This study analyzed global data on epidemic control measures and economic conditions in different countries during different mutant strain epidemic periods, including the Alpha, Delta, and Omicron strains. The study estimated the elasticity coefficient through a log-log model, which represents the percent change of the confirmed case number with respect to a percent change in the total number of screening tests in a country for epidemic control. The 7-day rolling data of screening tests and confirmed cases from the Our World in Data database for the pandemic periods of Alpha strain in 2020, Delta strain in 2021, and Omicron strain in 2022, suggest that the magnitude of the elasticity was associated with the economic condition of a country. Compared with the results during either Alpha or Delta pandemic period, the Omicron pandemic has a much higher estimated elasticity coefficient of 1.317 (Alpha: 0.827 and Delta: 0.885). Further examining economic conditions categorized by quartile ranges, the results indicate that the elasticity is statistically significantly lower in countries with gross domestic product (GDP) per capita between $11,354 and $26,651, and in countries with GDP per capita above $26,651 than in countries with GDP per capita below $3,335. These results suggest that countries should consider not only epidemiological measures but also economic conditions when formulating epidemic control strategies. This study highlights the importance of assessing the appropriateness of epidemic control strategies within a country and provides valuable insights into the effectiveness of such strategies, particularly in the context of community screening.

UNASSIGNED: Understanding and minimizing existing global coronavirus disease 2019 (COVID-19) vaccination disparities is critical to global population health and eliminating health inequities. The study aims to investigate the disparities of vaccination coverage and progression and the associated economic and educational determinants to inform global COVID-19 vaccination strategies.
UNASSIGNED: COVID-19 vaccination coverage data from 206 countries used in the study were derived from \"Our World in Data\" website. After obtaining the vaccination coverage indicators, we fitted the progression indicators for vaccination. Correlation and multiple linear regression analysis were used to examine the effects of gross domestic product (GDP) per capita, Gini index, education, and their interactions on the coverage and progression of the COVID-19 vaccination.
UNASSIGNED: The coverage of COVID-19 vaccination ranged from less than 30 doses to more than 150 doses per hundred people, from less than 15% to more than 75% for proportion of people vaccinated, from less than 15% to more than 60% for proportion of people fully vaccinated. Similarly, the progression of vaccination ranged from less than 0.1 to more than 0.6 for progression of total number of doses, from less than 0.1 to more than 0.3 for progression of proportion of people vaccinated, and from less than 0.1 to more than 0.4 for progression of proportion of people fully vaccinated. GDP per capita and education were positively associated with the coverage and progression, while Gini index was negatively associated with the coverage and progression. Negative interaction between GDP per capita and education was also observed for coverage (β = -0.012 to -0.011, P < 0.05) and progression (β = -0.012 to -0.011, P < 0.05).
UNASSIGNED: Substantial geographic disparities existed for the coverage and progression of COVID-19 vaccination. Economy and education are two important factors contributing to the disparities. Different countries may adopt varied strategies to promote the national distribution and vaccination of COVID-19 vaccines.

BACKGROUND: Determining the cost-effectiveness thresholds for healthcare interventions has been a severe challenge for policymakers, especially in low- and middle-income countries. This study aimed to estimate the cost per disability-adjusted life-year (DALY) averted for countries with different levels of Human Development Index (HDI) and Gross Domestic Product (GDP).
METHODS: The data about DALYs, per capita health expenditure (HE), HDI, and GDP per capita were extracted for 176 countries during the years 2000 to 2016. Then we examined the trends on these variables. Panel regression analysis was performed to explore the correlation between DALY and HE per capita. The results of the regression models were used to calculate the cost per DALY averted for each country.
RESULTS: Age-standardized rate (ASR) DALY (DALY per 100,000 population) had a nonlinear inverse correlation with HE per capita and a linear inverse correlation with HDI. One percent increase in HE per capita was associated with an average of 0.28, 0.24, 0.18, and 0.27% decrease on the ASR DALY in low HDI, medium HDI, high HDI, and very high HDI countries, respectively. The estimated cost per DALY averted was $998, $6522, $23,782, and $69,499 in low HDI, medium HDI, high HDI, and very high HDI countries. On average, the cost per DALY averted was 0.34 times the GDP per capita in low HDI countries. While in medium HDI, high HDI, and very high HDI countries, it was 0.67, 1.22, and 1.46 times the GDP per capita, respectively.
CONCLUSIONS: This study suggests that the cost-effectiveness thresholds might be less than a GDP per capita in low and medium HDI countries and between one and two GDP per capita in high and very high HDI countries.