Statistical modeling of the effect of rainfall flushing on dengue transmission in Singapore

Abstract

Background: Rainfall patterns are one of the main drivers of dengue transmission as mosquitoes require standing water to reproduce. However, excess rainfall can be disruptive to the Aedes reproductive cycle by "flushing out" aquatic stages from breeding sites. We developed models to predict the occurrence of such "flushing" events from rainfall data and to evaluate the effect of flushing on dengue outbreak risk in Singapore between 2000 and 2016.

Methods: We used machine learning and regression models to predict days with "flushing" in the dataset based on entomological and corresponding rainfall observations collected in Singapore. We used a distributed lag nonlinear logistic regression model to estimate the association between the number of flushing events per week and the risk of a dengue outbreak.

Results: Days with flushing were identified through the developed logistic regression model based on entomological data (test set accuracy = 92%). Predictions were based upon the aggregate number of thresholds indicating unusually rainy conditions over multiple weeks. We observed a statistically significant reduction in dengue outbreak risk one to six weeks after flushing events occurred. For weeks with five or more flushing events, compared with weeks with no flushing events, the risk of a dengue outbreak in the subsequent weeks was reduced by 16% to 70%.

Conclusions: We have developed a high accuracy predictive model associating temporal rainfall patterns with flushing conditions. Using predicted flushing events, we have demonstrated a statistically significant reduction in dengue outbreak risk following flushing, with the time lag well aligned with time of mosquito development from larvae and infection transmission. Vector control programs should consider the effects of hydrological conditions in endemic areas on dengue transmission.

Fig 1. Timeline of observed Ae. aegypti breeding sites in Geylang, Singapore, August 2014 –August 2015.

There were 107 days of entomological observations where 53 breeding sites, once identified as positive for Ae. aegypti breeding, were monitored for changes in hydrological conditions. Breeding sites where water exceeded the drainage threshold were classified as “Flushed”. For each day of observation, if at least one breeding site was observed as flushed, the day of observation was defined as flushed. If no breeding sites were observed as flushed then the day of observation was classified as not flushed. This figure, “Timeline of observed Ae. aegypti breeding sites in Geylang, Singapore, August 2014 –August 2015 is a derivative of “Timeline of the breeding drains of Aedes aegypti in Geylang, Singapore: August 2014 –August 2015” by Seidahmed and Eltahir [34], used under CC BY.

Fig 2. Results of PLUM model associating flushing with the number of high risk thresholds met for cumulative and daily rainfall variables.

There is a clearly defined threshold that almost perfectly separates flushed (blue) and non-flushed (orange) observations based upon the aggregate number of high risk thresholds that were met per day for both cumulative and daily rainfall variables. Each gray line represents Eq (1) fit to each leave-one-out cross validation sample while the blue line represents the mean fit from all of the leave-one-out cross validation samples.

Fig 3. The average prevalence of flushing events and dengue outbreak weeks by month, Singapore, 2000–2016.

In months where flushing event prevalence is highest (blue) dengue outbreak week prevalence (red) is lowest, and vice versa.

Fig 4. Association between number of flushing events per week and dengue outbreak occurrence over 20 lag weeks.

The risk of an outbreak occurring within one to six weeks after the week of consideration was significantly lower if five or more flushing events occurred during the considered week.