Background: Our objective was to assess racial differences in the 5-year relative survival rates (RSRs) of Cervical Cancer (CerCancer) by stage at diagnosis, between Black and White women, living in Alabama, USA.Methods: Data for 3484 Blacks and 21,059 Whites diagnosed with CerCancer were extracted from the 2004 to 2013 Surveillance, Epidemiology, and End Results (SEER) database. We incorporated age groups, CerCancer stages, county, and year of diagnosis to compare the RSR between Blacks and Whites, using SEER*Stat software.Results: In urban, Black Belt (BB) and other rural counties, Whites diagnosed with localized stage of CerCancer always had better chances of survival because their RSRs were always more than 77%, compared to Blacks. Only exception was in Blacks living in other rural counties, who had a significantly higher RSR of 83.8% (95% Cl, 74.2–90.1). Which was the same as in Whites (83.8% (95% CI 74.5–89.9) living in BBC. Although, in other rural counties, Whites had a slightly lower RSR of 83.7% (95% CI 79.9–86.8%), their RSR was better compared to Blacks and Whites living in BB and other rural counties who had slightly higher RSRs of 83.8%. This was due to statistical precision, which depended on their larger sample size and a lower variability therefore, more reliability resulting in a tighter confidence interval with a smaller margin of error. In all the three county groups, Whites 15–44 years old diagnosed with localized stage of CerCancer had a higher RSR of 93.6% (95% CI 91.4–95.2%) for those living in urban and BB counties, and 94.6% (95% CI 93.6–95.4) for those living in other rural counties. The only exception was in Blacks 65–74 years old living in other rural counties who had the highest RSR of 96.9% (95% Cl, 82.9–99.5). However, Whites were considered to have a better RSR. This was also due to the statistical precision as mentioned above.Conclusion: There were significant racial differences in the RSRs of CerCancer. Overall, Black women experienced the worst RSRs compared to their White counterparts.

The COVID-19 pandemic has posed an unprecedented challenge to public health across the world and has further exposed health disparities and the vulnerability of marginal groups. Since the pandemic has exhibited marked regional differences, it is necessary to better understand the levels of vulnerability to the disease at local levels and provide policymakers with additional tools that will allow them to develop finely targeted policies. In this study, we develop for the State of Alabama (USA) a composite vulnerability index at county level that can be used as a tool that will help in the management of the pandemic. Twenty-four indicators were assigned to the following three categories: exposure, sensitivity, and adaptive capacity. The resulting subindices were aggregated into a composite index that depicts the vulnerability to COVID-19. A multivariate analysis was used to assign factor loadings and weights to indicators, and the results were mapped using Geographic Information Systems. The vulnerability index captured health disparities very well. Many of the most vulnerable counties were found in the Alabama Black Belt region. A deconstruction of the overall index and subindices allowed the development of individual county profiles and the detection of local strengths and weaknesses. We expect the model developed in this study to be an efficient planning tool for decision-makers.