Data sources on COVID-19 infection and vaccination in pregnancy on the island of Ireland: strengths, weaknesses, and recommendations for future pandemic preparedness

Background

On the 11th of March 2020, the World Health Organization (WHO) declared SARS-CoV-2 (COVID-19) as a global pandemic¹. Emerging evidence has demonstrated the adverse effects of COVID-19 on vulnerable populations, particularly on pregnant women². The impact of COVID-19 on pregnant women and their unborn babies is multifaceted because of the potential risks associated with the virus itself, medicines to treat the virus, safety of vaccines, and indirect effects of pandemic-related stress³. COVID-19 infection during pregnancy may negatively impact maternal health and fetal development and increase the risk of preterm birth and congenital anomalies (CA; 3, 4). Despite the potential risk of infection, a high proportion of pregnant women remain unvaccinated during the pandemic, largely because of vaccine hesitancy⁵. Longitudinal follow-up studies using population-based datasets of women vaccinated earlier in pregnancy are required to assess maternal, pregnancy, and infant outcomes. However, the availability of detailed, accurate, and timely data is crucial to achieve this.

On the Island of Ireland (IOI), pregnancy-related data were collected through clinical and administrative processes within healthcare settings during the pandemic. The IOI comprises the Republic of Ireland (ROI), a sovereign country within the European Union (EU), and Northern Ireland (NI), which is part of the United Kingdom (UK). The national datasets in the ROI (https://covid19ireland-geohive.hub.arcgis.com/) and NI (https://www.health-ni.gov.uk/articles/covid-19-dashboard-updates) provided critical information and reported confirmed cases of COVID-19 infection by age, sex, and other demographic variables. However, there is a significant lack of data specific to pregnant women. While extensive research on COVID-19 has been conducted using administrative data from the IOI^6,7, studies specifically addressing the impact of the virus during pregnancy are lacking. This deficit in the understanding of the impact of COVID-19 during pregnancy highlights the urgent need for more comprehensive data collection to ensure future pandemic preparedness.

This article aimed to describe the strengths and weaknesses of available data sources on COVID-19 infection and vaccination uptake rates during pregnancy on the IOI, with differing healthcare systems in the two jurisdictions. Based on our findings, we suggest recommendations for improving access to data for research on pandemic preparedness during pregnancy.

Methods

Results

Discussion

This article describes the existing data sources available on COVID-19 infection and vaccination during pregnancy on the IOI as well as their strengths and weaknesses. Across the IOI, there were key differences in the data access procedures. In the ROI, each of the available datasets involved separate applications with various procedures. In NI, access was more streamlined and could be requested through a central data provider with the existence of an HCN to support data linkage. Conversely, while the implementation of IHI numbers in the ROI continues to be rolled out, with the COVID-19 pandemic arguably expediting this implementation, it has not yet been fully implemented in all health care settings.

Several notable differences between the two jurisdictions on the IOI emerged when requesting data on COVID-19 infection and vaccination during pregnancy. In the ROI, the process of data access appeared fragmented, marked by disparate systems and the inability to link pregnant women’s data throughout the healthcare system. Furthermore, applications for data access in the ROI often necessitate the addition of an HSE representative to the research team. Conversely, in NI, data access procedures demonstrated a more integrated approach with various components of the healthcare system linked by HCNs for more streamlined access via a single data provider, the HBS. These differences in accessing pregnancy-related COVID-19 data in the ROI and NI highlight the disparate infrastructure between the jurisdictions that affect research capabilities.

Strengths, limitations and recommendations

To further facilitate research using available data on COVID-19 infection and vaccination during pregnancy, recommendations and limitations are discussed. First, the lack of an expected timeframe for accessing data in both the ROI and NI prevents researchers from effectively managing expectations and communicating timelines with stakeholders and funders. Researchers need to have detailed timeframes to gain access to these data and effectively plan their research projects. Knowing the duration of data access processes allows researchers to schedule their workloads effectively, set realistic timelines for project completion, and allocate appropriate resources. Data can quickly become outdated, and an upper time limit on data access requests would ensure that information used in research is timely enough to inform recommendations for current public health practices. Furthermore, many data protection and privacy regulations, such as the General Data Protection Regulation (GDPR), impose specific time constraints on data usage and retention.

Accessing and analyzing available data on COVID-19 infection and vaccination during pregnancy is crucial for evaluating public health guidelines and improving research on maternal and child health across the IOI. In NI, there are clear processes for requesting and accessing data on COVID-19 infection and vaccination during pregnancy, while the arrival of the European Health Data Space (EHDS) places a requirement on the ROI to facilitate access to health data for researchers¹⁸. Having detailed instructions for accessing population-based and maternal data on COVID-19 infection, vaccination, and pregnancy in the ROI is crucial to ensure accurate, transparent, and timely information. This approach will enhance the ability to conduct comprehensive research, promote consistency and reproducibility of research findings, and improve public health outcomes.

The implementation of the IHI is currently underway in the ROI. The IHI, which was utilized in the COVAX initiative, has significant potential for streamlining data linkage. Advocating the accelerated rollout of the IHI, akin to the HCN number used for linked datasets available in NI, could further support research and public health efforts. The ability to link individual records from different databases using a unique identifier has many advantages. The use of an IHI enables researchers to combine anonymized administrative datasets to answer research questions without intrusion into patients' lives, particularly if individuals are severely ill. It is an efficient and cost-effective method to conduct population-based research that is feasible during emergency response. In this instance, it would mean that each data source would not need to collect the same data, and each data source could concentrate on collecting quality data in one area (e.g., COVID-19 test) and be linked to another data source (e.g., clinical maternal records with pregnancy outcome data). In relation to research on exposure during pregnancy, the study would not be impeded by an unknown pregnancy status or early pregnancy as the pregnancy status would be obtained from the maternity records, and the gestational age at infection or vaccination can be accurately estimated, which is essential for safety studies.

Access to metadata i,e, detailed information on all variables as well as definitions of these variables and the size of the data in each dataset was limited in ROI. Effectively managing data relies on both clear documentation and an understanding of its scale. A data dictionary is essential for ensuring consistency, clarity, and proper documentation of variables, as understanding the variable definitions, formats, and relationships is crucial. Due to the lack of metadata in ROI, it is not possible to assess the consistency between variables in the ROI datasets. In NI, the variables recording covid-19 infections, vaccinations, types of vaccinations in the NIMATS data will be compared to the infection (Pillar 1, Pillar 2) and vaccination data to assess consistency and reliability. To our knowledge, there have been no studies assessing the rate of infections and vaccination use in pregnant women on the IOI. The NI team have published studies using the NIMATS data^19,20.

Additionally, detailing the size of the data would inform computational requirements, needed storage capacity, and the feasibility of different analytical approaches. Standardized procedures for using anonymized linked data ensure that accessing sensitive data on COVID-19 and pregnancy complies with legal and ethical requirements, further protecting the privacy and rights of the public. Transparent processes promote accountability when data access and usage protocols are upheld. This helps prevent misuse or unauthorized access to pregnancy data and fosters accountability for any breach or misconduct. To further enhance access to large datasets, funding agencies and academic institutions should establish a formal partnership with health services. This collaboration can help navigate the practical steps required, despite legislative changes. A dedicated funding body could facilitate coordination between these groups and promote effective data sharing. This process was developed at NI, where the HBS within the HSC provides data access to researchers.

Future directions

In the ROI, a national standardized data access process with transparent expected timelines would help to reduce the complexity of accessing COVID-19 and pregnancy data. Further implementation of the IHI system, similar to the HCNs in NI, will enable seamless data linkage across various healthcare sectors. A linked data network can ensure uniform data collection and ease of access for research purposes. An Italian study proposed that a data-driven framework could ensure real-time data updates regarding the risk of COVID-19 and enable the identification of high-risk areas²¹. Furthermore, as suggested by Maher et al., the formation of data science teams (embedded in organizations such as the National Perinatal Epidemiology Centre) to assist with data management and handling of data requests in ROI would enhance the provision of pregnancy data for secondary use¹⁶.

To further enhance the scope and quality of research on COVID-19 and pregnancy, improving data linkages and accessibility across nations is crucial. One key approach is to establish a joint task force between the ROI and NI to facilitate cross-border data sharing.

To reduce the application timelines for accessing data on COVID-19 and pregnancy in the ROI and NI, implementing clear guidelines and support mechanisms for researchers would help expedite data access. This should include detailed information on what is required in an application and what criteria are used for evaluation and approval. Furthermore, support mechanisms such as Frequently Asked Questions (FAQs), dedicated personnel, and help desks that can assist researchers in navigating the application process would be beneficial. Additionally, synthetic data to allow piloting of data cleaning and analysis syntax would allow researchers to progress their research while waiting for data to be made available. Transparent communication channels would keep researchers informed and up-to-date regarding the status of an application and expected timelines to help manage funders’ expectations. Clear and transparent timelines would optimize the process of data access for research on COVID-19 and pregnancy, using secondary data.

Throughout the COVID-19 pandemic, challenges and concerns related to reducing the data entry burden on healthcare workers and protecting patient privacy became key topics of debate. Now referred to as "documentation burden" the extensive administrative tasks healthcare workers must perform, particularly related to patient records, is identified as a significant contributor to healthcare worker burnout²². The demands of the COVID-19 pandemic further exacerbated this burden. Streamlining the documentation process is not without its challenges. As outlined in this paper, the development of a national maternity repository that integrates data from various sources could reduce the data entry burden on healthcare professionals. By streamlining data collection processes, this electronic system would perhaps minimise the duplication of efforts on behalf of hospital staff and enhance the efficiency of data management especially in the ROI where data linkage is currently not possible.

Furthermore, the rapid increase in health data collection throughout the pandemic has raised concern regarding the security and potential misuse of sensitive personal information. While specific studies detailing pregnant women's concerns about data breaches following the COVID-19 pandemic remain limited, the broader issue of health data protection is highly debated. This paper highlights the use of anonymized data as a key strategy to increase willingness to share information by addressing privacy concerns and regulatory requirements (e.g., GDPR). The removal of personally identifiable information would aim to reduce the risk of re-identification, misuse, and ethical concerns, fostering trust among healthcare providers, institutions, and patients. In NI, the anonymized data are made available to researchers in a “safe haven” within the Honest Broker Service, with strict processes to ensure data protection. All researchers must complete the Safe Researcher Training before access will be granted.

Pandemic preparedness

Timeliness of data access is important in a pandemic situation. Timely access to data is needed not only to contribute to international research efforts but also to quickly assess the impact of the new infection during pregnancy and to assess the safety of the vaccine for pregnant women as it is rolled out, particularly in relation to rarer outcomes such as CA. Pandemic preparedness should include a focus on information systems and how they will provide important information about pregnancy and pregnancy outcomes. Accurate information is needed regarding pregnancy status, most importantly in early pregnancy, and gestational age in relation to exposures, such as infection and vaccination, since the impact of exposure is gestational age-dependent. Precise data regarding the timing of pregnancy was available in NI but were limited in ROI in this study. Given the critical nature of the first trimester in congenital anomaly development, accurate information correlating the timing of both COVID-19 infection and COVID-19 vaccination with gestational stage is essential for identifying potential associations with such anomalies. Inevitably, an unknown early pregnancy may result in a false-negative pregnancy status; however, further administrative delays should be avoided. Emergency responses often neglect to consider the benefits of collecting data for research, with immediate priorities of surge capacity. A recommendation is to record the date of changes to the metadata when they are made to allow for the accurate interpretation of missing or unknown data fields. Rapid data access systems for pandemics should be planned, including explicit access to pregnancy data.

Conclusion

The process of accessing health data in both the ROI and the NI was rigorous, with many safeguards to protect the privacy of the public’s administrative data and the security of sensitive data. Several challenges hinder the acquisition of anonymized data on COVID-19 infection and vaccination uptake during pregnancy, particularly in the ROI. These include data fragmentation, privacy concerns, incomplete reporting, lack of standardization surrounding data access procedures, and issues related to data quality. In the ROI, delays in obtaining data, even after acquiring ethical approval, led to significant setbacks in research timelines. The absence of clear procedural guidance outlining the steps involved in accessing the requisite data in the ROI further complicates the process. In summary, the contrasting processes between NI and ROI underscore the complexities inherent in accessing data on COVID-19 infection and vaccination rates during pregnancy. To effectively address these challenges, it is essential to focus on improving the research infrastructure, including data-sharing protocols, and simplifying access procedures in the ROI. These steps will promote the development of strong research initiatives and enable informed decision making within public health policies.

Ethics & consent

This project was approved by the Ethics Committee of Cork Teaching Hospitals for Cork University Maternity Hospital (CUMH): ECM 4 (b) 01/08/2023 & ECM 3 (c) 05/12/2023. Following approval, a research application form was submitted to the Local Information Governance Group.