Meteorological indicators as predictor of timing and duration of malaria transmission

Abstract

<title>Abstract</title> Satellite derived climate variables are potential indicators malaria transmission season. However, there is dearth of information required for investigating the relationship between climate and malariometric data. The influence of climatic risk variables on the temporal distribution of malaria in Epe and Ibeju Lekki (IbL) Local Government Areas (LGAs), Nigeria was assessed. Monthly malaria cases data of Epe and IbL LGAs, from January, 2018 to June, 2019 was obtained from Ministry of Health, Lagos. Monthly climate data including rainfall, maximum and minimum temperatures, and relative humidity of Lagos was obtained from the Nigerian Meteorological Agency (NIMET). Association between monthly malaria cases and climate parameters was analysed using principal component analysis. Malaria cases was highest (2157) in May, 2018 and lowest (874) in March, 2018 in Epe while IbL recorded the highest (2886) in May, 2019 and lowest (1435) in June. Monthly malaria cases variation was significant in Epe, P &lt; 0.05 and IbL, P &lt; 0.05. Monthly malaria cases inversely varied between Epe and IbL r = -0.16. Biplot axis one (F1) of the principal component plan was explained positively by rainfall (Eigen Vector, EV = 0.85) and relative humidity (EV = 0.81), related to positive malaria predictor in Epe (EV = 0.22) and IbL (EV = 0.09), while negative predictors were maximum temperature (EV = -0.91) and minimum temperature (-0.74). The positive relationship between malaria cases, and rainfall and relative humidity in both Epe and IbL is an indication of a geographic location independence of the impact of the meteorological indices on malaria heterogeneity.