Figure 2. Eco-epidemiological factors and model fit to notified cases.

(A) Zika case data (black) and daily climatic series for rainfall (gold), humidity (blue) and mean temperature (green) for Feira de Santana (FSA). Climate data available as Dataset 1. (B) Resulting Bayesian MCMC fit to weekly (black line: data, purple line: model fit) and cumulative incidence (black line: data, grey line: model fit). (A,B) The grey areas highlight the period before the Zika outbreak, the white areas highlight the period for which notified case data was available, and the yellow shaded areas highlight the period for which mean climatic data was used (see Materials and Methods). (C) Climatic series as in A and estimated $R_0$ for the period of the outbreak (2015–2017) ($R_0$ absolute values in Figure 2—figure supplement 3). (D) Correlations between the estimated $R_0$ and climatic variables (intercepts: 0.839 for humidity, 0.067 for rainfall and 0.658 for temperature). (E) Correlations between the case counts and climatic variables (intercepts: 0.487 for humidity, 0.024 for rainfall and 0.862 for temperature). (D,E) Points presented are from timepoints (weeks) for which incidence was notified. (A–E) Y-axis normalised between 0 and 1 for visualisation purposes.

Figure 2—figure supplement 1. Relationship between temperature and egg hatching success.

Empirical data on Aedes aegypti’s and albopictus’s egg hatching success (in the model $\dot{c}$) is taken from (Dickerson, 2007). Data includes measurements of hatching for 5 different temperatures above 15 Celsius, including 2 wild and 1 laboratory populations for each of the vector-species. Fitting implemented with a third degree polynomial. When modelling, negative proportions below 10 Celsius are manually corrected to zero (left of shaded grey line).

Figure 2—figure supplement 2. Prior selection and sensitivity.

(A1) Priors for the linear coefficients $\alpha$ (scaling factor for effect of temperature on mosquito incubation period - EIP) and $\eta$ (scaling factor for effect of temperature on mosquito mortality - life-span). Priors follow Gaussian distributions: $\alpha$ with $mean=2.0$ and $SD=0.33$ (standard deviation); $\eta$ with $mean=3.0$ and $SD=0.33$. Means and SDs are chosen to obtain biologically relevant ranges on the parameters being scaled (see subplots A2-A3). (A2) With prior set for each coefficient ($\eta ,\alpha$) as in A1, temperature values of one year from Feira de Santana are used to demonstrate expected variation in the scaled parameters in time. Lines represent the expected mean per day. (A3) Distributions of life-span and EIP for the time period presented in A2. (A1–A3) The selected priors derive into life-span and EIP ranges that are biologically relevant for Aedes mosquitoes, namely that on average the EIP is assumed to be $\approx 7$ days and the life-span just below 2 weeks (Trpis et al., 1995; Trpis and Hausermann, 1986; Andraud et al., 2012; Hugo et al., 2014 and Table 3). It should be noted that the priors have been set to be above 1, as we assume that the effects of climate are stronger outside the ideal laboratory conditions for which mathematical relationships have been formulated (see description of the model). (B) Priors for the human incubation and infectious period. Means and SDs based on previous estimations (Ferguson et al., 2016). (A1–A3, B) Distributions are drawn using 20,000 samples. Representative samples of 500 MCMC chain states are available in Supplementary files 1–6.

Figure 2—figure supplement 3. Eco-epidemiological factors and model fit to notified cases.

(A) Daily climatic series for rainfall (black), humidity (orange) and mean temperature (purple) for Feira de Santana (FSA). (B) Estimated vector lifespan (green), extrinsic incubation period (EIP, blue) and basic reproduction number ($R_0$, red). Median values are represented by horizontal dashed lines, with around 9 days for the mosquito lifespan, 5 days for the EIP and 2.5 for $R_0$. (C) Resulting Bayesian MCMC fit to weekly (black line: data, blue line: model fit) and cumulative incidence (black line: data, green line: model fit). The grey areas highlight the period before the Zika outbreak, the white areas highlight the period for which Zika virus (ZIKV) notified case data was available, and the yellow shaded areas highlight the period for which mean climatic data was used.