Information systems for vaccine safety surveillance

A scoping review of active, participant centred, digital adverse events following immunization (AEFI) surveillance of WHO approved COVID-19 vaccines: A Canadian immunization Research Network study

This scoping review examines the role of digital solutions in active, participant-centered surveillance of adverse events following initial release of COVID-19 vaccines. The goals of this paper were to examine the existing literature surrounding digital solutions and technology used for active, participant centered, AEFI surveillance of novel COVID-19 vaccines approved by WHO. This paper also aimed to identify gaps in literature surrounding digital, active, participant centered AEFI surveillance systems and to identify and describe the core components of active, participant centered, digital surveillance systems being used for post-market AEFI surveillance of WHO approved COVID-19 vaccines, with a focus on the digital solutions and technology being used, the type of AEFI detected, and the populations under surveillance. The findings highlight the need for customized surveillance systems based on local contexts and the lessons learned to improve future vaccine monitoring and pandemic preparedness.

Detailed review of mortality reported following COVID-19 vaccination in Victoria, Australia: 2021-2023

INTRODUCTION

The scale of the COVID-19 vaccine program, and appropriate focus on older individuals, emphasised monitoring of mortality as an important part of COVID-19 vaccine safety surveillance, noting many deaths temporally associated with vaccination may not be causally related. This cross-sectional study describes Victoria's vaccine safety service (SAEFVIC) process of reviewing mortality reports following COVID-19 vaccination, summarises report characteristics and identifies trends in mortality reporting.

METHODS

Mortality cases reported to SAEFVIC following COVID-19 vaccination from 22 February 2021 to 22 February 2023 were included. Report characteristics, demographics, and cause of death information were described. Proportions of mortality reports per 100,000 vaccine doses administered were calculated, overall and stratified by age (<60 years, ≥60 years), sex, vaccine type and dose number. Rate ratios (RR) were used to compare proportions.

RESULTS

Reporting proportions were higher in the first three months of the vaccine program (3.98 per 100,000 doses), compared to the following 21 months (0.71 per 100,000 doses), RR:5.61, p < 0.001. Of 159 mortality reports included, 135/159 (84.9 %) were in individuals ≥60 years. Most individuals (121/159, 90.3 %) had comorbidities relevant to cause(s) of death, and 143/159 (89.9 %) were categorised as having a 'likely alternate' cause of death based on treating clinician/forensic assessment. For 11/159 (6.9 %) reports vaccine contribution to death could not be determined. Five deaths (0.03 per 100,000 doses administered), all publicly reported, were assessed by the national regulator as likely vaccine-associated.

CONCLUSIONS

Mortality reporting predominantly reflected the health status of the population receiving vaccines, vaccine administration patterns and contextual factors surrounding COVID-19 vaccines (including public concerns regarding serious adverse events of special interest), as well as extremely rare but fatal adverse events that were likely vaccine-associated. Jurisdictional vaccine safety services such as SAEFVIC play an important role in follow-up of mortality reports, supporting the work of national regulators, and thereby supporting vaccine safety surveillance and vaccine confidence more broadly.

Near Real-Time Syndromic Surveillance of Emergency Department Triage Texts Using Natural Language Processing: Case Study in Febrile Convulsion Detection

BACKGROUND

Collecting information on adverse events following immunization from as many sources as possible is critical for promptly identifying potential safety concerns and taking appropriate actions. Febrile convulsions are recognized as an important potential reaction to vaccination in children aged <6 years.

OBJECTIVE

The primary aim of this study was to evaluate the performance of natural language processing techniques and machine learning (ML) models for the rapid detection of febrile convulsion presentations in emergency departments (EDs), especially with respect to the minimum training data requirements to obtain optimum model performance. In addition, we examined the deployment requirements for a ML model to perform real-time monitoring of ED triage notes.

METHODS

We developed a pattern matching approach as a baseline and evaluated ML models for the classification of febrile convulsions in ED triage notes to determine both their training requirements and their effectiveness in detecting febrile convulsions. We measured their performance during training and then compared the deployed models' result on new incoming ED data.

RESULTS

Although the best standard neural networks had acceptable performance and were low-resource models, transformer-based models outperformed them substantially, justifying their ongoing deployment.

CONCLUSIONS

Using natural language processing, particularly with the use of large language models, offers significant advantages in syndromic surveillance. Large language models make highly effective classifiers, and their text generation capacity can be used to enhance the quality and diversity of training data.

Integrating Digital Health Solutions with Immunization Strategies: Improving Immunization Coverage and Monitoring in the Post-COVID-19 Era

The COVID-19 pandemic underscored the critical importance of vaccination to global health security and highlighted the potential of digital health solutions to improve immunization strategies. This article explores integrating digital health technologies with immunization programs to improve coverage, monitoring, and public health outcomes. It examines the current landscape of digital tools used in immunization initiatives, such as mobile health apps, electronic health records, and data analytics platforms. Case studies from different regions demonstrate the effectiveness of these technologies in addressing challenges such as vaccine hesitancy, logistics, and real-time monitoring of vaccine distribution and adverse events. The paper also examines ethical considerations, data privacy issues, and the need for a robust digital infrastructure to support these innovations. By analyzing the successes and limitations of digital health interventions in immunization campaigns during and after the COVID-19 pandemic, we provide recommendations for future integration strategies to ensure resilient and responsive immunization systems. This research aims to guide policymakers, health professionals, and technologists in leveraging digital health to strengthen immunization efforts and prepare for future public health emergencies.

Current Approaches in Postapproval Vaccine Safety Studies Using Real-World Data: A Systematic Review of Published Literature

PURPOSE

Well-designed observational postmarketing studies using real-world data (RWD) are critical in supporting an evidence base and bolstering public confidence in vaccine safety. This systematic review presents current research methodologies in vaccine safety research in postapproval settings, technological advancements contributing to research resources and capabilities, and their major strengths and limitations.

METHODS

A comprehensive search was conducted using PubMed to identify relevant articles published from January 1, 2019, to December 31, 2022. Eligible studies were summarized overall by study design and other study characteristics (eg, country, vaccine studied, types of data source, and study population). An in-depth review of select studies representative of conventional or new designs, analytical approaches, or data collection methods was conducted to summarize current methods in vaccine safety research.

FINDINGS

Out of 977 articles screened for inclusion, 135 were reviewed. The review shows that recent advancements in scientific methods, digital technology, and analytic approaches have significantly contributed to postapproval vaccine safety studies using RWD. "Near real-time surveillance" using large datasets (via collaborative or distributed databases) has been used to facilitate rapid signal detection that complements passive surveillance. There was increasing appreciation for self-controlled case-only designs (self-controlled case series and self-controlled risk interval) to assess acute-onset safety outcomes, artificial intelligence, and natural language processing to improve outcome accuracy and study timeliness and emerging artificial intelligence-based analysis to capture adverse events from social media platforms.

IMPLICATIONS

Continued development in the area of vaccine safety research methodologies using RWD is warranted. The future of successful vaccine safety research, especially evaluation of rare safety events, is likely to comprise digital technologies including linking RWD networks, machine learning, and advanced analytic methods to generate rapid and robust real-world safety information.

Enhancing Pharmacovigilance in Côte d'Ivoire: Impact of GSK's Training and Mentoring Pilot Project in the Abidjan Region

INTRODUCTION

Pharmacovigilance (PV) in sub-Saharan Africa relies on passive surveillance but underreporting of adverse events (AEs) by health care professionals (HCPs) is a major challenge. A PV enhancement project was implemented to address this in Côte d'Ivoire.

OBJECTIVE

To improve safety surveillance of medicines through PV training and mentoring of HCPs in selected health care facilities (HCFs).

METHODS

This collaborative project between national PV stakeholders, GSK, and PATH was implemented from September 2018 to February 2020 in Abidjan region, Côte d'Ivoire. Trained PV focal points provided training and regular mentoring of HCPs. Key performance indicator (KPI) categories for AE reporting were the volume of AE reports, efficiency of report transmission and data entry, quality of reports, and quality of the central (Vigilance Unit) response to AE reports.

RESULTS

Overall, 1427 HCPs at 91 HCFs were trained. In the 8 months before implementation, 33 AE reports were received versus 85 after 3 months and 361 after 18 months of implementation (71 [83.5%] and 278 [77.0%], respectively, from Abidjan). The KPIs with the highest proportions were: AE reports received centrally (100%), complete AE reports (69.0%), AE reports entered into the local PV database within 48 h (99.6%), and AE reports entered into the global database, VigiBase (86.7%). Report notification within 72 h, causality assessment, and serious AE reporting had proportions below 20%; feedback to reporters was provided for only 0.4% of reports.

CONCLUSION

Regular PV trainings and mentoring improved AE reporting in Côte d'Ivoire but further enhancement is required to improve passive safety surveillance.

Pooled rates and demographics of POTS following SARS-CoV-2 infection versus COVID-19 vaccination: Systematic review and meta-analysis

PURPOSE

To address recent concerns of postural orthostatic tachycardia syndrome (POTS) occurring after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and coronavirus disease 2019 (COVID-19) vaccination.

METHODS

We searched PubMed, Web of Science, and Scopus as of 1st June 2023. We performed a systematic review and meta-analysis of pooled POTS rate in SARS-CoV-2-infected and COVID-19-vaccinated groups from epidemiological studies, followed by subgroup analyses by characteristic. Meta-analysis of risk ratio was conducted to compare POTS rate in infected versus uninfected groups. Meta-analysis of demographics was also performed to compare cases of post-infection and post-vaccination POTS from case reports and series.

RESULTS

We estimated the pooled POTS rate of 107.75 (95 % CI: 9.73 to 273.52) and 3.94 (95 % CI: 0 to 16.39) cases per 10,000 (i.e., 1.08 % and 0.039 %) in infected and vaccinated individuals based on 5 and 2 studies, respectively. Meta-regression revealed age as a significant variable influencing 86.2 % variance of the pooled POTS rate in infected population (P < 0.05). Moreover, POTS was 2.12-fold more likely to occur in infected than uninfected individuals (RR = 2.12, 95 % CI: 1.71 to 2.62, P < 0.001). Meta-analyzed demographics for cases of post-infection (n = 43) and post-vaccination (n = 17) POTS found no significant differences in several variables between groups, except that the time from exposure to symptom onset was shorter for cases of post-vaccination POTS (P < 0.05).

CONCLUSION

Although evidence is limited for post-vaccination POTS, our study showed that POTS occur more frequently following SARS-CoV-2 infection than COVID-19 vaccination.