scholarly journals Evaluation of the epidemiological behavior of mortality due to COVID-19 in Brazil: A time series study

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0256169
Author(s):  
Ketyllem Tayanne da Silva Costa ◽  
Thiffany Nayara Bento de Morais ◽  
Dayane Caroliny Pereira Justino ◽  
Fábia Barbosa de Andrade
Keyword(s):  
Time Series ◽  
Secondary Data ◽  
Health Surveillance ◽  
World Health ◽  
Microsoft Excel ◽  
Time Series Study ◽  
The World ◽  
Independent Variable ◽  
Health Organization ◽  
Series Study

The World Health Organization declared, at the end of 2019, a pandemic caused by SARS-CoV-2, a virus that causes Coronavirus Disease—COVID-19. Currently, Brazil has become the epicenter of the disease, registering approximately 345 thousand deaths. Thus, the study has scientific relevance in health surveillance as it identifies, quantifies and monitors the main behavioral patterns of the mortality rate due to COVID-19, in Brazil and in their respective regions. In this context, the study aims to assess the epidemiological behavior of mortality due to COVID-19 in Brazil: a time series study, referring to the year 2020. This is an ecological time series study, constructed using secondary data. The research was carried out in Brazil, having COVID-19 deaths as the dependent variable that occurred between the 12th and 53rd Epidemiological Week of 2020. The independent variable will be the epidemiological weeks. The data on deaths by COVID-19 were extracted in February 2021, on the Civil Registry Transparency Portal. The cleaning of the database and the information were treated in the Microsoft Excel® Software and, for statistical analysis, the JoinPoint software, version 4.7.0.0 was used. It was observed that Brazil presents an upward curve between the 12th and 19th SE, when it reaches saturation at the peak of mortality, which remains until the 35th SE and, subsequently, a downward curve was identified until the 47th SE, period in the which curve turns back up.

Use of the World Health Organization Access, Watch, and Reserve Classification to Follow Trends in Prescription of Antibiotic Use in Two Pediatric Intensive Care Units in Rio de Janeiro, Brazil

2020 ◽  
Vol 15 (03) ◽  
pp. 155-160
Author(s):  
André Ricardo Araujo da Silva ◽  
Cristina Vieira de Souza Oliveira ◽  
Cristiane Henriques Teixeira ◽  
Izabel Alves Leal
Keyword(s):  
Time Series ◽  
Intensive Care ◽  
Time Series Analysis ◽  
World Health Organization ◽  
Pediatric Intensive Care ◽  
Antibiotic Use ◽  
Antibiotic Consumption ◽  
World Health ◽  
The World ◽  
Health Organization

Abstract Objective The recommended percentage of antibiotic use in pediatric intensive care units (PICUs) using the World Health Organization (WHO) Access, Watch, and Reserve (AWaRE) classification is not known. Methods We have conducted an interrupted time series analysis in two PICUs in Rio de Janeiro, Brazil, over a period of 18 months. The type of antibiotics used was evaluated using the WHO AWaRE classification, and the amount of antibiotic was measured using days of therapy/1,000 patient-days (DOT/1000PD) after implementation of an antimicrobial stewardship program (ASP). The first and last semesters were compared using medians and the Mann–Whitney's test. The trends of antibiotic consumption were performed using time series analysis in three consecutive 6-month periods. Results A total of 2,205 patients were admitted, accounting for 12,490 patient-days. In PICU 1, overall antibiotic consumption (in DOT/1000PD) was 1,322 in the first 6 months of analysis and 1,264.5 in the last 6 months (p = 0.81). In PICU 2, the consumption for the same period was 1,638.5 and 1,344.5, respectively (p = 0.031). In PICU 1, the antibiotics classified in the AWaRE groups were used 33.2, 57.9, and 8.4% of the time, respectively. The remaining 0.5% of antibiotics used were not classified in any of these groups. In PICU 2, the AWaRE groups corresponded to 30.2, 60.5, and 9.3% of all antibiotics used, respectively. There was no use of unclassified antibiotics in this unit. The use of all three groups of WHO AWaRE antibiotics was similar in the first and the last semesters, with the exception of Reserve group in PICU 2 (183.5 × 92, p = 0.031). Conclusion A significant reduction of overall antibiotic use and also in the Reserve group was achieved in one of the PICU units studied. The antibiotics classified in the Watch group were the most used in both units, representing ∼60% of all the antibiotics consumed.

scholarly journals Clinical and epidemiological indicators and spatial analysis of leprosy cases in patients under 15 years old in an endemic area of Northeast Brazil: an ecological and time series study

BMJ Open ◽  
2019 ◽  
Vol 9 (7) ◽  
pp. e023420 ◽  
Author(s):  
Márcio Bezerra Santos ◽  
Allan Dantas dos Santos ◽  
Aline Silva Barreto ◽  
Mariana do Rosário Souza ◽  
Marco Aurélio de Oliveira Goes ◽  
...  
Keyword(s):  
Time Series ◽  
Spatial Analysis ◽  
Physical Disability ◽  
Endemic Area ◽  
Temporal Trends ◽  
Secondary Data ◽  
Lower Percentage ◽  
Northeast Brazil ◽  
Time Series Study ◽  
Series Study

ObjectiveThis study aimed to analyse the clinical and epidemiological indicators, temporal trends and the spatial distribution of leprosy in patients under 15 years old in an endemic area of Northeast Brazil.DesignRegional surveillance study of all reported cases.SettingState of Sergipe, endemic area of Northeast Brazil.MethodsAn ecological and time series study was conducted, based on secondary data reported by the Brazilian Information System on Notifiable Diseases for leprosy cases diagnosed in Sergipe state (2002–2015). The analysis of temporal trends was performed using the Joinpoint Regression Programme through Poisson regression. We performed spatial analysis by Kernel estimator and Moran index.ResultsThe incidence rate was reduced from 6.29 to 3.78 cases per 100 000 inhabitants in 2002 and 2015, respectively. However, Sergipe was still classified as highly endemicity in 2015. The mean number of household contacts (HHC) examined was significantly lower than those registered. Clinical data indicated that 21.4% of the patients developed leprosy reactions, and 31.3% presented with some physical disability in the multibacillary groups. Patients diagnosed by examination within the HHC presented better indicators, such as lower percentage of leprosy reaction and physical disability. Spatial analysis showed the most risk areas distributed on the northeast and cities around the capital, Aracaju.ConclusionThe data indicate that there is a persistence of activeMyobacterium lepraetransmission and a delay in disease detection, following a pattern of high endemicity in many municipalities. The early detection by HHC examination is important to stop transmission and also to detect the cases in a less severe state.

scholarly journals Time series analysis of tuberculosis registration rates from 2007 to 2019 and prediction: could tuberculosis control milestones be achieved in 2020 and 2025 in Henan Province, China?

2020 ◽  
Author(s):  
Yanqiu Zhang ◽  
Weibin Li ◽  
Jianguo Jiang ◽  
Guolong Zhang ◽  
Yan Zhuang ◽  
...  
Keyword(s):  
Time Series ◽  
Confidence Interval ◽  
Early Response ◽  
Information Management System ◽  
Early Summer ◽  
Henan Province ◽  
World Health ◽  
The World ◽  
Response Measures ◽  
Health Organization

Abstract Background: The World Health Organization (WHO) End TB Strategy meant that compared with 2015 baseline, the reduction in pulmonary tuberculosis(PTB) incidence rate should be 20% and 50% in 2020 and 2025, respectively. The incidence number of PTB in China accounted for 9% of the global total in 2018, which ranked the second high in the world. From 2007 to 2019, 854,672active PTB cases were registered and treated in Henan Province, China. We need to assess whether the WHO milestones could be achieved in Henan Province. Methods: The active PTB numbers in Henan Province from 2007 to2019, registered in Chinese Tuberculosis Information Management System (CTIMS) were analyzed to predict the active PTB registration rates in 2020 and 2025, which is conductive to early response measures to ensure the achievement of the WHO milestones. The time series model was created by monthly active PTB registration rates from 2007 to 2016, and the optimal model was verified by data from 2017 to 2019. Monthly and annual active PTB registration rates and 95% confidence interval (CI) from 2020 to 2025 were predicted. Results: High active PTB registration rates in March, April, May and June showed the seasonal variations. The exponential smoothing winter’s multiplication model was selected as the best-fitting model. The predicted values were approximately consistent with the observed ones from 2017 to 2019. The annual active PTB registration rates were predicted as 49.2 (95% CI: 36.0-62.5) and 34.3 (95% CI: 17.7-50.8) per 100 ,000 population in 2020 and 2025 , respectively. Compared with the active PTB registration rate in 2015, the reduction will reach 23.7% (95% CI: 3.1%-44.2%) and 46.9% (95% CI: 21.3%-72.5%) in 2020 and 2025, respectively. Conclusions: The high active PTB registration rates in spring and early summer indicates that high risk of tuberculosis infection in late autumn and winter in Henan Province. Without regard to the confidence interval, the first milestone of WHO End TB Strategy in 2020 will be achieved. However, the second milestone in 2025 will not be easily achieved unless there are early response measures in Henan Province, China. Trial registration: Not applicable

scholarly journals Food independence determinant (Rice) In Supporting The Availability Of National Rice

2019 ◽  
Vol 17 (1) ◽  
pp. 55
Author(s):  
Lendi Ageng Kurnia ◽  
Deden Dinar Iskandar
Keyword(s):  
Time Series ◽  
Research Design ◽  
Secondary Data ◽  
Appropriate Technology ◽  
Rice Production ◽  
Least Square ◽  
Time Series Study ◽  
Rice Prices ◽  
The Stability ◽  
Series Study

In maintaining the stability of national rice availability, 3 supporting aspects are needed, namely increasing domestic rice production, procuring government rice reserves through Bulog and importing rice. The purpose of this study is 1) to find out the factors that influence the availability of national rice, 2) to find out the factors that influence food independence, especially rice. The data used is secondary data sourced from BPS, FAO statistics and IRRI statistics. The research design used in this study is a time series study from 1970-2016. The model used in the study is Least Square (LS). The results of the analysis show partially the availability of national rice influenced by domestic rice production, government rice reserves and rice imports. While the ability of domestic rice production in supplying the availability of national rice, which is represented in the substance of food independence, is influenced by productivity, rice supply stability, price gap of rice / rice and farmers' welfare. However, it is not influenced by the application of appropriate technology (in this case the use of subsidized fertilizer). The conclusion of this study is that the availability of national rice is not only supplied from within the country but must still be supported by the procurement of imported rice. In increasing food independence, productivity must be increased, ensuring that government rice reserves are always available, monitoring the development of rice / rice prices are always stable, and paying attention to the welfare of farmers as the main actors in rice trading. Whereas the government's policy of providing subsidized fertilizers needs to be refined and monitored in the field because so far only serves as a complement in the provision of rice to the community.

scholarly journals Tuberculosis forecasting and temporal trends by sex and age in a high endemic city in northeastern Brazil: where were we before the Covid-19 pandemic?

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hamilton Leandro Pinto de Andrade ◽  
Dulce Gomes ◽  
Antônio Carlos Vieira Ramos ◽  
Luiz Henrique Arroyo ◽  
Marcelino Santos-Neto ◽  
...  
Keyword(s):  
Time Series ◽  
Moving Average ◽  
Arima Model ◽  
Temporal Trends ◽  
Northeastern Brazil ◽  
World Health ◽  
Age Group ◽  
Health Organization ◽  
The City ◽  
Series Study

Abstract Background The aim of this study was to describe the temporal trend of tuberculosis cases according to sex and age group and evidence the level of disease before the Covid-19 pandemic in a TB high endemic city. Methods This was a time series study carried out in a city in northeast Brazil. The population was composed of cases of tuberculosis, excluding those with HIV-positive status, reported between the years 2002 and 2018. An exploratory analysis of the monthly rates of tuberculosis detection, smoothed according to sex and age group, was performed. Subsequently, the progression of the trend and prediction of the disease were also characterized according to these aspects. For the trends forecast, the seasonal autoregressive linear integrated moving average (ARIMA) model and the usual Box-Jenkins method were used to choose the most appropriate models. Results A total of 1620 cases of tuberculosis were reported, with an incidence of 49.7 cases per 100,000 inhabitants in men and 34.0 per 100,000 in women. Regarding the incidence for both sexes, there was a decreasing trend, which was similar for age. Evidence resulting from the application of the time series shows a decreasing trend in the years 2002–2018, with a trend of stability. Conclusions The study evidenced a decreasing trend in tuberculosis, even before the Covid-19 pandemic, for both sex and age; however, in a step really slow from that recommended by the World Health Organization. According to the results, the disease would have achieved a level of stability in the city next years, however it might have been aggravated by the pandemic. These findings are relevant to evidence the serious behavior and trends of TB in a high endemic scenario considering a context prior to the Covid-19 pandemic.

scholarly journals COVID-19 Pandemic Data Visualization with Moment about Midpoint: Exploratory and Expository Analyses

2020 ◽  
pp. 15-37
Author(s):  
Stephen Olusegun Are ◽  
Matthew Iwada Ekum
Keyword(s):  
Cross Sections ◽  
Secondary Data ◽  
Total Sample ◽  
World Health ◽  
The Central Limit Theorem ◽  
Time Period ◽  
The World ◽  
Exploratory Data ◽  
Novel Coronavirus ◽  
Health Organization

Aims: To visualize COVID-19 data using Exploratory Data Analysis (EDA) to tell the COVID-19 story expository. Study Design: The study uses EDA approach to visualize the COVID-19 data. The study uses secondary data collected from World Health Organization (WHO) in a panel form and partition the world using WHO regions. Moment about a midpoint and EDA are jointly used to analyze the data. Place and Duration of Study: Department of Mathematics & Statistics, Statistical Laboratory, Lagos State Polytechnic and Federal Polytechnic, Ilaro. The data used covered all regions of the world from January 2020 to July 2020. Methodology: We included 198 countries (cross-sections) partitioned into 7 WHO regions over 7 months (190 days) time period, spanning 3000 datasets. The EDA and moment about a midpoint is used for the analysis. This is a purely descriptive and expository analysis to tell the story of the novel coronavirus disease (COVID-19). Results: The total sample points used for this analysis are 30,010, which can be taken as a big data and it is large enough to assume the central limit theorem. The results of the analysis showed that cumulative cases and deaths are increasing but at a slower rate. Some WHO region curves are already flattening. Conclusion: The study concluded that average number of new cases and new deaths will decrease in coming months but there will be increase in the cumulative cases and deaths but at a slower rate.

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