EDITORIAL Year : 2023  Volume : 16  Issue : 1  Page : 712 Human monkeypox pandemic in 2022 Rathinasamy Muthusami^{1}, Kandhasamy Saritha^{2}, ^{1} Department of Computer Applications, Dr. Mahalingam College of Engineering and Technology, Pollachi, Tamil Nadu, India ^{2} Department of Mathematics, P.A. College of Engineering and Technology, Pollachi, Tamil Nadu, India Correspondence Address:
Characteristics of the Monkeypox Virus Monkeypox is a severe infectious illness induced by the monkeypox virus that infects humans and other animals. It is thought to be the most devastating orthopoxvirus infection since the abolition of smallpox. Fever, enlarged lymph nodes, and a rash that boils and crusts up are all symptoms. The interval between absorption and the development of symptoms spans between 5 and 21 days.[1],[2] Symptoms usually persist 2 to 4 weeks. There are minimal signs, however, it is unknown impact degree it may arise even without symptoms. The characteristic appearance of fever and muscular aches, followed by enlarged glands and lesions all at the same stage, has not been observed in all outbreaks. Severe cases are possible, particularly in children, pregnant women, and those with weakened immune systems. Monkeypox virus, a zoonotic virus of the family Orthopoxvirus, causes the illness. This species also contained the variola virus, the leading cause of smallpox.[3],[4],[5] Monkeypox is an acute infection characterized by the Zoonotic Orthopoxvirus, which is linked to cowpox and smallpox and is a member of the Poxviridae genus. It is usually transmitted by monkeys and rodents, although humantohuman transmission is really common.[6],[7] Monkeypox is not widely transmitted from person to person. Frequent contact with harmful bacteria out of an injured person's carious lesions, respiratory droplets in prolonged facetoface contact, and fungus spores all lead to human propagation. The prevalence of diagnosed human monkeypox virus cases among men having sex with men in the current epidemic, as well as the pattern of the exhibiting sores in certain instances, imply that spreading transpired while sexually.[8] Although monkeypox is not as infectious as COVID19, the majority of instances continues to climb. In 1990, there were only 50 occurrences of monkeypox in West and Central Africa. However, by 2020, the number of instances had risen to 5000. Monkeypox is thought to have solely occurred in Africa in the past, but in 2022, numerous nonAfrican nations in Europe and the United States announced the characterization of persons affected by the disease. As a result, widespread panic and despair are spreading.[9] Monkeypox Lineage Some recent investigations have revealed that the real prevalence of monkeypox virus in prevalent African nations has been inadequately characterized. Furthermore, the variety and size of susceptible animals are unclear. Furthermore, the generalizability of the squirrel community in Africa has likely risen in recent years, resulting in greater biological contacts and consequently higher monkeypox virus propagation. Monkeypox virus sequencing investigations had conventionally used two lineages classified as the “West African” and “Central African or Congo basin” lineages. However, in order to construct a nondiscriminatory and nonstigmatizing naming scheme, some researchers proposed using alphanumeric lineages, which Nextstrain currently uses.[10],[11] Genome patterns in the ongoing 2022 outbreak are now publicly disclosed by countries including Portugal, Spain, France, Switzerland, Italy, Slovenia, the Netherlands, Germany, the United Kingdom, Israel, the United States of America, Canada, and Brazil. The genetic biostatistics context of the present multicountry epidemic reveals an exclusive origin, with most genomes clustering on the B.1 and A.2 lineages, with the B.1 clade seeming to be an emerging lineage that separated from A.1. Genomic sequences observation must be strengthened as needed to aid in identifying the virus's genesis and probable dissemination paths in the current epidemic.[12],[13],[14],[15] Does the Monkeypox Virus Currently have any Approved Treatments? There is presently no approved therapy or scientific proof guideline available to cure human monkeypox. As a result, healthcare system tries to deal with the symptoms, term of sustainability, and try to minimize the consequences. The World Health Organization has published an interim appropriate medical recommendation. The US Food and Drug Administration has authorized tecovirimat and brincidofovir for the therapy of smallpox. Neither of these medications has been evaluated in people in phase 3 clinical studies, although both have demonstrated activity over other orthopoxviruses in animal studies, notably monkeypox.[10],[16],[17] Monkeypox is a significant worldwide health risk that may spread across borders and spread quickly. While ideal disease management and treatment solutions for this extremely hazardous illness have yet to be established, the very first data suggest brincidofovir has limited efficiency; consequently, further research into tecovirimat in human monkeypox is essential. In future outbreaks, the infection prevention and control ramifications of anterior respiratory tract viral shedding should be investigated. As the human monkeypox virus pandemic grows into new countries, threatening to become a global outbreak, observational studies must be examined in such a way that the perspective of quantitative visualization and analysis may raise public awareness of the situation in the near future. What does this Study's Key Contribution Consist of? An overview of the research's main contribution is the AutoRegressive Integrated Moving Average (ARIMA) statistical model was used to anticipate the infection rate for the top 5 countries with the highest rates of confirmed cases, including the United States, Spain, Germany, England, and France commencing on August 2, 2022, and spanning for the following 50 days. Where was the Dataset Compiled? Our World in Data, an open public platform for sharing research and data against global problems was used to collect the data for this study on the human monkeypox virus. There were statistics about the human monkeypox virus concerning 107 different countries and territories that were collected between May 6, 2022 and August 1, 2022.[18] Visualization of the Proposed Time Series Forecasting Model The infection rates of the human monkeypox virus have been predicted using an ARIMA model on time series data.[19],[20] [Figure 1] depicts a graphical depiction of the proposed time series forecasting model, which is divided into three phases: Establish, estimate, and predict. Provide the time series data on which stationarity tests have been performed to determine whether differencing is required during the establish stage. In addition, autocorrelations are used to identify one or more ARIMA models that could have been fitted. During the estimate phase, it calculates the model's features and generates diagnostic statistics to assess the model's appropriateness. Forecast future quantities of the time series and create optimism ranges for these forecasts using the ARIMA model developed by the prior estimate phase in the predicting phase.{Figure 1} What is Time Series Data? Time series, in general, refers to a collection of data points arranged chronologically; it can be divided into three components; a significant forward or downward shift in the data over time is called a trend; seasonality is periodic deviation; noise is arbitrary ups and downs. Before using the proposed ARIMA statistical model, make sure the time series is stable. For instance, statistical stationary is perceived as having no systematic change in the mean or variance of the observation. If a time series doesn't exhibit any trend or seasonal influences, it is considered stationary. Since the number of observations keeps increasing, a trend is present if seasonal spikes and drops in the data happen. In general, a trend can be both increasing and decreasing. Are Time Series Data Stationary? How do you Know? Two primary statistical methods can be used to determine whether a time series is stationary. It has been demonstrated that the time series is stationary using rolling statistics, which is one way that has been evaluated with time series data that has been collected. In rolling statistics, the rolling mean and rolling standard deviation remains constant over time. An alternative is the augmented DickeyFuller (ADF) test, which relies on the statistical parameter P value and confidence interval to identify the data as stationary. The outcome is shown in [Table 1].{Table 1} Key Components that Make Out the AutoRegressive Integrated Moving Average Model The researchers can create an ARIMA statistical model based on these two findings. Based on its own historical values, the ARIMA model forecasts a given time series. It can be used for any nonseasonal number series that shows patterns and is not a collection of random occurrences. Data are gathered across a number of constant, regular intervals, which is one of its primary features. When predicting future demand, such as the rate of infection, the ARIMA model is commonly used. The “autoregressive” (AR) in this case stands for autoregression, which denotes a model that depicts a variable that changes and regresses on its own prior or lagged values. In other words, it extrapolates future values from the past. The letter “I” stands for integrated, which implies it notices the variation between current values and prior values for static data. It has been determined by utilizing the ADF test that the objective is to obtain stationary data that is not prone to seasonality. The third one, “moving average” (MA), stands for the MA, which is the relationship between an observed value and a residual error resulting from the application of a MA model to earlier data. Three variables make up an ARIMA model: AR (P), which represents the number of lag observations or autoregressive components in the model; I (d), which represents the difference between the nonseasonal data; and MA (q), which represents the size of the MA window. The model has been trained on the dataset to forecast the infection rate based on the nonnegative values of these parameters. Monkeypox Virus Statistical Inference Employing TimeSeries Data The daily case observations time series, 3day rolling mean, and standard deviation are show that they don't change over time because the lines are straight and parallel to the Xaxis, which represents time data. The results of the ADF test are shown in [Table 1], where the time series is assumed to be stationary because the P < 0.05, which is statistically significant, and the critical values at the 1%, 5%, and 10% confidence intervals are as close as they can be. The table also demonstrates that the data used are stationary at the 90% confidence level, which is a significant level. [Table 1] shows the results of the ADF test performed on timeseries data of the human monkeypox virus for the period from May 6 to August 1, 2022. Rolling statistics' abovefavorable findings and the ADF test confirmed that the chosen dataset contains stationary data that would be used to construct an ARIMA statistical model. The ARIMA statistical model has been fitted to timeseries data for the United States, Spain, Germany, England, and France in order to anticipate infection rates with respect to the top 5 nations with confirmed cases as of August 1, 2022 globally. Prior to developing the ARIMA model, an autocorrelation plot was also generated to detect threshold lags and establish the parameter control limits necessary to launch the model. Researchers can visually represent the degree to which an observation in a time series is related to observations made at prior time steps using an autocorrelation plot. Each variable's distribution fits a Gaussian distribution in that situation, where the correlation among the variables is summarized using Pearson's correlation coefficient. The Pearson's correlation coefficient, which ranges from − 1 to 1, is used to determine if a correlation is positive or negative. With a value of 0, there is no relationship. Following that, determine the relationships between observations made during lags, or earlier time steps, and observations made during a time series. Since it is created by comparing time series data to values from prior iterations of the same series, this sort of correlation is also referred to as stationarity or autocorrelation. Timeseries data for the human monkeypox virus are autocorrelated, according to the computation. The autocorrelation suggests a peak between lags 1 and 3, hence the ARIMA model can be trained using a parameter value in the range of 1 to 3. Analyzing the Residual Out of an AutoRegressive Integrated Moving AverageFitted Model to Diagnostic Concerns Moreover, the components p, d, and q were used to develop the ARIMA model. The model uses a MA model of 3, a difference order of 2, and an initial lag value for autoregression of 1. The model was then utilised to identify the fittest ARIMA model's ranking using the Akaike's information criterion, and the right amount of differencing using the ADF test. As a consequence, ARIMA (3, 2, 0) was selected as the best model for the United States, ARIMA (1, 2, 1) for Spain, ARIMA (0, 2, 1) for Germany, ARIMA (2, 2, 0) for England, and ARIMA (3, 2, 0) for France. Following a diagnostic analysis of the residual, as seen in [Figure 2]a, [Figure 2]b, [Figure 2]c, [Figure 2]d, [Figure 2]e, it was found that the variances are mutually independent and can have a 0 mean.{Figure 2} For the countries of the United States, Spain, Germany, England, and France using time series dataset, the fitted ARIMA model currently predicts the infection rate in the ensuing 50 days starting on August 2, 2022. [Figure 3] (red line) shows that in the 50 days starting on August 2, 2022, the infection rate in United States will be close to 7.5%, whereas it will be closer to 330% in Spain, 2.4% in Germany, 19% in England, and 350% in France.{Figure 3} Conclusion According to the study, from May 6, 2022 to August 1, 2022, there are 5156 confirmed cases in the United States (22.24%), 4300 cases (18.48%) in Spain, 2677 cases (11.54%) in Germany, 2359 cases (10.13%) in England, and 1955 cases (8.44%) in France. The ARIMA statistical model has been used to forecast the infection rate of the top 5 nations with the highest confirmed case rates, including the United States, Spain, Germany, England, and France, using timeseries data of the monkeypox virus. Starting on August 2, 2022, the infection rate in the United States will be close to 7.5% with 5543 cases, whereas it will be closer to 330% with 18,490 cases in Spain, 2.4% with 2741 cases in Germany, 19% with 2807 cases in England, and 350% with 8798 cases in France for the following 50 days. This study discovered that the infection rate has increased rapidly in the United States and Europe and is dynamic, which implies that even if it spreads to new nations; it might become a global outbreak. Vaccine against smallpox and some modified vaccines of that are currently recommended by many nations to prevent monkeypox infection. While this may reduce the expected infection rate, it shows that prompt public health action is essential to prevent the spread of monkeypox. References


