The spread of awareness can significantly impact the progression of epidemic outbreaks. When a disease emerges, people's behaviors change in response to the outbreak, reducing their susceptibility. Awareness can arise through personal observation or word of mouth, even without centralized information. A mathematical model was developed to analyze how awareness spreads in a population and how it affects the spread of a disease. The model shows that awareness can reduce the size of an outbreak but does not affect the epidemic threshold. However, if awareness spreads locally and is influenced by the social network structure, it can prevent the disease from spreading, especially if the infection rate is below a certain threshold. The overlap between the social network of potential infection events and the network of communication enhances the impact of locally spreading awareness, particularly in highly clustered networks. The study highlights the importance of considering both disease parameters and social network structures when predicting the fate of future outbreaks. Awareness can reduce the number of infected individuals during an epidemic, but the threshold for disease invasion remains unchanged. In a spatial model, locally spreading awareness can prevent an outbreak if the infection rate is below a threshold. The effectiveness of awareness depends on the overlap between the disease and communication networks, and the structure of these networks. The study also shows that the basic reproductive number can be reduced through awareness, which can prevent the disease from reaching epidemic proportions. The interaction between awareness and disease spread is complex and depends on factors such as the quality of information, the rate of information spread, and the structure of the social network. The findings suggest that understanding the dynamics of awareness and its interaction with disease spread is crucial for predicting and controlling future outbreaks.The spread of awareness can significantly impact the progression of epidemic outbreaks. When a disease emerges, people's behaviors change in response to the outbreak, reducing their susceptibility. Awareness can arise through personal observation or word of mouth, even without centralized information. A mathematical model was developed to analyze how awareness spreads in a population and how it affects the spread of a disease. The model shows that awareness can reduce the size of an outbreak but does not affect the epidemic threshold. However, if awareness spreads locally and is influenced by the social network structure, it can prevent the disease from spreading, especially if the infection rate is below a certain threshold. The overlap between the social network of potential infection events and the network of communication enhances the impact of locally spreading awareness, particularly in highly clustered networks. The study highlights the importance of considering both disease parameters and social network structures when predicting the fate of future outbreaks. Awareness can reduce the number of infected individuals during an epidemic, but the threshold for disease invasion remains unchanged. In a spatial model, locally spreading awareness can prevent an outbreak if the infection rate is below a threshold. The effectiveness of awareness depends on the overlap between the disease and communication networks, and the structure of these networks. The study also shows that the basic reproductive number can be reduced through awareness, which can prevent the disease from reaching epidemic proportions. The interaction between awareness and disease spread is complex and depends on factors such as the quality of information, the rate of information spread, and the structure of the social network. The findings suggest that understanding the dynamics of awareness and its interaction with disease spread is crucial for predicting and controlling future outbreaks.