Modelled habitat suitability of a malaria causing vector (Anopheles arabiensis) relates well with human malaria incidences in Zimbabwe

Abstract

Accurate modelling of the geographic distribution of disease vectors is an important step towards developing strategies for effective control of vector borne diseases. In this study, we used maximum entropy (Maxent) to develop a spatially explicit model to predict the habitat of a malaria causing vector, Anopheles arabiensis, based on key environmental factors. Our results show that altitude combined with isothermality, temperature seasonality, annual precipitation and precipitation of the wettest month can be used to successfully model habitat suitability of A. arabiensis. Based on these five key factors, our results show that areas that are highly suitable for A. arabiensis are generally in the north, northeast, south and south eastern parts of Zimbabwe. In fact, our results show that all the five factors had AUC values ≥70% which is classified as good for predictive purposes. The results of our Maxent model overall show AUC values of 0.84 for training and 0.88 for test data. In addition, our results also show that the habitat suitability model positively correlated (p < 0.05) with malaria incidences recorded at health facilities for the period 1974–1981 and the years 1996, 1997, 1998 and 1999 although the correlations are weak. Our results suggest that A. arabiensis habitat suitability can be used as an indicator of malaria incidences.