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

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, q = 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.EU project QWeCI (Quantifying Weather and Climate Impacts on health in developing countries; funded by the European Commission’s Seventh Framework Research Programme under the Grant agreement 243964).http://link.springer.com/journal/103932016-03-31hb201

Exploring the influence of climate change and capital assets on livelihood formations in central region of Uganda

Current research provides less understanding of how climate change affects the livelihood process at a household level. This study explores household’s perceptions of climate change and its implications on livelihood formation process using empirical data from Uganda. Climatic data, household surveys and key-informant interviews from Wakiso and Gomba districts served as data sources for the study analysis. Majority of the respondents observed climate changes in the last 10–20 years and perceived them to have affected their capital assets in the process of forming livelihoods. As a result, households’ livelihoods have diversified and are pursuing livelihood strategies for sustenance. The study underlines the need to access credit conditioned to climate change resilience, access to improved varieties of crops, availing extension services and targeted resources allocations. Incorporating climate change into the planning process at a local level and associated local institutions in order to improve livelihood formation processes of households is recommended.UNISA postdoctoral fellowshiphttps://www.springer.com/journal/106682022-01-19hj2021Geography, Geoinformatics and Meteorolog

Impact of climate on health : a specific focus on Malaria in South Africa's Limpopo Province

Climate change is the defining crisis of our moment and a critical concern for the global economy. One of the big concerns of climate change is its potential impact on health and the health sector in general through the increase in climate-sensitive diseases such as Malaria. The presence of mosquitoes that transmit malaria is influenced by climatic factors: temperature, precipitation, and humidity. Areas in South Africa with optimum conditions for malaria are KwaZulu-Natal, Limpopo, and Mpumalanga Provinces. Limpopo Province (approximately 22 25ºS, 27 32ºE) is South Africa s northernmost province that shares its international borders with Botswana, Zimbabwe, and Mozambique. Socio-economic factors and other environmental factors also affect the spread of malaria. In the Limpopo Province of South Africa malaria is shifting and is now observed in originally non-malaria districts. It is unclear, however, whether climate drives this shift, and if it does, which of the two main climate drivers rainfall or temperature are responsible. It is also important to understand which of the two is more significant, when does the malaria season begin, how long does the malaria season last, and what are the policy implications in terms of the timings of malaria interventions for Limpopo Province? This study attempts to answer these questions. In so doing, it examines the distribution of malaria at district level in the Limpopo Province, determines the direction and strength of the linear relationship and causality between malaria and the meteorological variables (rainfall and temperature), and ascertains their short and long run variations. It identifies the beginning of the malaria season, as well as its duration, and suggests policy directions for the timing of malaria intervention programmes. The spatio-temporal method, correlation analysis, and econometric methods (Auto-Regressive Distributed Lag (ARDL) model, Multiple Regression Analysis and Impulse Response Function (IRF) in a Vector Moving Average (VMA)) are applied. Time series monthly meteorological data (1998 2007) are obtained from South Africa Weather Services (SAWS) and clinical malaria data came from the Malaria Control Centre in Tzaneen (Limpopo Province) and the South African Department of Health. Global data ERA-Interim, TRMM and TRMMv7 are obtained from the European Centre for Medium-Range Weather Forecasts (ECMWF). The study found that malaria changes and pressures vary in different districts with a strong positive correlation between temperature and 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 (but not vice versa): F (1, 117) = 3.89, q = 0.0232 and F (1, 117) = 20.08, P < 0.001. A bi-directional causality exists and between rainfall and temperature: F (1, 117) = 19.80; F (1,117) = 17.14, P < 0.001, respectively. This means that rainfall affects temperature and vice versa. Results show evidence of the strong existence of a long-run relationship between climate variables and malaria, with temperature maintaining a much higher level of significance than rainfall. Temperature, therefore, is more important in influencing the transmission of malaria in Limpopo Province. Furthermore, the study finds that malaria in Limpopo Province is seasonal with initial cases observed at the end of the third quarter of the year, that is, the end of the winter season in August, and reaching a peak between the fourth quarter of the year (September, October and November) and the first quarter (March, April and May) of the following year. Vector control for anopheles mosquito should therefore begin at the end of July and into mid-August and should be intensified for at least three and a half months for it to be effective. To curb imported malaria there is also a need for collaboration with neighbouring countries. Care should also be take in terms of the use of DDT as a means of malaria control as it will poison water and destroy vegetation, both of which are absorbed by all living things, and thereby amplify human health challenges beyond climate change impacts.Thesis (PhD)--University of Pretoria, 2016.tm2016Geography, Geoinformatics and MeteorologyPhDUnrestricte

Time aggregation and the contradictions with causal relationships : can economic theory come to the rescue?

The literature on causality takes contradictory stands on the direction of causal relationships based on whether one uses temporally aggregated or systematically sampled data. As an example, using the relationship between a nominal target and the instrument used to achieve it, we show that one can fall back upon the data in itself, and analyse it from the perspective of economic theory, not only as a source of second opinion to econometric theories and Monte Carlo simulations, but also to draw proper conclusions regarding the form of the causal relationship that might be actually existing in the data

Time aggregation and the contradictions with causal relationships : can economic theory come to the rescue?

The literature on causality takes contradictory stands regarding the direction of causal relationships based on whether one uses temporally aggregated or systematically sampled data. Using the relationship between a nominal target and the instrument used to achieve it, as an example, we show that one can fall back upon the data in itself, and analyse it from the perspective of economic theory, not only as a source of second opinion to econometric theories and Monte Carlo simulations, but also to draw proper conclusions regarding the form of the causal relationship that might be actually existing in the data