Control Disease Spread Research Articles

Effect of Vaccination and Culling on the Dynamics of Rabies Transmission from Stray Dogs to Domestic Dogs

In this paper, the population dynamics of rabies-infected dogs are studied. The mathematical model is constructed by dividing the dog population into two categories: stray dogs and domestic dogs. On the other hand, the rabies virus is likely to spread in both populations. In the current model, disease-controlling strategies such as vaccination and culling are applied, and their impact is studied. Both subpopulations of susceptible individuals are vaccinated to control disease spread. The current study assumes that stray dogs can transmit rabies to domestic dogs but not the other way around. Because domestic dogs are under the control of their owners, they are well vaccinated. The model is medically and analytically correct because the findings are idealistic and limited. The next-generation matrix technique is used to compute the effective reproductive amount, and also, each parameter is subjected to sensitivity analysis. The equilibrium point free from disease is discovered, demonstrating that it was asymptotically steady locally and globally. A conditionally global asymptotically stable point of endemic equilibrium is also discovered using the Lyapunov function method. The numerical simulation, which makes use of approximations for parameter values, shows that the most efficient method for avoiding rabies transmission is a combination of vaccination and the culling of infected stray dogs. Using MATLAB’s ode45, this numerical simulation investigation was carried out. Our early findings indicated that the annual dog birth rate is a critical factor in influencing the occurrence of rabies. In the body of the paper, the findings and discussion are organized logically.

Detection of Chicken Respiratory Pathogens in Live Markets of Addis Ababa, Ethiopia, and Epidemiological Implications.

Simple SummaryIt is unclear what microorganisms are associated with respiratory disease in chickens sold in live markets of Addis Ababa, Ethiopia. Identifying microorganisms in diseased animals is the first step to delineating programs to control disease spread. Two Addis Ababa markets were visited weekly for three months to understand better the microorganisms found in chickens with respiratory disease. During this time, 18 sick chickens were acquired and tested for common microorganisms that cause respiratory disease in chickens. Three or more microorganisms, including viruses and bacteria, were detected in 17 of the 18 cases, showing that detection of multiple pathogens is widespread in live markets. These microorganisms possibly cause substantial productive loss in Ethiopia. Further studies are warranted to investigate their contribution to disease and economic losses in the country.A moderate to high seroprevalence of exposure to Newcastle disease (NDV), avian metapneumovirus (aMPV), infectious laryngotracheitis virus (ILTV), infectious bronchitis virus (IBV) and Mycoplasma gallisepticum (MG) has recently been reported in Ethiopia, but it is unclear to what extent these contribute to clinical cases of respiratory disease. This study investigated the presence of these pathogens in chickens exhibiting respiratory disease in two live markets in Addis Ababa. Markets were visited weekly for three months, and 18 chickens displaying respiratory clinical signs were acquired. Swab samples were taken from the choana, trachea, air sac and larynx for bacteriology and PCR tests targeting these five pathogens. PCR-positive samples were sequenced. All 18 chickens were PCR-positive for aMPV, 50% for each of Mg and NDV, 39% for IBV and 11% for ILTV. Infections with >3 pathogens were detected in 17 of 18 chickens. Potentially pathogenic bacteria such as Escherichia coli, Klebsiella spp., Streptococcus spp. and Staphylococcus were found in 16 to 44% of chickens. IBV-positive samples were of the 793B genotype. The results associate the presence of these organisms with clinical respiratory disease and are consistent with recent serological investigations, indicating a high level of exposure to multiple respiratory pathogens.

Privacy and contact tracing efficacy.

As the COVID-19 pandemic emerged, public health authorities and software designers considered the possibility that smartphones could be used for contact tracing to control disease spread. Smartphone-based contact tracing was attractive in part because it promised to allow the tracing of contacts that might not be reported using traditional contact tracing methods. Comprehensive contact tracing raises distinctive privacy concerns, however, that have not been previously explored. Contacts outside of an individual's ordinary social network are more likely to be privacy-sensitive, making fear that such contacts will be disclosed a potential disincentive to adoption of smartphone contact tracing. Here, we modify the standard SEIR infectious disease transmission model to incorporate contact tracing and perform a series of simulations aimed at studying the importance of tracing socially distant (and potentially privacy-sensitive) contacts. We find that, for a simple model network, ensuring that distant contacts are traced is surprisingly unimportant as long as contact tracing adoption is sufficiently high. These results suggest that policy-makers designing contact tracing systems should be willing to trade off comprehensiveness for more widespread adoption.

Recent Advances in CRISPR-Based Biosensors for Point-of-Care Pathogen Detection.

Infectious pathogens are pressing concerns due to their heavy toll on global health and socioeconomic infrastructure. Rapid, sensitive, and specific pathogen detection methods are needed more than ever to control disease spreading. The fast evolution of clustered regularly interspaced short palindromic repeats (CRISPR)-based diagnostics (CRISPR-Dx) has opened a new horizon in the field of molecular diagnostics. This review highlights recent efforts in configuring CRISPR technology as an efficient diagnostic tool for pathogen detection. It starts with a brief introduction of different CRISPR-Cas effectors and their working principles for disease diagnosis. It then focuses on the evolution of laboratory-based CRISPR technology toward a potential point-of-care test, including the development of new signaling mechanisms, elimination of preamplification and sample pretreatment steps, and miniaturization of CRISPR reactions on digital assay chips and lateral flow devices. In addition, promising examples of CRISPR-Dx for pathogen detection in various real samples, such as blood, saliva, nasal swab, plant, and food samples, are highlighted. Finally, the challenges and perspectives of future development of CRISPR-Dx for infectious disease monitoring are discussed.

Frequency of Detection and Prevalence Factors Associated with Common Respiratory Pathogens in Equids with Acute Onset of Fever and/or Respiratory Signs (2008-2021).

A voluntary biosurveillance program was established in 2008 in order to determine the shedding frequency and prevalence factors for common respiratory pathogens associated with acute onset of fever and/or respiratory signs in equids from the USA. Over a period of 13 years, a total of 10,296 equids were enrolled in the program and nasal secretions were analyzed for the qPCR detection of equine influenza virus (EIV), equine herpesvirus-1 (EHV-1), EHV-4, equine rhinitis A and B virus (ERVs), and Streptococcus equi subspecies equi (S. equi). Single infections with respiratory pathogens were detected in 21.1% of the submissions with EIV (6.8%) and EHV-4 (6.6%) as the two most prevalent viruses, followed by S. equi (4.7%), ERVs (2.3%), and EHV-1 (0.7%). Multiple pathogens were detected in 274 horses (2.7%) and no respiratory pathogens in 7836 horses (76.2%). Specific prevalence factors were determined for each of the six respiratory pathogen groups; most differences were associated with age, breed, and use of the horses, while the clinical signs were fairly consistent between viral and bacterial respiratory infections. Monitoring the frequency of detection of common respiratory pathogens is important in order to gain a better understanding of their epidemiology and to implement management practices aimed at controlling disease spread.

Case-control study to identify risk factors for SARS-CoV-2 infection among university students in the northeastern USA.

Curbing the coronavirus disease 2019 (COVID‐19) pandemic requires a thorough understanding of risk factors for transmission of SARS‐CoV‐2, the etiologic agent. Institutions of higher education present unique challenges for controlling disease spread because of features inherent to these settings. Our objective was to determine risk factors for SARS‐CoV‐2 infection among a university student population in the northeastern USA during the spring and fall 2021 semesters, using the case–control study design. Cases were defined as students with a newly diagnosed SARS‐CoV‐2 infection detected either through the robust PCR‐based surveillance testing program on campus or through healthcare testing if symptoms compatible with COVID‐19 were present. Controls were defined as students with negative SARS‐CoV‐2 status, based on consistently negative PCR results at the time of selection. A comprehensive questionnaire was administered to each student enrolled in the study, covering a broad range of campus life activities. A total of 446 cases and 1,185 controls were included in this study. Multivariable logistic regression analysis showed that recent party attendance (adjusted OR = 2.3, p < .0001), recently visiting a bar (aOR = 1.6, p = .007), living in a campus residence hall (aOR = 1.6, p = .001), fraternity/sorority membership (aOR = 1.8, p = .002), and recent travel (aOR = 1.3, p = .04) were associated with being a COVID‐19 case. Having an on‐campus job was negatively associated with being a COVID‐19 case (aOR = 0.6, p = .0003). Among cases, the most commonly reported symptoms were cough (43.9%), fatigue (38.1%) and sore throat (30.3%). These findings can be used to inform the development of COVID‐19 mitigation strategies and public health outreach efforts in university settings, thus reducing SARS‐CoV‐2 transmission among students and helping to preserve the vital education and research missions of these institutions.

Phylodynamic and phylogeographic reconstruction of beak and feather disease virus epidemiology and its implications for the international exotic bird trade.

Beak and feather disease virus (BFDV) infects domestic and wild psittacine species and is able to cause progressive beak, claw and feather malformation and necrosis. In addition to having an impact on the health and welfare of domesticated birds, BFDV represents a significant threat to wild endangered species. Understanding the epidemiology, dynamics, viral migration rate, interaction between wild and domestic animals and the effect of implemented control strategies is fundamental in controlling the spread of the disease. With this in mind, a phylodynamic and phylogeographic analysis has been performed on a database of more than 400 replication-associated protein (Rep) gene (ORF1) sequences downloaded from Genbank including some recently generated sequences from fifteen samples collected in Namibia. The results allowed us to reconstruct the variation of viral population size and demonstrated the effect of enforced international bans on these dynamics. A good correlation was found between viral migration rate and the intensity of animal trade between regions over time. A dominant flux of viral strains was observed from wild to domestic populations, highlighting the directionality of viral transmission and the risk associated with the capturing and trade of wild birds. Nevertheless, the flow of viruses from domestic to wild species was not negligible and should be considered as a threat to biodiversity. Therefore, considering the strong relationship demonstrated in this study between animal trade and BFDV viral fluxes more effort should be made to prevent contact opportunities between wild and domestic populations from different countries in order to control disease spread.

Promise of nonthermal plasmas in addressing emerging environmental and health problems: Present and future

Nonthermal atmospheric pressure plasmas transform input electrical energy efficiently into reactive species, charged particles, and photons. This “activated gas” is being investigated as solutions for a range of environmental and health problems facing society today. In this Perspective, we take a cursory look at a few of these societal problems and the reflected role that plasmas may play in charting the pathway to a solution buoyed by supporting research. Here, we survey the plasma-based opportunities in the removal of trace contaminants in water supporting methodologies such as water reuse, which addresses scarcity and pollution, the opportunity posed by plasmas-based chemical depolymerization for plastics recycling, and the application of plasmas for food security, which includes sterilization of foodstuffs and the improvement of crop yield. Finally, we also included a short review on how plasmas may help control disease spread. In each case, the scope of the problem is presented along with the potential plasma-based solution.

The Impact of Active Screening and Management on COVID-19 in Plateau Region of Sichuan, China.

BackgroundIn December 2019, the cases of pneumonia of unknown etiology emerged in Wuhan, China, and rapidly spread throughout the country. The disease was later designated by the World Health Organization (WHO) as Coronavirus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS CoV-2). Few studies have assessed the clinical characteristics of COVID-19 and control strategies used to mitigate disease spread in high-altitude plateau regions of China.Study ObjectiveTo assess the impact of real-world strategies to control COVID-19 spread in remote plateau regions.MethodsA retrospective study was performed to assess the epidemiology of COVID-19 and strategies used to control disease spread in the high-altitude plateau of Sichuan, China from 24 January 2020 to 19 March 2020.ResultsCOVID-19 spread and outbreaks in Sichuan were attributed to mass gatherings. A total of 70 patients and 20 asymptomatic individuals were found in the hypoxic plateau region of Sichuan. Twelve patients were admitted after the onset of symptoms, while 58 patients and 20 asymptomatic individuals were found by active screening. The symptomatic patients included those with uncomplicated illness (16/70, 22.9%), mild pneumonia (44/70, 62.9%), and severe pneumonia (10/70, 14.3%). Most patients in the study area showed relatively mild and atypical symptoms such as low or no fever and dyspnea. The incidence of severe pneumonia, fever, dyspnea, and interstitial abnormalities identified by chest CT were all significantly lower in screened patients than those admitted after symptom onset (P < 0.05). Severe pneumonia was noted in patients with chronic conditions like hypertension, diabetes etc. as compared to less severe pneumonia in healthy subjects (P <0.05). No patients died and all were eventually discharged.ConclusionMass gatherings increased risk of spread of SARS-CoV-2 responsible for COVID-19. Active screening and early management have collectively contributed to reduced incidence of severe pneumonia and satisfactory prognoses of infections with COVID-19 in this hypoxic plateau region.

Development of a highly efficient virus-free regeneration system of Salvia miltiorrhiza from Sichuan using apical meristem as explants

BcakgroundThe dry root and rhizome of Salvia miltiorrhiza are used to treat cardiovascular diseases, chronic pain, and thoracic obstruction over 2000 years in Asian countries. For high quality, Sichuan Zhongjiang is regarded as the genuine producing area of S. miltiorrhiza. Given its abnormal pollen development, S. miltiorrhiza from Sichuan (S.m.-SC) relies on root reproduction and zymad accumulation; part of diseased plants present typical viral disease symptoms and seed quality degeneration. This study aim to detected unknown viruses from mosaic-diseased plants and establish a highly efficient virus-free regeneration system to recover germplasm properties.ResultsTobacco mosaic virus (TMV) and cucumber mosaic virus (CMV) were detected from mosaic-diseased plants. Primary apical meristem with two phyllo podium in 0.15–0.5 mm peeled from diseased plants were achieved 73.33% virus-free rate. The results showed that the medium containing MS, 0.5 mg/L 6-BA, 0.1 mg/L NAA, 0.1 mg/L GA3, 30 g/L sucrose and 7.5 g/L agar can achieve embryonic-tissue (apical meristem, petiole and leaf callus) high efficient organogenesis. For callus induction, the optimal condition was detected on the medium containing MS, 2 mg/L TDZ, 0.1 mg/L NAA by using secondary petiole of virus-free plants under 24 h dark/d condition for 21 d. The optimal system for root induction was the nutrient solution with 1/2 MS supplemented with 1 mg/L NAA. After transplant, the detection of agronomic metric and salvianolic acid B content confirmed the great germplasm properties of S.m.-SC virus-free plants.ConclusionsA highly efficient virus-free regeneration system of S.m.-SC was established based on the detected viruses to recover superior seed quality. The proposed system laid support to control disease spread, recover good germplasm properties in S.m.-SC.

A study on prosocial behavior of wearing a mask and self-quarantining to prevent the spread of diseases underpinned by evolutionary game theory

In the wake of COVID-19, mask-wearing practice and self-quarantine is thought to be the most effective means of controlling disease spread. The current study develops an epidemiological model based on the SEIR process that takes into account dynamic human behavior toward those two preventive measures. In terms of quantifying the effect of wearing a mask, our model distinguishes itself by accounting for the effect of self-protection as well as the effect of reducing a potential risk to other individuals in different formulations. Each of the two measures derived from the so-called behavior model has a dynamical equation that takes into account the delicate balance between the cost of wearing a mask/self-quarantine and the risk of infection. The dynamical system as a whole contains a social dilemma structure because of whether to commit to preventing measures or seek the possibility of infection-free without paying anything. The numerical result was delivered along the social efficiency deficit, quantifying the extent to which Nash equilibrium has been improved to a social optimal state.PACS numbersTheory and modeling; computer simulation, 87.15.Aa; Dynamics of evolution, 87.23.Kg

Demographics, Socioeconomic Context, and the Spread of Infectious Disease: The Case of COVID-19.

Importance: Due to the evolving variants of coronavirus disease 2019 (COVID-19), it is important to understand the relationship between the disease condition and socioeconomic, demographic, and health indicators across regions. Background: Studies examining the relationships between infectious disease and socioeconomic variables are not yet well established. Design: A total of 3042 counties in the United States are included as the observation unit in the study. Two outcome variables employed in the study are the control of disease spread and infection prevalence rates in each county. Method: Data are submitted to quantile regression, hierarchical regression, and random forest analyses to understand the extent to which health outcomes are affected by demographics, socioeconomics, and health indicators. Results: Counties with better control of the disease spread tend to have lower infection rates, and vice versa. When measuring different outcome variables, the common risk factors for COVID-19 with a 5% level of statistical significance include employment ratio, female labor ratio, young population ratio, and residents’ average health risk factors, while protective factors include land size, housing value, travel time to work, female population ratio, and ratio of residents who identify themselves as mixed race. Conclusions: The implications of the findings are that the ability to maintain social distancing and personal hygiene habits are crucial in deterring disease transmission and lowering incidence rates, especially in the early stage of disease formation. Relevant authorities should identify preventive factors and take early actions to fight infectious diseases in the future.

Design of a University Pandemic Response Decision Support System

The global effort to combat the COVID-19 pandemic has changed how people conduct their daily lives. Institutions of higher education have been greatly impacted by these changes and must find ways to adapt to this new environment. Universities are a unique case because they must control disease spread, while maintaining the same or similar quality of education. The University Pandemic Response Decision Support System (UPRDSS) is a system designed to help universities pick the most suitable method for instruction delivery when faced with any pandemic. Using George Mason University as a case study, the goal was to design a system that allows university administrations to make an educated operations decision. The UPRDSS achieves this by simulating the spread of disease, analyzing learning outcome data, and using a multi-attribute utility function to determine the most appropriate method of instruction that enables positive learning and health outcomes.

Saliva-based COVID-19 detection: A rapid antigen test of SARS-CoV-2 nucleocapsid protein using an electrical-double-layer gated field-effect transistor-based biosensing system

Facing the unstopped surges of COVID-19, an insufficient capacity of diagnostic testing jeopardizes the control of disease spread. Due to a centralized setting and a long turnaround, real-time reverse transcription polymerase chain reaction (real-time RT-PCR), the gold standard of viral detection, has fallen short in timely reflecting the epidemic status quo during an urgent outbreak. As such, a rapid screening tool is necessitated to help contain the spread of COVID-19 amid the countries where the vaccine implementations have not been widely deployed. In this work, we propose a saliva-based COVID-19 antigen test using the electrical double layer (EDL)-gated field-effect transistor-based biosensor (BioFET). The detection of SARS-CoV-2 nucleocapsid (N) protein is validated with limits of detection (LoDs) of 0.34 ng/mL (7.44 pM) and 0.14 ng/mL (2.96 pM) in 1× PBS and artificial saliva, respectively. The specificity is inspected with types of antigens, exhibiting low cross-reactivity among MERS-CoV, Influenza A virus, and Influenza B virus. This portable system is embedded with Bluetooth communication and user-friendly interfaces that are fully compatible with digital health, feasibly leading to an on-site turnaround, an effective management, and a proactive response taken by medical providers and frontline health workers.

Cribriform-morular variant of papillary thyroid carcinoma with poorly differentiated features: report of a case and review of the literature

IntroductionCribrifrom-morular variant of papillary thyroid carcinoma (CMVPTC) is an uncommon thyroid neoplasm that occurs predominantly in women and is sometime associated with familial adenomatous polyposis (FAP). Some of these tumors may undergo dedifferentiation to poorly differentiated thyroid carcinoma (PDTC). We describe a rare case of this carcinoma in a women without a history of FAP.Case presentationA 49-year-old woman with a history of breast carcinoma presented with a thyroid mass. A CMVPTC was diagnosed after excision. There was no history of FAP. Histological examination showed classical features of CMVPTC in most areas, but about 20% of the carcinoma showed features of a poorly differentiated carcinoma with a solid pattern of growth, increase mitotic activity and a high Ki-67 proliferative index (25%). Immunohistochemical stains were positive for nuclear and cytoplasmic beta catenin staining. These special studies supported the diagnosis.ConclusionCMVPTC with dedifferentiation to PDTC is a rare carcinoma with only 4 previous documented cases in the literature. This aggressive variant of thyroid carcinoma is more common in females, as is CMVPTC, and is often associated with an aggressive biological course. The cases usually express nuclear beta catenin and estrogen, progesterone and androgen receptors have been reported in some cases. Some cases may have somatic alterations of the APC gene and TERT promoter mutations. These carcinomas may metastasize to lung, bones and lymph nodes. Because of its aggressive behavior, patient with this diagnosis should be treated aggressively to control disease spread and mortality from the carcinoma.

Microsimulation based quantitative analysis of COVID-19 management strategies.

Pandemic management requires reliable and efficient dynamical simulation to predict and control disease spreading. The COVID-19 (SARS-CoV-2) pandemic is mitigated by several non-pharmaceutical interventions, but it is hard to predict which of these are the most effective for a given population. We developed the computationally effective and scalable, agent-based microsimulation framework PanSim, allowing us to test control measures in multiple infection waves caused by the spread of a new virus variant in a city-sized societal environment using a unified framework fitted to realistic data. We show that vaccination strategies prioritising occupational risk groups minimise the number of infections but allow higher mortality while prioritising vulnerable groups minimises mortality but implies an increased infection rate. We also found that intensive vaccination along with non-pharmaceutical interventions can substantially suppress the spread of the virus, while low levels of vaccination, premature reopening may easily revert the epidemic to an uncontrolled state. Our analysis highlights that while vaccination protects the elderly from COVID-19, a large percentage of children will contract the virus, and we also show the benefits and limitations of various quarantine and testing scenarios. The uniquely detailed spatio-temporal resolution of PanSim allows the design and testing of complex, specifically targeted interventions with a large number of agents under dynamically changing conditions.

Rhetoric, Persuasion, Compulsion, and the Stubborn Problem of Vaccine Hesitancy.

Despite the impact of vaccination on the control and prevention of many infectious diseases, vaccine opposition and hesitancy remain significant barriers to fully protecting individuals and communities against serious disease. The primary response to the problem of vaccine hesitancy includes persuasion and some degree of compulsion, usually in the form of vaccine mandates. Persuasion, if it can be successfully leveraged to provide sufficient control of disease spread, is the ethically preferred approach. Yet persuasion has proven less than adequate, leading to increasing calls for vaccination mandates and the elimination of nonmedical exemptions to those mandates. Four scholars have recently examined the underlying causes of vaccine hesitancy in the interest of improving rhetoric surrounding vaccination. This article reviews those books and offers suggestions for optimizing the strategy of persuasion in the interest of reducing the need for compulsion.

An Analytical Model for Confronting the Omicron Variant During COVID-19 Pandemic: A System Dynamic Approach

The global outbreak of COVID-19 began in December 2019 in Wuhan, China, and affected the entire world in a short time. Over time, the emergence of new species of the disease, the pace of response to it has also strongly affected, and with the emergence of the newest species called Omicron. Knowing and reviewing the system and publishing publications in the community is essential for sound policies. It is necessary to investigate the spread of COVID-19 to make proper policies. System dynamic can be adopted as an approach to the behavior evaluation of the COVID-19 pandemic. The present study introduces a system dynamic model to explore the effects of different factors on the pandemic and therapeutic and non-therapeutic modalities. Vaccination is evaluated as the main approach to prevent the disease. The influential factors of pandemic prevention and control are examined based on the SEIR model and policies such as vaccination. The safest way to prevent this epidemic is vaccination. Therefore, a policy that benefits the entire population and will be necessary is producing and purchasing vaccines. From 19 July 2021, the rate of vaccine imports to Iran has increased significantly, and therefore it is predicted that by the end of 2022, Iran's general vaccination will end, after which the number of cases and mortality rates will decline. Vaccines are the ultimate solution to contagious diseases to control disease spread and provide safety to deal with the infection. The results suggested that the fatality rate of the susceptible population was reduced by vaccination and protective protocols. Thus, this paper aims to analyze factors influencing the spread of COVID-19 and prevent the disease.

Prognostic Biomarkers in Uveal Melanoma: The Status Quo, Recent Advances and Future Directions.

Simple SummaryAlthough rare, uveal melanoma (UM) is the most common cancer that develops inside adult eyes. The prognosis is poor, since 50% of patients will develop lethal metastases in the first decade, especially to the liver. Once metastases are detected, life expectancy is limited, given that the available treatments are mostly unsuccessful. Thus, there is a need to find methods that can accurately predict UM prognosis and also effective therapeutic strategies to treat this cancer. In this manuscript, we initially compile the current knowledge on epidemiological, clinical, pathological and molecular features of UM. Then, we cover the most relevant prognostic factors currently used for the evaluation and follow-up of UM patients. Afterwards, we highlight emerging molecular markers in UM published over the last three years. Finally, we discuss the problems preventing meaningful advances in the treatment and prognostication of UM patients, as well as forecast new roadblocks and paths of UM-related research.Uveal melanoma (UM) is the most common malignant intraocular tumour in the adult population. It is a rare cancer with an incidence of nearly five cases per million inhabitants per year, which develops from the uncontrolled proliferation of melanocytes in the choroid (≈90%), ciliary body (≈6%) or iris (≈4%). Patients initially present either with symptoms like blurred vision or photopsia, or without symptoms, with the tumour being detected in routine eye exams. Over the course of the disease, metastases, which are initially dormant, develop in nearly 50% of patients, preferentially in the liver. Despite decades of intensive research, the only approach proven to mildly control disease spread are early treatments directed to ablate liver metastases, such as surgical excision or chemoembolization. However, most patients have a limited life expectancy once metastases are detected, since there are limited therapeutic approaches for the metastatic disease, including immunotherapy, which unlike in cutaneous melanoma, has been mostly ineffective for UM patients. Therefore, in order to offer the best care possible to these patients, there is an urgent need to find robust models that can accurately predict the prognosis of UM, as well as therapeutic strategies that effectively block and/or limit the spread of the metastatic disease. Here, we initially summarized the current knowledge about UM by compiling the most relevant epidemiological, clinical, pathological and molecular data. Then, we revisited the most important prognostic factors currently used for the evaluation and follow-up of primary UM cases. Afterwards, we addressed emerging prognostic biomarkers in UM, by comprehensively reviewing gene signatures, immunohistochemistry-based markers and proteomic markers resulting from research studies conducted over the past three years. Finally, we discussed the current hurdles in the field and anticipated the future challenges and novel avenues of research in UM.

The cost-effectiveness of social distancing measures for mitigating the COVID-19 pandemic in a highly-populated country: A case study in Indonesia

BackgroundAs one of the strategies to mitigate the COVID-19 pandemic, social distancing (SD) measures are recommended to control disease spread and reduce the attack rate. Therefore, this study aims to estimate the costs and effects of SD measures through school closures, workforce, and community contact reductions for mitigating the COVID-19 pandemic in Indonesia. MethodsTwo mitigation scenarios of SD for 1 month and continuous SD were compared with the baseline (no intervention). A modified Susceptible-Exposed-Infected-Recovered (SEIR) compartmental model accounting for disease spread during the latent period was applied by considering a 1-year time horizon. The costs of healthcare, school closures, and productivity loss due to disease as well as intervention were considered to estimate the total pandemic cost among all scenarios. ResultsIn a comparison with the baseline, the result showed that total savings in scenarios of SD for 1 month and continuous SD was approximately $415 billion and $699 billion, respectively, while the averted deaths were 4.6 million and 8.5 million, respectively. Sensitivity analysis showed that basic reproduction number, infectious period, daily wage, incubation period, daily ICU admission cost, and case fatality rate were the most influential parameters affecting the savings and the number of averted deaths. ConclusionsSD measures through school closures, workforce, and community contact reductions were concluded to be cost-saving. Increasing the duration of social distancing tends to increase both the savings and the number of averted deaths.