COVID-19 forecast for 13 Caribbean countries using ARIMA modeling for confirmed, death, and recovered cases

Background: The rapid spread of the Covid-19 virus in the Caribbean region has led to increased surveillance with an increasing trend of confirmed cases of COVID-19 in 13 Caribbean countries. Our study aims to analyze the impact of Covid-19 (SARS nCoV-2) in 13 Caribbean countries in terms of the number of confirmed cases, deaths, and recovered cases. Methods: The study uses the ARIMA model based on the time series pattern according to data retrieved from John Hopkins University. The data were analyzed using Stata 14 SE software for the period January 22, 2020, and August 16, 2021, and forecasted till December 31, 2021. All chosen models were compared with other models in terms of various factors like AIC/BIC, log-likelihood, p-value significance, coefficient < 1, and 5% significance. The ACF and PACF graphs were plotted to reduce bias and select the best-fitting model. Results: The results show the predicted trend in terms of confirmed, death, and recovered cases of COVID-19 for 13 Caribbean countries. The projected ARIMA model forecast for the period December 16, 2021, to December 31, 2021, shows 2470272 (95% CI 2438965 - 2501579) confirmed cases, 27220 (95% CI 26886 - 27555) deaths, and 818105 (95% CI 818085 - 818125) recovered cases related to Covid-19. The final ARIMA model chosen for confirmed COVID-19 cases, several deaths, and recovered cases are ARIMA (9,2,4), ARIMA (1,2,1), and ARIMA (1,2,1), respectively. Conclusions As per the results of the forecasted COVID-19 models, there is a steady rise in confirmed, death, and recovered cases during the period June 1, 2020, until November 30, 2020, and April 1, 2021, until June 15, 2021. It shows an increasing trend for confirmed and recovered COVID-19 cases and a slowing of the number of deaths.

Epidemiology and Viral Etiology of Pediatric Immune Thrombocytopenia through Korean Public Health Data Analysis

Immune thrombocytopenic purpura (ITP) is prevalent in children aged 2–5 years but may occur in all pediatric age groups. In 50–60% of pediatric patients, ITP is preceded by an upper respiratory tract infection 1–4 weeks before its onset. In this study, the relationship between the development of ITP and viral infections in children was assessed. We analyzed data of 6487 patients aged < 18 years with incident ITP from the Health Insurance Review and Assessment Open Access Big Data Platform (2015 to 2018) and the Korea Disease Control and Prevention Agency. The monthly positive detection rate (PDR) of seven respiratory and four acute diarrhea viruses was calculated. The virus PDR seasonal trend data was analyzed through ARIMA modeling. The ITP diagnostic data and prevalence of viral infection 1 and 2 months prior were analyzed using the Granger test. The overall male to female (M/F) ratio was 1.2, whereas it was 1.4 in the youngest age group (< 1 year). The overall ITP incidence rate was 18.1 per 100,000 person-years. Respiratory syncytial virus, rhinovirus, rotavirus, and astrovirus infections influenced ITP occurrence in children. However, rotavirus infection is positively associated with the etiology of ITP after 1–2 months.

Forecasting of Rice Production using the Meteorological Factor in Major States in India and its Role in Food Security

The world as well as in India, rice is playing a major role in food security. Production factors (like rainfall, minimum temperature, fertilizer consumption, an area under irrigation for a particular crop) are very crucial for crop productivity. Forecasting is always important for policy implication and planning purposes of the country. In the present investigation, the projection has been made using simple ARIMA and ARIMAX (with the inclusion of crop inputs in ARIMA models). In terms of less error in model and projection, wise ARIMAX model was found better compared to simple ARIMA. In this present study, forecasting has been attempted with the inclusion of meteorological factors using ARIMA modeling up to the year 2022. This study reveals the future trend of rice production as well as a factor affecting productivity. Among the major states, West Bengal would lead the state in India in rice production, with a productivity of 4758 kg/ha, while Punjab will be the leader in productivity in the year 2022. This prediction would be helpful for policy implication and food security of the country.

Exploring regional variability in the short-term impact of COVID-19 on property crime in Queensland, Australia

Confronted by rapidly growing infection rates, hospitalizations and deaths, governments around the world have introduced stringent containment measures to help reduce the spread of COVID-19. This public health response has had an unprecedented impact on people’s daily lives which, unsurprisingly, has also had widely observed implications in terms of crime and public safety. Drawing upon theories from environmental criminology, this study examines officially recorded property crime rates between March and June 2020 as reported for the state of Queensland, Australia. We use ARIMA modeling techniques to compute 6-month-ahead forecasts of property damage, shop theft, residential burglary, fraud, and motor vehicle theft rates and then compare these forecasts (and their 95% confidence intervals) with the observed data for March through to June. We conclude that, with the exception of fraud, all property offence categories declined significantly. For some offence types (shop stealing, other theft offences, and residential burglary), the decrease commenced as early as March. For other offence types, the decline was lagged and did not occur until April or May. Non-residential burglary was the only offence type to significantly increase, which it did in March, only to then decline significantly thereafter. These trends, while broadly consistent across the state’s 77 local government areas still varied in meaningful ways and we discuss possible explanations and implications.

Previsão da exportação brasileira de açúcar avaliada por meio de gráficos de controle de resíduos

Sugar production and exportation are important factors for the Brazilian economy, because Brazil produces the largest amount of sugar and accounts for almost half of the world´s sugar exports. This research aimed to monitor the sugar export from January 2000 to April 2019, by means of residual control charts with pretreatment of autoregressive integrated moving average (ARIMA) models. The data used in the study were collected from the Portal Única website. We opted for the application of ARIMA modeling because the data was not stationarity and presented autocorrelated values. The best model to predict the Brazilian sugar exports was SARIMA (1,1,1)(1,0,1)6 due to the seasonal behavior of the series, which may be related to the sugarcane planting and harvesting period. It was possible to observe the presence of upper-limit outliers in the residual control chart, in October 2012 and February 2016, which characterize a sugar exports higher than forecasted exports.

Peramalan Penyebaran Jumlah Kasus Covid19 Provinsi Jawa Tengah dengan Metode ARIMA

Covid 19 virus disease (corona virus disease), a name given by WHO for patients with coronavirus infection, was first reported from the city of Wuhan, China at the end of 2018. The spread occurred rapidly and created a new pandemic threat. The purpose of this study was to analyze the development of a pandemic in Indonesia, especially in Central Java province. The method used is ARIMA modeling, to determine the percentage of covid19 developments in Central Java. By using the ARIMA method, the ARIMA model (1,1,1) is obtained as a suitable model for the spread of the number of positive cases of Covid-19. Based on this model, with the results that the number of spread of the number of positive cases can be predicted over the next 10 periods, with the result that the number of spread of the number of cases of the Covid-19 virus has decreased from the ece period.