Thermal ecology of melanistic and non-melanistic species of Cordylid lizards in the Western Cape of South Africa

BACKGROUND The impact of climate temperature on the counts (number of positive COVID-19 cases reported), recovery, and death rates of COVID-19 cases in South Africa's nine provinces was investigated. The data for confirmed cases of COVID-19 were collected for March 25 and June 30, 2020 (14 weeks) from South Africa's Government COVID-19 online resource, while the daily provincial climate temperatures were collected from the website of the South African Weather Service. Our result indicates that a higher or lower climate temperature does not prevent or delay the spread and death rates but shows significant positive impacts on the recovery rates of COVID-19 patients. Thus, it indicates that the climate temperature is unlikely to impose a strict limit on the spread of COVID-19. There is no correlation between the cases and death rates, an indicator that no particular temperature range is closely associated with a faster or slower death rate of COVID-19 patients. As evidence from our study, a warm climate temperature can only increase the recovery rate of COVID-19 patients, ultimately impacting the death and active case rates and freeing up resources quicker to enable health facilities to deal with those patients' climbing rates who need treatment. OBJECTIVE This study aims to investigate the impact of climate temperature variation on the counts, recovery, and death rates of COVID-19 cases in all South Africa's provinces. The findings were compared with those of countries with comparable climate temperature values. METHODS The data for confirmed cases of COVID-19 were collected for March 25 and June 30 (14 weeks) for South African provinces, including daily counts, death, and recovery rates. The dates were grouped into two, wherein weeks 1-5 represent the periods of total lockdown to contain the spread of COVID-19 in South Africa. Weeks 6-14 are periods where the lockdown was eased to various levels 4 and 3. The daily information of COVID-19 count, death, and recovery was obtained from South Africa's Government COVID-19 online resource (https://sacoronavirus.co.za). Daily provincial climate temperatures were collected from the website of the South African Weather Service (https://www.weathersa.co.za). The provinces of South Africa are Eastern Cape, Western Cape, Northern Cape, Limpopo, Northwest, Mpumalanga, Free State, KwaZulu-Natal, Western Cape, and Gauteng. Weekly consideration was given to the daily climate temperature (average minimum and maximum). The recorded values were considered, respectively, to be in the ratio of death-to-count (D/C) and recovery-to-count (R/C). Descriptive statistics were performed for all the data collected for this study. The analyses were performed using the Person’s bivariate correlation to analyze the association between climate temperature, death-to-count, and recovery-to-count ratios of COVID-19. RESULTS The results showed that higher climate temperatures aren't essential to avoid the COVID-19 from being spread. The present results conform to the reports that suggested that COVID-19 is unlike the seasonal flu, which does dissipate as the climate temperature rises [17]. Accordingly, the ratio of counts and death-to-count cannot be concluded to be influenced by variations in the climate temperatures within the study areas. CONCLUSIONS The study investigates the impact of climate temperature on the counts, recovery, and death rates of COVID-19 cases in all South Africa's provinces. The findings were compared with those of countries with comparable climate temperatures as South Africa. Our result indicates that a higher or lower climate temperature does not prevent or delay the spread and death rates but shows significant positive impacts on the recovery rates of COVID-19 patients. Warm climate temperatures seem not to restrict the spread of the COVID-19 as the count rate was substantial at every climate temperatures. Thus, it indicates that the climate temperature is unlikely to impose a strict limit on the spread of COVID-19. There is no correlation between the cases and death rates, an indicator that there is no particular temperature range of the climatic conditions closely associated with a faster or slower death rate of COVID-19 patients. However, other shortcomings in this study's process should not be ignored. Some other factors may have contributed to recovery rates, such as the South African government's timely intervention to announce a national lockout at the early stage of the outbreak, the availability of intensive medical care, and social distancing effects. Nevertheless, this study shows that a warm climate temperature can only help COVID-19 patients recover more quickly, thereby having huge impacts on the death and active case rates.

Download Full-text

Performance in grade 12 mathematics and science predicts student nurses’ performance in first year science modules at a university in the Western Cape

Curationis ◽

10.4102/curationis.v40i1.1776 ◽

2017 ◽

Vol 40 (1) ◽

Cited By ~ 1

Author(s):

Katlego D.T. Mthimunye ◽

Felicity M. Daniels

Keyword(s):

South Africa ◽

Academic Performance ◽

Predictive Validity ◽

Life Science ◽

Student Nurses ◽

First Year ◽

Western Cape ◽

Cross Sectional ◽

Mathematics And Science ◽

First Year Student

Background: The demand for highly qualified and skilled nurses is increasing in South Africa as well as around the world. Having a background in science can create a significant advantage for students wishing to enrol for an undergraduate nursing qualification because nursing as profession is grounded in scientific evidence.Aim: The aim of this study was to investigate the predictive validity of grade 12 mathematics and science on the academic performance of first year student nurses in science modules.Method: A quantitative research method using a cross-sectional predictive design was employed in this study. The participants included first year Bachelor of Nursing students enrolled at a university in the Western Cape, South Africa. Descriptive and inferential statistics were performed to analyse the data by using the IBM Statistical Package for Social Sciences versions 24. Descriptive analysis of all variables was performed as well as the Spearman’s rank correlation test to describe the relationship among the study variables. Standard multiple linear regressions analysis was performed to determine the predictive validity of grade 12 mathematics and science on the academic performance of first year student nurses in science modules.Results: The results of this study showed that grade 12 physical science is not a significant predictor (p > 0.062) of performance in first year science modules. The multiple linear regression revealed that grade 12 mathematics and life science grades explained 37.1% to 38.1% (R2 = 0.381 and adj R2 = 0.371) of the variation in the first year science grade distributions.Conclusion: Based on the results of the study it is evident that performance in grade 12 mathematics (β = 2.997) and life science (β = 3.175) subjects is a significant predictor (p < 0.001) of the performance in first year science modules for student nurses at the university identified for this study.

Download Full-text