Ct values can be used to estimate epidemic dynamics UPDATE! Ct values are expected to change depending on whether the epidemic is growing or declining, and we harness this to estimate the epidemic trajectory. Lots of cool new analyses and methods!

Highlights:
- Cts from symptom-based surveillance change over time, but the effect is weaker
- Methods to infer incidence using single cross-sections of Cts
- Unbiased by changing testing coverage
- Gaussian process (wiggly line) model for incidence tracking using Ct values
2/12
This work is *JOINTLY led* with @LeekShaffer and PI’d by @michaelmina_lab. Thank you also to the ever insightful @mlipsitch and to coauthors @SanjatKanjilal @gabriel_stacey and @nialljlennon. 3/12
Premise: times since infection depend on the epidemic trajectory. Distributions of randomly sampled viral loads proxy times since infection. With calibration, Ct values can estimate growth rate. We focus on qPCR in SARS-CoV-2, but the principle applies to any outbreak. 4/12
Result 1: viral loads are shifted higher (Cts lower) during epidemic growth and lower (Cts higher) during decline when individuals are sampled *based on the onset of symptoms*. We simulated linelist data under symptom-based surveillance and looked at TSI and Cts over time. 5/12
This is crucial when considering virulence in emerging SARS-CoV-2 variants. Lower Cts over time do not *necessarily* mean newly dominant variants have higher virulence. If incidence of a new variant is increasing, then we expect to see more recent infections and lower Cts. 6/12
**However, the effect is smaller than under random surveillance, so I would not rule out the possibility of increased virulence.** But important to consider. Thank you to @charliewhittak for chatting through this! 7/12
Result 2: we reconstructed the epidemic curve using single-cross sectional samples from well-observed nursing homes, finding that single cross sections using the full Ct distribution provided similar insights to point prevalence across three sample times. 8/12
Result 3: we compared Ct-based to case-count based methods when testing is changing. Rt estimates are biased when testing is increasing or decreasing (not a problem with the method, just the data!). Our method uses the Ct distribution so does not care about test numbers. 9/12
Result 4: we use multiple cross-sectional samples to reconstruct incidence without making assumptions about the trajectory shape (a Gaussian “wiggly” process model). We can track the incidence curve in MA using routinely collected hospital tests. 10/12
… and here is a gif that reminds me of a nematode worm. Every week we add on a new cross section of Cts and accurately track true incidence (in simulation, red line). 11/12
Conclusion: we are generating loads of (semi) quantitative data in the form of Cts. We can harness these to get unbiased estimates of the epidemic trajectory. Hopefully these ideas will help public health surveillance efforts and interpret data in the light of new variants. 12/12

More from Science

An interesting thing about carp is that they can go into anoxic hibernation and switch to an anaerobic metabolism based on converting glycogen to ethanol.

The waste ethanol is diffused out the gills

https://t.co/V3D1umHf04

Carp can switch over to an anaerobic metabolism and quietly exhale booze until the situation gets better.

They basically evolved the same metabolic pathway as yeast, independently.

In theory, if you spent a few thousand years breeding carp for it, you could use them to make booze.

They'd be enormous, almost entirely glycogen deposits with a fish added as an afterthought.

The really interesting thing about anaerobic carp, is that they can go 4-5 months without oxygen by relying on liver glycogen.

You, a human, have only about 100 grams of glycogen in your liver, about 400 more grams in your skeletal muscles. Call it 500 grams total.

In humans, glycogen is also burned for energy. This is where the marathon runner's bonk comes from: you only have about 2,000 calories worth, and running a marathon burns those 2,000 calories.
Hard agree. And if this is useful, let me share something that often gets omitted (not by @kakape).

Variants always emerge, & are not good or bad, but expected. The challenge is figuring out which variants are bad, and that can't be done with sequence alone.


You can't just look at a sequence and say, "Aha! A mutation in spike. This must be more transmissible or can evade antibody neutralization." Sure, we can use computational models to try and predict the functional consequence of a given mutation, but models are often wrong.

The virus acquires mutations randomly every time it replicates. Many mutations don't change the virus at all. Others may change it in a way that have no consequences for human transmission or disease. But you can't tell just looking at sequence alone.

In order to determine the functional impact of a mutation, you need to actually do experiments. You can look at some effects in cell culture, but to address questions relating to transmission or disease, you have to use animal models.

The reason people were concerned initially about B.1.1.7 is because of epidemiological evidence showing that it rapidly became dominant in one area. More rapidly that could be explained unless it had some kind of advantage that allowed it to outcompete other circulating variants.

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और उन्होनें ब्रह्मविद्या का ज्ञान अश्विनि कुमारों को दे दिया। गुप्तचरों के माध्यम से जब खबर इन्द्रदेव तक पहुंची तो वे क्रोध में खड़ग ले कर गए और महर्षि दधीचि का सर धड़ से अलग कर दिया।मगर अश्विनी कुमार भी कहां चुप बैठने वाले थे।उन्होने तुरंत एक अश्व का सिर महर्षि के धड़ पे...


...प्रत्यारोपित कर उन्हें जीवित रख लिया।उस दिन के पश्चात महर्षि दधीचि अश्वशिरा भी कहलाए जाने लगे।अब आगे सुनिये की किस प्रकार महर्षि दधीचि का सर काटने वाले इन्द्र कैसे अपनी रक्षा हेतु उनके आगे गिड़गिड़ाए ।

एक बार देवराज इन्द्र अपनी सभा में बैठे थे, तो उन्हे खुद पर अभिमान हो आया।


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अभिमान के कारण ऋषि बृहस्पति के पधारने पर न तो इन्द्र ही खड़े हुए और न ही अन्य देवों को खड़े होने दिया।देवगुरु बृहस्पति इन्द्र का ये कठोर दुर्व्यवहार देख कर चुप चाप वहां से लौट गए।कुछ देर पश्चात जब देवराज का मद उतरा तो उन्हे अपनी गलती का एहसास हुआ।