Actions to Integrate Treatment of Opioid and Infectious Disease Epidemics

2019 ◽  
Vol 170 (7) ◽  
pp. 509
Author(s):  
Joshua A. Barocas
Keyword(s):  
Infectious Disease ◽  
Disease Epidemics

scholarly journals Experience of a global laboratory network in responding to infectious disease epidemics

2006 ◽  
Vol 6 (9) ◽  
pp. 538-540 ◽  
Author(s):  
Jean-Paul Chretien ◽  
David L Blazes ◽  
Joel C Gaydos ◽  
Sheryl A Bedno ◽  
Rodney L Coldren ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Laboratory Network ◽  
Disease Epidemics

scholarly journals Integrating Responses to the Opioid Use Disorder and Infectious Disease Epidemics

JAMA ◽  
2020 ◽  
Vol 324 (1) ◽  
pp. 37 ◽  
Author(s):  
Sandra A. Springer ◽  
Andrew P. Merluzzi ◽  
Carlos del Rio
Keyword(s):  
Infectious Disease ◽  
Opioid Use Disorder ◽  
Opioid Use ◽  
Disease Epidemics

Modeling Large-Scale Epidemics

2017 ◽  
Author(s):  
Sanjay Basu
Keyword(s):  
Infectious Disease ◽  
Infectious Diseases ◽  
Markov Model ◽  
Simulation Modeling ◽  
Large Scale ◽  
Basic Feature ◽  
Risk Of Infection ◽  
Critical Aspect ◽  
Modeling Framework ◽  
Disease Epidemics

Previous chapters ignored a critical aspect of modeling some major diseases: the infectious nature of many diseases. For infectious diseases, the risk of getting the disease is related to how many people are infectious at a given time: the more infectious people in the area, the higher the risk of infection among susceptible people. In a typical Markov model, we can’t account for this basic feature of infectious diseases because the risk of moving from one state (healthy) to another state (diseased) is assumed to be constant. In this chapter, the author introduces a simulation modeling framework that has been used for decades to simulate infectious disease epidemics.

scholarly journals An online decision tree for vaccine efficacy trial design during infectious disease epidemics: The InterVax-Tool

Vaccine ◽  
2019 ◽  
Vol 37 (31) ◽  
pp. 4376-4381 ◽  
Author(s):  
Steven E. Bellan ◽  
Rosalind M. Eggo ◽  
Pierre-Stéphane Gsell ◽  
Adam J. Kucharski ◽  
Natalie E. Dean ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Decision Tree ◽  
Vaccine Efficacy ◽  
Trial Design ◽  
Efficacy Trial ◽  
Disease Epidemics

scholarly journals Twenty Years of Integrated Disease Surveillance and Response in Sub-Saharan Africa: Challenges and Opportunities for Effective Management of Infectious Disease Epidemics

2020 ◽  
Author(s):  
Irene Mremi ◽  
Janeth George ◽  
Susan F. Rumisha ◽  
Calvin Sindato ◽  
Leonard E.G. Mboera ◽  
...  
Keyword(s):  
Public Health ◽  
Infectious Disease ◽  
Health Information ◽  
Disease Surveillance ◽  
Sub Saharan Africa ◽  
Health Management Information System ◽  
Support Functions ◽  
Surveillance And Response ◽  
Sub Saharan ◽  
Disease Epidemics

Abstract Background: Public health surveillance requires valid, timely and complete health information for early detection of outbreaks. Countries in Sub-Saharan Africa (SSA) adopted Integrated Disease Surveillance and Response (IDSR) strategy in 1998 in response to an increased frequency of emerging and re-emerging diseases in the region. This systematic review aimed to analyse how IDSR implementation has embraced advancement in information technology, big data analytics techniques and wealth of data sources to strengthen detection and management of infectious disease epidemics in SSA. Methods: A search for eligible articles was done through HINARI, PubMed, and advanced Google Scholar databases. The review followed Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols checklist. Using the key search descriptors, 1,809 articles were identified and screened at two stages and 45 studies met the inclusion criteria for detailed review.Results: Of the 45 studies, 35 were country-specific, seven studies covered the region and three studies covered 3-4 countries. A total of 24 studies assessed the IDSR core functions while 42 studies assessed the support functions. Twenty-three studies addressed both the core and support functions. Most of the studies involved Tanzania (9), Ghana (6) and Uganda (5). The implementation of the IDSR strategy has shown improvements mainly in the support functions. The Health Management Information System (HMIS) has remained the main source of IDSR data. However, the HMIS system is characterised by inadequate data completeness, timeliness, quality, analysis and utilisation as well as lack of integration of data from sources other than health care facilities. Conclusion: In most SSA, HMIS is the main source of IDSR data, characterised by incompleteness, inconsistency and inaccuracy. This data is considered to be biased and reflects only the population seeking care from healthcare facilities. Community-based event-based surveillance is weak and non-existence in the majority of the countries. Data from other systems are not effectively utilized and integrated for surveillance. It is recommended that SSA countries consider and adopt multi-sectoral, multi-disease and multi-indicator platforms that integrate the existing surveillance systems with other sources of health information to provide support to effective detection and prompt response to public health threats.

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