Fig 1.
Map of Australia and Torres Strait identifying the UCLs of focus.
Study locations are based on the Australian Bureau of Statistics UCL land definitions. The data used to create this figure has been sourced from the Bureau of Meteorology.
Table 1.
Equation variable descriptions with corresponding values/equations used.
Fig 2.
R0 estimations for best- and worst-case scenarios from 1995 to 2019 for the significant UCLs.
CHIKV R0 from 1995 to 2019 by averaging monthly estimations for each year for A) Brisbane, B) Cairns, C) Darwin, D) Rockhampton, E) Thursday Island and F) Townsville. Best- and worst-case scenarios were estimated using the limits of each variable from the R0 equation, where best-case correlates with least transmission and worst-case correlates with most transmission of CHIKV. Each scenario also has upper and lower standard deviation limits, with averages in bolder lines.
Fig 3.
Sensitivity analysis using correlation matrix of R0 variables.
Sensitivity analysis was performed by Partial Rank Correlation Coefficient using Monte Carlo methods and Latin Hypercube Sampling. Numeric and graphic displays of the correlation coefficient are displayed in the lower left-hand side segment and the upper right-hand side, respectively. The colour and direction of ellipse relates to the degree of correlation between parameters. The variables are displayed diagonally, where T is average temperature, v is human-to-vector transmission rate, w is vector-to-human transmission rate, M is mosquito population density, H is human population density, c is vector control efficiency, y is infectious period, t is extrinsic incubation period, u is vector mortality rate, b is vector biting rate, and R0 is the basic reproduction number.
Fig 4.
R0 forecast estimations for each significant UCL.
Forecasts of the best- and worst-case scenarios of R0 for A) Brisbane, B) Cairns, C) Darwin, D) Rockhampton, E) Thursday Island, and F) Townsville for 2020 to 2029. Forecasts are calculated using the R0 equation with bold lines representing the yearly average and dashed lines representing the monthly variation as standard deviation.