Automated evaluation of public health policies for cervical cancer prevention and surveillance
Cervical cancer (CC) is the second leading cause of cancer-related deaths among Colombian women, caused most commonly by the consequences of Human Papillomavirus (HPV) infection. Screening programs, vaccination against HPV and improved socio-economic conditions have significantly reduced CC mortalit...
- Autores:
-
Angulo Díaz, Karen Daniela
- Tipo de recurso:
- Fecha de publicación:
- 2018
- Institución:
- Universidad de los Andes
- Repositorio:
- Séneca: repositorio Uniandes
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.uniandes.edu.co:1992/34227
- Acceso en línea:
- http://hdl.handle.net/1992/34227
- Palabra clave:
- Neoplasmas del cuello uterino - Prevención - Investigaciones - Métodos de simulación
Epidemiología - Investigaciones - Colombia - Estudio de casos
Ingeniería
- Rights
- openAccess
- License
- https://repositorio.uniandes.edu.co/static/pdf/aceptacion_uso_es.pdf
| Summary: | Cervical cancer (CC) is the second leading cause of cancer-related deaths among Colombian women, caused most commonly by the consequences of Human Papillomavirus (HPV) infection. Screening programs, vaccination against HPV and improved socio-economic conditions have significantly reduced CC mortality rate over the last 40 years. The proper definition of public health policies for prevention and surveillance is of paramount importance to ensure cost-effective disease control strategies are deployed, which make the best usage of the limited available resources. However, predicting the long-term effects of vaccination and screening programs is no trivial at all, as it builds upon the ability to compound the uncertainties associated with the results of interventions on a growing population such as the Colombian one. We propose a compartmentalized epidemiological simulation model based on differential equations, which represents population dynamics, HPV transmission within the population, likelihood of infection clearance, virus induced appearance of precancerous lesions and eventually of CC, as well as the immunity gained with vaccination and the likelihood of early detection provided by screening policies. The model is implemented into an open software tool that allows evaluating the predicted effects of public health policies against HPV, providing valuable support to healthcare decision-makers. |
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