Modelling disease mitigation at mass gatherings: A case study of COVID-19 at the 2022 FIFA World Cup.

The 2022 FIFA World Cup was the first major multi-continental sporting Mass Gathering Event (MGE) of the post COVID-19 era to allow foreign spectators. Such large-scale MGEs can potentially lead to outbreaks of infectious disease and contribute to the global dissemination of such pathogens. Here we adapt previous work and create a generalisable model framework for assessing the use of disease control strategies at such events, in terms of reducing infections and hospitalisations. This framework utilises a combination of meta-populations based on clusters of people and their vaccination status, Ordinary Differential Equation integration between fixed time events, and Latin Hypercube sampling. We use the FIFA 2022 World Cup as a case study for this framework (modelling each match as independent 7 day MGEs). Pre-travel screenings of visitors were found to have little effect in reducing COVID-19 infections and hospitalisations. With pre-match screenings of spectators and match staff being more effective. Rapid Antigen (RA) screenings 0.5 days before match day performed similarly to RT-PCR screenings 1.5 days before match day. Combinations of pre-travel and pre-match testing led to improvements. However, a policy of ensuring that all visitors had a COVID-19 vaccination (second or booster dose) within a few months before departure proved to be much more efficacious. The State of Qatar abandoned all COVID-19 related travel testing and vaccination requirements over the period of the World Cup. Our work suggests that the State of Qatar may have been correct in abandoning the pre-travel testing of visitors. However, there was a spike in COVID-19 cases and hospitalisations within Qatar over the World Cup. Given our findings and the spike in cases, we suggest a policy requiring visitors to have had a recent COVID-19 vaccination should have been in place to reduce cases and hospitalisations.

Photoswitchable Temperature Nanosensors Based on the Chemical Kinetics of Photochromic Naphthopyran for Live Cell Imaging.

Microscopic temperature imaging holds significant importance in various fields, particularly in the development of nanomaterials for photothermal therapy (PTT). In this study, we present an analytical method to probe cellular temperature based on chemical kinetics and additional luminescence quenching by photoswitchable naphthopyrans. Taking advantage of the rapid ring-closing reaction of naphthopyran, temperature sensing was realized with a linear relationship between the logarithmic decay time constant (ln τ) and the reciprocal temperature (T-1). To create luminescent temperature nanosensors, we harnessed the ability of ring-opened naphthopyran to quench the luminescence of a semiconducting polymer, resulting in a diverse array of probes. Structural modifications on the naphthopyran also provided a way to fine-tune the sensitivity and response window of the nanosensors. The method allowed cellular temperature imaging on a cost-effective fluorescence microscopic setup. As an application, the temperature increase induced by gold nanorods (AuNRs) in cell lysosomes was successfully monitored, laying the foundation for a new class of photoswitchable nanosensors with promising biological applications.

Randomized clinical trial on D2 lymphadenectomy versus D2 lymphadenectomy plus complete mesogastric excision in patients undergoing gastrectomy for cancer (DCGC01 study).

BACKGROUND: It is unknown whether D2 lymphadenectomy + complete mesogastric excision for gastric cancer improves survival compared with just D2 lymphadenectomy. METHODS: Between September 2014 and June 2018, patients with advanced gastric cancer were randomly assigned (1 : 1) to laparoscopic D2 lymphadenectomy or D2 lymphadenectomy + complete mesogastric excision gastrectomy. The modified intention-to-treat population was defined as patients who had pathologically confirmed gastric adenocarcinoma (pT1 N1-3 M0 and pT2-4 N0-3 M0). The primary endpoint was 3-year disease-free survival. Secondary endpoints were the recurrence pattern and overall survival. RESULTS: The median follow-up of patients in the D2 lymphadenectomy group (169 patients) and patients in the D2 lymphadenectomy +complete mesogastric excision group (169 patients) was 55 (interquartile range 37-60) months and 51 (interquartile range 40-60) months respectively. Recurrence occurred in 50 patients in the D2 lymphadenectomy group (29.6%) versus 33 patients in the D2 lymphadenectomy + complete mesogastric excision group (19.5%) (P = 0.032). The 3-year disease-free survival was 75.5% (95% c.i. 68.3% to 81.3%) in the D2 lymphadenectomy group versus 85.0% (95% c.i. 78.7% to 89.6%) in the D2 lymphadenectomy + complete mesogastric excision group (log rank P = 0.042). The HR for recurrence in the D2 lymphadenectomy + complete mesogastric excision group versus the D2 lymphadenectomy group was 0.64 (95% c.i. 0.41 to 0.99) by Cox regression (P = 0.045). The 3-year overall survival rate was 77.5% (95% c.i. 70.4% to 83.1%) in the D2 lymphadenectomy group versus 85.8% (95% c.i. 79.6% to 90.2%) in the D2 lymphadenectomy + complete mesogastric excision group (log rank P = 0.058). The HR for death in the D2 lymphadenectomy + complete mesogastric excision group versus the D2 lymphadenectomy group was 0.64 (95% c.i. 0.41 to 1.02) (P = 0.058). CONCLUSION: Compared with conventional D2 dissection, D2 lymphadenectomy + complete mesogastric excision is associated with better disease-free survival, but there is no statistically significant difference in overall survival. REGISTRATION NUMBER: NCT01978444 (http://www.clinicaltrials.gov).

Evaluating infectious disease outbreak potential and mitigation effectiveness on cruise ships.

The cruise ship sector is a major part of the tourism industry, and an estimated over 30 million passengers are transformed worldwide each year. Cruise ships bring diverse populations into proximity for many days, facilitating the transmission of respiratory illnesses. The objective of this study is to develop a modeling framework to inform the development of viable disease risk management policies and measures to control disease outbreaks on cruises. Our model, parameterized and calibrated using the data of the COVID-19 outbreak on the Diamond Princess cruise ship in 2020, is used to assess the impact of the mitigation measures such as mask wearing, vaccination, on-board and pre-traveling testing measures. Our results indicate mask wearing in public places as the cheapest and most affordable measure can drop the number of cumulative confirmed cases by almost 50%. This measure along with the vaccination by declining the number of the cumulative confirmed cases by more than 94% is the most effective measure to control outbreaks on cruises. According to our findings, outbreaks are more predominant in the passenger population than the crew members, however, the protection measures are more beneficial if they are applied by both crew members and passengers. Regarding the testing measure, pre-traveling testing is more functional than the on-board testing to control outbreaks on cruises.

Choice intention for the national volume-based procurement drug and its associated factors: a cross-sectional study on patients with late-life depression in China.

BACKGROUND: The national volume-based procurement (NVBP) policy has significantly decreased prices and increased the accessibility of NVBP drugs. Nevertheless, issues such as heightened adverse reactions and suboptimal efficacy have arisen. Concerns regarding the quality of low-cost medications and the absence of long-term research have been widely recognized. This has led to caution among patients with late-life depression (LLD) due to their delicate health and the severity of their condition. This study evaluated the choice intention for NVBP drugs and associated factors in older patients with LLD. METHODS: A weighted sample of 408 participants between December 2022 and March 2023 were included. Data were collected via face-to-face interviews and questionnaires. To identify significant associated factors of choice intention, a multilevel logistic regression model was employed. RESULTS: Over half (53.68%) of older patients with LLD intended to choose NVBP drugs. Associated factors included self-assessed poor economy, higher out-of-pocket expenses, monthly household income exceeding CNY 6000, absence of other non-communicable chronic diseases, ordinary registration, urban employee medical insurance, no requirements for brand-name drugs, adverse reactions after using NVBP drugs, and rejection of physicians' recommendation for NVBP drugs. The interaction effect between the real economic condition and patients self-assessed economy significantly influences choice intention for NVBP drugs. Among 124 patients with self-assessed poor economy, 75 showed a higher intention to use NVBP drugs. In these patients, age, medical insurance reimbursement, and brand awareness were significantly associated with choice intention. CONCLUSION: Economic factors, physical conditions, medical needs, and physician recommendations significantly influenced the choice intention for NVBP drugs. The choice intention can be improved by strengthening physician-patient communication, increasing the scope and proportion of medical insurance reimbursement, improving substitution studies, and conducting post-marketing re-evaluations of NVBP drugs.

Viral infection dynamics with immune chemokines and CTL mobility modulated by the infected cell density.

We study a viral infection model incorporating both cell-to-cell infection and immune chemokines. Based on experimental results in the literature, we make a standing assumption that the cytotoxic T lymphocytes (CTL) will move toward the location with more infected cells, while the diffusion rate of CTL is a decreasing function of the density of infected cells. We first establish the global existence and ultimate boundedness of the solution via a priori energy estimates. We then define the basic reproduction number of viral infection R 0 and prove (by the uniform persistence theory, Lyapunov function technique and LaSalle invariance principle) that the infection-free steady state E 0 is globally asymptotically stable if R 0 < 1 . When R 0 > 1 , then E 0 becomes unstable, and another basic reproduction number of CTL response R 1 becomes the dynamic threshold in the sense that if R 1 < 1 , then the CTL-inactivated steady state E 1 is globally asymptotically stable; and if R 1 > 1 , then the immune response is uniform persistent and, under an additional technical condition the CTL-activated steady state E 2 is globally asymptotically stable. To establish the global stability results, we need to prove point dissipativity, obtain uniform persistence, construct suitable Lyapunov functions, and apply the LaSalle invariance principle.

Serotonin syndrome caused by escitalopram in Parkinson's disease psychosis: a case report.

BACKGROUND: Serotonin syndrome and Parkinson's disease (PD) are two diseases whose symptoms partially overlap; this poses challenges in distinguishing them in clinical practice. Early manifestations such as tremor, akathisia, diaphoresis, hypertonia and hyperreflexia are common in mild-to-moderate serotonin syndrome and can also occur in PD. Without prompt recognition and treatment, serotonin syndrome can rapidly progress, potentially leading to severe complications such as multiple organ failure within hours. Given their disparate treatment strategies, accurate clinical distinction is crucial for effective treatment. This case study explores a patient with serotonin syndrome triggered by escitalopram in the context of PD psychosis (PDP), providing insights into diagnosis and treatment planning. CASE PRESENTATION: A 75-year-old Asian woman with a one-year history of PD, a two-month history of PDP, and a six-year history of depression presented with symptoms including hyperreflexia, tremor, hypertonia, impaired level of consciousness, and inappropriate behavior following a recent one-month adjustment in medication. Initially suspected of being drug-induced parkinsonism or worsening PD, therapeutic drug monitoring revealed warning levels of escitalopram. Subsequent diagnoses confirmed serotonin syndrome. This syndrome may result from increased cortical serotonin activity at the serotonin2A receptor due to dopamine and serotonin imbalances in PDP, compounded by increased dopamine-mediated serotonin release. Additionally, being an intermediate metabolizer of cytochrome P450 enzyme 2C19, the patient experienced excessive escitalopram accumulation, exacerbating her condition. CONCLUSIONS: This case underscores the critical need to differentiate between symptoms of serotonin syndrome and PD, particularly in manifestations like tremor and hypertonia. Careful consideration of receptor profiles in patients with PDP is essential when selecting antidepressants to mitigate the risk of serotonin syndrome.

Impact assessment of self-medication on COVID-19 prevalence in Gauteng, South Africa, using an age-structured disease transmission modelling framework.

OBJECTIVE: To assess the impact of self-medication on the transmission dynamics of COVID-19 across different age groups, examine the interplay of vaccination and self-medication in disease spread, and identify the age group most prone to self-medication. METHODS: We developed an age-structured compartmentalized epidemiological model to track the early dynamics of COVID-19. Age-structured data from the Government of Gauteng, encompassing the reported cumulative number of cases and daily confirmed cases, were used to calibrate the model through a Markov Chain Monte Carlo (MCMC) framework. Subsequently, uncertainty and sensitivity analyses were conducted on the model parameters. RESULTS: We found that self-medication is predominant among the age group 15-64 (74.52%), followed by the age group 0-14 (34.02%), and then the age group 65+ (11.41%). The mean values of the basic reproduction number, the size of the first epidemic peak (the highest magnitude of the disease), and the time of the first epidemic peak (when the first highest magnitude occurs) are 4.16499, 241,715 cases, and 190.376 days, respectively. Moreover, we observed that self-medication among individuals aged 15-64 results in the highest spreading rate of COVID-19 at the onset of the outbreak and has the greatest impact on the first epidemic peak and its timing. CONCLUSION: Studies aiming to understand the dynamics of diseases in areas prone to self-medication should account for this practice. There is a need for a campaign against COVID-19-related self-medication, specifically targeting the active population (ages 15-64).

Is monkeypox a new, emerging sexually transmitted disease? A rapid review of the literature.

Monkeypox, a milder disease compared to smallpox, is caused by a virus initially discovered and described in 1958 by the prominent Danish virologist von Magnus, who was investigating an infectious outbreak affecting monkey colonies. Currently, officially starting from May 2022, an outbreak of monkeypox is ongoing, with 51 000 cases being notified as of September 1, 2022-51 408 confirmed, 28 suspected, and 12 fatalities, for a grand total of 51 448 cases. More than 100 countries and territories are affected, from all the six World Health Organization regions. There are some striking features, that make this outbreak rather unusual when compared with previous outbreaks, including a shift on average age and the most affected age group, affected sex/gender, risk factors, clinical course, presentation, and the transmission route. Initially predominantly zoonotic, with an animal-to-human transmission, throughout the last decades, human-to-human transmission has become more and more sustained and effective. In particular, clusters of monkeypox have been described among men having sex with men, some of which have been epidemiologically linked to international travel to nonendemic countries and participation in mass gathering events/festivals, like the "Maspalomas (Gran Canaria) 2022 pride." This review will specifically focus on the "emerging" transmission route of the monkeypox virus, that is to say, the sexual transmission route, which, although not confirmed yet, seems highly likely in the diffusion of the infectious agent.

Epidemiological trends and clinical features of the ongoing monkeypox epidemic: A preliminary pooled data analysis and literature review.

An emerging outbreak of monkeypox infection is quickly spreading worldwide, being currently reported in more than 30 countries, with slightly less than 1000 cases. In the present preliminary report, we collected and synthesized early data concerning epidemiological trends and clinical features of the ongoing outbreak and we compared them with those of previous outbreaks. Data were pooled from six clusters in Italy, Australia, the Czech Republic, Portugal, and the United Kingdom, totaling 124 cases (for 35 of which it was possible to retrieve detailed information). The ongoing epidemic differs from previous outbreaks in terms of age (54.29% of individuals in their thirties), sex/gender (most cases being males), risk factors, and transmission route, with sexual transmission being highly likely. Also, the clinical presentation is atypical and unusual, being characterized by anogenital lesions and rashes that relatively spare the face and extremities. The most prevalent sign/symptom reported was fever (in 54.29% of cases) followed by inguinal lymphadenopathy (45.71%) and exanthema (40.00%). Asthenia, fatigue, and headache were described in 22.86% and 25.71% of the subjects, respectively. Myalgia was present in 17.14% of the cases. Both genital and anal lesions (ulcers and vesicles) were reported in 31.43% of the cases. Finally, cervical lymphadenopathy was described in 11.43% of the sample, while the least commonly reported symptoms were diarrhea and axillary lymphadenopathy (5.71% of the case series for both symptoms). Some preliminary risk factors can be identified (being a young male, having sex with other men, engaging in risky behaviors and activities, including condomless sex, human immunodeficiency virus positivity (54.29% of the sample analyzed), and a story of previous sexually transmitted infections, including syphilis). On the other hand, being fully virally suppressed and undetectable may protect against a more severe infectious course. However, further research in the field is urgently needed.

Adaptive changes in sexual behavior in the high-risk population in response to human monkeypox transmission in Canada can help control the outbreak: Insights from a two-group, two-route epidemic model.

Monkeypox, a zoonotic disease, is emerging as a potential sexually transmitted infection/disease, with underlying transmission mechanisms still unclear. We devised a risk-structured, compartmental model, incorporating sexual behavior dynamics. We compared different strategies targeting the high-risk population: a scenario of control policies geared toward the use of condoms and/or sexual abstinence (robust control strategy) with risk compensation behavior change, and a scenario of control strategies with behavior change in response to the doubling rate (adaptive control strategy). Monkeypox's basic reproduction number is 1.464, 0.0066, and 1.461 in the high-risk, low-risk, and total populations, respectively, with the high-risk group being the major driver of monkeypox spread. Policies imposing condom use or sexual abstinence need to achieve a 35% minimum compliance rate to stop further transmission, while a combination of both can curb the spread with 10% compliance to abstinence and 25% to condom use. With risk compensation, the only option is to impose sexual abstinence by at least 35%. Adaptive control is more effective than robust control where the daily sexual contact number is reduced proportionally and remains constant thereafter, shortening the time to epidemic peak, lowering its size, facilitating disease attenuation, and playing a key role in controlling the current outbreak.

Clinical applications and utility of ctDNA in cervical cancer and its precursor lesions: from screening to predictive biomarker.

Cervical cancer is a leading cause of gynecological cancer death in the world. Human papillomavirus (HPV) is the most causative factor of cervical cancer. In addition, many genetic factors are involved in cervical cancer development. Most studies focus on cervical samples to do research work about cervical cancer and precancerous lesions, but no sensitive or specific biomarkers were found. High-throughput genomic technologies are able to capture information from tumors and precancerous lesions in blood, thus providing a new way for the early diagnosis of cervical precancer and cervical cancer. Blood is an ideal specimen for detecting cancer biomarkers because it contains a lot of information, such as circulating tumor cells and circulating tumor DNA (ctDNA). This article reviews the clinical use and challenges of blood ctDNA testing in patients with cervical precancer and cervical cancer.

Epidemic dynamics with time-varying transmission risk reveal the role of disease stage-dependent infectiousness.

A key characteristic of acute communicable diseases is the infectiousness that varies over time as the infection dynamics evolve within a host, which influences the risk of transmission in different stages of the disease. Despite the evidence of time-varying transmission risk, most dynamic models of epidemics assume a constant transmission rate during the infectious period. Recent work has shown the difference in epidemic dynamics when this assumption is relaxed and different transmission rates are used by discretizing the infectious period into multiple sub-periods. Here, we develop an age-structured model to integrate a continuous time-varying transmission risk, based on an established correlation between the viral dynamics and infectiousness profile. Taking into account the natural history and parameter estimates of COVID-19 caused by the original strain of SARS-CoV-2, we demonstrate the difference in temporal epidemic dynamics when a continuous time-varying transmission probability is used as compared to multiple constant transmission probabilities. Our results show a significant difference between the incidence curves in terms of the magnitude and peak time, even when the reproduction number and total number of infections are the same for continuous and discrete transmission probabilities. Finally, we demonstrate the spurious outcome of preventing an epidemic through the isolation of infectious individuals when constant transmission probabilities are used, highlighting the importance of integrating a continuous time-dependent transmission parameter in dynamic models. These findings suggest a more cautious interpretation of model outcomes, especially those that are intended to evaluate the effectiveness of interventions and inform policy decisions for disease mitigation strategies.

Hot-topics cross-propagation and opinion-transfer dynamics in the Chinese Sina-microblog social media: A modeling study.

On social media platforms, hot topics often contain several pieces of related information that can influence internet users, generating either positive or negative opinion orientation. Some of them will choose to retain or change their original opinions after exposure to multiple related messages. To describe the opinion-transfer transient and collective behaviors in this scenario, this paper proposes an opinion-transfer susceptible-forwarding-immunized (OT-SFI) information cross-propagation model. Real multiple information in messages with opinions obtained from the Chinese Sina microblog is used for data fitting to illustrate how model parameters can be estimated and used to predict the accumulative numbers of users with a particular view. The study attempts to relate changes in group views in the network to initial opinion distribution and individuals' opinion choices at the macro level. Furthermore, the model parameters at the micro level are used to measure the probability of "retention" and "reversal" of views in events, as well as the extent to which the masses are influenced by new information views. The result illustrates that the viewpoint distribution of the initial message and the opinion selection of the new message opinion leaders play crucial roles in promoting attention to the topic and driving for a desired collective opinion.

Workplace absenteeism due to COVID-19 and influenza across Canada: A mathematical model.

The continual distress of COVID-19 cannot be overemphasized. The pandemic economic and social costs are alarming, with recent attributed economic loss amounting to billions of dollars globally. This economic loss is partly driven by workplace absenteeism due to the disease. Influenza is believed to be a culprit in reinforcing this phenomenon as it may exist in the population concurrently with COVID-19 during the influenza season. Furthermore, their joint infection may increase workplace absenteeism leading to additional economic loss. The objective of this project will aim to quantify the collective impact of COVID-19 and influenza on workplace absenteeism via a mathematical compartmental disease model incorporating population screening and vaccination. Our results indicate that appropriate PCR testing and vaccination of both COVID-19 and seasonal influenza may significantly alleviate workplace absenteeism. However, with COVID-19 PCR testing, there may be a critical threshold where additional tests may result in diminishing returns. Regardless, we recommend on-going PCR testing as a public health intervention accompanying concurrent COVID-19 and influenza vaccination with the added caveat that sensitivity analyses will be necessary to determine the optimal thresholds for both testing and vaccine coverage. Overall, our results suggest that rates of COVID-19 vaccination and PCR testing capacity are important factors for reducing absenteeism, while the influenza vaccination rate and the transmission rates for both COVID-19 and influenza have lower and almost equal affect on absenteeism. We also use the model to estimate and quantify the (indirect) benefit that influenza immunization confers against COVID-19 transmission.

Ingenious use of autocatalytic hydrodeoxygenation for the separation and recovery of oil and iron from rolling oil sludge.

This paper introduces a transformative hydrodeoxygenation process for the simultaneous recovery of oil and iron from hazardous rolling oil sludge (ROS). Leveraging the inherent catalytic capabilities of iron/iron oxide nanoparticles in the sludge, our process enables the conversion of fatty acids and esters into hydrocarbons under conditions of 4.5 MPa, 330 °C, and 500 rpm. This reaction triggers nanoparticle aggregation and subsequent separation from the oil phase, allowing for effective resource recovery. In contrast to conventional techniques, this method achieves a high recovery rate of 98.3% while dramatically reducing chemical reagent consumption. The reclaimed petroleum and iron-ready for high-value applications-are worth 3910 RMB/ton. Moreover, the process facilitates the retrieval of nanoscale magnetic Fe and Fe0 particles, and the oil, with an impressive hydrocarbon content of 87.8%, can be further refined. This energy-efficient approach offers a greener, more sustainable pathway for ROS valorization.

A coupled algebraic-delay differential system modeling tick-host interactive behavioural dynamics and multi-stability.

We propose a coupled system of delay-algebraic equations to describe tick attaching and host grooming behaviors in the tick-host interface, and use the model to understand how this tick-host interaction impacts the tick population dynamics. We consider two critical state variables, the loads of feeding ticks on host and the engorged ticks on the ground for ticks in a particular development stage (nymphal stage) and show that the model as a coupled system of delay differential equation and an algebraic (integral) equation may have rich structures of equilibrium states, leading to multi-stability. We perform asymptotic analyses and use the implicit function theorem to characterize the stability of these equilibrium states, and show that bi-stability and quadri-stability occur naturally in several combinations of tick attaching and host grooming behaviours. In particular, we show that in the case when host grooming is triggered by the tick biting, the system will have three stable equilibrium states including the extinction state, and two unstable equilibrium states. In addition, the two nontrivial stable equilibrium states correspond to a low attachment rate and a large number of feeding ticks, and a high attachment rate and a small number of feeding ticks, respectively.

Optimal control by deep learning techniques and its applications on epidemic models.

We represent the optimal control functions by neural networks and solve optimal control problems by deep learning techniques. Adjoint sensitivity analysis is applied to train the neural networks embedded in differential equations. This method can not only be applied in classic epidemic control problems, but also in epidemic forecasting, discovering unknown mechanisms, and the ideas behind can give new insights to traditional mathematical epidemiological problems.

Mpox Panic, Infodemic, and Stigmatization of the Two-Spirit, Lesbian, Gay, Bisexual, Transgender, Queer or Questioning, Intersex, Asexual Community: Geospatial Analysis, Topic Modeling, and Sentiment Analysis of a Large, Multilingual Social Media Database.

BACKGROUND: The global Mpox (formerly, Monkeypox) outbreak is disproportionately affecting the gay and bisexual men having sex with men community. OBJECTIVE: The aim of this study is to use social media to study country-level variations in topics and sentiments toward Mpox and Two-Spirit, Lesbian, Gay, Bisexual, Transgender, Queer or Questioning, Intersex, Asexual (2SLGBTQIAP+)-related topics. Previous infectious outbreaks have shown that stigma intensifies an outbreak. This work helps health officials control fear and stop discrimination. METHODS: In total, 125,424 Twitter and Facebook posts related to Mpox and the 2SLGBTQIAP+ community were extracted from May 1 to December 25, 2022, using Twitter application programming interface academic accounts and Facebook-scraper tools. The tweets' main topics were discovered using Latent Dirichlet Allocation in the sklearn library. The pysentimiento package was used to find the sentiments of English and Spanish posts, and the CamemBERT package was used to recognize the sentiments of French posts. The tweets' and Facebook posts' languages were understood using the Twitter application programming interface platform and pycld3 library, respectively. Using ArcGis Online, the hot spots of the geotagged tweets were identified. Mann-Whitney U, ANOVA, and Dunn tests were used to compare the sentiment polarity of different topics and countries. RESULTS: The number of Mpox posts and the number of posts with Mpox and 2SLGBTQIAP+ keywords were 85% correlated (P<.001). Interestingly, the number of posts with Mpox and 2SLGBTQIAP+ keywords had a higher correlation with the number of Mpox cases (correlation=0.36, P<.001) than the number of posts on Mpox (correlation=0.24, P<.001). Of the 10 topics, 8 were aimed at stigmatizing the 2SLGBTQIAP+ community, 3 of which had a significantly lower sentiment score than other topics (ANOVA P<.001). The Mann-Whitney U test shows that negative sentiments have a lower intensity than neutral and positive sentiments (P<.001) and neutral sentiments have a lower intensity than positive sentiments (P<.001). In addition, English sentiments have a higher negative and lower neutral and positive intensities than Spanish and French sentiments (P<.001), and Spanish sentiments have a higher negative and lower positive intensities than French sentiments (P<.001). The hot spots of the tweets with Mpox and 2SLGBTQIAP+ keywords were recognized as the United States, the United Kingdom, Canada, Spain, Portugal, India, Ireland, and Italy. Canada was identified as having more tweets with negative polarity and a lower sentiment score (P<.04). CONCLUSIONS: The 2SLGBTQIAP+ community is being widely stigmatized for spreading the Mpox virus on social media. This turns the community into a highly vulnerable population, widens the disparities, increases discrimination, and accelerates the spread of the virus. By identifying the hot spots and key topics of the related tweets, this work helps decision makers and health officials inform more targeted policies.

Big data- and artificial intelligence-based hot-spot analysis of COVID-19: Gauteng, South Africa, as a case study.

The coronavirus disease 2019 (COVID-19) has developed into a pandemic. Data-driven techniques can be used to inform and guide public health decision- and policy-makers. In generalizing the spread of a virus over a large area, such as a province, it must be assumed that the transmission occurs as a stochastic process. It is therefore very difficult for policy and decision makers to understand and visualize the location specific dynamics of the virus on a more granular level. A primary concern is exposing local virus hot-spots, in order to inform and implement non-pharmaceutical interventions. A hot-spot is defined as an area experiencing exponential growth relative to the generalised growth of the pandemic. This paper uses the first and second waves of the COVID-19 epidemic in Gauteng Province, South Africa, as a case study. The study aims provide a data-driven methodology and comprehensive case study to expose location specific virus dynamics within a given area. The methodology uses an unsupervised Gaussian Mixture model to cluster cases at a desired granularity. This is combined with an epidemiological analysis to quantify each cluster's severity, progression and whether it can be defined as a hot-spot.