Mortality and years of life lost of colorectal cancer in China, 2005-2020: findings from the national mortality surveillance system.

BACKGROUND: Colorectal cancer (CRC) is the fourth cause of cancer death in China. We aimed to provide national and subnational estimates and changes of CRC premature mortality burden during 2005-2020. METHODS: Data from multi-source on the basis of the national surveillance mortality system were used to estimate mortality and years of life lost (YLL) of CRC in the Chinese population during 2005-2020. Estimates were generated and compared for 31 provincial-level administrative divisions in China. RESULTS: Estimated CRC deaths increased from 111.41 thousand in 2005 to 178.02 thousand in 2020; age-standardized mortality rate decreased from 10.01 per 100,000 in 2005 to 9.68 per 100,000 in 2020. Substantial reduction in CRC premature mortality burden, as measured by age-standardized YLL rate, was observed with a reduction of 10.20% nationwide. Marked differences were observed in the geographical patterns of provincial units, and they appeared to be obvious in areas with higher economic development. Population aging was the dominant driver which contributed to the increase in CRC deaths, followed by population growth and age-specific mortality change. CONCLUSIONS: Substantial discrepancies were observed in the premature mortality burden of CRC across China. Targeted considerations were needed to promote a healthy lifestyle, expand cost-effective CRC early screening and diagnosis, and improve medical treatment to reduce CRC mortality among high-risk populations and regions with inadequate healthcare resources.

COVID-19 seeding time and doubling time model: an early epidemic risk assessment tool.

BACKGROUND: As COVID-19 makes its way around the globe, each nation must decide when and how to respond. Yet many knowledge gaps persist, and many countries lack the capacity to develop complex models to assess risk and response. This paper aimed to meet this need by developing a model that uses case reporting data as input and provides a four-tiered risk assessment output. METHODS: We used publicly available, country/territory level case reporting data to determine median seeding number, mean seeding time (ST), and several measures of mean doubling time (DT) for COVID-19. We then structured our model as a coordinate plane with ST on the x-axis, DT on the y-axis, and mean ST and mean DT dividing the plane into four quadrants, each assigned a risk level. Sensitivity analysis was performed and countries/territories early in their outbreaks were assessed for risk. RESULTS: Our main finding was that among 45 countries/territories evaluated, 87% were at high risk for their outbreaks entering a rapid growth phase epidemic. We furthermore found that the model was sensitive to changes in DT, and that these changes were consistent with what is officially known of cases reported and control strategies implemented in those countries. CONCLUSIONS: Our main finding is that the ST/DT Model can be used to produce meaningful assessments of the risk of escalation in country/territory-level COVID-19 epidemics using only case reporting data. Our model can help support timely, decisive action at the national level as leaders and other decision makers face of the serious public health threat that is COVID-19.