Current Outbreak Research Articles

Systematic In-Silico Evaluation of the Diagnostic Impact of Mpox Genome Variants in the Current Outbreak.

The rapid rate at which the current mpox virus outbreak has spread across the globe has led the World Health Organization to declare it a Public Health Emergency of International Concern. Polymerase chain reaction-based methods are one of the cornerstones for effective molecular detection of viruses including mpox virus. Genetic variants in primer binding sites are known to impact the efficiency of polymerase chain reaction and therefore diagnosis.Here we have analyzed the genetic variants and their impact on efficient binding of oligonucleotides used in diagnostics. In this study, we have systematically collected primers and probes used in the detection of mpox virus from published literature and public resources, and assessed the impact of primer binding region genetic variants in the detection of mpox virus by analysing the thermodynamic parameters, Gibbs free energy and melting temperature. These were calculated using the nearest neighbour method for variants in mpox virus genomes available and the deviation in parameters was computed with respect to the reference genome sequence. We have identified 170 genetic variations that fall within the oligo binding region in 1176 mpox virus genomes out of which five oligos showed at least a 2°C decrease in melting temperature, which could potentially affect the diagnostic efficacy. Our analysis shows the importance of continuous monitoring of mpox virus detection primer efficacy and provides the list of oligos with potentially reduced detection efficiency in the current mpox virus outbreak.

Using time-dependent reproduction number to predict turning points of COVID-19 outbreak in Dalian, Liaoning province, China.

To forecast the development trend of current outbreak in Dalian, mainly to predict turning points of COVID-19 outbreak in Dalian, Liaoning province, China, the results can be used to provide a scientific reference for timely adjustment of prevention and control strategies. During the outbreak, Bayesian framework was used to calculated the time-dependent reproduction number ([Formula: see text]), and then above acquired [Formula: see text] and exponential trend equation were used to establish the prediction model, through the model, predict the [Formula: see text] value of following data and know when [Formula: see text] smaller than 1. From July 22 to August 5, 2020, and from March 14 to April 2, 2022, 92 and 632 confirmed cases and asymptomatic infected cases of COVID-19 were reported (324 males and 400 females) in Dalian. The R square for exponential trend equation were 0.982 and 0.980, respectively which fit the [Formula: see text] with illness onset between July 19 to July 28, 2020 and between March 5 to March 17, 2022. According to the result of prediction, under the current strength of prevention and control, the [Formula: see text] of COVID-19 will drop below 1 till August 2, 2020 and March 26, 2022, respectively in Dalian, one day earlier or later than the actual date. That is, the turning point of the COVID-19 outbreak in Dalian, Liaoning province, China will occur on August 2, 2020 and March 26, 2022. Using time-dependent reproduction number values to predict turning points of COVID-19 outbreak in Dalian, Liaoning province, China was effective and reliable on the whole, and the results can be used to establish a sensitive early warning mechanism to guide the timely adjustment of COVID-19 prevention and control strategies.

Mpox Evolution: Has the Current Outbreak Revealed a Pox on "U"?

The recent mpox (monkeypox) outbreak has prompted genomic studies to track global spread of the disease. These studies have also revealed unexpected patterns of mutations that implicate the action of the immune defense APOBEC3 family of enzymes, which catalyze conversion of cytosine (C) to uracil (U) in DNA, in viral evolution. As poxviruses have conventionally been regarded as slow-evolving viruses, the rapid emergence of APOBEC3 mutational signatures begs a series of important and open questions regarding how host-pathogen interactions may have changed and whether these mutations are bystanders or have roles in pathogenesis.

Foot and Mouth Disease Outbreak in Indonesia: Summary and Implications

This Watching Brief details a foot-and-mouth disease (FMD) outbreak in livestock in Indonesia. The outbreak, first reported in May 2022, is causing significant socioeconomic, animal health and biosecurity concerns in a country that has been FMD-free without vaccination since 1986. Delayed index case notification, difficulties with vaccination (e.g. accessibility issues, waning vaccine immunity and lack of cross-protection), limited understanding of persistent infection in carrier animals and lengthy restocking processes all present challenges for Indonesia in containing and recovering from this FMD outbreak. Thus, despite extensive research, the disease continues to present substantial challenges for outbreak prevention, surveillance and containment, which have important implications considering the widespread global prevalence of FMD and its impact on agriculture and trade in many countries. The socioeconomic burden of the current outbreak in Indonesia on individuals, households and communities is devastating, particularly in poor and rural areas. These impacts will likely continue after the outbreak is over, highlighting the need for co-ordinated support in strengthening outbreak detection and control in FMD-affected and other vulnerable areas.

Adaptive behaviors and vaccination on curbing COVID-19 transmission: Modeling simulations in eight countries

Current persistent outbreak of COVID-19 is triggering a series of collective responses to avoid infection. To further clarify the impact mechanism of adaptive protection behavior and vaccination, we developed a new transmission model via a delay differential system, which parameterized the roles of adaptive behaviors and vaccination, and allowed to simulate the dynamic infection process among people. By validating the model with surveillance data during March 2020 and October 2021 in America, India, South Africa, Philippines, Brazil, UK, Spain and Germany, we quantified the protection effect of adaptive behaviors by different forms of activity function. The modeling results indicated that (1) the adaptive activity function can be used as a good indicator for fitting the intervention outcome, which exhibited short-term awareness in these countries, and it could reduce the total human infections by 3.68, 26.16, 15.23, 4.23, 7.26, 1.65, 5.51 and 7.07 times, compared with the reporting; (2) for complete prevention, the average proportions of people with immunity should be larger than 90%, 92%, 86%, 71%, 92%, 84%, 82% and 76% with adaptive protection behaviors, or 91%, 97%, 94%, 77%, 92%, 88%, 85% and 90% without protection behaviors; and (3) the required proportion of humans being vaccinated is a sub-linear decreasing function of vaccine efficiency, with small heterogeneity in different countries. This manuscript was submitted as part of a theme issue on “Modelling COVID-19 and Preparedness for Future Pandemics”.

Outbreaks of human monkeypox during the COVID-19 pandemic: a systematic review for healthcare professionals.

The ongoing 2022 multicountry monkeypox epidemic has drawn worldwide attention. Human monkeypox is a virus that spreads from animals to humans. It is an endemic disease in the rain forests of Central and West Africa. However, the disease recently emerged in India, and also in United States through imported wild rodents from Africa, even though the world is still struggling to escape from the clutches of the COVID-19 pandemic. Monkeypox is one of the contagious zoonotic diseases caused by the monkeypox virus (MPXV), transmitted to humans by direct contact with an infected person or animal or contact with virus-contaminated material. Its lesions are similar to smallpox in humans with various medical complications including flu-like symptoms, fever, malaise, back pain, headache, and a characteristic rash. Public health experts around the world are very concerned about the rapid spread of the infection, which has intensified efforts to find the source and cause of this phenomenon. Several viral infections with epidemic potential threaten global health security. Early recognition of cases and timely intervention of potential transmission chains are necessary to contain further outbreaks. At this early stage of monkeypox outbreaks, the current review provides updated information on the current worldwide monkeypox outbreak status, disease aetiology, clinical presentation, therapy, and preventive measures worldwide. Our review will also provide useful information to health professionals and the general public.

Monkeypox a Concern for Donor-derived Infection?

Monkeypox a Concern for Donor-derived Infection?

Using WhatsApp Group & Google Meet during Online Class, Why Not?

Due to this current outbreak of Covid-19, the process of teaching and learning is now completely held online. For students, every teacher/lecturer must find the appropriate learning platform. Consequently, this article examines the effect of the Covid-19 pandemic on the college students’ perception in 2 English classes in Salatiga (an Islamic university) and Solo (a private university) during online learning. Researchers would respond to theories and facts emerging in the field, as well as answer problems that have not been solved in previous research. This type of research was descriptive qualitative. The data was collected using Google forms. Then, inductive analysis was used to test the data. The findings show that, despite the effects of the Covid-19 pandemic on online English classes, such as unstable signal problems and the need to be constantly in front of gadgets, students can understand the material. They also have a good time in online English classes because the lecturers in WhatsApp Groups (WAG) include games, puzzles, quizzes, and other interesting activities to keep them entertained during online classes. They can also learn the correct pronunciation by using WhatsApp Voice Note and Google Meet. During online learning, both lecturers and students face numerous challenges. They also suggested being creative in class and livening up the atmosphere, despite the fact that it was held online due to a massive pandemic.

Monkeypox: A challenge for and to geographers

AbstractThe World Health Organisation declared the 2022 Monkeypox outbreak a ‘Public Health Emergency of International Concern’, following the rapid spread of infections in non‐endemic countries. Unlike its usual epidemiology in Africa, most cases reported since May 2022 have been among gay, bisexual, and other men who have sex with men (GBMSM). This commentary provides an overview of the current Monkeypox outbreak and public health responses to it, drawing out their uneven geographies and the contribution geographers could make to understanding this. The empirical focus is on Monkeypox in England, but the challenges posed are relevant to the dynamics of the outbreak in the USA and Europe. The commentary concludes by challenging geographers to collaborate across sub‐disciplinary boundaries to undertake research that can understand and explain not only the specific dynamics of Monkeypox but also broader geographical aspects of GBMSM's lives that could underpin effective public health work with these populations.

Intersecting HIV and mpox epidemics: more questions than answers.

Intersecting HIV and mpox epidemics: more questions than answers.

Comparison of Monkeypox virus genomes from the 2017 Nigeria outbreak and the 2022 outbreak.

The current Monkeypox virus (MPX) outbreak is not only the largest known outbreak to date caused by a strain belonging to the West-African clade, but also results in remarkably different clinical and epidemiological features compared to previous outbreaks of this virus. Here, we consider the possibility that mutations in the viral genome may be responsible for its changed characteristics. Six genome sequences of isolates from the current outbreak were compared to five genomes of isolates from the 2017 outbreak in Nigeria and to two historic genomes, all belonging to the West-African clade. We report differences that are consistently present in the 2022 isolates but not in the others. Although some variation in repeat units was observed, only two were consistently found in the 2022 genomes only, and these were located in intergenic regions. A total of 55 single nucleotide polymorphisms were consistently present in the 2022 isolates compared to the 2017 isolates. Of these, 25 caused an amino acid substitution in a predicted protein. The nature of the substitution and the annotation of the affected protein identified potential candidates that might affect the virulence of the virus. These included the viral DNA helicase and transcription factors. This bioinformatic analysis provides guidance for wet-lab research to identify changed properties of the MPX.

Global monkeypox case hospitalisation rates: A rapid systematic review and meta-analysis.

Estimates of the case hospitalization rate and case fatality rate when hospital care is available for monkeypox (MPX) infections have not been well defined. This rapid systematic review and meta-analysis aimed to estimate the case hospitalisation rate and case fatality rate where hospital care is available. We systematically searched PubMed, Embase, the Lancet Preprints, and MedRxiv for studies published between Jan 1, 1950 and Aug 2, 2022. We included documents which contained both the number of cases and associated hospitalisations of MPX infections. From eligible studies we extracted the country, the year of the study, the study design type, the clade of MPX, the participant characteristics, transmission type, any treatments used, number of cases (including suspected, probable, or laboratory confirmed diagnosis), number of hospitalizations, hospitalized patient outcomes, and case definition. Case hospitalization rate (CHR) was defined as the proportion of cases that were admitted to hospital care while case fatality rate (CFR) was defined as the proportion of cases that died. CHR and CFR were analysed in a fully Bayesian meta-analytic framework using random effects models, including sub-group analysis with heterogeneity assessed using I2. Of the 259 unique documents identified, 19 studies were eligible for inclusion. Included studies represented 7553 reported cases among which there were 555 hospitalizations. Of the 7540 cases for which outcomes were available, there were 15 recorded deaths. The median age of cases was 35 years (interquartile range 28-38, n=2010) and primarily male (7339/7489, 98%) in studies where age or sex were available. Combined CHR was estimated to be 14.1% (95% credible interval, 7.5-25.0, I2 97.4%), with a high degree of heterogeneity. Further analysis by outbreak period indicates CHRs of 49.8% (28.2-74.0, I2 81.4%), 21.7% (7.2-52.1, I2 57.7%), and 5.8% (3.2-9.4, I2 92.4%) during the pre-2017, 2017-2021, and 2022 outbreaks, respectively, again with high levels of heterogeneity. CFR was estimated to be 0.03% (0.0-0.44, I2 99.9%), with evidence of large heterogeneity between the studies. There is limited data for MPX hospitalization rates in countries where MPX has been traditionally non-endemic until the current outbreak. Due to substantial heterogeneity, caution is needed when interpreting these findings. Health care organizations should be cognizant of the potential increase in healthcare utilization. Rapid identification of infection and use of appropriate therapies such as antivirals play a role reducing the CHR and associated CFR. None.

An Update on the Pharmacological Aspects of Vaccines and Antivirals for the Management of Monkeypox

Monkeypox is a self-limiting zoonotic disease caused by the monkeypox virus belonging to the genus of orthopox viruses. Initially considered an ‘African disease’, this infection has crossed the boundaries to affect other continents and it has raised tremendous concerns among the general public as well as the medical fraternity all over the world, particularly because of the lack of specific vaccinations and drugs for the management of the illness. Epidemiological evaluation of the current infection has reported that it is mainly transmitted through sexual contact in bisexual men, mostly whites, and in those with pre-existing human immunodeficiency virus infection. The most common presentations were skin rash, anogenital lesions, or mucosal lesions along with systemic symptoms. It has been established that the vaccines and drugs approved for the management of smallpox could be used for the management of the current monkeypox outbreak. Vaccinia Immune Globulin (VIG) and vaccines like JYNNEOS and ACAM2000 and antiviral drugs like tecovirimat, cidofovir (CDV), and brincidofovir are being considered for those patients with serious diseases. It is imperative for physicians to understand the pharmacological aspects of these drugs for delivering better care to patients with monkeypox, which is eventually essential for the containment of this infection. This review covers updates on vaccines as well as drugs for the prevention and management of monkeypox.

Monkeypox virus infection in women and non-binary people: uncommon or neglected?

Monkeypox virus infection in women and non-binary people: uncommon or neglected?

PulDi-COVID: Chronic obstructive pulmonary (lung) diseases with COVID-19 classification using ensemble deep convolutional neural network from chest X-ray images to minimize severity and mortality rates

Background and ObjectiveIn the current COVID-19 outbreak, efficient testing of COVID-19 individuals has proven vital to limiting and arresting the disease's accelerated spread globally. It has been observed that the severity and mortality ratio of COVID-19 affected patients is at greater risk because of chronic pulmonary diseases. This study looks at radiographic examinations exploiting chest X-ray images (CXI), which have become one of the utmost feasible assessment approaches for pulmonary disorders, including COVID-19. Deep Learning(DL) remains an excellent image classification method and framework; research has been conducted to predict pulmonary diseases with COVID-19 instances by developing DL classifiers with nine class CXI. However, a few claim to have strong prediction results; because of noisy and small data, their recommended DL strategies may suffer from significant deviation and generality failures. MethodsTherefore, a unique CNN model(PulDi-COVID) for detecting nine diseases (atelectasis, bacterial-pneumonia, cardiomegaly, covid19, effusion, infiltration, no-finding, pneumothorax, viral-Pneumonia) using CXI has been proposed using the SSE algorithm. Several transfer-learning models: VGG16, ResNet50, VGG19, DenseNet201, MobileNetV2, NASNetMobile, ResNet152V2, DenseNet169 are trained on CXI of chronic lung diseases and COVID-19 instances. Given that the proposed thirteen SSE ensemble models solved DL's constraints by making predictions with different classifiers rather than a single, we present PulDi-COVID, an ensemble DL model that combines DL with ensemble learning. The PulDi-COVID framework is created by incorporating various snapshots of DLmodels, which have spearheaded chronic lung diseases with COVID-19 cases identification process with a deep neural network produced CXI by applying a suggested SSE method.That is familiar with the idea of various DL perceptions on different classes. ResultsPulDi-COVID findings were compared to thirteen existing studies for nine-class classification using COVID-19. Test results reveal that PulDi-COVID offers impressive outcomes for chronic diseases with COVID-19 identification with a 99.70% accuracy, 98.68% precision, 98.67% recall, 98.67% F1 score, lowest 12 CXIs zero-one loss, 99.24% AUC-ROC score, and lowest 1.33% error rate. Overall test results are superior to the existing Convolutional Neural Network(CNN). To thebest of our knowledge, the observed results for nine-class classification are significantly superior to the state-of-the-art approaches employed for COVID-19 detection. Furthermore, the CXIthat we usedto assess our algorithm is one of the larger datasets for COVID detection with pulmonary diseases. ConclusionThe empirical findings of our suggested approach PulDi-COVIDshow that it outperforms previously developed methods. The suggested SSE method with PulDi-COVID can effectively fulfill the COVID-19 speedy detection needs with different lung diseases for physicians to minimize patient severity and mortality.

GenomeBits Characterization of MPXV

Genome sequences of the monkeypox virus (MPXV) causing the current outbreak are being reported from an increasing number of countries. We present a letter-to-numerical sequence study via GenomeBits signal mapping in order to characterize the evolution of the MPXV via simple statistical analysis. Histograms, empirical and theoretical cumulative distribution curves and the resulting scatter plots for the base nucleotides A and C versus their complementary base nucleotides T and G are discussed. GenomeBits may help the surveillance of emergent infectious diseases.

Ensemble Machine Learning for Monkeypox Transmission Time Series Forecasting

Public health is now in danger because of the current monkeypox outbreak, which has spread rapidly to more than 40 countries outside of Africa. The growing monkeypox epidemic has been classified as a “public health emergency of international concern” (PHEIC) by the World Health Organization (WHO). Infection outcomes, risk factors, clinical presentation, and transmission are all poorly understood. Computer- and machine-learning-assisted prediction and forecasting will be useful for controlling its spread. The objective of this research is to use the historical data of all reported human monkey pox cases to predict the transmission rate of the disease. This paper proposed stacking ensemble learning and machine learning techniques to forecast the rate of transmission of monkeypox. In this work, adaptive boosting regression (Adaboost), gradient boosting regression (GBOOST), random forest regression (RFR), ordinary least square regression (OLS), least absolute shrinkage selection operator regression (LASSO), and ridge regression (RIDGE) were applied for time series forecasting of monkeypox transmission. Performance metrics considered in this study are root mean square (RMSE), mean absolute error (MAE), and mean square error (MSE), which were used to evaluate the performance of the machine learning and the proposed Stacking Ensemble Learning (SEL) technique. Additionally, the monkey pox dataset was used as test data for this investigation. Experimental results revealed that SEL outperformed other machine learning approaches considered in this work with an RMSE of 33.1075; a MSE of 1096.1068; and a MAE of 22.4214. This is an indication that SEL is a better predictor than all the other models used in this study. It is hoped that this research will help government officials understand the threat of monkey pox and take the necessary mitigation actions.

Maximizing the impact of limited vaccine supply under different early epidemic conditions: a 2-city modelling analysis of monkeypox virus transmission among men who have sex with men.

The current global monkeypox virus (MPXV) outbreak has disproportionately affected gay, bisexual and other men who have sex with men (GBMSM). Given that many jurisdictions have been faced with limited supplies of MPXV vaccine, we aimed to explore optimal vaccine allocation between 2 linked GBMSM transmission networks over a short-term time horizon, across several epidemic conditions. We constructed a deterministic compartmental MPXV transmission model. We parameterized the model to reflect 2 representative, partially connected GBMSM sexual networks ( cities), using 2022 data from Ontario. We simulated a roll-out of 5000 vaccine doses over 30 days that started 45 days after epidemic seeding with 10 imported cases. Within this model, we varied the relative city (network) sizes, epidemic potentials (R 0), between-city mixing and distribution of seed cases between cities. For each combination of varied factors, we identified the allocation of doses between cities that maximized infections averted by day 90. Under our modelling assumptions, we found that a limited MPXV vaccine supply could generally avert more early infections when prioritized to networks that were larger, had more initial infections or had greater R 0. Greater between-city mixing decreased the influence of initial seed cases and increased the influence of city R 0 on optimal allocation. Under mixed conditions (e.g., fewer seed cases but greater R 0), optimal allocation required doses shared between cities. In the context of the current global MPXV outbreak, we showed that prioritization of a limited supply of vaccines based on network-level factors can help maximize infections averted during an emerging epidemic. Such prioritization should be grounded in an understanding of context-specific risk drivers and should acknowledge potential connectedness of multiple transmission networks.

Peran Diaspora Di Masa Pandemi Covid-19

This paper tries to understand the phenomenon of the role of the diaspora in the Covid-19 pandemic. With the current pandemic outbreak, humans are always challenged to carry out various forms of adaptation that allow themselves to remain active and productive from within the home. The term diaspora is often used to denote different phenomena depending on the interests and focus of the study. “Diaspora” are immigrants, namely people who leave their homeland to go to another region or country in search of a better life, rather than in their own region or country. A number of migration and diaspora studies conclude that international migration that occurs in the era of globalization can not only expand the distribution of diaspora, but can also strengthen their existence. Another existence of the diaspora is related to their role in realizing a symbiosis that is beneficial for both the destination country and the country of origin. The Indonesian diaspora has the potential to be empowered for national defense. In this analysis using descriptive qualitative analysis method, using data collection techniques on the study of literature. The diaspora is not only a large global community but an extraordinary movement and idealism. Some parties use the term transnational communities to refer to the experiences of citizens who are doing contemporary migration or who have chosen to move from their country of origin but who still maintain a relationship or relationship with the land where they were born.

Monkeypox: A Mini-Review on the Globally Emerging Orthopoxvirus

Monkeypox is a zoonotic infectious disease belonging to the orthopoxvirus family that has predominantly occurred in West and Central Africa since it was initially discovered in 1958. In May 2022, a global outbreak of monkeypox began to occur on an international scale, with case numbers still rising as this review is being written. This mini review sought to analyze the existing literature on monkeypox published from 2017 onward to provide epidemiological context to current outbreaks. PubMed and Google Scholar databases were used to gather both peer-reviewed and grey literature on the routes of transmission, case definitions, clinical characteristics, diagnosis, management, prevention, vaccination, and epidemiology of monkeypox. Epidemiological studies indicate that the age of onset of monkeypox has increased over time. Antivirals, such as Tecovirimat and Brincidofovir, are recommended to manage confirmed cases of monkeypox. Although mass vaccination is not currently recommended, the smallpox vaccine can be used as a preventative measure for at-risk groups, such as men who have sex with men and frontline healthcare workers. Further peer-reviewed research addressing animal reservoirs and sexual transmission dynamics is needed.