Name: Modeling cancer parameters using Globocan Zimbabwe 2020 estimates: Book Series on Modeling Cancer Incidence-Mortality and Cum.Risk. Insights for Predicting Future Trends in Public Health.DE (en Inglés)
SKU: 67255521
Price: 112040.00 CLP
Availability: InStock
ISBN: 9786209820076

portada Modeling cancer parameters using Globocan Zimbabwe 2020 estimates: Book Series on Modeling Cancer Incidence-Mortality and Cum.Risk. Insights for Predicting Future Trends in Public Health.DE (en Inglés)

Modeling cancer parameters using Globocan Zimbabwe 2020 estimates: Book Series on Modeling Cancer Incidence-Mortality and Cum.Risk. Insights for Predicting Future Trends in Public Health.DE (en Inglés)

Formato

Libro Físico

Editorial

GlobeEdit

Idioma

Inglés

Encuadernación

Tapa Blanda

Dimensiones

22x15 cm

ISBN13

9786209820076

Modeling cancer parameters using Globocan Zimbabwe 2020 estimates: Book Series on Modeling Cancer Incidence-Mortality and Cum.Risk. Insights for Predicting Future Trends in Public Health.DE (en Inglés)

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Reseña del libro "Modeling cancer parameters using Globocan Zimbabwe 2020 estimates: Book Series on Modeling Cancer Incidence-Mortality and Cum.Risk. Insights for Predicting Future Trends in Public Health.DE (en Inglés)"

Cancer remains a major public health burden in Zimbabwe, requiring quantitative analyzes to support prevention and control strategies. Using Globocan 2020 estimates, this study models cancer incidence, mortality, and cumulative risk in the Zimbabwe population. In 2020, an estimated 16,083 new cases and 10,676 deaths occurred. The most frequent cancers were Cervix uteri, Breast, Prostate, Kaposi sarcoma, and Non-Hodgkin lymphoma, showing the highest lethality (Nd/Nc = 96.4%) for Pancreas cancer. The global mortality ratio (slope = 0.63) suggests that about three-quarters of new cases result in death. Linear and power-law correlations (Eqs. 1-7) describe the causal link between incidence and mortality, while the parameters ( = 0.9955, k = 0.65942, Gammai> 1) express behavioral and severity indices. Gender disparities are evident, with Prostate, and Kaposi sarcoma cancers dominating in males, and Cervix uteri and Breast in females. The modeling framework offers predictive insight for evaluating cancer dynamics and improving early detection and public health interventions in Zimbabwe.