12. This work was a collaboration with UiO, NMBU, SVA #adaptCWD #wilimanid. Huge thanks to Atle Mysterud for being the driving force of this project, and Stefan Widgren, Michael Tranulis, and my colleagues in the NVI epi-team Katharine Dean and Hildegunn Viljugrein. | 12/12

Our study shows that host genetics can completely change how a CWD epidemic unfolds. But to forecast future risks, we need solid data on host factors: how PRNP genotypes affect infection, duration, and shedding.| 11/12

The epidemic trajectories are sensitive to the mechanistic parameter assumptions. Varying them within reasonable ranges we get the similar shapes, but shifting prevalences and timings
| 10/12

We observe a temporally confined peak followed by fade out in Scenario 1, stabilizing high prevalence in Scenario 2, and slow peak followed by slow decline in Scenario 3. | 9/12

Averaged over simulations we see rapid selection and genotype frequencies substantially altered in all scenarios after 40 years across all scenarios. | 8/12

A cool result is that when PRNP affects on susceptibility only, the epidemic progresses through a peak followed by a rapid decline, but when less susceptible PRNP genotypes with a longer disease duration is included, the prevalence peaks and remains high. 7/12

We simulated for 80 yrs, starting with 1 infected adult male. Many runs die out stochastically—even if R₀ > 1 — e.g. when early cases die by natural mortality or is hunted before transmitting the disease. Outbreak probabilities differ substantially between scenarios. | 6/12

We simulated CWD dynamics under 4 PRNP mechanisms:
• No effect
• Susceptibility (S1).
• Susceptibility + shedding duration (S2).
• Susceptibility + duration + clinical shedding level (S3).
We based assumptions on literature on closely related species with similar PRNP alleles |
5/12

CWD susceptibility is tied to PRNP gene variation. But exactly how PRNP genotypes alter susceptibility, shedding duration & shedding level is still unknown. For a good overview of Cervidae PRNP variants see: doi.org/10.1186/s135...
| 4/12

We built a stochastic transmission model for CWD in SimInf, matching the reindeer demography, hunting, and dynamics at Hardangervidda – the only wild herd where contagious CWD is thought to be present in Europe | 3/12

CWD was first detected in Europe in reindeer in Norway (2016). One herd (~2,000) was culled, but CWD reappeared in the larger less confined population—2 confirmed cases, prevalence unclear. CWD is devastating and hard to control as seen by the spread to 36 US states & 4 Canadian provinces | 2/12

Our first WiLiMan project paper is out #wilimanid! 🎉 We modelled how host genetics might shape Chronic Wasting Disease (CWD) dynamics in wild reindeer (Rangifer tarandus). Read here: doi.org/10.1016/j.ec... (Photo: Olav Strand/NINA) | 1/12

Huge thanks to Kristian Alfsnes for steering the ship and great team effort with Vegard Eldholm and Dominique A. Caugant! 🎉 | 13/13

Using branch lengths, pathogen generation time, and molecular clock estimates, one can infer which branches are longer than expected, suggesting silent transmission or new incursions, and hence the relative contribution of local transmission versus incursions. But we didn’t cover this here. | 12/13

From the Norwegian Surveillance System for Communicable Diseases (MSIS; www.fhi.no/ut/msis/
), ~22% of people diagnosed in 2019 reported infection abroad, compared to ~18% in 2023. | 11/13

Alternatively, the Norwegian epidemic mirrors global clade diversity, so even travel-associated lineages weren’t very distinct from those already present and that’s why the major lineages looked largely unchanged. 10/13

Summing up: Before and after lockdown, the same major lineages remained in circulation, indicating persistent silent transmission. But ST-1580 shifted towards a higher fraction of female cases and then surged rapidly in frequency post-pandemic | 9/13

Here’s the “mother phylogeny” of Norwegian isolates spanning nearly a decade. Too many resistance patterns to unpack here, but AZM, CFM, and CIP phenotypes/mechanistic markers are shown in the columns. | 8/13

Zooming in using phylodynamics, ST-1580 comprises two BAPS groups: 7 and 1, which we estimate to have diverged far back in time. One of the clades is the female-associated (BAPS7), and the other is associated with men (BAPS1). The “female” clade is the one in explosive growth! | 7/13

MLST 1580 grew exponentially in the pandemic aftermath. This sequence type contains a higher fraction of females than the “typical gonorrhoeae lineage” in Norway. This points to a shift in the demography of the group making up most ST-1580 cases. | 6/13

Surprisingly, the major lineages remained before and after the lockdown period in Norway. The “other” group, encapsulating new genetic diversity - e.g travel-associated lineages - did not grow substantially. | 5/13

We used Bayesian Analysis of Population Structure (BAPS) to delineate lineages and followed these to determine if specific lineages changed dramatically in frequency before and after the pandemic.
| 4/13

From ~1,704 cases in Norway in 2019, the incidence fell to ~555 in 2021 under lockdown. But by 2023, it skyrocketed to 2,985. One of our major questions was which lineages fueled this dramatic resurgence? | 3/13

Neisseria gonorrhoeae is a human obligate pathogen - its only reservoir is humans. Unbroken transmission chains are therefore required to keep the pathogen alive. So what happens when you significantly decrease social contact through social distancing? | 2/13

Genome analysis of Neisseria gonorrhoeae in Norway, 2016–2023, reveals shifting epidemiology in the wake of the COVID-19 pandemic The incidence of gonorrhoea has increased significantly in Norway over the past 10 years. The emergence of antimicrobial resistance and potential for increased rates of future treatment failure make e...

What happens to a sexually transmitted pathogen during a pandemic with social distancing measures?! We have a new paper out from the genome epidemiology team at NIPH! Led by Kristian Alfsnes. Read here: 👾https://doi.org/10.1099/mgen.0.001479 | 1/13

CDC’s top laboratory on sexually transmitted diseases is shut by Trump administration The Trump administration fired everyone in a CDC lab that is crucial to tracking drug-resistant gonorrhea and other sexually transmitted diseases. "We are blind," an expert says.

If lost there's no going back: "...the lab holds the world’s largest repository of gonorrhea isolates — over 50,000, dating back to 1988 when the CDC began to collect them."

www.statnews.com/2025/04/05/c...

Perspective from @kgandersen.bsky.social, Purushotham, Lutz, & @edythparker.bsky.social "Immunological drivers of zoonotic virus emergence, evolution, and endemicity." authors.elsevier.com/a/1ks2e3qNrU...

Postdoc Opportunity

Got a PhD in disease evolution, or something similarly hardcore? Know your way around phylodynamics? Good. We need you.

If you’re up for real-world research getting hands-on with fieldwork, sequencing, and making sense of viral evolution, apply here: jobs.inrae.fr/en/ot-25456.

JUNIPER: Reconstructing Transmission Events from Next-Generation Sequencing Data at Scale Transmission reconstruction--the inference of who infects whom in disease outbreaks--offers critical insights into how pathogens spread and provides opportunities for targeted control measures. We dev...

We present JUNIPER, our outbreak reconstruction tool that incorporates within-host variants, models missing data, and scales to large, sparsely sampled datasets to achieve state-of-the-art performance. Led by @ivan_specht et al. @sabeti_lab. www.medrxiv.org/content/10.1... 1/12 🧵

Also a cool analysis on the host state along the branch representing the jump from birds to cattle for the D.1.1 clade. Sampling wild birds near detected outbreaks could have broken up that long ancestral branch of D1.1 and given more insight into this host jump and the potential adaptive phase