The impact of climate variability on dengue fever risk in central java, Indonesia

Abstract

Background: Dengue fever is a growing concern for public health under future climate variability. This study aims to investigate the dengue fever from 35 cities/counties linked with historical observation and anomaly of weather variables from 4 weather stations in Indonesia. Method: We collected monthly surveillance data of dengue fever in central java, temperature and precipitation from Tegal, Semarang, Tunggul wulung and Sleman weather stations, and flood event from 2009 to 2019. The distributed non-linear model was adopted to evaluate the effect of extremes weather variables and anomalies on the dengue risks. The extreme thresholds were defined at 5th and 99th percentile. Random-effects meta-analysis was applied to estimate weather station-specific pooled relative risk (RR) and 95% confidence intervals (CI) for the studied areas. Result: Dengue prevalence rates were higher in the rainy season (Nov–March) compared to dry season (Apr–Oct). Extreme high temperature was positively associated with dengue fever in Semarang with RR of 4.92 (95 % CI: 1.01, 24.0). Extreme low precipitation was positively associated with dengue fever in Tegal with RR of 9.60 (95 % CI: 2.65, 34.6). The risk of dengue fever in western part of Central Java, especially in the Tunggul wulung, was positively associated with extreme high anomaly of precipitation [RR = 4.05 (95 % CI: 1.86, 13.7). Meanwhile, extreme low anomaly of precipitation was positively associated with the risk of dengue fever with RR of 2.75 (95 % CI: 1.75, 4.32) in Semarang. Conclusion: These findings highlight the importance of considering weather variability in addressing the risks associated with dengue fever in Central Java, Indonesia.

Keywords

• Dengue fever
• Distributed lag non-linear models