Modelling the historical distribution of schistosomiasis-transmitting snails in South Africa using ecological niche models.

Schistosomiasis is a vector-borne disease transmitted by freshwater snails and is prevalent in rural areas with poor sanitation and no access to tap water. Three snail species are known to transmit schistosomiasis in South Africa (SA), namely Biomphalaria pfeifferi, Bulinus globosus and Bulinus africanus. In 2003, a predicted prevalence of 70% was reported in tropical climates in SA. Temperature and rainfall variability can alter schistosomiasis-transmitting snails' development by increasing or decreasing their abundance and geographical distribution. This study aimed to map the historical distribution of schistosomiasis from 1950 to 2006 in SA. The snail sampling data were obtained from the historical National Snail Freshwater Collection (NFSC). Bioclimatic variables were extracted using ERA 5 reanalysis data provided by the Copernicus Climate Change Service. In this study, we used 19 bioclimatic and four soil variables. The temporal aggregation was the mean climatological period pre-calculated over the 40-year reference period with a spatial resolution of 0.5° x 0.5°. Multicollinearity was reduced by calculating the Variance Inflation Factor Core (VIF), and highly correlated variables (> 0.85) were excluded. To obtain an "ensemble" and avoid the integration of weak models, we averaged predictions using the True Skill Statistical (TSS) method. Results showed that the ensemble model achieved the highest Area Under the Curve (AUC) scores (0.99). For B. africanus, precipitation-related variables contributed to determining the suitability for schistosomiasis. Temperature and precipitation-related variables influenced the distribution of B. globosus in all three models. Biomphalaria pfeifferi showed that Temperature Seasonality (bio4) contributed the most (47%) in all three models. According to the models, suitable areas for transmitting schistosomiasis were in the eastern regions of South Africa. Temperature and rainfall can impact the transmission and distribution of schistosomiasis in SA. The results will enable us to develop future projections for Schistosoma in SA based on climate scenarios.

State of ambient air quality in a low-income urban settlement of South Africa.

Air pollution remains one of the leading global environmental-health challenges the world is facing today, particularly within urban environments. amidst the COVID-19 pandemic, air pollution has been brought back into the spotlight as both attack the human respiratory systems. The purpose of the study was to investigate the quality of ambient air in a low-income urban settlement of Jabavu located within the City of Johannesburg during the year 2018. Air pollution and meteorological data were gathered from the South African Air Quality System network. The study focused on three pollutants namely PM10, SO2 and O3. Findings were that the seasonal ambient mean concentrations for PM10 in summer was (28.99 µg/m3), autumn (33.32 µg/m3), winter (61.71 µg/m3) and spring (48.44 µg/m3). On the other hand, the seasonal ambient mean concentrations for SO2 was summer (4.45ppb), autumn (3.19ppb), winter (5.65ppb) and spring (3.54ppb). The O3 seasonal ambient mean concentrations were summer (40.97ppb), autumn (21.01ppb), winter (15.90ppb) and spring (33.59ppb). Furthermore, the study observed that in summer, winter and spring the dominant long-range transport air masses originated from the South Atlantic Ocean, Madagascar Island-India Ocean and the Indian Ocean while in autumn the dominant air masses are short-range inland air masses. For SO2 and PM10, ambient concentrations were found to be more problematic during winter; while for O3 substantial levels were unexpectedly recorded in summer. When analysing the diurnal profiles of PM10, SO2 and O3, each of these pollutants revealed a unique distribution pattern, which, despite having seasonal variance, was consistent throughout the year. For instance, irrespective of the season, PM10 mostly peaked in the mornings and evenings; meanwhile SO2 and O3 often spiked during the midday and mid-afternoon, respectively. These findings indicate that air quality within this low-income settlement is poor. To improve air quality within low-income settlements there is a need for a shift from reliance on solid fuels to cleaner energy sources such as LP gas, biogas and solar accompanied by an increase in community awareness about air quality issues. This study contributes to knowledge building within the air quality monitoring scientific community while for policymakers it assists in policy formulation to enable air quality management.