A consequence of not knowing the seasonality behind COVID-19 is that some activities are inherently safer. Positivity peaks around midday and SARS-Cov2 follows patterns of solar activity, mainly UVB.
Other examples of its seasonality are winter and summer as well as the min and max points within the solar cycle. Finding other similar points could help to understand its transmission.
Grouping cases and environmental data by day of the week shows a linear correlation between changes in atmospheric ozone and cases.
This specific pattern as well as all the data hints that the bulk of the transmission happens in the daytime. And something similar happens at weekends.
Engaging in activities at low susceptibility conditions will lead to believe that everything is safe. But it was just less likely to happen.
SARS Cov 2 molecular mimicry
https://open.substack.com/pub/tavoglc/p/sars-cov-2-molecular-mimicry?r=1yafgh&utm_campaign=post&utm_medium=web
A lack of agreement between environmental variables could also drive the generation of new COVID-19 variants. Bursts in isolations are closely located near environmental disagreement at a specific geographic location. #COV1D #CovidIsNotOver
Similar anomalies can be found at present times in the case of the swine flu and COVID-19. #COVID #COV1D #CovidIsNotOver
Similar anomalies can be found at present times in the case of the swine flu and COVID-19. #COVID #COV1D #CovidIsNotOver
Adaptations to solar radiation can also be found inside the SARS Cov2 genome. The genome changes its size over time, reaching a minimum at a season with large sunshine duration and large UV radiation. #COV1D #covidisnotover #COVID
Looking at other cycles with different duration points towards the bubonic plague and other prominent outbreaks. #COV1D #covidisnotover #COVID
Regardless of the means used to make those predictions, there's a key metric that correlates with the emergence of large outbreaks. Stationary points in the Schwabe or solar cycle cluster many of the different large outbreaks. #COV1D #covidisnotover #COVID
https://www.sciencedirect.com/science/article/pii/S2319417023000033#bib15
Esta adaptación resulta de la eliminación de diversos fragmentos a lo largo del genoma del virus. #COVID19 3/4
El uso de redes neuronales ordena las secuencias en una serie de grupos según el día del año que fueron aisladas. Estos grupos podrían representar quasi especies virales que contienen las diferentes variantes que son aisladas a lo largo del año. #COVID19 2/4
El análisis de la frecuencia de fragmentos pequeños muestra que cambios en la frecuencia están relacionados con la aparición de nuevas variantes. Sin embargo al intentar combinaciones mas grandes el análisis se dificulta. #COVID19 1/4
Reducción de la dimensionalidad y clasificación de secuencias biológicas.
https://tavoglc.substack.com/p/reduccion-de-la-dimensionalidad-y
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