############################################################################################ ### Mosquito Survival, giving all mosquitoes the same survival because of a lack of data ### ############################################################################################ ## Create a matrix of all mosquitoes for which we have any competence data mosq_comp_sp <- unique(h_to_m_emp$species) mosq_surv_for_R0 <- matrix(nrow = mosq_days_max, ncol = length(mosq_comp_sp), data = 0) dimnames(mosq_surv_for_R0) <- list( seq(1, mosq_days_max, by = 1) , mosq_comp_sp ) ## Exponential rates survival model based on daily survival probability for (i in 1:ncol(mosq_surv_for_R0)) { mosq_surv_for_R0[, i] <- exp(-mosq_daily_surv) ^ seq(1, nrow(mosq_surv_for_R0), by = 1) } ## Could inject uncertainty in survival, but since we have no species-variability in survival ## this would not serve to change any relative importance so seems to be a bit unnecessary for now ## so just repeat the predicted mean for all matrix n_samps to align with other models with uncertainty mosq_surv_for_R0_all_samps <- array(dim = c(nrow(mosq_surv_for_R0), ncol(mosq_surv_for_R0), n_samps), data = c(mosq_surv_for_R0)) dimnames(mosq_surv_for_R0_all_samps)[[2]] <- as.character(unique(h_to_m_emp$species)) mosq_surv_for_R0_all_samps.gg <- melt(mosq_surv_for_R0_all_samps) names(mosq_surv_for_R0_all_samps.gg) <- c("day", "mosq", "samp", "proportion") mosq_surv_for_R0_all_samps.gg <- mosq_surv_for_R0_all_samps.gg %>% group_by(day, mosq) %>% summarize( est = mean(proportion) ) mosq_surv_for_R0_all_samps.gg.s <- mosq_surv_for_R0_all_samps.gg %>% filter(mosq == "cx_annulirostris") %>% mutate(mosq = mapvalues(mosq, from = "cx_annulirostris", to = "Cx annnulirostris")) ggplot(mosq_surv_for_R0_all_samps.gg.s, aes(day, est)) + geom_line() + xlab("Day") + ylab("Proportion Surviving") + ggtitle("Culex annulirostris survival at half max of optimal laboratory conditions from Shocket et al. 2018 Elife") ## for the conceptual figure ggplot(mosq_surv_for_R0_all_samps.gg.s, aes(day, est)) + geom_line(lwd = 1) + xlab("Day") + ylab("Proportion Surviving")