The weak public health system’s response to the pandemic in the United States helped ensure that the nation led the world in infections nearly from the beginning of the pandemic, and it has remained ever since. Initially, a slow federal government response in restricting overseas travel to the United States was the reason. This was followed by a confused personal protective equipment (PPE) and treatment supplies acquisition strategy, again at the federal level. This slowed the access of states to critical supplies of masks and other PPE and treatment supplies, such as ventilators.
With vaccines now becoming available, are we done and dusted with the problem. The speed at which the vaccines have been developed is a testimony to the technology advances, data, and Analytics, but at the same time kudos to Human determination. Several viable vaccines are being manufactured at scale in many places around the world simultaneously.
The challenges ahead
Distributing the vaccine is complicated, even in a country like the US with experienced transportation providers, infrastructure for determining how many vials should be packed and dispersed, efficient distributors and where and when the vials should be transported.
It is because there are several promising vaccines, each of them with two doses. Each will come in multiple vials that add to the complexity in distribution. It would be the most complex supply chain problems to be solved.
Data and Prediction models for COVID-19 Vaccination Planning
A good supply chain analytic system also considers into account any future transmission scenarios. A well-constructed statistical framework can be used for short-term forecasting, for example, by using machine learning and regression to crunch epidemiological data from the past and different places. Instead of focusing on forecasts based on a single set of assumptions, analytical models can adapt and use various data sources and statistical tools, from epidemiological data to data on human covid-19 cases, to predict future transmission scenarios. A framework exposed to various conditions – from the human transmission to human transmission of covid-19 to recover – mimics the way they spread and can use mechanistic models that can predict and simulate future transmission scenarios.
In total, the United states may require about 600 million doses. It is a big assumption based on near perfect planning and given that responsibility for the final allocation, planning and distribution will be split among state health departments, each of which has its own way of operating.
Vaccine Supply Chain Planning
Vaccine supply chain capability and integrity are dependent not only on manufacturing but also on the availability of components and ancillary resources (e.g., vials, syringes, alcohol swabs), cold-chain storage availability and distribution methodologies. The storage procedures must be employed to ensure maximum shelf-life capacity and minimize deterioration and waste of what will likely constrain the supply of vaccines.
The vaccination programme will be successful only with proper implementation, and it requires reliable planning capability to deliver it. In other words, life science must follow data science, and optimizing the use of advanced data and analytics capabilities is just as crucial as the syringes and needles used to administer vaccines.
HumaneBITS data, analytics, and AI services enable organizations to deliver value across the customers’ journey by empowering users with more agile and intuitive data science processes. Our CoE for Data and Analytics has been closely observing and studying various supply chain and distribution scenarios that can be solved using efficient data and statistical models.
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