Household Structure Projection: A Monte-Carlo based Approach

The kernel of an agent based simulation system for spreading of infectious disease needs a so called household structure (HSD) of the area being simulated which contains a list of households with the age of each member in the household being recorded. Such a household structure is available in a Census that is usually released every 10 years. Previous researches have shown the changing of the household structure has a great impact on disease spreading patterns. It is observed that the changing of the household structure e.g., the average citizen ages and household size, is at a faster speed. However, serious infectious diseases, such as SARS (year 2002), H1N1 (year 2009) and COVID-19 (year 2019), occur with a higher frequency now than previous eras. For example, it would be bad to use HSD₂₀₁₀ built using Census 2010 to simulate COVID-19. In view of this situation, we need a better way to obtain a good household structure in between the Census years in order for an agent-based simulation system to be effective. Note that though a detailed Census is not available every year, aggregated information such as the number of households with a particular size, and the number of people of a particular age are usually available almost monthly. Given HSD_x, the household structure for year x, and the aggregated information from year y where y > x, we propose a Monte-Carlo based approach “patching” HSD_x to get an approximated HSD_y . To validate our algorithm, we pick x and y = x + 10 which both Censuses are available and find out the root-mean-square error (RMSE) between Census’s HSD_y and generated HSD_y is fairly small for x = 1990 and 2000. The spreading patterns obtained by our simulation system have good matches. We hence obtain HSD₂₀₂₀ to be used in your system for studying the spreading of COVID-19.