Introduction: India’s Third COVID Wave – When will the third wave peak?
India’s Third COVID Wave – When will the third wave peak? Predictive analysis about India’s third wave with open source data using mathematical models. Omicron variant is a super spreader and sheer numbers can overwhelm the healthcare infrastructure in India despite its less severe nature. The prediction is dark and scary.
Wash your hands.
Wear a mask.
Maintain social distancing.
Get vaccinated and get your booster shots now!
Numbers: India’s Third COVID Wave – When will the third wave peak?
Here are the numbers based on the predictive analysis –
-
Peak: Cases per day to reach between: 850,000 to 1,000,000
-
Cases to peak by: Jan 15th to Feb 10, 2022.
-
Peak to last: 20 – 30 days.
-
Hospitalization per day: 65,000 to 80,000
-
Cases will come down slowly and not as rapidly as they grow.
-
Hospitalizations will be 2 weeks behind cases.
-
Deaths will be 2 weeks behind hospitalizations.
-
A regression phase after the peak will last for 30-40 days.
-
India is in a race against time to get vaccinated and boosted.
-
Variants, raw material shortages are going to throw a wrench.
We need to discuss vaccinations, curtailment measures, which are critical to stem the spread of this variant of the COVID-19 virus. Vaccinations are not the be all and end all solution, COVID-19 is here to stay with us. You still need to practice social distancing, wear masks, wash hands regularly even after you are vaccinated and boosted. If you are eligible to take booster shots, please do so. This is going to be an endemic, this is a game of time, we need to be patient till the virus loses its potency to survive within the host. We need to be mentally prepared, this virus will stay on till 2025-2030 at the bare minimum before loosing its potency to harm humans and become like a common flu.
Also Read: India’s second wave – Predictive analysis
COVID-19 Vaccinations:
We need to have a global approach to vaccinations. We cannot think about vaccinations on a country by country basis. We need at least 30-45 different vaccinations that can fill the diverse void by covid variants. We as a human race need to plan for 32-40 Billion vaccination doses. Why? Well, variants and vaccine adjustments mean we would need multiple doses to out pace Covid.
Also Read: The role of AI in vaccine distribution.
The role of artificial intelligence in vaccine distribution will be very critical in vaccinating the global population against COVID-19. Vaccine distribution is one of the biggest logistical challenges humanity has faced so far and I think AI can be leveraged to help us with the equitable distribution of the vaccine.
The role of artificial intelligence in vaccine distribution involves the following challenges that AI can help with provided we have quality and accurate data.
Demand forecasting.
Distribution network.
Supply chain management.
Inoculation priorities.
Waste reduction.
Adverse event surveillance.
Vulnerability mapping
Accurately forecasting demand for the vaccine is particularly important for vaccine distribution and this exercise helps in the distribution network that these vaccines need to be on for an efficient rollout. We would like the right amount of doses of vaccines to reach the right population that critically needs it before than anyone else.
Also Read: How can Artificial Intelligence help with the Coronavirus (Covid-19) vaccine search?
Demand Forecasting
Demand forecasting can be done by identifying the right parameters for the set of the population that is most vulnerable, this means collating anonymous data of co-morbid conditions that impact the severity of the disease. Once we have this information we can equitably distribute the doses across the globe and save more lives. This will help the distribution be fair and most effective. Running AI-based algorithms to identify vulnerable patients and the critical mass of the patients is very important for effective vaccine distribution. The role of artificial intelligence in vaccine distribution cannot be understated, especially if we want the vaccine to be distributed in an effective and efficient manner. We could have been better prepared for vaccine distribution if we had better demand forecasting across the globe for vaccine distribution. We should start collecting anonymous data for future pandemics so we are better prepared.
Distribution network
Ensuring efficiency is even more important with any vaccines as demand will far exceed supply initially, making each dose precious. When vaccines are such an in-demand commodity it makes them both precious and expensive. Reducing wastage in these situations is very valuable.
Identifying storage facilities and setting them up in places based on demand forecasting in a phased manner will be a huge help for efficient distribution. This will help in reducing the wastage of precious doses.
Once a distribution network is up and running, keeping tabs on how it is functioning and tracking doses as they move through the supply chain is another area where A.I. will play a valuable role.
Supply Chain Management
The supply chain is an integral part of vaccine production, distribution, and administration. AI has the capability of providing autonomous supply operations. This is true, especially where decisions about the allocation of material and distribution of vaccines are being made, from existing pharmaceutical ingredient shortages to temperature management.
Inoculation Priorities
AI could be the engine that generates the vaccine index. This engine could use medical, socioeconomic, and experiential data from prior pandemics to make the care recommendations. One of these recommendations could be to determine inoculation priorities based on co-morbidity data (there could be a privacy concern here, but as long as the data is secure and encrypted).
This prioritization can help stop the spread of pandemic through vulnerable population within our communities and can also help in identifying key super spreaders based on how pandemic behaves within human species.
Waste Reduction
AI can help in controlling waste on the supply chain side, manufacturing side and in coordinating a distribution network that ensures each vaccine is only shipped to facilities that can properly handle it and are within reasonable proximity to the phased population groups.
Adverse Event Surveillance
Governments and drug manufacturers are now turning to Artificial Intelligence for help. AI systems can analyze the report data, identify patterns indicating the emergence of safety issues, and flag the issue. This way, experts can conduct further investigations and this will also reduce the trial time for any vaccine, the benefit of this is a thousand fold if we can reduce the time and improve the speed to market.
Vulnerability Mapping
In most countries, poverty data sets come from census and other household surveys usually held after ten years or more. But these data sets are not enough to paint a map of the vulnerable population within a country. Besides the poor, the vulnerable population includes the elderly, sick, unemployed, racial and ethnic minorities.
Countries need to look into experimental data sources to fill in the missing information about their vulnerable population. Experimental data can serve as a proxy where vulnerable members reside. It’s crucial to ensure that these people get help during any pandemic as soon as possible.
AI systems can factor in experimental data to update the Vulnerability Map to represent these populations.
AI systems can add another layer on the map for environmental and social determinants of health, including food insecurity, low-income jobs, and air pollution. An AI updated vulnerability map makes it easier to identify individuals who need to be prioritized for any pandemic spread and control.
Some technologists have lamented that the role of artificial intelligence in vaccine distribution hasn’t been a big help during the pandemic. While some A.I. software helped sound early warnings that a worrisome new respiratory virus seemed to be circulating in Wuhan, China, the technology certainly didn’t help prevent the pandemic. And its impact on epidemiological modeling and policymaking has been minimal. This is mostly because of a lack of an accurate and good data set. This should be a lesson for us and we should start building the data sets that can help us in future pandemics.
In helping to ensure that vaccines are distributed quickly and safely, the role of artificial intelligence in vaccine distribution may yet prove its worth.
Conclusion: India’s Third COVID Wave – When will the third wave peak?
India’s third COVID Wave is imminent and based on the population density and ease of spread of Omicron variant, this will be a very fast and radical spread. It will be next to impossible for us to curtail the spread of this variant, if we don’t practice some basic common sense rules, like – Social distancing, avoiding crowds as much as possible, washing hands, and getting vaccinated and boosted on time. It is important for India to monitor the R-nought value very carefully. India may need to take some tough decisions to be pro-active. Healthcare infrastructure may collapse just because of the sheer number of folks that may be infected and may need hospitalization because of complications from co-morbid conditions. I am fairly confident in the medical fraternity of India, we have always produced the best of doctors and scientists. Good luck to all the doctors, nurses, ward boys and hospital administrative staff. We stand with you!
Introduction: India’s Third COVID Wave – When will the third wave peak?
India’s Third COVID Wave – When will the third wave peak? Predictive analysis about India’s third wave with open source data using mathematical models. Omicron variant is a super spreader and sheer numbers can overwhelm the healthcare infrastructure in India despite its less severe nature. The prediction is dark and scary.
Wash your hands.
Wear a mask.
Maintain social distancing.
Get vaccinated and get your booster shots now!
Numbers: India’s Third COVID Wave – When will the third wave peak?
Here are the numbers based on the predictive analysis –
Peak: Cases per day to reach between: 850,000 to 1,000,000
Cases to peak by: Jan 15th to Feb 10, 2022.
Peak to last: 20 – 30 days.
Hospitalization per day: 65,000 to 80,000
Cases will come down slowly and not as rapidly as they grow.
Hospitalizations will be 2 weeks behind cases.
Deaths will be 2 weeks behind hospitalizations.
A regression phase after the peak will last for 30-40 days.
India is in a race against time to get vaccinated and boosted.
Variants, raw material shortages are going to throw a wrench.
We need to discuss vaccinations, curtailment measures, which are critical to stem the spread of this variant of the COVID-19 virus. Vaccinations are not the be all and end all solution, COVID-19 is here to stay with us. You still need to practice social distancing, wear masks, wash hands regularly even after you are vaccinated and boosted. If you are eligible to take booster shots, please do so. This is going to be an endemic, this is a game of time, we need to be patient till the virus loses its potency to survive within the host. We need to be mentally prepared, this virus will stay on till 2025-2030 at the bare minimum before loosing its potency to harm humans and become like a common flu.
Also Read: India’s second wave – Predictive analysis
COVID-19 Vaccinations:
We need to have a global approach to vaccinations. We cannot think about vaccinations on a country by country basis. We need at least 30-45 different vaccinations that can fill the diverse void by covid variants. We as a human race need to plan for 32-40 Billion vaccination doses. Why? Well, variants and vaccine adjustments mean we would need multiple doses to out pace Covid.
Also Read: The role of AI in vaccine distribution.
The role of artificial intelligence in vaccine distribution will be very critical in vaccinating the global population against COVID-19. Vaccine distribution is one of the biggest logistical challenges humanity has faced so far and I think AI can be leveraged to help us with the equitable distribution of the vaccine.
The role of artificial intelligence in vaccine distribution involves the following challenges that AI can help with provided we have quality and accurate data.
Accurately forecasting demand for the vaccine is particularly important for vaccine distribution and this exercise helps in the distribution network that these vaccines need to be on for an efficient rollout. We would like the right amount of doses of vaccines to reach the right population that critically needs it before than anyone else.
Also Read: How can Artificial Intelligence help with the Coronavirus (Covid-19) vaccine search?
Demand Forecasting
Demand forecasting can be done by identifying the right parameters for the set of the population that is most vulnerable, this means collating anonymous data of co-morbid conditions that impact the severity of the disease. Once we have this information we can equitably distribute the doses across the globe and save more lives. This will help the distribution be fair and most effective. Running AI-based algorithms to identify vulnerable patients and the critical mass of the patients is very important for effective vaccine distribution. The role of artificial intelligence in vaccine distribution cannot be understated, especially if we want the vaccine to be distributed in an effective and efficient manner. We could have been better prepared for vaccine distribution if we had better demand forecasting across the globe for vaccine distribution. We should start collecting anonymous data for future pandemics so we are better prepared.
Distribution network
Ensuring efficiency is even more important with any vaccines as demand will far exceed supply initially, making each dose precious. When vaccines are such an in-demand commodity it makes them both precious and expensive. Reducing wastage in these situations is very valuable.
Identifying storage facilities and setting them up in places based on demand forecasting in a phased manner will be a huge help for efficient distribution. This will help in reducing the wastage of precious doses.
Once a distribution network is up and running, keeping tabs on how it is functioning and tracking doses as they move through the supply chain is another area where A.I. will play a valuable role.
Supply Chain Management
The supply chain is an integral part of vaccine production, distribution, and administration. AI has the capability of providing autonomous supply operations. This is true, especially where decisions about the allocation of material and distribution of vaccines are being made, from existing pharmaceutical ingredient shortages to temperature management.
Inoculation Priorities
AI could be the engine that generates the vaccine index. This engine could use medical, socioeconomic, and experiential data from prior pandemics to make the care recommendations. One of these recommendations could be to determine inoculation priorities based on co-morbidity data (there could be a privacy concern here, but as long as the data is secure and encrypted).
This prioritization can help stop the spread of pandemic through vulnerable population within our communities and can also help in identifying key super spreaders based on how pandemic behaves within human species.
Waste Reduction
AI can help in controlling waste on the supply chain side, manufacturing side and in coordinating a distribution network that ensures each vaccine is only shipped to facilities that can properly handle it and are within reasonable proximity to the phased population groups.
Adverse Event Surveillance
Governments and drug manufacturers are now turning to Artificial Intelligence for help. AI systems can analyze the report data, identify patterns indicating the emergence of safety issues, and flag the issue. This way, experts can conduct further investigations and this will also reduce the trial time for any vaccine, the benefit of this is a thousand fold if we can reduce the time and improve the speed to market.
Vulnerability Mapping
In most countries, poverty data sets come from census and other household surveys usually held after ten years or more. But these data sets are not enough to paint a map of the vulnerable population within a country. Besides the poor, the vulnerable population includes the elderly, sick, unemployed, racial and ethnic minorities.
Countries need to look into experimental data sources to fill in the missing information about their vulnerable population. Experimental data can serve as a proxy where vulnerable members reside. It’s crucial to ensure that these people get help during any pandemic as soon as possible.
AI systems can factor in experimental data to update the Vulnerability Map to represent these populations.
AI systems can add another layer on the map for environmental and social determinants of health, including food insecurity, low-income jobs, and air pollution. An AI updated vulnerability map makes it easier to identify individuals who need to be prioritized for any pandemic spread and control.
Some technologists have lamented that the role of artificial intelligence in vaccine distribution hasn’t been a big help during the pandemic. While some A.I. software helped sound early warnings that a worrisome new respiratory virus seemed to be circulating in Wuhan, China, the technology certainly didn’t help prevent the pandemic. And its impact on epidemiological modeling and policymaking has been minimal. This is mostly because of a lack of an accurate and good data set. This should be a lesson for us and we should start building the data sets that can help us in future pandemics.
In helping to ensure that vaccines are distributed quickly and safely, the role of artificial intelligence in vaccine distribution may yet prove its worth.
Conclusion: India’s Third COVID Wave – When will the third wave peak?
India’s third COVID Wave is imminent and based on the population density and ease of spread of Omicron variant, this will be a very fast and radical spread. It will be next to impossible for us to curtail the spread of this variant, if we don’t practice some basic common sense rules, like – Social distancing, avoiding crowds as much as possible, washing hands, and getting vaccinated and boosted on time. It is important for India to monitor the R-nought value very carefully. India may need to take some tough decisions to be pro-active. Healthcare infrastructure may collapse just because of the sheer number of folks that may be infected and may need hospitalization because of complications from co-morbid conditions. I am fairly confident in the medical fraternity of India, we have always produced the best of doctors and scientists. Good luck to all the doctors, nurses, ward boys and hospital administrative staff. We stand with you!
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