Rural-Urban Disparities in Hospital Admissions and Mortality Among Patients with COVID-19: Evidence from South Carolina from 2021 to 2022

Impacts of travel duration on urban-rural resident free vaccination behavior: Chinese COVID-19 vaccine booster dose evidence

This study aimed to evaluate how the duration of travel affects the behavior of urban and rural residents regarding free COVID-19 vaccination, and provide scientific evidence for promoting free vaccination and building an immune barrier to cope with future epidemics. From August 3, 2022 to February,18,2023, A follow-up survey was conducted in urban and rural adults in four cities in China to collect information on socio-demographic factors, vaccination status and travel time for vaccination. Propensity score matching (PSM) analysis was deployed to measure the net difference of the enhanced vaccination rate between urban and rural residents in different traffic time distribution. A total of 5780 samples were included in the study. The vaccination rate of the booster dose of COVID-19 vaccine among rural residents was higher than that of urban residents with a significant P-value (69.36% VS 64.49%,p < .001). The traffic time had a significant negative impact on the COVID-19 booster vaccination behavior of urban and rural residents. There was a significant interaction between the travel time to the vaccination point and the level of trust in doctors. Travel time had a negative impact on the free vaccination behavior of both urban and rural residents. The government should optimize and expand the number of vaccination sites and enhance residents' trust in the medical system. This is crucial for promoting free vaccination and effective epidemic management in the future.

Quantifying Disparities in COVID-19 Vaccination Rates by Rural and Urban Areas: Cross-Sectional Observational Study

BACKGROUND

Vaccination plays an important role in preventing COVID-19 infection and reducing the severity of the disease. There are usually differences in vaccination rates between urban and rural areas. Measuring these differences can aid in developing more coordinated and sustainable solutions. This information also serves as a reference for the prevention and control of emerging infectious diseases in the future.

OBJECTIVE

This study aims to assess the current coverage rate and influencing factors of COVID-19 (second booster) vaccination among Chinese residents, as well as the disparities between urban and rural areas in China.

METHODS

This cross-sectional study used a stratified random sampling approach to select representative samples from 11 communities and 10 villages in eastern (Changzhou), central (Zhengzhou), western (Xining), and northeast (Mudanjiang) Mainland China from February 1 to February 18, 2023. The questionnaires were developed by experienced epidemiologists and contained the following: sociodemographic information, health conditions, vaccine-related information, information related to the Protective Motivation Theory (PMT), and the level of trust in the health care system. Vaccination rates among the participants were evaluated based on self-reported information provided. Binary logistic regression models were performed to explore influencing factors of vaccination among urban and rural participants. Urban-rural disparities in the vaccination rate were assessed using propensity score matching (PSM).

RESULTS

A total of 5780 participants were included, with 53.04% (3066/5780) being female. The vaccination rate was 12.18% (704/5780; 95% CI 11.34-13.02) in the total sample, 13.76% (341/2478; 95% CI 12.40-15.12) among the rural participants, and 10.99% (363/3302; 95% CI 9.93-12.06) among the urban participants. For rural participants, self-reported health condition, self-efficacy, educational level, vaccine knowledge, susceptibility, benefits, and trust in the health care system were independent factors associated with vaccination (all P＜.05). For urban participants, chronic conditions, COVID-19 infection, subjective community level, vaccine knowledge, self-efficacy, and trust in the health care system were independent factors associated with vaccination (all P＜.05). PSM analysis uncovered a 3.42% difference in vaccination rates between urban and rural participants.

CONCLUSIONS

The fourth COVID-19 vaccination coverage rate (second booster) among the Chinese population was extremely low, significantly lower than the previous vaccine coverage rate. Given that COVID-19 infection is still prevalent at low levels, efforts should focus on enhancing self-efficacy to expand the vaccine coverage rate among the Chinese population. For rural residents, building awareness of the vaccine's benefits and improving their overall health status should be prioritized. In urban areas, a larger proportion of people with COVID-19 and patients with chronic illness should be vaccinated.

Rural-urban Differences in Long-term Mortality and Readmission Following COVID-19 Hospitalization, 2020 to 2023

Background

We compared long-term mortality and readmission rates after COVID-19 hospitalization based on rural-urban status and assessed the impact of COVID-19 vaccination introduction on clinical outcomes by rurality.

Methods

The study comprised adults hospitalized for COVID-19 at 17 hospitals in 4 US states between March 2020 and July 2022, followed until May 2023. The main analysis included all patients, whereas a sensitivity analysis focused on residents from 4 states containing 17 hospitals. Additional analyses compared the pre- and postvaccination periods.

Results

The main analysis involved 9325 COVID-19 hospitalized patients: 31% were from 187 rural counties in 31 states; 69% from 234 urban counties in 44 states; the mean age was 65 years (rural, 66 years; urban, 64 years); 3894 women (rural, 41%; urban, 42%); 8007 Whites (rural, 87%; urban, 83%); 1738 deaths (rural, 21%; urban, 17%); and 2729 readmissions (rural, 30%; urban, 29%). During a median follow-up of 602 days, rural residence was associated with a 22% higher all-cause mortality (log-rank, P < .001; hazard ratio, 1.22; 95% confidence interval, 1.10-1.34, P < .001), and a trend toward a higher readmission rate (log-rank, P = .038; hazard ratio, 1.06; 95% confidence interval, .98-1.15; P = .130). The results remained consistent in the sensitivity analysis and in both pre- and postvaccination time periods.

Conclusions and Relevance

Patients from rural counties experienced higher mortality and tended to be readmitted more frequently following COVID-19 hospitalization over the long term compared with those from urban counties, a difference that remained even after the introduction of COVID-19 vaccines.

COVID-19 Testing Among People with HIV: A Population Level Analysis Based on Statewide Data in South Carolina

People with HIV (PWH) are at an elevated risk of developing severe COVID-19 outcomes because of compromised immunity and more comorbidities. However, existing literature suggests a lower rate of COVID-testing among PWH. This study aimed to explore the temporal trend of county-level COVID-19 testing rate and multi-level predictors of COVID-19 ever-testing among PWH in South Carolina (SC). Leveraging linked statewide HIV and COVID-19 datasets, we defined the study population as all adult (18 + years) PWH who were alive on March 2020 and living in SC. PWH with a COVID-19 testing record between March 2020 and October 2021 were defined as COVID-19 ever-testers. Logistic regression and generalized mixed models were used to investigate the association of PWH's demographic profile, HIV clinical characteristics (e.g., CD4 count, viral load), comorbidities, and social factors with COVID-19 testing among PWH. Among 15,660 adult PWH, 8,005 (51.12%) had ever tested for COVID-19 during the study period (March 2020-October 2021). PWH with older age, being male, and Hispanics were less likely to take COVID-19 testing, while men who have sex with men or injection drug users were more likely to take COVID-19 testing. PWH with higher recent viral load (10,000-100,000 copies/ml vs. <200 copies/ml: adjusted odds ratio [AOR]: 0.64, 95%CI: 0.55-0.75) and lower CD4 counts (> 350 cells/mm3 vs. <200 cells/mm3: AOR: 1.25, 95%CI: 1.09-1.45) had lower odds for COVID-19 testing. Additionally, PWH with lower comorbidity burden and those living in rural areas were less likely to be tested for COVID-19. Differences in COVID-19 test-seeking behaviors were observed among PWH in the current study, which could help provide empirical evidence to inform the prioritization of further disease monitoring and targeted intervention. More efforts on building effective surveillance and screening systems are needed to allow early case detection and curbing disease transmission among older, male, Hispanic, and immune-suppressed PWH, especially in rural areas.