 |
|
This module provides a refresher on the foundations of epidemiology. It covers the measures of frequency which include count, prevalence, and incidence. It concludes by discussing descriptive epidemiology, which answers the questions, what, who, when and where about health events.
Completing this module will improve knowledge on descriptive data analysis, which is used to assess population health, identifying whether health issues are increasing or decreasing, where they are occurring most and who are the most affected.
Core competencies: Definition of Epidemiology, Role of Epidemiology in Public Health, Measures of Disease Frequency (Point/Period Prevalence, Incidence Rate, Mortality and Case Fatality Rate), Descriptive Epidemiology. |
|
|
 |
|
 |
|
 |
|
 |
|
 |
|
 |
|
 |
|
 |
|
 |
|
 |
|
 |
|
 |
|
 |
|
 |
|
 |
|
 |
|
This electronic course on medical certification of cause of death will help physicians and other health care staff to understand the critical importance of medical certification. This will allow them to produce high quality mortality data for government agencies to effectively make evidenced-based policy decisions.
|
|
|
 |
|
 |
|
La seguridad vial es uno de los elementos mas significativos en torno a la operacin de la infraestructura, la movilidad y el comportamiento de los diferentes actores viales de las ciudades. La siniestralidad vial contribuye de manera sustancial a la morbilidad y mortalidad de la poblacin y el conocimiento de la magnitud y circunstancias de estos eventos es necesario para orientar la toma de decisiones relacionadas a la aplicacin de normas que regulan la movilidad de un pas, as como a travs de la concientizacin y de la educacin de todos los actores que intervienen en las vas. Tomando la perspectiva de salud pblica, este curso proporciona elementos sobre el anlisis, interpretacin y presentacin de datos de seguridad vial, as como de los indicadores de siniestralidad vial definidos para el pas de Colombia, a partir de fuentes de informacin existentes, que permitan la generacin de lneas base para la toma de decisiones en el diseo e implementacin de intervenciones efectivas y basadas en la evidencia.
|
|
|
 |
|
 |
|
 |
|
 |
|
 |
|
 |
|
 |
|
 |
|
 |
|
|
|
|
|
|
|
 |
|
|
|
|
|
|
|
|
|
 |
|
Accurate civil registration and vital statistics (CRVS) data are critical to understanding national health status and developing appropriate strategies and relevant policies to improve population health. In the absence of CRVS data, countries lack a clear picture of birth and death rates and the causes of death. This data gap makes it difficult to allocate resources appropriately to health, education, and other key government sectors. As part of the Bloomberg Philanthropies Data for Health Initiative, countries around the world are investing in expanding and improving the quality of the CRVS systems. However, unless data are regularly analyzed and used, neither government nor citizens will not reap the benefits of this investment. Vital statistics generated by well-functioning civil registration systems are crucial for policy development and decision-making and are central to monitoring several Sustainable Development Goal (SDG) targets.
Here in Module 1 of 10, you'll get an overview of CRVS and the social and health benefits from high-quality data from civil registration records. Participants will learn about the public health uses of data from CRVS systems, including developing public health policies, monitoring health systems, and evaluating public health programs. Upon completion of the module, participants will understand how to define civil registration and vital statistics, the types of vital records recognized by the UN, and both the challenges and benefits of CRVS systems.
|
|
|
 |
|
During Module 2, participants will understand how low-quality data can adversely affect the accuracy of vital statistics. The module reviews methods (both direct and indirect) on estimating the completeness of birth and death registration and how to assess the plausibility of mortality measures. Participants will also learn about the importance of high-quality cause-of-death data and how this data can be assessed, using tools such as ANACoD4 or ANACONDA.
|
|
|
 |
|
This module
introduces birth statistics that are important for monitoring, tracking
Sustainable Development Goals, reporting, and understanding the fertility
trends in a country. Upon completion of the module, participants will know how
to calculate birth statistics such as sex ratio, crude birth rate, and total
fertility rate, which are important to report on in a national vital statistics
report. |
|
|
 |
|
The module on death statistics provides an overview of mortality measures that are important for monitoring, tracking Sustainable Development Goals, reporting, and understanding the mortality trends in a country. These measures include: the crude death rate, age-specific mortality rates, under-5 mortality rate, and the infant mortality rate. Participants will learn about the importance of age standardization to account for the differing age distributions across populations. Finally, participants will be introduced to how to calculate key mortality measures using life tables. |
|
|
 |
|
Upon completion of this module, participants will understand how cause of death (COD) data are generated, including the sources of COD data, and how to conduct basic analyses of this data. Participants will also learn why COD data are important for various stakeholders (e.g., agencies, researchers, medical practitioners) and how COD data can be used. Finally, the module will provide an overview of verbal autopsy, which is used to ascertain cause of death and cause-specific mortality fractions when medical certification of cause of death (MCCD) is unavailable. |
|
|
 |
|
Module
6 will help participants understand how to use descriptive epidemiology to
assess and interpret vital statistics. This will include using epidemiological
topics such as rate difference and rate ratio to compare and make meaning of
vital statistics. Participants will gain an understanding of inequalities in
mortality when disaggregating vital statistics by demographic factors and learn
how to calculate and interpret excess mortality, an important concept to the
COVID-19 pandemic. |
|
|
 |
|
Module 7. Upon completion of this module, participants will be able to describe and compare the main types of visualizations used to depict vital statistics and understand the factors involved in determining which visualization best suits a communication purpose. Participants will also understand important design principles that contribute to effective data visualization.
|
|
|
 |
|
Module 8. In this module, participants will dive deeper into how CRVS data can be applied to calculate epidemiological measures such as attributable mortality, years of life lost (YLL), and measures to assess the burden of disease.
|
|
|
 |
|
Module 9.This session provides an overview of how to identify and communicate findings to a targeted audience and how to identify the best way to communicate the message. Participants will learn about different types of analytical reports, including national vital statistics reports, that can be produced to disseminate vital statistics and learn about other types of media, such as press release, to communicate findings.
|
|
|
 |
|
Module 10. Upon completion of this module, participants will understand how vital statistics can be used to inform policy decisions, program planning, and program evaluation. Participants will hear about examples of where CRVS indicators such as cause-specific mortality and infant mortality rate were used to identify a problem and evaluate a program.
|
|
|
 |
|
 |
|
 |
|
 |
|
 |
|