Merry Christmas

The long journey of Christmas from reluctant celebration in 4th century AD to current cosmopolitan, kaleidoscopic, cultural extravaganza merits a brief historical look back. The early puritans confined celebrations of Jesus of Nazareth to Easter. Even the precise date of birth was apparently kept a mystery to preempt celebration of Jesus’s birth.

Christmas was first celebrated in 4th century AD and increasingly found an enlarging audience. By middle ages Pagan celebrations were comprehensibly substituted by Christmas. There were brief periods of puritanical cancel Christmas outbursts, both in England and USA. Those outburst had the longevity of ephemeral effervescence of yesterday’s bubbly.

The legend of Santa Claus goes back to 280 AD when a monk named St. Nicholas catered to needy, sick and children. His generosity has since been immortalized in the slightly modified name of Santa Clause. He still puts smiles on children’s faces.

In 1870, Christmas was declared a federal holiday in USA.

From proximity to Winter Solstice, birth of Jesus and advent of a new year, the politically correct connotation of Holiday Season, bundles an assortment of joys. For the faithful, reasons for gratitude maybe many. But joy seems to be universal, and that we can be grateful for.

As we anxiously step out of the smothering confines of the pandemic, prayers may seek answers in the attenuated virulence of Omicron. Let it be a vaccine for the world. Thats a miracle this Christmas may well be remembered for.

Meanwhile, from my house to yours, Merry Christmas!


Cohabitating with Covid

The chaos that marked the first two years of pandemic is finally settling in to a sharpening focus. The virus is no longer novel and vulnerability no longer universal. The degree of contagiousness and severity of virulence of continually mutating virus will keep us vigilant but wont push us in to a paralysis of locked doors.

We have learned much about the virus. We know how it spreads and deep cleaning is a resource wastefulness. From the peak in hospital mortality of twenty plus percent, improved care has favorably reduced the death rate to mid single digit. We know virus lethality favors elderly, obese and those with comorbidities. We are better able to triage our efforts to those at most risk. At risk patients can significantly lower risk through out patient monoclonal antibodies.

Vaccines and boosters remain the most effective preventative tools.

Unfortunately, virus also shed light on some of our flaws. We humans think differently. Cognitive bias can lock our brains in a hermetic seal. The fat based virtue of open mindedness that welcomes persuasiveness does not stand a chance.  Facts get distorted and reason gets reduced to derision. It is what it is.

The vaccine divide whether by personal choice or barriers of access is here to stay. Issues of access are being incrementally remedied. Naturally acquired immunity also makes a “natural” ally in the fight against the virus.

Pharma, mRNA based vaccines, compliance to mitigating measures etc by many give us rising hope.

Against this background, we have to choreograph a realtime readiness as new variants morph in to the next surge. Fortunately, here we are dealing with only two variables: hospitalization rate and numbers likely to be hospitalized. We don’t have a three body problem. We can work with this modeling.

If we take only hospitalization as a metric to calibrate mitigation measures, we look at a lagging indicator and predictably doom the healthcare as a large number of newly infected will faithfully stress supply chain as time lag catches up.

The projected hospitalization rate based upon prevalence of infection and severity will lend a workable calculation on hospital occupancy two weeks hence. Current occupancy is only relevant when blended with projected peak hospital occupancy. This integrated model can lessen uncertainty and rectify future demand supply disequilibrium. A calibrated approach that guides mitigation measures is our key to unburdened health care and open businesses.

Example: lets say healthcare need to be determined in a community of 1000,000. Lets say the new variant infects 10% over a period of couple weeks(an extreme scenario). If the variant causes hospitalization in 2% of the infected, then projected cumulative demand over next 2-4 weeks will equal 2000 beds.

These numbers are not static. New infections, adoption of mitigation measures, recoveries, existing hospitalizations, length of stay in hospital, ICU occupancy etc are many variables that can be predictably modeled.

On the other hand if downstream hospitalization rate is less than 0.5% then virus essentially becomes a vaccine. Putting emphasis only on number of infections in a community is an incomplete and practically useless metric.