Long-run relative importance of temperature as the main driver to malaria transmission in Limpopo Province, South Africa: a simple econometric approach

Ecohealth. 2015 Mar;12(1):131-43. doi: 10.1007/s10393-014-0992-1. Epub 2014 Dec 17.

Abstract

Malaria in Limpopo Province of South Africa is shifting and now observed in originally non-malaria districts, and it is unclear whether climate change drives this shift. This study examines the distribution of malaria at district level in the province, determines direction and strength of the linear relationship and causality between malaria with the meteorological variables (rainfall and temperature) and ascertains their short- and long-run variations. Spatio-temporal method, Correlation analysis and econometric methods are applied. Time series monthly meteorological data (1998-2007) were obtained from South Africa Weather Services, while clinical malaria data came from Malaria Control Centre in Tzaneen (Limpopo Province) and South African Department of Health. We find that malaria changes and pressures vary in different districts with a strong positive correlation between temperature with malaria, r = 0.5212, and a weak positive relationship for rainfall, r = 0.2810. Strong unidirectional causality runs from rainfall and temperature to malaria cases (and not vice versa): F (1, 117) = 3.89, ρ = 0.0232 and F (1, 117) = 20.08, P < 0.001 and between rainfall and temperature, a bi-directional causality exists: F (1, 117) = 19.80; F (1,117) = 17.14, P < 0.001, respectively, meaning that rainfall affects temperature and vice versa. Results show evidence of strong existence of a long-run relationship between climate variables and malaria, with temperature maintaining very high level of significance than rainfall. Temperature, therefore, is more important in influencing malaria transmission in Limpopo Province.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Climate
  • Humans
  • Malaria / epidemiology
  • Malaria / transmission*
  • Models, Econometric
  • Rain
  • South Africa / epidemiology
  • Spatio-Temporal Analysis
  • Temperature*