Anders Erlandson

Thesis title: Does vaccine efficacy depend on the time of day of delivery?

Biography

Background

I completed an undergraduate in biological sciences (immunology) at the University of Edinburgh, where I researched whether the time of day of immunisation affected immunogenicity and efficacy using a rodent malaria model. I then undertook an MScR in infectious diseases, at the University of Glasgow (supervised by Professor Poppy Lamberton), where I used a combination of latent class analysis and genetic sibship analysis to investigate the infection dynamics of Schistosoma mansoni in Uganda. I am now an MRC-funded Precision Medicine Doctoral Training Program (DTP) PhD researcher, investigating whether the time of day of delivery affects vaccine efficacy.

Qualifications

Biological Sciences (Immunology) (BSc Hons) - University of Edinburgh (2025)

Research summary

I'm interested in infectious disease biology, immunology and epidemiology as well as host-pathogen interactions.

Current research interests

There are circadian rhythms (i.e. over a 24-hour period) in the immune systems of many taxa, including mammals. These rhythms drive time-dependent responses to infection, affecting severity and survival. Recently, it has been shown in rodent and human studies that the time of day of vaccination may affect humoral and cellular immunity, disease severity and hospitalisation rates, however, there remains no consensus as to when the optimal time of day to vaccinate is, and what factors influence this. For my Precision Medicine DTP, I am investigating whether the time of day of delivery affects vaccine efficacy in a new model: sheep.

Past research interests

During my undergraduate, I researched whether the time of day of immunisation affected immunogenicity and efficacy in rodent malaria models. I also took part in a project investigating the function of a candidate Drosophila antiviral immune gene using a natural Drosophila DNA virus and contributed to a project building a database of all known human-infective RNA viruses. For my MScR, I studied the infection dynamics of the parasite Schistosoma mansoni in Uganda. Specifically, I used Bayesian latent class analysis methods to combine multiple imperfect diagnostics to estimate the proportions of 'true' S. mansoni infections pre/post-praziquantel treatment. I then used genetic sibship analysis to determine whether post-treatment infections were caused by adult worms that survived praziquantel or were new infections from the environment.

Conference details

British Society for Parasitology (2026) - 3 minute talk and poster presentation (received best talk award)

BioInference (2026) - talk (received best talk award)

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