Disease Dynamics
Expert-defined terms from the Professional Certificate in Mathematical Epidemiology course at London School of Planning and Management. Free to read, free to share, paired with a globally recognised certification pathway.
Disease Dynamics #
The field of study that focuses on understanding how infectious diseases spread through populations over time. Disease dynamics involves examining the interactions between the host, pathogen, and environment to predict and control the transmission of diseases.
Basic Reproduction Number (R0) #
The average number of secondary infections produced by a single infected individual in a completely susceptible population. R0 is a key parameter in disease dynamics as it helps determine the potential for an outbreak to occur.
Effective Reproduction Number (Re) #
The average number of secondary infections produced by a single infected individual in a population that is not completely susceptible. Re takes into account factors such as immunity, vaccination, and behavior changes that affect the transmission of the disease.
Incubation Period #
The time between exposure to a pathogen and the onset of symptoms in an infected individual. Understanding the incubation period is crucial in disease dynamics as it influences the spread of the disease and the effectiveness of control measures.
Case Fatality Rate (CFR) #
The proportion of deaths among confirmed cases of a particular disease. CFR is an important measure in disease dynamics as it helps assess the severity of an outbreak and the effectiveness of treatment and prevention strategies.
Herd Immunity #
The indirect protection from infectious diseases that occurs when a large percentage of a population becomes immune, either through vaccination or previous infection. Herd immunity plays a critical role in disease dynamics by reducing the spread of diseases and protecting vulnerable individuals.
Transmission Dynamics #
The study of how infectious diseases spread from one individual to another within a population. Transmission dynamics involve factors such as contact rates, pathogen characteristics, and host immunity that influence the transmission and progression of the disease.
Compartmental Models #
Mathematical models used to describe the transmission of infectious diseases within populations by dividing individuals into compartments based on their disease status. Compartmental models in disease dynamics help simulate the spread of diseases and evaluate the impact of control measures.
Susceptible #
Infectious-Recovered (SIR) Model: A classic compartmental model that divides the population into three compartments: susceptible, infectious, and recovered. The SIR model is commonly used in disease dynamics to study the dynamics of epidemics and the impact of interventions.
Susceptible #
Exposed-Infectious-Recovered (SEIR) Model: An extension of the SIR model that includes an exposed compartment to account for the latent period of the disease. The SEIR model is used in disease dynamics to capture the progression of infectious diseases with an incubation period.
Compartmental Models #
Mathematical models used to describe the transmission of infectious diseases within populations by dividing individuals into compartments based on their disease status. Compartmental models in disease dynamics help simulate the spread of diseases and evaluate the impact of control measures.
Compartmental Models #
Mathematical models used to describe the transmission of infectious diseases within populations by dividing individuals into compartments based on their disease status. Compartmental models in disease dynamics help simulate the spread of diseases and evaluate the impact of control measures.
Stochastic Models #
Mathematical models that incorporate random variation in disease transmission and progression. Stochastic models are used in disease dynamics to account for uncertainty and variability in the spread of infectious diseases, particularly in small populations.
Agent #
Based Models: Simulation models that represent individual agents, such as people or animals, and their interactions within a population. Agent-based models in disease dynamics are used to study the transmission of infectious diseases at the individual level and assess the effectiveness of control strategies.
Network Models #
Mathematical models that represent the structure of social or contact networks within a population. Network models in disease dynamics help analyze the spread of infectious diseases through contact patterns and identify key individuals or groups that influence transmission.
Vector #
Borne Diseases: Infectious diseases transmitted to humans through the bite of infected vectors such as mosquitoes, ticks, or flies. Vector-borne diseases play a significant role in disease dynamics as the presence and behavior of vectors impact the transmission and control of the disease.
Zoonotic Diseases #
Infectious diseases that can be transmitted from animals to humans. Zoonotic diseases are a key aspect of disease dynamics as they involve complex interactions between different host species and can lead to spillover events and outbreaks in human populations.
Phylogenetic Analysis #
The study of evolutionary relationships between different strains or isolates of a pathogen based on genetic sequences. Phylogenetic analysis in disease dynamics helps track the spread of infectious diseases, identify transmission routes, and monitor the emergence of new variants.
Super #
Spreading Events: Events or settings where a small number of individuals infect a disproportionately large number of contacts. Super-spreading events play a significant role in disease dynamics as they contribute to the rapid spread of infectious diseases and the occurrence of outbreaks.
Vaccination Coverage #
The proportion of a population that has been vaccinated against a particular disease. Vaccination coverage is a critical factor in disease dynamics as it determines the level of immunity within the population and affects the transmission and control of the disease.
Mass Vaccination Campaigns #
Large-scale efforts to vaccinate a significant portion of the population against a specific disease within a short period. Mass vaccination campaigns are important in disease dynamics to achieve high vaccination coverage, build herd immunity, and prevent outbreaks.
Quarantine #
The separation and restriction of movement of individuals who have been exposed to a contagious disease to prevent the spread of infection. Quarantine is a key control measure in disease dynamics to isolate cases, break the chain of transmission, and reduce the risk of outbreaks.
Contact Tracing #
The process of identifying and monitoring individuals who have come into contact with a confirmed case of a contagious disease. Contact tracing is essential in disease dynamics to identify potential sources of infection, isolate cases, and prevent further spread of the disease.
Social Distancing #
Public health measures that aim to reduce close contact between individuals to minimize the transmission of infectious diseases. Social distancing is a crucial strategy in disease dynamics to slow down the spread of the disease, flatten the epidemic curve, and alleviate pressure on healthcare systems.
Antimicrobial Resistance #
The ability of microorganisms, such as bacteria, viruses, and parasites, to resist the effects of antimicrobial drugs. Antimicrobial resistance is a growing concern in disease dynamics as it limits the effectiveness of treatment options and poses a threat to public health.
One Health Approach #
An interdisciplinary approach that recognizes the interconnectedness of human, animal, and environmental health. The One Health approach is important in disease dynamics to address complex health challenges, such as zoonotic diseases and antimicrobial resistance, through collaboration and coordination across sectors.
Epidemic Curve #
A graphical representation of the number of new cases of a disease over time. The epidemic curve is used in disease dynamics to visualize the progression of an outbreak, identify patterns of transmission, and assess the effectiveness of control measures.
Peak of the Epidemic #
The point in an outbreak where the number of new cases reaches its highest level before declining. The peak of the epidemic is a critical phase in disease dynamics as it represents the maximum burden on healthcare resources and the need for timely interventions.
Herd Immunity Threshold #
The proportion of immune individuals in a population required to achieve herd immunity and interrupt the transmission of a disease. The herd immunity threshold is a key concept in disease dynamics to guide vaccination strategies and control measures.
Secondary Attack Rate #
The proportion of susceptible individuals who become infected after exposure to a primary case within a defined setting. The secondary attack rate is used in disease dynamics to assess the contagiousness of a disease and the risk of transmission in specific populations or environments.
Isolation #
The separation of individuals who have been diagnosed with a contagious disease from others to prevent the spread of infection. Isolation is a fundamental control measure in disease dynamics to protect vulnerable individuals, reduce transmission, and contain outbreaks.
Modelling Assumptions #
Simplifying assumptions made in mathematical models to describe the transmission dynamics of infectious diseases. Modelling assumptions in disease dynamics help simplify complex systems, make predictions, and evaluate the impact of interventions.
Case Isolation #
The practice of isolating individuals who have been diagnosed with a specific disease to prevent the spread of infection. Case isolation is a key control measure in disease dynamics to manage individual cases, break the chain of transmission, and control outbreaks.
Chain of Transmission #
The sequence of events that leads to the spread of an infectious disease from one individual to another. Understanding the chain of transmission is essential in disease dynamics to identify opportunities for intervention, interrupt transmission, and control outbreaks.
Prevalence #
The total number of cases of a disease in a population at a specific point in time. Prevalence is a key measure in disease dynamics to assess the burden of disease, monitor trends, and evaluate the effectiveness of control measures.
Incidence #
The number of new cases of a disease that occur within a population over a defined period. Incidence is an important measure in disease dynamics to track the spread of infectious diseases, identify outbreaks, and assess the impact of interventions.
Case Control Study #
A type of observational study that compares individuals with a specific disease (cases) to those without the disease (controls) to identify risk factors and associations. Case control studies are used in disease dynamics to investigate outbreaks, determine causes, and inform control strategies.
Cohort Study #
A type of observational study that follows a group of individuals over time to assess the development of a specific outcome, such as disease. Cohort studies are used in disease dynamics to evaluate risk factors, measure incidence, and identify predictors of disease transmission.
Randomized Controlled Trial (RCT) #
A type of experimental study that randomly assigns participants to different interventions or control groups to evaluate the effectiveness of treatments. Randomized controlled trials are used in disease dynamics to assess the impact of interventions on disease transmission and control.
Case Study #
An in-depth analysis of a specific case or outbreak to understand the transmission dynamics of a disease. Case studies in disease dynamics provide insights into the epidemiology of infectious diseases, the effectiveness of control measures, and the lessons learned from outbreaks.
Sensitivity Analysis #
An analysis that evaluates the impact of uncertainty in model parameters on the outcomes of a mathematical model. Sensitivity analysis in disease dynamics helps assess the robustness of model predictions, identify key drivers of disease transmission, and inform decision-making.
Model Validation #
The process of assessing the accuracy and reliability of a mathematical model by comparing its predictions to real-world data. Model validation is crucial in disease dynamics to ensure that models capture the dynamics of infectious diseases and provide useful insights for decision-making.
Model Calibration #
The process of adjusting model parameters to match observed data and improve the performance of a mathematical model. Model calibration in disease dynamics helps refine models, validate assumptions, and enhance the predictive power of the model.
Parameter Estimation #
The process of determining the values of model parameters based on data and statistical methods. Parameter estimation in disease dynamics is essential to calibrate models, validate predictions, and make informed decisions about disease transmission and control.
Infectious Period #
The duration of time during which an infected individual can transmit the disease to others. The infectious period is a critical parameter in disease dynamics as it influences the rate of transmission, the size of the outbreak, and the effectiveness of control measures.
Latent Period #
The time between exposure to a pathogen and the onset of infectiousness in an infected individual. The latent period is an important parameter in disease dynamics as it affects the timing of interventions, the spread of the disease, and the control of outbreaks.
Age #
Structured Models: Mathematical models that divide the population into different age groups to capture age-specific patterns of disease transmission. Age-structured models in disease dynamics help analyze the impact of age on the spread of infectious diseases and the effectiveness of interventions.
Gender #
Structured Models: Mathematical models that differentiate between male and female individuals to study gender-specific aspects of disease transmission. Gender-structured models in disease dynamics help assess the role of gender in infection rates, susceptibility, and healthcare-seeking behavior.
Seasonality #
The variation in disease transmission and incidence over different seasons or time periods. Seasonality is a common feature in disease dynamics, affecting the spread of infectious diseases, the behavior of pathogens, and the effectiveness of control measures.
Vector Control #
Strategies to reduce the population of vectors, such as mosquitoes or ticks, that transmit infectious diseases to humans. Vector control is an essential component of disease dynamics to prevent vector-borne diseases, interrupt transmission, and protect public health.
Environmental Factors #
External factors, such as temperature, humidity, and rainfall, that influence the transmission of infectious diseases. Environmental factors play a significant role in disease dynamics by affecting the survival and behavior of pathogens, vectors, and hosts.
Host #
Pathogen Interactions: The complex interactions between a host organism and a pathogenic microorganism that determine the outcome of infection. Host-pathogen interactions in disease dynamics influence disease transmission, progression, and the development of immunity.
Immune Response #
The body's defense mechanism against pathogens, including the production of antibodies and immune cells to protect against infection. The immune response is a key aspect of disease dynamics as it influences the severity of disease, the duration of immunity, and the effectiveness of vaccines.
Vaccine Efficacy #
The effectiveness of a vaccine in preventing infection or reducing the severity of disease in vaccinated individuals. Vaccine efficacy is a critical factor in disease dynamics to assess the impact of vaccination programs, achieve herd immunity, and control outbreaks.
Vaccine Hesitancy #
The reluctance or refusal to vaccinate despite the availability of vaccines. Vaccine hesitancy is a challenge in disease dynamics as it can undermine vaccination efforts, reduce herd immunity, and increase the risk of outbreaks of vaccine-preventable diseases.
Global Health Security #
The collective efforts to prevent, detect, and respond to public health threats that have the potential to cross borders and impact populations worldwide. Global health security is essential in disease dynamics to address emerging infectious diseases, pandemics, and other health risks.
Public Health Surveillance #
The systematic collection, analysis, and interpretation of health data to monitor and control the spread of diseases within populations. Public health surveillance is a fundamental tool in disease dynamics to detect outbreaks, track trends, and inform public health interventions.
Outbreak Investigation #
The process of identifying, characterizing, and controlling an outbreak of an infectious disease within a community or population. Outbreak investigations are essential in disease dynamics to understand the transmission dynamics, implement control measures, and prevent further spread of the disease.
Healthcare Epidemiology #
The branch of epidemiology that focuses on the study of infectious diseases within healthcare settings, such as hospitals and long-term care facilities. Healthcare epidemiology plays a critical role in disease dynamics to prevent healthcare-associated infections, control outbreaks, and ensure patient safety.
Biostatistics #
The application of statistical methods to analyze and interpret health data in epidemiology and public health. Biostatistics is essential in disease dynamics to quantify disease risk, assess the impact of interventions, and make evidence-based decisions for disease control.
Health Economics #
The study of how resources are allocated and used in healthcare systems to promote health and prevent disease. Health economics is important in disease dynamics to evaluate the cost-effectiveness of interventions, allocate limited resources, and improve healthcare delivery.
Risk Communication #
The process of informing, educating, and empowering individuals and communities to make decisions about health risks and protective actions. Risk communication is crucial in disease dynamics to build trust, promote behavior change, and enhance public understanding of disease threats.
Disaster Preparedness #
The planning and coordination of resources and activities to respond effectively to emergencies, including natural disasters, disease outbreaks, and other health threats. Disaster preparedness is essential in disease dynamics to ensure timely and coordinated responses to public health emergencies.
Health Equity #
The absence of unfair and avoidable differences in health outcomes among different populations or groups. Health equity is a fundamental principle in disease dynamics to address disparities in disease burden, access to healthcare, and social determinants of health.
Community Engagement #
The involvement of individuals, communities, and stakeholders in decision-making processes and actions to improve health outcomes. Community engagement is vital in disease dynamics to build trust, mobilize resources, and implement effective interventions that address local needs.
Emergency Response #
The rapid deployment of resources, personnel, and strategies to address public health emergencies and mitigate the impact of disasters. Emergency response is crucial in disease dynamics to contain outbreaks, protect populations, and save lives during crises.
Capacity Building #
The process of strengthening the knowledge, skills, and infrastructure of individuals, organizations, and systems to improve public health outcomes. Capacity building is essential in disease dynamics to enhance preparedness, response capabilities, and sustainability of health interventions.
Resilience #
The ability of individuals, communities, and systems to adapt, recover, and thrive in the face of adversity, challenges, and disasters. Resilience is a key factor in disease dynamics to withstand health threats, maintain essential services, and promote long-term health and well-being.
Health Promotion #
The process of enabling individuals and communities to increase control over their health and improve their well-being. Health promotion is essential in disease dynamics to prevent disease, promote healthy behaviors, and address social determinants of health.
Behavioral Change #
The modification of individual or collective behaviors to improve health outcomes and prevent disease. Behavioral change is a critical component of disease dynamics to promote vaccination, adherence to treatment, and adoption of protective measures against infectious diseases.
Capacity Development #
The process of enhancing the skills, knowledge, and resources of individuals, organizations, and systems to improve public health outcomes. Capacity development is essential in disease dynamics to strengthen surveillance, response capabilities, and healthcare delivery in preparedness for outbreaks.
Health Communication #
The dissemination of health information to individuals and communities to promote health outcomes, prevent disease, and address public health challenges. Health communication is a key component of disease dynamics to build awareness, influence behaviors, and empower individuals to make informed decisions.
Infodemiology #
The study of the distribution and determinants of information on health and disease in electronic media. Infodemiology is important in disease dynamics to monitor public perceptions, assess the impact of health messages, and address misinformation during outbreaks.
One Health #
An approach that recognizes the interconnectedness of human, animal, and environmental health in addressing complex health challenges. One Health is essential in disease dynamics to understand zoonotic diseases, antimicrobial resistance, and other health threats that transcend disciplinary boundaries.
Risk Assessment #
The systematic evaluation of potential health risks and hazards to determine the likelihood and consequences of adverse events. Risk assessment is essential in disease dynamics to identify threats, prioritize interventions, and mitigate the impact