Analysis of Daily Rainfall in São Carlos/SP, Brazil over 1979-2017 Using Laplace Trend Test

Rainfall expresses one of the most complex climate factors in Southeastern Brazil. Understanding the dynamics and temporal trends of rainfall represents a significant challenge due to regional and even global mechanisms, such as FS (Frontal Systems) and the SACZ (South Atlantic Convergence Zone), and the interaction with the Atlantic and Pacific Oceans. The present study aimed at analyzing the pluviometric tendencies in São Carlos/SP, in the countryside of São Paulo State. Laplace trend test was used to comprehend the temporal evolution of daily rainfall in the region in the historical series 1979-2017, in seven pluviometric stations (climatological or surface stations). Significant fluctuations in interannual trends and between seasons were observed. However, it was noted that the beginning of the 1980s showed positive trends, whereas, as of the year 2000, most of the stations demonstrated negative trends, indicating a reduction in daily rainfall volume due to the great tropical climatic variability of Brazil. Emphasis should also be given to the regional and local effects, such as elevation and urbanization, respectively, which corroborate such differences among the analyzed stations. This methodology is of considerable value for the observation of pluviometric trends, and future studies can validate such a tool in climatological studies.

COVID-19 prevalence estimation:Four most affected African countries

The world at large has been confronted with several disease outbreak which has posed and still posing a serious menace to public health globally.Recently,COVID-19 a new kind of coronavirus emerge from Wuhan city in China and was declared a pandemic by the World Health Organization.There has been a reported case of about 8622985 with global death of 457,355 as of 15.05 GMT,June 19,2020.South-Africa,Egypt,Nigeria and Ghana are the most affected African countries with this outbreak.Thus,there is a need to monitor and predict COVID-19 prevalence in this region for effective control and management.Different statistical tools and time series model such as the linear regression model and autoregressive integrated moving average(ARIMA)models have been applied for disease prevalence/incidence prediction in different diseases outbreak.However,in this study,we adopted the ARIMA model to forecast the trend of COVID-19 prevalence in the aforementioned African countries.The datasets examined in this analysis spanned from February 21,2020,to June 16,2020,and was extracted from theWorld Health Organization website.ARIMA models with minimum Akaike information criterion correction(AICc)and statistically significant parameters were selected as the best models.Accordingly,the ARIMA(0,2,3),ARIMA(0,1,1),ARIMA(3,1,0)and ARIMA(0,1,2)models were chosen as the best models for SA,Nigeria,and Ghana and Egypt,respectively.Forecasting was made based on the best models.It is noteworthy to claim that the ARIMA models are appropriate for predicting the prevalence of COVID-19.We noticed a form of exponential growth in the trend of this virus in Africa in the days to come.Thus,the government and health authorities should pay attention to the pattern of COVID-19 in Africa.Necessary plans and precautions should be put in place to curb this pandemic in Africa.