Analyzing the Research Evolution in Response to COVID-19

In order to understand how these studies are evolving to respond to COVID-19 and to facilitate the containment of COVID-19, this paper accurately extracted the spatial and topic information from the metadata of papers related to COVID-19 using text mining techniques, and with the extracted information, the research evolution was analyzed from the temporal, spatial, and topic perspectives. From a temporal view, in the three months after the emergence of COVID-19, the number of published papers showed an obvious growth trend, and it showed a relatively stable cyclical trend in the later period, which is basically consistent with the development of COVID-19. Spatially, most of the authors who participated in related research are concentrated in the United States, China, Italy, the United Kingdom, Spain, India, and France. At the same time, with the continuous spread of COVID-19 in the world, the distribution of the number of authors has gradually expanded, showing to be correlated with the severity of COVID-19 at a spatial scale. From the perspective of topic, the early stage of COVID-19 emergence, the related research mainly focused on the origin and gene identification of the virus. After the emergence of the pandemic, studies related to the diagnosis and analysis of psychological health, personal security, and violent conflict are added. Meanwhile, some categories are most closely related to the control and prevention of the epidemic, such as pathology analysis, diagnosis, and treatment; epidemic situation and coping strategies; and prediction and assessment of epidemic situation. In most time periods, the majority of studies focused on these three categories.

A Study of Price Trend behaviour for Phyllanthus emblica in Madhya Pradesh, India

Price analysis and trend of Phyllanthus emblica was studied in view of its increasing price in the last few years. Time series data (2015-2020) of different market national, state and district level were taken and linear regression analysis was done. Price trend of aonla revealed a sharply increasing trend in the years 2017 and 2018 indicating scarcity of aonla in all markets with high demand, thereafter the price stabilised. All markets were integrated as revealed by similar price movements in markets. The price movement did not show any cyclical trend.

Fiscal Deficit of Rajasthan: Trends, Cycles and Seasonal

The paper has explored the smooth cyclical trend,cycles and seasonal patterns of fiscal deficit in gross and in per cent of net state domestic product of Rajasthan in current prices during 1990-91-2018-19 by applying Hamilton regression filter model(2018) which was also passed through ARIMA(p,d,q) forecasting model for 2030 and was also verified by heteroscedasticity test.Both the fiscal deficits in gross and in per cent of NSDP showed many peaks and troughs in cyclical patterns but only one peak and trough were found in the smooth cyclical trends and the inverse v shaped seasonal fluctuations were visible with no heteroscedasticity problems.Their ARIMA forecast models for 2030 are convergent,significant and move towards equilibrium.

Changes in Socioeconomic Inequalities in Amenable Mortality after the Economic Crisis in Cities of the Spanish Mediterranean Coast

Several studies have described a decreasing trend in amenable mortality, as well as the existence of socioeconomic inequalities that affect it. However, their evolution, particularly in small urban areas, has largely been overlooked. The aim of this study is to analyse the socioeconomic inequalities in amenable mortality in three cities of the Valencian Community, namely, Alicante, Castellon, and Valencia, as well as their evolution before and after the start of the economic crisis (2000–2007 and 2008–2015). The units of analysis have been the census tracts and a deprivation index has been calculated to classify them according to their level of socioeconomic deprivation. Deaths and population were also grouped by sex, age group, period, and five levels of deprivation. The specific rates by sex, age group, deprivation level, and period were calculated for the total number of deaths due to all causes and amenable mortality and Poisson regression models were adjusted in order to estimate the relative risk. This study confirms that the inequalities between areas of greater and lesser deprivation in both all-cause mortality and amenable mortality persisted along the two study periods in the three cities. It also shows that these inequalities appear with greater risk of death in the areas of greatest deprivation, although not uniformly. In general, the risks of death from all causes and amenable mortality have decreased significantly from one period to the other, although not in all the groups studied. The evolution of death risks from before the onset of the crisis to the period after presented, overall, a general pro-cyclical trend. However, there are population subgroups for which the trend was counter-cyclical. The use of the deprivation index has made it possible to identify specific geographical areas with vulnerable populations in all three cities and, at the same time, to identify the change in the level of deprivation (ascending or descending) of the geographical areas throughout the two periods. It is precisely these areas where more attention is needed in order to reduce inequalities.

Analyses of case-based surveillance data on malaria in pregnancy in Plateau State, Nigeria 2013–2017

Background: Malaria in pregnancy accounts for 11% of maternal death in Nigeria. Plateau State has a low uptake of intermittent preventive treatment of malaria among women attending antenatal care. Objectives: This study examined the trend and made projections of reported cases of malaria in pregnancy in Plateau State. Methods: Data were extracted from the state disease surveillance system from January 2013 to December 2017. Reported cases of malaria in pregnancy within the 5 years under investigation were retrieved, merged and sorted by month of reporting and Local Government Area (LGA). Prevalence was calculated yearly for each LGA in Plateau State using Geographic Information System. Seasonal variation and projection were based on a multiplicative time series model. Results: In total, 62,997 cases of malaria in pregnancy were retrieved. Prevalence was 6.9% in 2013 and increased to 15.1% in 2017. Higher prevalence was observed in Wase, Kanam and Shendam LGAs. A cyclical trend with highest number of malaria in pregnancy cases was found within the third quarter of all the years. Within the 5 years, there was higher seasonal variation for quarters three (1.209834) and one (1.099711). The highest number of cases of malaria in pregnancy was likely to occur in the third quarter, while the least was found in the second quarter. The projected numbers of malaria in pregnancy cases are 20,121, 22,593 and 25,064 for year 2018, 2019 and 2020, respectively, and the highest number of cases occurs in the third quarter. Conclusion: Malaria in pregnancy follows an increasing trend in Plateau State, with greatest severity in the third quarter of the year. An effective intervention strategy against malaria among pregnant women is advocated.

Research on forecasting coal bed methane demand and resource allocation system based on time series

The mining area is the main place for the development and utilization of Coalbed Methane (CBM), and there are a series of systems for the development and utilization of CBM. However, owing to lack of a clear understanding of demand-side gas consumption rules and a reasonable resource allocation system, a large amount of CBM resources in the mining area are wasted. In order to predict the demand for CBM dynamically, the Seasonal Auto Regressive Integrated Moving Average (SARIMA) model, Additive Holt-Winters (AHW) model and Multiplicative Holt-Winters (MHW) model based on time series are used to predict the monthly demand for CBM in Yangquan Mine Area in 2020, respectively. Then the predicted results are evaluated by using the prediction model parameters combined with the characteristics of actual demand for CBM. Finally, a resource allocation system under different supply and demand conditions is built to reduce the waste of resources. In this paper, it is found that the information of the actual data is not sufficiently extracted in the MHW model while the SARIMA model can reflect the cyclical trend of monthly demand for CBM under ideal conditions. Furthermore, the AHW model can reasonably predict the demand for CBM under the influence of COVID-19, with a mean relative error of 0.099. The supply and demand distribution system built based on the proposed models can solve the problem of seasonal unevenness of CBM demand in mining areas and ensure the economic benefits of mining areas.

Assessment of Early Mitigation Measures Against COVID-19 in Puerto Rico: March 15-May 15, 2020

ABSTRACTBackgroundOn March 15, 2020 Puerto Rico implemented non-pharmaceutical interventions (NPIs), including a mandatory curfew, as part of a state of emergency declaration to mitigate the community transmission of the SARS-CoV-2 virus. The strict enforcement of this curfew was extended through May 25, with a gradual relaxation beginning on May 1. This report summarizes an assessment of these early mitigation measures on the progression of COVID-19 in the island.Methods and FindingsFrom March 15 to May 15, 2020, 41,748 results of molecular (RT-PCR) tests were reported to the Puerto Rico Department of Health. Of these, 1,866 (4.5%) were positive, corresponding to 1,219 individuals with COVID-19 included in the study. We derived the epidemic growth rates (r) and the corresponding reproductive numbers (R) from the epidemic curve of these 1,219 individuals with laboratory-confirmed diagnosis of COVID-19 using their date of test collection as a proxy for symptoms onset. We then compared the observed cases with the R-based epidemic model projections had the mitigation measures not been implemented. Computations were conducted in the R packages forecast, incidence and projections.The number of daily RT-PCR-confirmed cases peaked on March 30 (84 cases), showing a weekly cyclical trend, with lower counts on weekends and a decreasing secular trend since March 30. The initial exponential growth rate (r) was 17.0% (95% CI: 8.4%, 25.6%), corresponding to a doubling of cases every 4.1 days, and to a reproduction number (Ro) of 1.89 (95% CI: 1.41, 2.39). After March 30, the r value reverted to an exponential decay rate (negative) of −3.6% (95% CI: −5.7%, −1.4%), corresponding to a halving of cases every 19.4 days and to an Ro of 0.90 (95% CI: 0.84, 0.97). Had the initial growth rate been maintained, a total of 18,699 (96%CI: 4,113, 87,438) COVID-19 cases would have occurred by April 30 compared with 1,119 observed.ConclusionsOur findings are consistent with very effective implementation of early non-pharmaceutical interventions (NPIs) as mitigation measures in Puerto Rico. These results serve as a baseline to assess the impact of the transition from mitigation to containment stages in Puerto Rico.

USA Income Distribution Counter-Business-Cyclical Trend

In this paper, the L1 norm of continuous functions and corresponding continuous estimation of regression parameters are defined. The continuous L1 norm estimation problems of linear one and two parameters models are solved. We proceed to use the functional form and parameters of the probability distribution function of income to exactly determine the L1 norm approximation of the corresponding Lorenz curve of the statistical population under consideration. U.S. economic data used to estimate income distribution. An interesting finding of these calculations is that the distribution of income obeys counter-wise business cycles fluctuations. This finding is a new area for research in the realm of the theory and application of income distribution and business cycles interrelationship.

Stock Market Volatility Measure Using Non-Traditional Tool Case of Germany

This study examines the stock market volatility of German bench-mark stock index DAX 30 using logarithmic extreme day return. German stock markets have been analyzed extensively in literature. We look into volatility issue from the standpoint of extreme-day changes. Our analysis indicates the non-normality of German stock market and higher probability of negative trading days. We measure the occurrences of extreme-day returns and their significance in measuring annual volatility. Our time series analysis indicates that the occurrences of extreme-days show a cyclical trend over the sample time period. Our comparison of negative and positive extreme-days indicates that negative extreme-days overweigh the positive extreme days. Standard deviation, as measure of volatility used traditionally, gives altered ranks of annual volatility to a considerable extent as compared to extreme-day returns. Lastly, existence of extreme day returns can be explained by past period occurrences, which show predictability.

Measles occurrence, vaccination coverages and malnutrition in India: correlations, trends, and projections by time series analysis

Background: Measles is a highly infectious viral disease responsible for a considerable morbidity and mortality in childhood. India has committed to achieve measles elimination by 2020. Currently, Sustainable Development Goals (SDG) have placed a lot of emphasis on measles elimination. Methods: Data on reported measles cases, immunization coverages and malnutrition status of children specific to India for a period from 1980 to 2017 were collected from WHO, UNICEF and related official online web sources. Also, various official measles elimination strategy documents, available literature and experiences from various countries were reviewed. The data were analysed for correlations, trends. Time series model projections were made till 2020 using two different software tools. Results: The occurrence of measles cases showed a significant downward trend especially since 2000, but continues to exhibit mild cyclical trend of 3-4 years with strong seasonality. Measles vaccine coverages are steadily and significantly increasing more so since 2014. Reduction in measles cases is strongly and significantly correlated with the vaccination coverages; moderate correlation with wasting and mild correlation with stunting was observed. Current progress in India to achieve elimination appears to be well on track with remarkable strides made in strengthening case based surveillance, immunization with 2 doses of measles containing vaccine (MCV) and establishment of high quality laboratory network. MCV1 and MCV 2 coverage forecasts look promising to reach about 95% by 2020 at current rates. Also, the projections of measles case occurrence indicate the reduction in incidence to about 20 per million, which may even be augmented further with concurrent enhancements in nutritional status and socio-economic growth. Conclusions: India is well on track to achieve measles elimination goal as per the commitment made in 2014, using the established strategies.