Causality assessment of an adverse event following immunization -AEFI
User manual for the revised WHO AEFI causality assessment classification
Serious or unexpected adverse events can rarely manifest following immunization, and it is important for health care providers as well as public health officials to assess and try to determine if there is a causal relationship with the administration of one or more vaccines. The fact that one was vaccinated within a reasonable time period of the occurrence of an event does not automatically suggest that the vaccine(s) caused or contributed to the event. Many challenges are involved in deciding whether an adverse event is actually caused by vaccination.
The Global Advisory Committee for Vaccine Safety (GACVS) commissioned a group of experts from GACVS, Advisory Committee on Causality Assessment (ACCA), Vaccine Adverse Event Surveillance & Communication of the European Union (EU/VAESCO), Clinical Immunization Safety Assessment (CISA) and the Council for International Organizations of Medical Sciences (CIOMS) to review the WHO AEFI causality assessment methodology and aide-memoire previously published, and to develop a systematic and user friendly method to assist in reviewing and interpreting data, and to assess causality after individual AEFIs. Several prototypes were developed and tested by the group and the final revised WHO approach was piloted in four middle-income countries in the South East Asia Region and reviewed by the GACVS before it was approved for distribution.
This manual incorporates the recent definitions and terms recommended by the CIOMS/WHO Working Group on Vaccine Pharmacovigilance. It also takes into account the needs of emerging countries to address challenges in collecting essential information during AEFI investigation and classification of AEFI cases in a standardized and transparent manner. Effort has also been made to make the method simple, practical and “hands on” to guide assessors in deciding causality through the application of logic and their experience for arriving at the best conclusion with available evidence.