Cancer continues to be a leading cause of mortality and morbidity the world over. While the incidence of cancer is projected to increase by 70% over the next two decades, some research findings suggest a disproportionate distribution of new cancer cases and attendant fatalities across certain regions of the world, with poor and lower income countries worse affected at a time when advances in cancer research, medical technology, and drug development are giving rise to better cancer survival in developed countries. In this study, the role of selected social determinants of health in gauging cancer outcomes relative to incidence across various countries in different regions of the world was explored. The results indicated that the education index, income index, Gini coefficient, availability of cancer control policies and programs, as well as health system performance have an association with and are good predictors of the mortality to incidence ratio (MIR) of lung, breast, cervical, and colorectal cancers. In other words, populations with better education, higher incomes and lower inequalities, active cancer control policies and programs and high performing health systems have better cancer outcomes as reflected in lower MIRs relative to other populations.

Given that healthcare spending can mediate the relationship between HDI and NM and MM, increases in healthcare spending among countries with low HDI could improve NM and MM outcomes.

Aim COVID-19 has exerted distress on virtually every aspect of human life with disproportionate mortality burdens on older individuals and those with underlying medical conditions. Variations in COVID-19 incidence and case fatality rates (CFRs) across countries have incited a growing research interest regarding the effect of social factors on COVID-19 case-loads and fatality rates. We investigated the effect of population median age, inequalities in human development, healthcare capacity, and pandemic mitigation indicators on country-specific COVID-19 CFRs across countries and regions. Subject and methods Using population secondary data from multiple sources, we conducted a cross-sectional study and used regional analysis to compare regional differences in COVID-19 CFRs as influenced by the selected indicators. Results The analysis revealed wide variations in COVID-19 CFRs and the selected indicators across countries and regions. Mean CFR was highest for South America at 1.973% (± 0.742) and lowest for Oceania at 0.264% (± 0.107), while the Africa sub-region recorded the lowest scores for pandemic preparedness, vaccination rate, and other indicators. Population Median Age [0.073 (0.033 0.113)], Vaccination Rate [−3.3389 (−5.570.033 −1.208)], and Inequality-Adjusted Human Development Index (IHDI) [−0.014 (−0.023 −0.004)] emerged as statistically significant predictors of COVID-19 CFR, with directions indicating increasing Population Median Age, higher inequalities in human development and low vaccination rate are predictive of higher fatalities from COVID-19. Conclusion Regional differences in COVID-19 CFR may be influenced by underlying differences in sociodemographic and pandemic mitigation indicators. Populations with wide social inequalities, increased population Median Age and low vaccination rates are more likely to suffer higher fatalities from COVID-19.

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Aim: COVID-19 has exerted distress on virtually every aspect of human life with disproportionate mortality burdens on older individuals and those with underlying medical conditions. Variations in COVID-19 incidence and case fatality rates (CFRs) across countries have incited a growing research interest regarding the effect of social factors on COVID-19 case-loads and fatality rates. Our aim in this study was to investigate the effect of population median age, inequalities in human development, healthcare capacity, and pandemic mitigation indicators on country-specific COVID-19 CFRs across countries and regions. Subject and Methods: Using population secondary data from multiple sources, we conducted a cross-sectional study and used geospatial analysis to compare regional differences in COVID-19 CFRs as influenced by the selected indicators. Results: The analysis revealed wide variations in COVID-19 CFRs and the selected indicators across countries and regions. Mean CFR was highest for South America at 1.973% and lowest for Oceania at 0.264%, while the Africa sub-region recorded the lowest scores for pandemic preparedness, vaccination rate, and other indicators. Population Median Age, Vaccination Rate and Inequality-Adjusted Human Development Index (IHDI) emerged as statistically significant predictors of COVID-19 CFR, with directions indicating increasing Population Median Age, higher inequalities in human development and low vaccination rate are predictive of higher fatalities from COVID-19. Conclusion: Regional differences in COVID-19 CFR may be influenced by underlying differences in sociodemographic and pandemic mitigation indicators. Populations with wide social inequalities, increased population Median Age and low vaccination rates are more likely to suffer higher fatalities from COVID-19.