EXPLORING 23 YEARS DATA OF RAINFALL AND MALARIA POSITIVE FRACTION IN AREAS UNDER KILIFI HEALTH AND DEMOGRAPHIC SURVEILLANCE SYSTEM

Abstract

Malaria has been identified as the disease most likely to be affected by climatic changes. Identifying climatic factor that influence the incidence of malaria by modifying the abundance of mosquito populations or the length of the extrinsic parasite cycle in the mosquito, and the emergence of epidemics in areas of low endemicity is an important step in controlling episodes of malaria during periods of intense transmission. This study therefore, focused on one climatic factor, rainfall. The study was conducted in Kilifi County. It aimed at exploring the patterns of monthly rainfall and the monthly proportion of children who were positive for malaria parasites in areas under Kilifi Health and Demographic Surveillance System (KHDSS) for the past 23 years. Analysis of the data was done in R version 3.4.1. Spearman Rank correlation was used to test for association while Auto Regressive Integrated Moving Average model (ARIMA model) was used for forecasting. This study presented a similarity in rainfall patterns in both the South and North regions of Kilifi County. Spearman rank correlation analysis between rainfall and Malaria Positive Fraction (MPF) at one, two, three and four months lagged period was conducted and it was observed that all the lags gave a positive correlation. Even though, there was a weak relationship between contemporaneous rainfall and Malaria Positive Fraction (MPF), at two months lag i.e. comparing rainfall 2 months before the MPF, there was a stronger correlation of rainfall preceding malaria in both the Southern and Northern region of the county with the Southern region having p-value= 0.1x10-5 and r2= 0.08 while the Northern region had a pvalue= 0.0x10-5 and r2= 0.10. ARIMA model proved to be effective in predicting future values. Rainfall is still a threat which is likely to affect spatial and temporal distribution of malaria even if declining figures of malaria is being recorded at the Coastal region. A 2 months’ time lag between rainfall and malaria is enough for Anopheline mosquitoes to complete their life xii cycle. This information could form an insight basic foundation for policy formulation to lay down in advance appropriate measures for the control of malaria during periods of intense transmission. Keywords: Malaria Positive Fraction (MPF), Rainfall, Kilifi Health and Demographic Surveillance System (KHDSS), Correlation, Forecast.