27/04/2023
๐๐๐๐๐ง๐๐ ๐ฃ๐ข๐ฆ๐ง๐๐ฅ ๐๐ข๐ ๐ฃ๐๐ง๐๐ง๐๐ข๐ก-ORGANIZED BY CMS GCU LAHORE
๐พ๐๐๐๐๐'๐ ๐ท๐๐๐๐๐:
Hassan Aftab (8th Semester, GCU Lahore)
๐ท๐๐๐๐๐'๐ ๐ป๐๐๐๐:
๐๐ฌ๐ข๐ง๐ ๐๐๐ญ๐ก ๐๐จ ๐
๐ข๐ ๐ก๐ญ ๐๐ข๐ฌ๐๐๐ฌ๐: ๐๐๐๐๐๐๐๐๐๐ ๐๐๐ ๐๐๐๐๐๐๐๐, ๐๐๐๐๐๐๐๐๐๐ ๐๐๐ ๐๐๐๐๐๐๐๐๐ ๐๐๐๐ ๐๐๐๐๐๐๐๐๐๐๐๐ ๐๐๐๐๐๐๐๐๐๐๐๐!
๐ฐ๐๐๐๐๐๐๐๐๐๐:
He designed this research poster with a goal to make people aware regarding the field of mathematical epidemiology. He got inspiration of making this poster from his recent publication โMathematical study of lumpy skin disease with optimal control analysis through vaccinationโ in AEJ.
๐ซ๐๐๐๐๐๐๐๐๐๐:-
Mathematical epidemiology is a field that uses mathematical models to study the spread and control of infectious diseases. These models are based on mathematical equations that describe how a disease spreads through a population and how different interventions, such as vaccination or social distancing, can slow or stop the spread. One of the most important applications of mathematical epidemiology is predicting the course of an outbreak. By inputting data on the disease's characteristics, such as its transmission rate and incubation period, into mathematical models, researchers can forecast how the outbreak will progress over time. This information can be used to develop strategies for controlling the outbreak, such as implementing quarantine measures or increasing hospital capacity etc. Mathematical epidemiology can also help to evaluate the effectiveness of different interventions. By simulating the effects of different control strategies in a model, researchers can compare the impact of measures such as vaccination campaigns or non-pharmaceutical measures. This can help policymakers make more informed decisions about which interventions to implement and when. Another key area of research in mathematical epidemiology is understanding the dynamics of disease transmission. By developing models that describe how diseases spread through networks of individuals, researchers can identify the factors that contribute to the spread of diseases, such as the number and frequency of contacts between people. This information can be used to develop targeted interventions that are more effective at controlling the spread of diseases. Overall, mathematical epidemiology is a powerful tool for understanding and controlling the spread of infectious diseases. By using mathematical models to predict the course of outbreaks, evaluate control strategies, and study disease transmission dynamics, researchers can develop more effective interventions and improve public health outcomes.