The effects of flooding and weather conditions on leptospirosis transmission in Thailand

Abstract

The epidemic of leptospirosis in humans occurs annually in Thailand. In this study, we have developed mathematical models to investigate transmission dynamics between humans, animals, and a contaminated environment. We compared different leptospire transmission models involving flooding and weather conditions, shedding and multiplication rate in a contaminated environment. We found that the model in which the transmission rate depends on both flooding and temperature, best-fits the reported human data on leptospirosis in Thailand. Our results indicate that flooding strongly contributes to disease transmission, where a high degree of flooding leads to a higher number of infected individuals. Sensitivity analysis showed that the transmission rate of leptospires from a contaminated environment was the most important parameter for the total number of human cases. Our results suggest that public education should target people who work in contaminated environments to prevent Leptospira infections.

Figure 1

Dynamics of leptospirosis spread between humans, livestock, and the contaminated environment. The dashed green arrows show the transmission route from the contaminated environment to susceptible livestock ($S_a$) and human ($S_h$) with a transmission rate of the contaminated environment to human (${\beta }_{\mathit{hL}}$) and to livestock (${\beta }_{\mathit{aL}}$). Infected livestock ($I_a$) transmit leptospires to humans with a transmission rate of infected livestock to human (${\beta }_{\mathit{ha}}$) and this turns a susceptible human into an infected human ($I_h$). The infected livestock shed leptospires to the environment with a certain shedding rate ($\omega$), shown by the red dashed line. Infected livestock ($I_a$) can also transmit leptospires to other livestock with a transmission rate (${\beta }_{\mathit{aa}}$) (orange dashed line). Infected humans and animals that recover from the infections become recovered human ($R_h$) and recovered livestock ($R_a$).

Figure 2

The map of reported cases in Thailand. The annual reported cases during 2010–2016 (A). The total reported cases during 2010–2016 (B).

Figure 3

Bar chart of negative log-likelihood values for the ten models compared to a null model (M0). The parenthesis on each bar shows the time lag in weeks for flooding or rainfall and temperature (t₁, t₂).

Figure 4

(A) The average number of cases obtained from the stochastic modelling of the M1-FT model (red line) compared to the reported cases of leptospirosis (black dots) for 2010–2015. The orange shaded area displays 1000 curves from the stochastic simulations. The red dashed line represents the predicted cases for 2016. The time-dependent transmission rate from the contaminated environment to susceptible human and susceptible livestock (${\beta }_{\mathit{hL}}$ and ${\beta }_{\mathit{aL}}$) are shown in (B,C), respectively.

Figure 5

The estimated time-dependent reproduction number (solid line) with the 95% confidence interval (shaded red region).

Figure 6

The partial rank correlation coefficients (PRCCs) of the parameters summarised in Table S1. The $h_i$ and $a_i$ are constant values of the transmission rates ${\beta }_{\mathit{hL}}$ and ${\beta }_{\mathit{aL}}$, respectively. The error bars show the 95% confidence intervals.

Figure 7

The heat map showing the number of human cases when the transmission rate from the contaminated environment to human (${\beta }_{\mathit{hL}}$) in the M1-FT model is reduced.