contrast, middle-aged adults were more likely to be in the workforce, potentially increasing their risk of exposure to COVID-19 [32, 63]. Increased earlier vaccination Rates among older age groups in 2021 is another hypothesis for a decrease in the proportionate COVID-19 mortality among older adults [60, 64].

Our findings reflect significant regional disparities in COVID-19 AAMR and proportionate mortality patterns across the United States. The Northeast had the highest proportionate mortality, likely reflecting severe initial outbreaks in densely populated urban centers, such as New York City, where the virus spread rapidly before public health measures were implemented [65–67]. Moreover, these factors likely contributed to the highest AAMR in the Northeast in 2020 [66]. However, from 2021 to 2023, the South had the highest AAMR. This shift may be explained by several factors, including relatively lower COVID-19 vaccination rates, earlier relaxation of preventive measures, higher uninsured rates, and structural socioeconomic inequities prevalent in Southern states [67–71]. Moreover, Southern states have a higher prevalence of chronic comorbid conditions, potentially elevating individual mortality risk upon infection [35, 72]. Consistent with prior literature, Hawaii experienced the lowest AAMR, which is likely attributable to its geographic isolation and early and strict travel restrictions, factors known to reduce pathogen importation and local transmission.

Limitations

While our study provides a comprehensive contemporary analysis of disparities in age-adjusted and proportionate mortality related to COVID-19 from available mortality data in the US, it may have some limitations due to the nature of the CDC WONDER data, which is collected from a public health database of death certificates. For instance, variables such as social determinants of health, which could influence patient mortality, were not reported on death certificates. Additionally, stratified Analyses between rural and urban areas could not be conducted as the database does not report age-group-specific populations for rural and urban areas from 2021 onward. Because CDC WONDER data is derived from death certificates that rely on ICD codes to identify diseases, state-level differences in death certificate practices, misclassification bias, and under-reporting of COVID-19 deaths may affect the accuracy and comparability of subgroup analyses. Moreover, excess mortality or indirect pandemic effects (e.g., delayed care for non-COVID conditions) may have influenced the interpretation of the findings. Lastly, we exclude deaths for age < 15, which may limit generalizability for pediatric populations.

Conclusion

Our findings highlight profound disparities in COVID-19 mortality across the United States from 2020 to 2023. Men, elderly, and racial/ethnic minority groups, notably NH AI/AN, NH NH/PI, NH African American, and Hispanic populations, experienced significantly higher mortality. Regionally, the South had the highest COVID-19 mortality Rate, except in the Northeast, in 2020. These differences underscore the need for targeted public health interventions to address the underlying disparities in behavioral, socioeconomic, and healthcare accessibility, thereby improving future preparedness during healthcare emergencies.

Supplementary Information

Supplementary material 1. (405.3KB, docx)

Acknowledgements

Not Applicable.

Authors’ contributions

Z.A. Writing- Original draft preparation, Writing - Review & Editing, interpretation of data; drafted the work and substantively revised it; J.T. Writing - Review & Editing, substantively revised it; J.G. Writing - Review & Editing, substantively revised it; ABAJ Conceptualization, Methodology, Data curation, Acquisition, Formal analysis, Writing- Original draft preparation, Writing - Review & Editing, visualization, Supervision.

Funding

Not Applicable.

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Data availability

All data is publicly available at https://wonder.cdc.gov/.

Declarations

Ethics approval and consent to participate

not applicable.

Consent for publication

Not Applicable.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s Note

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References

  • 1.World Health Organization. WHO COVID-19 dashboard. WHO. Accessed 31 Jan 2025. https://data.who.int/dashboards/covid19/cases
  • 2.Campbell T, Galvani AP, Friedman G, Fitzpatrick MC. Exacerbation of COVID-19 mortality by the fragmented united States healthcare system: a retrospective observational study. The Lancet Regional Health. 2022;12: 100264. 10.1016/j.lana.2022.100264. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Zhang Jjin, Dong X, Liu G, hui, Gao Y. Risk and Protective Factors for COVID-19 Morbidity, Severity, and Mortality. Clin Rev Allergy Immunol. 2022;64(1):90–107. 10.1007/s12016-022-08921-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Landrigan PJ, Ferrer L, Keenan Sj J. COVID-19 and health disparities: structural evil unmasked. Ann Glob Health. 2021;87(1):34. 10.5334/aogh.3225. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Xie W, Shi L, Liu M, Yang J, Ma M, Sun G. Disparities and effectiveness of COVID-19 vaccine policies in three representative European countries. Int J Equity Health. 2024;23(1):16. 10.1186/s12939-024-02110-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Brosi DN, Mays GP. Local public health system capabilities and COVID-19 death rates. Public Health Reports®. 2022;137(5):980–7. 10.1177/00333549221097660. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Vestergaard LS, Pebody RG. Understanding excess mortality in Europe during the COVID-19 pandemic. The Lancet Regional Health. 2024;45: 101053. 10.1016/j.lanepe.2024.101053. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Peng A, Simmons A, Amoako A, Tuite A, Fisman D. Relative pandemic severity in Canada and four peer nations during the SARS-CoV-2 pandemic. Can Commun Dis Rep Releve Mal Transm Can. 2023;49(5):197–205. 10.14745/ccdr.v49i05a05. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Webb Hooper M, Nápoles AM, Pérez-Stable EJ. COVID-19 and racial/ethnic disparities. JAMA. 2020;323(24):2466. 10.1001/jama.2020.8598. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Bienvenu LA, Noonan J, Wang X, Peter K. Higher mortality of COVID-19 in males: sex differences in immune response and cardiovascular comorbidities. Cardiovasc Res. 2020;116(14):2197–206. 10.1093/cvr/cvaa284. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Carethers JM. Insights into disparities observed with COVID-19. J Intern Med. 2021;289(4):463–73. 10.1111/joim.13199. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Nana-Sinkam P, Kraschnewski J, Sacco R, et al. Health disparities and equity in the era of COVID-19. J Clin Transl Sci. 2021;5(1): e99. 10.1017/cts.2021.23. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.CDC WONDER, Accessed. 8 May 2024. https://wonder.cdc.gov/
  • 14.Centers for Disease Control and Prevention. Multiple Cause of Death, 1999–2020 Request. CDC. Accessed August 11. 2024. https://wonder.cdc.gov/mcd-icd10.html
  • 15.Organization. ICD-10 : international statistical classification of diseases and related health problems : tenth revision. World Health Organization; 2004. Accessed 5 Jan 2025. https://iris.who.int/handle/10665/42980
  • 16.anderson RN, Rosenberg HM. Age standardization of death rates: implementation of the year 2000 standard. Natl Vital Stat Rep Cent Dis Control Prev Natl Cent Health Stat Natl Vital Stat Syst. 1998;47(3):1–16. [PubMed] [Google Scholar]
  • 17.RECORD Reporting Guidelines. Accessed 28 Jul 2025. https://www.record-statement.org/
  • 18.Petrilli CM, Jones SA, Yang J, et al. Factors associated with hospital admission and critical illness among 5279 people with coronavirus disease 2019 in New York City: prospective cohort study. BMJ. 2020. 10.1136/bmj.m1966. Published online May 22, 2020:m1966. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Williamson EJ, Walker AJ, Bhaskaran K, et al. Factors associated with COVID-19-related death using opensafely. Nature. 2020;584(7821):430–6. 10.1038/s41586-020-2521-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Agodi A, Maugeri A, Favara G, et al. Gender differences in comorbidities of patients with COVID-19: an Italian local register-based analysis. Heliyon. 2023;9(7):e18109. 10.1016/j.heliyon.2023.e18109. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Galasso V, Pons V, Profeta P, Becher M, Brouard S, Foucault M. Gender differences in COVID-19 attitudes and behavior: panel evidence from eight countries. Proc Natl Acad Sci. 2020;117(44):27285–91. 10.1073/pnas.2012520117. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Stedman-Smith M, DuBois CLZ, Grey S. Workplace hand hygiene and wellness: a survey of knowledge, beliefs, and practices. Workplace Health Saf. 2012;60(11):477–85. 10.1177/216507991206001103. [DOI] [PubMed] [Google Scholar]
  • 23.Rushovich T, Boulicault M, Chen JT, et al. Sex disparities in COVID-19 mortality vary across US racial groups. J Gen Intern Med. 2021;36(6):1696–701. 10.1007/s11606-021-06699-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Chinwong D, Mookmanee N, Chongpornchai J, Chinwong S. A comparison of gender differences in smoking behaviors, intention to quit, and nicotine dependence among Thai university students. J Addict. 2018;2018:1–8. 10.1155/2018/8081670. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Hopkinson NS, Rossi N, El-Sayed_Moustafa J, et al. Current smoking and COVID-19 risk: results from a population symptom app in over 2.4 million people. Thorax. 2021;76(7):714–22. 10.1136/thoraxjnl-2020-216422. [DOI] [PubMed] [Google Scholar]
  • 26.Scully EP, Schumock G, Fu M, et al. Sex and gender differences in testing, hospital admission, clinical presentation, and drivers of severe outcomes from COVID-19. Open Forum Infect Dis. 2021;8(9): ofab448. 10.1093/ofid/ofab448. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Anca PS, Toth PP, Kempler P, Rizzo M. Gender differences in the battle against COVID-19: impact of genetics, comorbidities, inflammation and lifestyle on differences in outcomes. Int J Clin Pract. 2021;75(2):e13666. 10.1111/ijcp.13666. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Rossen LM, Ahmad FB, anderson RN, et al. Disparities in excess mortality associated with COVID-19 — United states, 2020. MMWR Morb Mortal Wkly Rep. 2021;70(33):1114–9. 10.15585/mmwr.mm7033a2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Aschmann HE, Riley AR, Chen R, et al. Dynamics of racial disparities in all-cause mortality during the COVID-19 pandemic. Proc Natl Acad Sci U S A. 2022;119(40): e2210941119. 10.1073/pnas.2210941119. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Slutske WS, Conner KL, Kirsch JA, et al. Explaining COVID-19 related mortality disparities in American Indians and Alaska natives. Sci Rep. 2023;13(1):20974. 10.1038/s41598-023-48260-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Penaia CS, Morey BN, Thomas KB, et al. Disparities in native Hawaiian and Pacific Islander COVID-19 mortality: A Community-Driven data response. Am J Public Health. 2021;111(S2):S49–52. 10.2105/AJPH.2021.306370. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Moore JT, Ricaldi JN, Rose CE, et al. Disparities in incidence of COVID-19 among underrepresented racial/ethnic groups in counties identified as hotspots during June 5–18, 2020–22 states, February–June 2020. MMWR Morb Mortal Wkly Rep. 2020;69(33):1122–6. 10.15585/mmwr.mm6933e1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Kaholokula JK, Samoa RA, Miyamoto RES, Palafox N, Daniels SA. COVID-19 special column: COVID-19 hits native Hawaiian and Pacific Islander communities the hardest. Hawaii J Health Soc Welf. 2020;79(5):144–6. [PMC free article] [PubMed] [Google Scholar]
  • 34.Lundberg DJ, Wrigley-Field E, Cho A, et al. COVID-19 mortality by race and ethnicity in US metropolitan and nonmetropolitan areas, March 2020 to February 2022. JAMA Netw Open. 2023;6(5):e2311098. 10.1001/jamanetworkopen.2023.11098. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Willems SJ, Castells MC, Baptist AP. The magnification of health disparities during the COVID-19 pandemic. J Allergy Clin Immunol Pract. 2022;10(4):903–8. 10.1016/j.jaip.2022.01.032. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Sumibcay JRC, Kunichoff D, Bassett MT. Racial and ethnic disparities in COVID-19 mortality. JAMA Netw Open. 2024;7(5):e2411656. 10.1001/jamanetworkopen.2024.11656. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Ruiz JM, Steffen P, Smith TB. Hispanic mortality paradox: a systematic review and meta-analysis of the longitudinal literature. Am J Public Health. 2013;103(3):e52–60. 10.2105/AJPH.2012.301103. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Martinez DA, Hinson JS, Klein EY, et al. SARS-CoV-2 positivity rate for Latinos in the Baltimore–Washington, DC region. JAMA. 2020;324(4):392. 10.1001/jama.2020.11374. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Kriss JL, Hung MC, Srivastav A, et al. COVID-19 vaccination coverage, by race and ethnicity — National immunization survey adult COVID module, united states, December 2020–November 2021. MMWR Morb Mortal Wkly Rep. 2022;71(23):757–63. 10.15585/mmwr.mm7123a2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Abedi V, Olulana O, Avula V, et al. Racial, economic, and health inequality and COVID-19 infection in the united States. J Racial Ethn Health Disparities. 2021;8(3):732–42. 10.1007/s40615-020-00833-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Martinez Leal I, Njoh J, Chen TA, et al. Exploring COVID-19 vaccine attitudes among racially and ethnically minoritized communities: community partners’ and residents’ perspectives. Int J Environ Res Public Health. 2023;20(4): 3372. 10.3390/ijerph20043372. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Lennon RP, Sakya SM, Miller EL, et al. Public Intent to Comply with COVID-19 Public Health Recommendations. HLRP Health Lit Res Pract. 2020;4(3). 10.3928/24748307-20200708-01. [DOI] [PMC free article] [PubMed]
  • 43.Anand S, Cao E, Kimura R, Guo W, Bassi N. Asian American vaccination, testing, and other healthcare knowledge & behaviors during COVID-19, a systematic review. Pathog Glob Health. 2023;117(2):120–33. 10.1080/20477724.2022.2106110. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Hales CM, Carroll MD, Fryar CD, Ogden CL. Prevalence of obesity among adults and youth: united states, 2015–2016. NCHS Data Brief. 2017;(288):1–8. [PubMed]
  • 45.Vas P, Hopkins D, Feher M, Rubino F, Whyte B. Diabetes, obesity and COVID-19: A complex interplay. Diabetes Obes Metab. 2020;22(10):1892–6. 10.1111/dom.14134. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Ra CK, Pehlivan N, Kim H, Sussman S, Unger JB, Businelle MS. Smoking prevalence among Asian Americans: associations with education, acculturation, and gender. Prev Med Rep. 2022;30: 102035. 10.1016/j.pmedr.2022.102035. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Patanavanich R, Glantz SA. Smoking is associated with worse outcomes of COVID-19 particularly among younger adults: a systematic review and meta-analysis. BMC Public Health. 2021;21(1):1554. 10.1186/s12889-021-11579-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Zhang H, Ruan WJ, Chou SP, et al. Exploring patterns of alcohol use and alcohol use disorder among Asian Americans with a finer lens. Drug Alcohol Depend. 2024;257: 111120. 10.1016/j.drugalcdep.2024.111120. [DOI] [PubMed] [Google Scholar]
  • 49.Wei B, Liu Y, Li H, Peng Y, Luo Z. Impact of alcohol consumption on coronavirus disease 2019 severity: a systematic review and meta-analysis. J Med Virol. 2023;95(2): e28547. 10.1002/jmv.28547. [DOI] [PubMed] [Google Scholar]
  • 50.Ho FK, Petermann-Rocha F, Gray SR, Feng YM, et al. Is older age associated with COVID-19 mortality in the absence of other risk factors? General population cohort study of 470,034 participants. PLoS One. 2020;15(11): e0241824. 10.1371/journal.pone.0241824. [DOI] [PMC free article] [PubMed]
  • 51.Bonanad C, García-Blas S, Tarazona-Santabalbina F, et al. The effect of age on mortality in patients with COVID-19: a meta-analysis with 611,583 subjects. J Am Med Dir Assoc. 2020;21(7):915–8. 10.1016/j.jamda.2020.05.045. [DOI] [PMC free article] [PubMed]
  • 52.Nikolich-Žugich J. Author correction: the twilight of immunity: emerging concepts in aging of the immune system. Nat Immunol. 2018;19(10):1146–1146. 10.1038/s41590-018-0205-0. [DOI] [PubMed] [Google Scholar]
  • 53.Mueller AL, McNamara MS, Sinclair DA. Why does COVID-19 disproportionately affect older people? Aging. 2020;12(10):9959–81. 10.18632/aging.103344. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54.Miller EJ, Linge HM. Age-Related changes in immunological and physiological responses following pulmonary challenge. Int J Mol Sci. 2017;18(6):1294. 10.3390/ijms18061294. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55.Liu K, Chen Y, Lin R, Han K. Clinical features of COVID-19 in elderly patients: A comparison with young and middle-aged patients. J Infect. 2020;80(6):e14–8. 10.1016/j.jinf.2020.03.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56.Santesmasses D, Castro JP, Zenin AA, et al. COVID-19 is an emergent disease of aging. Aging Cell. 2020;19(10): e13230. 10.1111/acel.13230. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57.Bajaj V, Gadi N, Spihlman AP, Wu SC, Choi CH, Moulton VR. Aging, immunity, and COVID-19: how age influences the host immune response to coronavirus infections?? Front Physiol. 2021;11:571416. 10.3389/fphys.2020.571416. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 58.Abrams HR, Loomer L, Gandhi A, Grabowski DC. Characteristics of U.S. nursing homes with COVID -19 cases. J Am Geriatr Soc. 2020;68(8):1653–6. 10.1111/jgs.16661. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 59.McMichael TM, Currie DW, Clark S, et al. Epidemiology of Covid-19 in a long-term care facility in King county, Washington. N Engl J Med. 2020;382(21):2005–11. 10.1056/NEJMoa2005412. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 60.Parra PNB, Atanasov V, Whittle J, et al. The effect of the COVID-19 pandemic on the elderly: population fatality rates, COVID mortality percentage, and life expectancy loss. Elder Law J. 2022;30:33–80. [PMC free article] [PubMed] [Google Scholar]
  • 61.Woolf SH, Chapman DA, Lee JH. COVID-19 as the leading cause of death in the united States. JAMA. 2021;325(2):123. 10.1001/jama.2020.24865. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 62.Piccirillo JF, Vlahiotis A, Barrett LB, Flood KL, Spitznagel EL, Steyerberg EW. The changing prevalence of comorbidity across the age spectrum. Crit Rev Oncol Hematol. 2008;67(2):124–32. 10.1016/j.critrevonc.2008.01.013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 63.U.S. Bureau of Labor Statistics. Labor Force Statistics from the Current Population Survey. Bureau of Labor Statistics. Accessed 7 Feb 2025. https://www.bls.gov/cps/cpsaat11b.htm
  • 64.Shiels MS, Haque AT, Berrington De González A, Freedman ND. Leading causes of death in the US during the COVID-19 pandemic, March 2020 to October 2021. JAMA Intern Med. 2022;182(8):883. 10.1001/jamainternmed.2022.2476. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 65.Alpert T, Brito AF, Lasek-Nesselquist E, et al. Early introductions and transmission of SARS-CoV-2 variant B.1.1.7 in the united States. Cell. 2021;184(10):2595–e260413. 10.1016/j.cell.2021.03.061. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 66.Woolf SH, Chapman DA, Sabo RT, Zimmerman EB. Excess deaths from COVID-19 and other causes in the US, March 1, 2020, to January 2, 2021. JAMA. 2021;325(17):1786. 10.1001/jama.2021.5199. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 67.Stoto MA, Schlageter S, Kraemer JD. COVID-19 mortality in the United States: it’s been two Americas from the start. PLoS One. 2022;17(4):e0265053. 10.1371/journal.pone.0265053. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 68.Akil L, Barner YM, Bisht A, Okoye E, Ahmad HA. COVID-19 incidence and death rates in the Southern region of the United States: a racial and ethnic association. Int J Environ Res Public Health. 2022;19(21): 13990. 10.3390/ijerph192113990. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 69.Stephens J, Artiga S, Published JP. Health Coverage and Care in the South in 2014 and Beyond. KFF. June 19, 2014. Accessed 27 Jul 2025. https://www.kff.org/racial-equity-and-health-policy/issue-brief/health-coverage-and-care-in-the-south-in-2014-and-beyond/
  • 70.Artiga S, Published AD. Health and Health Coverage in the South: A Data Update. KFF. February 10, 2016. Accessed 27 Jul 2025. https://www.kff.org/racial-equity-and-health-policy/issue-brief/health-and-health-coverage-in-the-south-a-data-update/
  • 71.Loop MS, Howard G, De Los Campos G, et al. Heat maps of hypertension, diabetes mellitus, and smoking in the continental united States. Circ Cardiovasc Qual Outcomes. 2017;10(1):e003350. 10.1161/CIRCOUTCOMES.116.003350. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 72.Guo Y, Yu H, Zhang G, Ma DT. Exploring the impacts of travel-implied policy factors on COVID-19 spread within communities based on multi-source data interpretations. Health Place. 2021;69:102538. 10.1016/j.healthplace.2021.102538. [DOI] [PMC free article] [PubMed] [Google Scholar]

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Supplementary Materials

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Data Availability Statement

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