The COVID-19 pandemic, which started in February 2020, caught many organisations unprepared. Tanzo Creative worked closely with a local public health team developed a COVID-19 forecasting model to inform the response of the health and care system. The model was developed very quickly using online modelling tools and delivered invaluable support during a period of intense need.
The COVID-19 pandemic created specific challenges in its early stages. There was little published information that could be relied upon, there were very few models to forecast the impact on the healthcare system, and there was a lot of misinformation when no information was available.
It was, therefore, very important to create a forecasting model that would show the impact on the health and care system very quickly. This model needed to be easy to understand yet capture sufficient complexity of the situation to be credible. Tanzo Creative worked with a local public health team to develop an online model using InsightMaker. This model was launched within 48 hours and updated over the next month to capture more detail.
The transmission of infectious diseases through a population can be forecast using existing Epidemiological models. One such model is the SEIR model which splits a homogeneous population into four groups- Susceptible, Exposed, Infected, Recovered. Members of the population move through these groups as they are exposed to the SARS-Cov-2 virus, become infected and recover. The rate at which people are exposed to the virus is proportional to the number of people who are already infected and the transmission properties of the virus. the rate at which people recover is determined by the disease characteristics and the healthcare system. Whilst the model is quite simple, for small geographical areas with a well-mixed population it is sufficient to capture the dynamics of the spread of the virus.
The model was calibrated using information published by public health epidemiological researchers in online journals based upon work done in China and the United Kingdom. It was further extended to include modelling by five-year age bands with a cross age band infection matrix to capture the dynamics of infections between different age groups.
In addition to modelling the spread of infections through the population, the model also included a module to forecast the requirement for hospital beds and other services. This provided additional information to the healthcare providers so that they could understand how COVID-19 would impact their services under a range of scenarios.
The model was implemented in InsightMaker, an online Systems Dynamics modelling tool. InsightMaker is openly available on the internet and is often used to teach Systems Dynamics modelling. InsightMaker was chosen because the model developed with it could be shared widely throughout the healthcare system without the need for licencing; and it provides a user interface which allows people to change model parameters and see the impact in real time.
The model had an immediate educational impact. For many working within the healthcare sector they had no experience of a wide-scale pandemic. It was difficult for them to conceptualise how the number of infections might evolve in response to government policy and what the impact on the healthcare system would be. The InsightMaker model, because his parameters could be changed quickly to show how things might evolve in different scenarios, provided clarity where none existed before. This helped consolidate senior managers understanding of the situation and help shape the development of the strategic response to the pandemic. As the pandemic progressed over the subsequent two years, development of the model continued. It proved highly valuable in informing operational decision making, particularly for the allocation of resources and staff.