Viral BRAIN - Viral Infections Research Assessment Linkage Big-data Research on Acute Infectious Neuropsychiatric complications

Project description

Background
Acute viral infections—such as SARS‑CoV‑2 and influenza—can lead to severe complications that extend beyond respiratory illness, including delirium, psychosis, or other neuropsychiatric conditions. Recent studies show that such post-infectious effects can heavily burden individuals and healthcare systems, yet large-scale data on their magnitude and timing remain limited. Understanding who is at highest risk, and when these complications tend to emerge, is pivotal for guiding prevention, improving outcomes, and optimizing resource allocation.

Project Description
Viral BRAIN (Viral Infections Research Assessment Linkage Big-data Research on Acute Infectious Neuropsychiatric Complications) harnesses Sweden’s extensive registry resources to explore how acute viral infections predispose individuals to first-time neuropsychiatric events. The project compiles data from 2015 onward on both positive and negative lab-confirmed test results for SARS‑CoV‑2 and influenza, then merges these records with clinical and demographic information (e.g., inpatient and outpatient visits, medication usage, and socioeconomic indicators).

1. Scope and Data Linkage
   • Nationwide Registries: The study integrates patient-level data from multiple Swedish registries. Each registry entry is connected via personal identity numbers (PINs), enabling a longitudinal perspective that traces clinical outcomes months or even years after infection. 
   • Clinical Outcomes: Primary endpoints include acute neuropsychiatric diagnoses such as psychosis, encephalitis, meningitis and delirium. By focusing on first-time diagnoses, Viral BRAIN distinguishes new-onset complications from chronic psychiatric or neurological issues.
2. Methods
   • Risk Quantification: Cox regression models estimate hazard ratios for new neuropsychiatric events in individuals with confirmed infections. This clarifies whether—and how much—viral infection elevates risk compared to uninfected or pre-infection baseline periods.
   • Temporal Dynamics: Self-controlled case series (SCCS) methods capture changes in risk windows before, during, and after infection, enabling fine-grained analysis of when complications are most likely to manifest.
   • High-Resolution Stratification: Advanced machine learning techniques—such as Double Machine Learning and Causal Forests—identify subpopulations (e.g., older adults, immunocompromised individuals) who face disproportionately high risks. This computational depth pinpoints at-risk groups more precisely than traditional methods alone.

3. Impact and Utility.

   • Targeted Prevention: By establishing both when risk spikes and which groups are most vulnerable, Viral BRAIN will guide resource allocation (e.g., enhanced monitoring or early psychiatric evaluations) to mitigate severe outcomes.

   • Public Health and Policy: The findings will help clinicians and health authorities anticipate and manage future post-infectious surges in neuropsychiatric morbidity, reducing hospital strain and societal costs.

   • Knowledge Translation: Engaging the Virus and Pandemic Foundation ensures regular communication of actionable insights to policymakers, public health officials, and clinical networks, accelerating the application of evidence-based strategies.

NeuroCov Consortium
NeuroCov, an EU-funded consortium, delves into the molecular, clinical, and population-level ramifications of COVID-19 on the brain. Its interdisciplinary teams utilize omics technologies, AI-driven modeling, and longitudinal patient cohorts to chart how SARS-CoV-2 impacts neurological function. Viral BRAIN complements these efforts with a specific focus on large-scale Swedish registry data, enabling cross-validation of findings and extending NeuroCov’s reach into broader population-based contexts. By uniting mechanistic and epidemiological insights, both initiatives aim to clarify why certain individuals endure severe post-viral neuropsychiatric consequences and how to intervene effectively.

https://neurocov.eu/

Participating Researchers

Assoc. Prof. Anne-Marie Fors Connolly (MD, PhD) – Principal Investigator. Has a background in Clinical Microbiology and Infectious Disease Epidemiology, and has led multiple nationwide registry-based projects on SARS‑CoV‑2 and other pathogens.

Angéle Ahebla (MD, MSc Molecular Biology, MPH) - Part of Fors Connolly team - Research assistant performing analysis of nationwide population data. 

Sebastian Kalucza (BSc Statistics) - Part of Fors Connolly team - data manager with extensive experience linking data from several nationwide registries.

Dr. Osvaldo Fonseca Rodriguez (DVM, PhD) - Part of Fors Connolly team - epidemiologist with extensive experience in the Self-controlled case series method

Prof Marie Eriksson (PhD) - works part-time as a statistical consultant in the Fors Connolly team, ensuring that all statistical assumptions are met and ensuring the highest level of statistical stringency

Assoc. Prof. Matilda Naesström (MD, PhD) – Senior Consultant Psychiatrist. She brings expertise in acute mental health outcomes, particularly delirium and psychosis in older populations, and provides clinical insights for study design and interpretation.

Dr. Sara Kalucza (PhD) – A data scientist and sociologist specialized in large-scale registry linkages, advanced statistics, and machine learning. She oversees data harmonization and the application of Double Machine Learning/Causal Forest algorithms.

Assoc. Prof. Jonatan Salzer (MD, PhD) – Senior consultant in Neurology. His expertise ensures robust definitions of neurological endpoints and guides interpretation of findings related to encephalitis and other CNS manifestations.

Prof. Niklas Arnberg (PhD) – General Secretary and Founder of the Virus and Pandemic Foundation. With extensive experience in virology and public engagement, he bridges research outputs and real-world policy by coordinating stakeholder communication and dissemination activities.