Reflecting on prediction strategies for epidemics Preparedness and public health response

Objective: To provide an overview of the literature on respiratory infectious disease epidemic prediction, preparedness, and response (including pharmaceutical and nonpharmaceutical interventions) and their impact on public health, with a focus on respiratory conditions such as asthma. Data Sources: Published literature obtained through PubMed database searches. Study Selections: Studies relevant to infectious epidemics, asthma, modeling approaches, health care access, and data analytics related to intervention strategies. Results: Prediction, prevention, and response strategies for infectious disease epidemics use extensive data sources and analytics, addressing many areas including testing and early diagnosis, identifying populations at risk of severe outcomes such as hospitalizations or deaths, monitoring and understanding transmission and spread patterns by age group, social interactions geographically and over time, evaluating the effectiveness of pharmaceutical and nonpharmaceutical interventions, and understanding prioritization of and access to treatment or preventive measures (eg, vaccination, masks), given limited resources and system constraints. Conclusion: Previous epidemics and pandemics have revealed the importance of effective preparedness and response. Further research and implementation need to be performed to emphasize timely and actionable strategies, including for populations with particular health conditions (eg, chronic respiratory diseases) at risk for severe outcomes. (c) 2020 American College of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved. Objective: To provide an overview of the literature on respiratory infectious disease epidemic prediction, preparedness, and response (including pharmaceutical and nonpharmaceutical interventions) and their impact on public health, with a focus on respiratory conditions such as asthma. Data Sources: Published literature obtained through PubMed database searches. Study Selections: Studies relevant to infectious epidemics, asthma, modeling approaches, health care access, and data analytics related to intervention strategies. Results: Prediction, prevention, and response strategies for infectious disease epidemics use extensive data sources and analytics, addressing many areas including testing and early diagnosis, identifying populations at risk of severe outcomes such as hospitalizations or deaths, monitoring and understanding transmission and spread patterns by age group, social interactions geographically and over time, evaluating the effectiveness of pharmaceutical and nonpharmaceutical interventions, and understanding prioritization of and access to treatment or preventive measures (eg, vaccination, masks), given limited resources and system constraints. Conclusion: Previous epidemics and pandemics have revealed the importance of effective preparedness and response. Further research and implementation need to be performed to emphasize timely and actionable