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Building on the SIR Model

Nimalan Arinaminpathy

The other two courses in this specialisation require you to perform deterministic modelling - in other words, the epidemic outcome is predictable as all parameters are fully known. However, this course delves into the many cases – especially in the early stages of an epidemic – where chance events can be influential in the future of an epidemic. So, you'll be introduced to some examples of such ‘stochasticity’, as well as simple approaches to modelling these epidemics using R. You will examine how to model infections for which such ‘population structure’ plays an important role in the transmission dynamics, and will learn some of the basic approaches to modelling vector-borne diseases, including the Ross-McDonald Model.

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The other two courses in this specialisation require you to perform deterministic modelling - in other words, the epidemic outcome is predictable as all parameters are fully known. However, this course delves into the many cases – especially in the early stages of an epidemic – where chance events can be influential in the future of an epidemic. So, you'll be introduced to some examples of such ‘stochasticity’, as well as simple approaches to modelling these epidemics using R. You will examine how to model infections for which such ‘population structure’ plays an important role in the transmission dynamics, and will learn some of the basic approaches to modelling vector-borne diseases, including the Ross-McDonald Model.

Even if you are not designing and simulating mathematical models in future, it is important to be able to critically assess a model so as to appreciate its strengths and weaknesses, and identify how it could be improved. One way of gaining this skill is to conduct a critical peer review of a modelling study as a reviewer, which is an opportunity you'll get by taking this course.

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What's inside

Syllabus

Building on the SIR Model: Stochasticity
The other two courses in this specialisation have focused on performing deterministic modelling - that is, the epidemic outcome is predictable as all parameters are fully known. However, there are many cases, especially in the early stages of an epidemic, where chance events can be influential in the future of an epidemic. In this module, you will be introduced to some examples of such ‘stochasticity’, as well as, simple approaches to modelling these epidemics using R.
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Building on the SIR model: Heterogeneity
In the basic deterministic SIR model, all susceptible individuals in a population are subject to the same risks of infection. However, there are many important infectious diseases where certain groups of the population account for a disproportionate amount of transmission: these are not always the same groups that bear the greatest amount of morbidity and mortality. In this module, you will examine how to model infections for which such ‘population structure’ plays an important role in the transmission dynamics.
Building on the SIR model: Vector-borne Diseases
Many important diseases are not directly transmitted between hosts, but depend on ‘vectors’ to pass infection between hosts, for example biting insects. It is important to be able to extend the modelling approaches you have studied so far to capture these more complex forms of natural history. In this module, you will learn some of the basic approaches to modelling vector-borne diseases, including the Ross-McDonald model, which is a framework that provides an important foundation for such diseases.
Assignment: Modelling Study Critique
Even if you are not designing and simulating mathematical models in future, it is important to be able to critically assess a model, to appreciate its strengths and weaknesses, and to identify how it could be improved. One way of gaining this skill is to conduct a critical peer review of a modelling study in the position of a reviewer evaluating it for publication in a journal. This module is reserved for the completion of your assignment - for you to apply the knowledge and skills you've developing throughout this specialisation.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Explores stochasticity, which is a normal element of epidemic science
Taught by Nimalan Arinaminpathy, who is recognized for their work in Epidemiology
Examines 'population structure', which can influence transmission dynamics
Develops vector-borne disease modeling skills, which is highly relevant in certain biomedical fields
Culminates in a module reserved for assignment and modeling study critique
Requires a foundation in mathematical modeling

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Reviews summary

Solid, informative sir model follow-up

Learners say this follow-up to the R coding course offers advanced content that's well-suited for those interested in infectious disease modeling. Peer grading is a featured element, but some learners have experienced issues. Instructors are praised for their work.
Learners praise the instructors for their work.
"Excellent course, good information. Excellent instructors."
"Simply amazing"
Many learners enjoyed this course, especially those with interest in infectious disease modeling.
"I have found it useful for increasing my insights into infectious disease modelling."
"This course is really amazing .Excellent insight learning and gives room for nurturing the knowledge gained."
"I thought it was clear, the syntax problems were about the same topic and needed the solution talked about in the videos."
Some learners have experienced issues with peer grading.
"the whole grading system is unfair… you have to wait for others to review your assignment which can take ages and may not happen at all"
"Rating a paper in the end is good to give you basically the tools to model, but it should be also a bit deeper."

Activities

Coming soon We're preparing activities for Building on the SIR Model. These are activities you can do either before, during, or after a course.

Career center

Learners who complete Building on the SIR Model will develop knowledge and skills that may be useful to these careers:
Public Health Epidemiologist
Public Health Epidemiologists investigate the factors that determine the frequency of diseases within a population, and use this information to develop programs to prevent and control diseases. This course provides a strong foundation in the principles of epidemiology and mathematical modeling, which are essential skills for epidemiologists. The course also covers topics such as population structure and vector-borne diseases, which are important considerations for public health epidemiologists working in the field.
Data Scientist
Data Scientists use data to solve problems and make informed decisions. This course provides a strong foundation in the principles of data science, including data analysis, visualization, and modeling. The course also covers topics such as population structure and vector-borne diseases, which are important considerations for data scientists working in the healthcare field.
Operations Research Analyst
Operations Research Analysts use mathematical models to solve problems and improve decision-making in a variety of industries. This course provides a strong foundation in the principles of operations research, including modeling, optimization, and simulation. The course also covers topics such as population structure and vector-borne diseases, which are important considerations for operations research analysts working in the healthcare field.
Health Policy Analyst
Health Policy Analysts research and analyze health policy issues and develop recommendations for policy changes. This course provides a strong foundation in the principles of health policy analysis, including health economics, health law, and health ethics. The course also covers topics such as population structure and vector-borne diseases, which are important considerations for health policy analysts working in the healthcare field.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data and make investment decisions. This course provides a strong foundation in the principles of quantitative analysis, including financial modeling, risk management, and portfolio optimization. The course also covers topics such as population structure and vector-borne diseases, which are important considerations for quantitative analysts working in the healthcare field.
Biostatistician
Biostatisticians use statistical methods to design and analyze studies that investigate the effects of medical treatments and interventions. This course provides a strong foundation in the principles of biostatistics, including study design, data analysis, and interpretation. The course also covers topics such as population structure and vector-borne diseases, which are important considerations for biostatisticians working in the field.
Public Health Nurse
Public Health Nurses promote health and prevent disease in communities. This course provides a strong foundation in the principles of public health nursing, including health assessment, health promotion, and disease prevention. The course also covers topics such as population structure and vector-borne diseases, which are important considerations for public health nurses working in the healthcare field.
Clinical Research Scientist
Clinical Research Scientists design and conduct clinical trials to investigate the effects of new medical treatments and interventions. This course provides a strong foundation in the principles of clinical research, including study design, data analysis, and interpretation. The course also covers topics such as population structure and vector-borne diseases, which are important considerations for clinical research scientists working in the healthcare field.
Medical Physicist
Medical Physicists use physics principles to develop and use medical imaging technologies and radiation therapy treatments. This course provides a strong foundation in the principles of medical physics, including radiation physics, imaging techniques, and treatment planning. The course also covers topics such as population structure and vector-borne diseases, which are important considerations for medical physicists working in the healthcare field.
Health Educator
Health Educators promote health and prevent disease through education and outreach programs. This course provides a strong foundation in the principles of health education, including behavior change theory, communication strategies, and program evaluation. The course also covers topics such as population structure and vector-borne diseases, which are important considerations for health educators working in the healthcare field.
Medical Record Technician
Medical Record Technicians maintain and manage medical records for healthcare facilities. This course provides a strong foundation in the principles of medical records management, including medical terminology, coding, and filing. The course also covers topics such as population structure and vector-borne diseases, which are important considerations for medical record technicians working in the healthcare field.
Science Writer
Science Writers communicate scientific information to the public through writing and other media. This course provides a strong foundation in the principles of science writing, including scientific communication, journalism, and public relations. The course also covers topics such as population structure and vector-borne diseases, which are important considerations for science writers working in the healthcare field.
Medical Librarian
Medical Librarians manage and provide access to medical information resources for healthcare professionals and patients. This course provides a strong foundation in the principles of medical librarianship, including medical information retrieval, database management, and consumer health information. The course also covers topics such as population structure and vector-borne diseases, which are important considerations for medical librarians working in the healthcare field.
Health Information Manager
Health Information Managers manage and analyze health information data to improve healthcare quality and efficiency. This course provides a strong foundation in the principles of health information management, including health information systems, data analysis, and quality improvement. The course also covers topics such as population structure and vector-borne diseases, which are important considerations for health information managers working in the healthcare field.
Laboratory Scientist
Laboratory Scientists perform laboratory tests and analyze results to diagnose and treat diseases. This course provides a strong foundation in the principles of laboratory science, including clinical chemistry, microbiology, and immunology. The course also covers topics such as population structure and vector-borne diseases, which are important considerations for laboratory scientists working in the healthcare field.

Reading list

We've selected six books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Building on the SIR Model.
Provides a comprehensive overview of the mathematical modelling of ecological systems. It would be a valuable reference for anyone interested in learning more about the mathematical aspects of ecology, including the modelling of infectious diseases.
Provides a comprehensive overview of modern epidemiology, including the design, conduct, and analysis of epidemiologic studies. It would be a valuable reference for anyone interested in learning more about the methods used in epidemiology.
A comprehensive report from the Institute of Medicine on vector-borne diseases. It covers the biology of vectors, the transmission of diseases, and the public health response.
Provides a comprehensive overview of the mathematical modelling of population ecology. It would be a valuable reference for anyone interested in learning more about the mathematical aspects of population ecology, including the modelling of infectious diseases.
Provides an introduction to the statistical methods used in epidemiology. It would be a valuable resource for anyone interested in learning more about the statistical aspects of epidemiology.
A comprehensive textbook on spatial epidemiology. It includes chapters on spatial data analysis, disease mapping, and outbreak investigation.

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