Lagged Effects of Rainfall on Malaria: A Case Study of Meghalaya

In the relationship between malaria and meteorological factors, existing studies mainly focus on the interaction between different climatic factors, while interaction within one specific climatic predictor at different lag times has been largely neglected.

This paper aims to explore the interaction of lagged rainfalls and their impact on malaria incidence.

Monthly malaria cases and three climatic variables of 4 districts in Meghalaya from 2005 to 2017 were analyzed with the varying coefficient-distributed lag nonlinear model. The correlation patterns of the 2nd-, 3rd-, and 4th-month lags would vary over different rainfall levels at the 1st-month lag. During the period 2005-2017, a total of 309,133 malaria cases were reported in all the districts under study.

The monthly average rainfall ranges from a minimum of 181.79 mm in South Garo to a maximum of 367.87 in Jaintia. Furthermore, South Garo and East Khasi are the hottest and the coolest places under study with 26.96°C and 16.86°C, respectively. Rainfall levels in the 1st-month lag affect the nonlinear patterns between the incidence of malaria and rainfall at each lag time. The low rainfall level at the 1st-month lag may promote malaria incidence as rainfall increases. However, for the high rainfall level at the 1st-month lag, malaria incidence decreases as rainfall increases.

The interaction effect between lagged rainfalls on malaria incidence was observed in this study, and highlights its importance for future studies to better understand and predict malaria transmission.