Our story started in 2016 by following local and travel case reports wanting to know when the Zika epidemic would be over.
We found this interesting spike in travel-related Zika cases from the Caribbean in 2017, when local cases were waning 🧐
🔎👩💻Looking more closely, we found that most of these 2017 Zika infected travelers were coming from Cuba… but Cuba didn’t report any local cases (at least not to the international community)
A missing outbreak?!
Now it was time to investigate 🕵️♂️👩💻👨🔬.
We found that the epi curves from local incidence rates matched travel incidence rates (travel cases/total travelers) from other locations, giving us confidence that the travel cases from Cuba were indeed from a missing local Zika outbreak
We then constructed a model 📈 to estimate that 1,000-20,000 Zika cases should have been reported in Cuba from 2016-2017 (187 Zika cases were reported in 2016 & none were reported in 2017).
Our estimates would put this on par with reported Zika outbreaks in the Caribbean 🏝️
@TAlexPerkins@RJOidtman So we detected an unreported Zika outbreak in Cuba, but the second part of this mystery is why did it occur in 2017 instead of 2016, when Zika outbreaks were peaking throughout the Americas 🌎?
And should we have expected this delay? 🤔
@TAlexPerkins@RJOidtman Based on our ✈️ travel surveillance, the #chikungunya outbreak in Cuba (which also was not reported) coincided with the rest of the Caribbean.
So no, outbreaks in Cuba are not somehow just universally disconnected from the rest of the Caribbean/Americas 🌎.
@TAlexPerkins@RJOidtman Next we ask, was the Zika outbreak delayed due to low transmission in Cuba, or because ZIKV was established later?
Here’s where we turned to the sequencing data 🦠🧬, which shows ZIKV was established in Cuba one year after other locations.
Was it due to less ✈️ travel from places 🌎 with Zika outbreaks? No🚫
Was it due to unsuitable mosquito 🦟 conditions for outbreaks? No🚫
Was it due to mosquito 🦟☠️ control? Maybe❓
We’d like to say how awesome it was to work (again) with such a great team. Our collaboration with the Florida DOH -led by Andrea Morrison’s - has been especially great 👏
It's based on a design led by @Scalene & @pathogenomenick originally for Zika virus that was adapted for SARS-CoV-2 ("ARTIC protocol") and used by labs around the world.
Our goal was for this to be plug n' play with current SARS-CoV-2 protocols. (2/8) nature.com/articles/nprot…
The primers were designed using PrimalScheme using a pre-outbreak A.1 clade reference genome (GenBank accession: MT903345).
The scheme comprises a total of 163 primer pairs with an amplicon length ranging between 1597 and 2497 bp (average length of 1977 bp). (3/8)
Using a logistic regression of the daily frequencies, we predict that as of today (July-14), BA.5 is probably 80-90% in Connecticut.
BA.4 is still 📈 as it outcompetes BA.2, but will probably start to 📉 in frequency soon after BA.2 is gone. (2/8)
We created a new dashboard to report variant sequencing data in Connecticut. You can still access it through our main website by clicking on the "Read the latest Connecticut report" link. (3/8)
Omicron BA.2.12.1 is still 📈 in Connecticut as it is across most of the US. Fitting the % of sequenced cases to a logistic growth curve, we estimate that BA.2.12.1:
1⃣ is ~80% frequency today (May019)
2⃣ surpassed 50% in early May
3⃣ may reach 95% in early/mid June
(2/13)
From the same logistic growth curve, we also estimate that BA.2.12.1 is:
➡️ ~24% more transmissible than background (mostly other BA.2 lineages)
➡️ doubling in proportion every ~12 days
(3/13)
Based on our TaqPath PCR data (S-gene detected), we estimate that:
➡️ BA.2 is >50% in Southern Connecticut
➡️ At this rate - BA.2 will be 95% by early April
➡️ BA.2 doubling rate = 7.8 days (BA.1 in December = 3-4 days)
➡️ BA.2 ~43% more transmissible than BA.1/.1
(2/7)
Over the past 4 weeks, all of the sequenced S-gene positive samples have been Omicron BA.2 and not Delta. So we trust the 👆 PCR results reflecting the rise in BA.2. (3/7)
Here are comparative results between 10 TaqPath S-gene detected samples tested by YNHH and with our validated VOC PCR assay. Most with our assay were actually SGTF, and looking at the YNHH results, the S-gene CTs for those were 5-7 higher than N/ORF. (5/16)
We are looking into these low level spike amplification samples that should be SGTF to see if this is a lab/TaqPath assay artifact or if there is something about these BA.1 sequences. So far doesn't seem to be sequence-related. Will report (6/16)
Our initial SGTF case definition – ORF/N <30 CT, S “not detected” - was conservative to not over-call BA.1.
We updated it yesterday to include S-gene 5 CTs higher than ORF/N, and compared the results. (7/16)