Control Disease Spread Research Articles

A fast, low-cost, robust and high-throughput method for viral nucleic acid isolation based on NAxtra magnetic nanoparticles

The year of 2020 was profoundly marked by a global pandemic caused by a strain of coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent of coronavirus disease 2019 (COVID-19). To control disease spread, a key strategy adopted by many countries was the regular testing of individuals for infection. This led to the rapid development of diagnostic testing technologies. In Norway, within a week, our group developed a test kit to quickly isolate viral RNA and safely detect SARS-CoV-2 infection with sensitivity comparable to available kits. Herein, the procedure employed for the detection of SARS-CoV-2 in swab samples from patients using the NTNU-COVID-19 test kit is described in detail. This procedure, based on NAxtra magnetic nanoparticles and an optimized nucleic acid extraction procedure, is robust, reliable, and straightforward, providing high-quality nucleic acids within 14 min. The NAxtra protocol is adaptable and was further validated for extraction of DNA and RNA from other types of viruses. A comparison of the protocol on different liquid handling systems is also presented. Due to the simplicity and low cost of this method, implementation of this technology to diagnose virus infections on a clinical setting would benefit health care systems, promoting sustainability.

A confinable female-lethal population suppression system in the malaria vector, Anopheles gambiae.

Malaria is among the world's deadliest diseases, predominantly affecting Sub-Saharan Africa and killing over half a million people annually. Controlling the principal vector, the mosquito Anopheles gambiae, as well as other anophelines, is among the most effective methods to control disease spread. Here, we develop a genetic population suppression system termed Ifegenia (inherited female elimination by genetically encoded nucleases to interrupt alleles) in this deadly vector. In this bicomponent CRISPR-based approach, we disrupt a female-essential gene, femaleless (fle), demonstrating complete genetic sexing via heritable daughter gynecide. Moreover, we demonstrate that Ifegenia males remain reproductively viable and can load both fle mutations and CRISPR machinery to induce fle mutations in subsequent generations, resulting in sustained population suppression. Through modeling, we demonstrate that iterative releases of nonbiting Ifegenia males can act as an effective, confinable, controllable, and safe population suppression and elimination system.

A CRISPR-based approach using dead Cas9-sgRNA to detect SARS-CoV-2.

Rapid, highly specific, and robust diagnostic kits to detect viruses and pathogens are needed to control disease spread and transmission globally. Of the many different methods proposed to diagnose COVID-19 infection, CRISPR-based detection of nucleic acids tests are among the most prominent. Here, we describe a new way of using CRISPR/Cas systems as a rapid and highly specific tool to detect the SARS-CoV-2 virus using the in vitro dCas9-sgRNA-based technique. As a proof of concept, we used a synthetic DNA of the M gene, one of the SARS-CoV-2 virus genes, and demonstrated that we can specifically inactivate unique restriction enzyme sites on this gene using CRISPR/Cas multiplexing of dCas9-sgRNA-BbsI and dCas9-sgRNA-XbaI. These complexes recognize and bind to the target sequence spanning the BbsI and XbaI restriction enzyme sites, respectively, and protect the M gene from digestion by BbsI and/or XbaI. We further demonstrated that this approach can be used to detect the M gene when expressed in human cells and from individuals infected with SARS-CoV-2. We refer to this approach as dead Cas9 Protects Restriction Enzyme Sites, and believe that it has the potential to be applied as a diagnostic tool for many DNA/RNA pathogens.

Rapid Detection of DNA and RNA Shrimp Viruses Using CRISPR-Based Diagnostics.

Timely detection of persistent and emerging pathogens is critical to controlling disease spread, particularly in high-density populations with increased contact between individuals and limited-to-no ability to quarantine. Standard molecular diagnostic tests for surveying pathogenic microbes have provided the sensitivity needed for early detection, but lag in time-to-result leading to delayed action. On-site diagnostics alleviate this lag, but current technologies are less sensitive and adaptable than lab-based molecular methods. Towards the development of improved on-site diagnostics, we demonstrated the adaptability of a loop-mediated isothermal amplification-CRISPR coupled technology for detecting DNA and RNA viruses that have greatly impacted shrimp populations worldwide; White Spot Syndrome Virus and Taura Syndrome Virus. Both CRISPR-based fluorescent assays we developed showed similar sensitivity and accuracy for viral detection and load quantification to real-time PCR. Additionally, both assays specifically targeted their respective virus with no false positives detected in animals infected with other common pathogens or in certified specific pathogen-free animals. IMPORTANCE The Pacific white shrimp (Penaeus vannamei) is one of the most valuable aquaculture species in the world but has suffered major economic losses from outbreaks of White Spot Syndrome Virus and Taura Syndrome Virus. Rapid detection of these viruses can improve aquaculture practices by enabling more timely action to be taken to combat disease outbreaks. Highly sensitive, specific, and robust CRISPR-based diagnostic assays such as those developed here have the potential to revolutionize disease management in agriculture and aquaculture helping to promote global food security.

The Emergence of Mpox: Epidemiology and Current Therapeutic Options.

The world recently witnessed the emergence of new epidemic outbreaks like COVID-19 and mpox. The 2022 outbreak of mpox amid COVID-19 presents an intricate situation and requires strategies to combat the status quo. Some of the challenges to controlling an epidemic include present knowledge of the disease, available treatment options, appropriate health infrastructures facilities, current scientific methods, operations concepts, availability of technical staff, financial funds, and lastly international policies to control an epidemic state. These insufficiencies often hinder the control of disease spread and jeopardize the health of countless people. Also, disease outbreaks often put a huge burden on the developing economies. These countries are the worst affected and are immensely dependent on assistance provided from the larger economies to control such outbreaks. The first case of mpox was reported in the 1970s and several outbreaks were detected thereafter in the endemic areas eventually leading to the recent outbreak. Approximately, more than 80,000 individuals were infected, and 110 countries were affected by this outbreak. Yet, no definite vaccines and drugs are available to date. The lack of human clinical trials affected thousands of individuals in availing definite disease management. This paper focuses on the epidemiology of mpox, scientific concepts, and treatment options including future treatment modalities for mpox.

A COMPREHENSIVE REVIEW ON DIAGNOSIS AND CLASSIFICATION OF PADDY LEAF DISEASES USING ADVANCED COMPUTER VISION TECHNOLOGIES

Food is required for human survival. Paddy is a vital food crop serving 60% of the Indian population. Food quality is determined by the plant yield. Unfavorable environmental circumstances, soil fertility, bacteria, viruses, nematodes, fertilizer use, and the absence of nutritional shortages substantially influence plant yield. As a result, it is critical to protect the plants from illness. Crop yield must be improved to meet food scarcity of growing population. Although disease symptoms are apparent in various parts of plant like leaves, stem, fruits and stem, the infections are commonly observed in the leaves. Understanding plant pathology plays a vital role in disease detection. Early detection of diseases is a prompt intervention that aids the farmers in controlling disease spread, resulting in increased agricultural quantity and quality. Image processing techniques with advanced computer vision technologies like machine learning and deep learning have proven the automation of plant disease diagnosis precisely. The main objectives of this research are to investigate computer vision technologies for the early identification of plant diseases and help novice researchers in the same domain learn about plant diseases and the methodologies for disease detection in paddy plant leaves. Consequently this manuscript reviews significant paddy plant infections, highlights related study of tools and techniques, current research, limitations and conclusions for future research in this field.

Syphilis vaccine: challenges, controversies and opportunities.

Syphilis is a sexually or vertically (mother to fetus) transmitted disease caused by the infection of Treponema pallidum subspecie pallidum (TPA). The incidence of syphilis has increased over the past years despite the fact that this bacterium is an obligate human pathogen, the infection route is well known, and the disease can be successfully treated with penicillin. As complementary measures to preventive campaigns and early treatment of infected individuals, development of a syphilis vaccine may be crucial for controlling disease spread and/or severity, particularly in countries where the effectiveness of the aforementioned measures is limited. In the last century, several vaccine prototypes have been tested in preclinical studies, mainly in rabbits. While none of them provided protection against infection, some prototypes prevented bacteria from disseminating to distal organs, attenuated lesion development, and accelerated their healing. In spite of these promising results, there is still some controversy regarding the identification of vaccine candidates and the characteristics of a syphilis-protective immune response. In this review, we describe what is known about TPA immune response, and the main mechanisms used by this pathogen to evade it. Moreover, we emphasize the importance of integrating this knowledge, in conjunction with the characterization of outer membrane proteins (OMPs), to expedite the development of a syphilis vaccine that can protect against TPA infection.

First report of bacterial leaf streak in sweet corn caused by Pantoea ananatis in southeast China.

Sweet corn (Zea mays convar. saccharata var. rugosa) is a popular vegetable crop in southeast China. During the spring seasons of 2018-2021, a serious outbreak of bacterial leaf streak was observed in sweet corn variety Yuetian28 in the field in Guangzhou, Guangdong Province. The disease incidence was 50%-70%. Infected leaves initially displayed long, chlorotic streaks parallel to veins at the V5-V6 stage, and then turned white or brown and dried out over the course of disease development. In severe infections, leaf lesion coalesced to form large irregular blight areas (Fig. S1A). To investigate this disease, we collected 0.5 cm2 samples of infected leaves from four plants after surface sterilization and rinsed them three times with sterile distilled water. We placed all leaf samples on nutrient agar (NA) medium and incubated them at 28℃ for 48 hours. Bright-yellowish colonies were observed near the edges of the samples. We picked the colonies and re-streaked them onto NA medium three times to obtain pure cultures. Four isolates, GZ2201, GZ2202, GZ2203, and GZ2204, were selected for further study. All isolates were gram-negative rods and were negative for oxidase, urease, nitrate reductase reactions, and gelatin liquefaction. They were positive for catalase, citrate utilization, indole production, and the Voges-Proskauer test. We sequenced the 16S rDNA, rpoB, leuS, and gyrB sequences using previously reported primers (Brady et al. 2008) and deposited the sequences in GenBank (accession nos. ON740665 to ON740668 for 16S rDNA; ON755167 to ON755170 for rpoB; ON755171 to ON755174 for leuS; and OP227136 to OP227139 for gyrB). The sequences share >98% identity with sequences from Pantoea ananatis type strain LMG2665 (GenBank JFZU01) indicating that the causal pathogen of bacteria leaf streak of sweet corn is P. ananatis (Fig. S1B). Phylogenetic analysis of gyrB, leuS, and rpoB concatenated sequence showed that the four isolates clustered with P. ananatis (Fig S2). To test the pathogenicity of the isolates of P. ananatis on the sweet corn variety Yuetian28, we inoculated plants at the V3 stage by syringe infiltration of bacterial suspension (108 CFU/ml) (Kini et al. 2020) or sterile distilled water as a negative control. Inoculated plants were placed in a growth chamber at 28 ℃, 60% relative humidity, 16-h/8-h light-dark cycle. After 7 days of incubation, chlorotic streaks resembling the original symptoms developed on inoculated plants (Fig. S1D), while control plants remained symptomless (Fig. S1C). We successfully re-isolated bacteria from the inoculated plants and confirmed their identity by sequencing of 16S rDNA, rpoB, leuS, and gyrB. P. ananatis was previously reported to cause leaf spot disease in maize grown in Argentina, Ecuador, and China (Alippi et al. 2010; Toaza et al. 2021; Cui et al. 2022). To our knowledge, this is the first report of P. ananatis causing leaf streak in sweet corn in southeast China. Further research on P. ananatis management is needed to help control disease spread.

Lessons Learned From Contact Tracing During the COVID-19 Pandemic: Public Health Students' Experiences in the Field.

Contact tracing is a cornerstone in public health practice, providing an effective response to infectious disease outbreaks. Beginning in April 2020, as the COVID-19 pandemic spread quickly in the United States, public health departments increasingly relied on contact tracers to control disease spread and reduce the impact on the community. The Florida Department of Health (DOH) employed hundreds of public health students to pursue transmission control statewide as contact tracers. This study employed a qualitative thematic approach to capture 11 graduate-level public health students' experiences, motivations, challenges, and recommendations on contact tracing procedures as DOH contract tracers. In-depth interview questions focused on students' interest in public health, experiences as a contact tracer, patient/case interactions, and personal outlook on the COVID-19 pandemic. The COVID-19 pandemic brought new experiences and challenges for public health students employed by local health departments as contact tracers. Three categories and subthemes emerged from interviews: (1) motivations to work as a contact tracer, (2) challenges faced throughout employment, and (3) overall assessment of the contact tracing process. Identifying and understanding the work of contact tracers from the system-level perspective is vital as they contribute to improving training and working relationships with management and ultimately extend to the community. Lessons learned during the early months of the COVID-19 pandemic should help inform public health practice, especially when considering recruitment, curricula, training, and retention of the public health workforce in the face of current and emerging public health emergencies.

An amplification-free, 16S rRNA test for Neisseria gonorrhoeae in urine.

An amplification-free, nanopore-based nucleic acid detection platform has been demonstrated for rapid, 16S rRNA sequence-specific detection of Neisseria gonorrhoeae at 10-100 CFU mL-1 in human urine against background bacterial flora at 1000 CFU mL-1. Gonorrhea is a very common notifiable communicable disease, antibiotic resistant strains have emerged, and the rate of reported gonococcal infections continues to increase. Since rapid clinical identification of bacterial pathogens in clinical samples is needed to guide proper antibiotic treatment and to control disease spread, it is important to engineer rapid, sensitive, selective, and inexpensive point-of-care (POC) diagnostic devices for pathogens such as N. gonorrhoeae. Our detector technology is based on straightforward conductometric detection of sustained blockage of a glass nanopore. Charge neutral, complementary peptide nucleic acid probes are conjugated to polystyrene beads to capture N. gonorrhoeae 16S rRNA selectively. In the presence of an electric field applied externally through a glass nanopore, the PNA-microbead conjugates that acquire substantial negative charge upon target hybridization are driven to the smaller diameter nanopore. At least partial blockage of the nanopore results in a sustained drop in ionic current that can be measured easily with simple electronics. The ability to detect N. gonorrhoeae over the range of 10 to 100 CFU mL-1 spiked in human urine was demonstrated successfully with estimated sensitivity and specificity of ∼98% and ∼100%, respectively. No false positives were observed for the control group of representative background flora (E. coli, K. pneumoniae, and E. faecalis) at 1000 CFU mL-1. Also, N. gonorrhoeae at 50 CFU mL-1 was successfully detected against 1000 CFU mL-1 of background flora in urine. These results suggest that this amplification-free technology may serve as the basis for rapid, inexpensive, low-power detection of pathogens in clinical samples at the POC.

Dynamics analysis of an SVEIR epidemic model in a patchy environment.

In this paper, we propose a multi-patch SVEIR epidemic model that incorporates vaccination of both newborns and susceptible populations. We determine the basic reproduction number $ R_{0} $ and prove that the disease-free equilibrium $ P_{0} $ is locally and globally asymptotically stable if $ R_{0} < 1, $ and it is unstable if $ R_{0} > 1. $ Moreover, we show that the disease is uniformly persistent in the population when $ R_{0} > 1. $ Numerical simulations indicate that vaccination strategies can effectively control disease spread in all patches while population migration can either intensify or prevent disease transmission within a patch.

Development of a TaqMan minor groove binding probe-based quantitative reverse transcription polymerase chain reaction for the detection and quantification of Zika virus.

Zika virus (ZIKV) infection has emerged as a global health concern following epidemic outbreaks of severe neurological disorders reported in Pacific and Americas since 2016. Therefore, a rapid, sensitive and specific diagnostic test for ZIKV infection is critical for the appropriate patient management and the control of disease spread. A TaqMan minor groove binding (MGB) probe-based quantitative reverse transcription-polymerase chain reaction (qRT-PCR) assay was developed based on the conserved sequence regions of 463 ZIKV NS2B genes. The designed ZIKV qRT-PCR assay was evaluated for its detection limit, strain coverage and cross-reactivity. We further assessed the clinical applicability of qRT-PCR assay for ZIKV RNA detection using a total 18 simulated clinical specimens. The detection limit of the qRT-PCR assay was 11.276 ZIKV RNA copies at the 95% probability level (probit analysis, p<= 0.05). Both Asian and African ZIKV strains were detected by the qRT-PCR assay without cross-reacting with DENV-1, DENV-2, DENV-3, DENV-4, CHIKV, JEV, LGTV, GETV and SINV. The qRT-PCR assay demonstrated a perfect agreement (k = 1.000, P < 0.001) with the reference assay; the sensitivity and specificity of the qRT-PCR assay were 100% (95% CI= 79.6-100) and 100% (95% CI= 43.9-100) respectively. The qRT-PCR assay developed in this study is a useful diagnostic tool for the broad coverage detection and quantification of both the Asian and African ZIKV strains.

NRAND: An efficient and robust dismantling approach for infectious disease network

Disease spread control is a challenging task with growing importance in recent years. Infectious disease networks have been proven to be a helpful resource for controlling the epidemic by targeting a smaller population. However, the information on these networks is often imprecise, diffused, concealed, and misleading, making it challenging to obtain a complete set of real-world data, i.e., some links might be missing, which can be a risk to the widespread of the pandemic. The former studies on infectious disease networks ignore the influence of neighborhood missing links in the infectious disease network topology, thus massively targeting the irrelevant population, resulting in poor epidemic control performance. In this paper, to address such a problem, we study how a small portion of the population should be targeted with incomplete network information to effectively prevent the pandemic. We propose an algorithm, namely, the Neighborhood Relation Aware Network Dismantling Algorithm (NRAND), to efficiently address the infectious disease network’s dismantling problem. For comparison, four network dismantling strategies are employed in our experiments. An extensive empirical study of real-world networks suggests that the proposed algorithm NRAND’s dismantling performance is significantly greater than the state-of-the-art algorithms, indicating that NRAND can be a smarter option for dismantling real-world infectious disease networks.

Identity and density of parasite exposures alter the outcome of coinfections: Implications for management

Abstract Although research has focused on density‐dependent responses of hosts to single‐parasite infections, hosts are exposed to numerous parasites simultaneously under natural conditions and if these exposures lead to infections, they can threaten host populations and ecosystem stability. Moreover, spatiotemporal variation in abundance of co‐occurring parasites might influence host infection intensity. If interactions are consistent between different coinfecting parasites, then these patterns could give managers another tool to control disease spread and even predict problematic disease emergences. We investigated how parasite density and identity alter within‐host coinfection dynamics. To test this, we simultaneously exposed Cuban treefrogs Osteopilus septentrionalis as a model amphibian species to all pairwise combinations of three problematic parasites that commonly coinfect amphibians: the fungus Batrachochytrium dendrobatidis (Bd), the nematode Aplectana hamatospicula and Ranavirus. Hosts were exposed to one parasite at a fixed dose and another parasite at a range of five doses. Higher doses of Bd decreased Ranaviral and A. hamatospicula loads, but Bd load was not influenced by the dose of either parasite. Ranaviral load was negatively associated with A. hamatospicula dose, but A. hamatospicula load was not affected by Ranaviral dose. We found that all the pairwise coinfections were dependent on parasite density and that pairwise interactions were highly asymmetric—strong in one direction and weak in the other—consistent with interactions dominating food webs. Synthesis and applications: We also revealed that the exposure dose of A. hamatospicula was positively associated with host tolerance to Bd infection and negatively associated with Ranaviral load in hosts. Ranavirus and Bd cause mass die‐offs in amphibians, but A. hamatospicula does not. Therefore, in systems where these parasites coexist, maintaining or increasing densities of A. hamatospicula could reduce the negative effects of Bd and Ranavirus infections. Additionally, if these asymmetric and density‐dependent patterns from community ecology are applicable to other amphibian coinfections or coinfections in other systems, this should allow conservation organizations and resource managers to predict outbreaks and manage host declines associated with deadly parasites by modifying the abundance of coinfecting parasites that might be easier to manage.

"They cannot afford to feed their children and the advice is to stay home. How‥?": A qualitative study of community experiences of COVID-19 response efforts across Syria.

COVID-19 highlighted the importance of meaningful engagement between communities and health authorities. This is particularly challenging in conflict-affected countries such as Syria, where social protection and food security needs can hinder adherence to non-pharmaceutical interventions (NPIs) and vaccine uptake. This study explored community perspectives of COVID-19 and health authority responses across the three main areas of control in Syria, i.e. Syrian government-controlled areas (GCA), autonomous administration-controlled areas (AACA), and opposition-controlled areas (OCA). We conducted a qualitative study, interviewing 22 purposively-sampled Syrians accessing health services in AACA, GCA, or OCA in 2021 to provide approximately equal representation by governance area and gender. We analysed data thematically using deductive and inductive coding. Interviewees in all areas described how their fears of COVID-19 and willingness to adhere to NPIs decreased as their local COVID-19 epidemics progressed and NPIs disrupted access to household essentials such as work and food. Community-level responses were minimal and ad hoc, so most people focused on personal or household protective efforts and many mentioned relying on their faith for comfort. Misinformation and vaccine hesitancy were common in all areas, linked to lack of transparency from and mistrust of local health authorities and information sources. The COVID-19 pandemic has increased health actors' need to engage with communities to control disease spread, yet most NPIs implemented in Syria were inappropriate and adherence decreased as the pandemic progressed. This was exemplified by lockdowns and requirements to self-isolate, despite precarious reliance on daily wages, no subsidies for lost income, individual self-reliance, and mistrust/weak communication between communities and health authorities. We found minimal community engagement efforts, consisting entirely of informing with no efforts to consult, involve, collaborate, or empower. This contributed to failures of health actors to contextualise interventions in ways that respected community understandings and needs.

Measuring the impact of COVID-19 vaccination and immunity waning: A modelling study for Portugal

Vaccination strategies to control COVID-19 have been ongoing worldwide since the end of 2020. Understanding their possible effect is key to prevent future disease spread. Using a modelling approach, this study intends to measure the impact of the COVID-19 Portuguese vaccination strategy on the effective reproduction number and explore three scenarios for vaccine effectiveness waning. Namely, the no-immunity-loss, 1-year and 3-years of immunity duration scenarios. We adapted an age-structured SEIR deterministic model and used Portuguese hospitalisation data for the model calibration. Results show that, although the Portuguese vaccination plan had a substantial impact in reducing overall transmission, it might not be sufficient to control disease spread. A significant vaccination coverage of those above 5 years old, a vaccine effectiveness against disease of at least 80% and softer non-pharmaceutical interventions (NPIs), such as mask usage and social distancing, would be necessary to control disease spread in the worst scenario considered. The immunity duration scenario of 1-year displays a resurgence of COVID-19 hospitalisations by the end of 2021, the same is observed in 3-year scenario although with a lower magnitude. The no-immunity-loss scenario presents a low increase in hospitalisations. In both the 1-year and 3-year scenarios, a vaccination boost of those above 65 years old would result in a 53% and 38% peak reduction of non-ICU hospitalisations, respectively. These results suggest that NPIs should not be fully phased-out but instead be combined with a fast booster vaccination strategy to reduce healthcare burden.

Understanding the exceptional pre-vaccination Era East Asian COVID-19 outcomes.

During the first year of the pandemic, East Asian countries have reported fewer infections, hospitalizations, and deaths from COVID-19 disease than most countries in Europe and the Americas. Our goal in this paper is to generate and evaluate hypothesis that may explain this striking fact. We consider five possible explanations: (1) population age structure (younger people tend to have less severe COVID-19 disease upon infection than older people); (2) the early adoption of lockdown strategies to control disease spread; (3) genetic differences between East Asian population and European and American populations that confer protection against COVID-19 disease; (4) seasonal and climactic contributors to COVID-19 spread; and (5) immunological differences between East Asian countries and the rest of the world. The evidence suggests that the first four hypotheses are unlikely to be important in explaining East Asian COVID-19 exceptionalism. Lockdowns, in particular, fail as an explanation because East Asian countries experienced similarly good infection outcomes despite vast differences in lockdown policies adopted by different countries to control the COVID-19 epidemic. The evidence to date is consistent with our fifth hypothesis – pre-existing immunity unique to East Asia – but there are still essential parts of this story left for scientists to check.

Assessing the spatial variability of raising public risk awareness for the intervention performance of COVID-19 voluntary screening: A spatial simulation approach

The rapid spread of a (re)emerging pandemic (e.g., COVID-19) is usually attributed to the invisible transmission caused by asymptomatic cases. Health authorities rely on large-scale voluntary screening to identify and isolate invisible spreaders as well as symptomatic people as early as possible to control disease spread. Raising public awareness is beneficial for improving the effectiveness of epidemic prevention because it could increase the usage and demand for testing kits. However, the effectiveness of testing could be influenced by the spatial demand for medical resources in different periods. Spatial demand could also be triggered by public awareness in areas with two geographical factors, including spatial proximity to resources and attractiveness of human mobility. Therefore, it is necessary to explore the spatial variations in raising public awareness on the effectiveness of COVID-19 screening. We implemented spatial simulation models to integrate various levels of public awareness and pandemic dynamics in time and space. Moreover, we also assessed the effects of the spatial proximity of testing kits and the ease of human mobility on COVID-19 testing at various levels of public awareness. Our results indicated that high public awareness promotes high willingness to be tested. This causes the demand to not be fully satisfied at the peak times during a pandemic, yet the shortage of tests does not significantly increase pandemic severity. We also found that when public awareness is low, concentrating on unattractive areas (such as residential or urban fringe areas) could promote a higher benefit of testing. On the other hand, when awareness is high, the factor of distances to testing stations is more important for promoting the benefit of testing; allocating additional testing resources in areas distant from stations could have a higher benefit of testing. This study aims to provide insights for health authorities into the allocation of testing resources against disease outbreaks with respect to various levels of public awareness.

Milder symptoms and shorter course in patients with re-positive COVID-19: A cohort of 180 patients from Northeast China.

China experienced another widespread Coronavirus disease 2019 (COVID-19) outbreak recently caused by the Omicron variant, which is less severe but far more contagious than the other COVID-19 variants, leading local governments to focus efforts on eliminating the spread of the disease. Previous studies showed that after “recovering” from the virus, some patients could re-test positive for COVID-19 with nucleic acid tests, challenging the control of disease spread. In this study, we aimed to analyze the clinical and laboratory characteristics of re-positive COVID-19 patients in Northeast China. We retrospectively analyzed data from confirmed reverse transcription polymerase chain reaction (RT-PCR) re-positive COVID-19 patients who were admitted to the First Hospital of Jilin University, Jilin Province, China, from March to June 2022. Detailed clinical symptoms, medical history, anti-Corona Virus (CoV) IgG and IgM levels, and CoV nucleic acid cycle threshold (Ct) values during the re-positive period were collected and analyzed. A total of 180 patients were included in this study, including 62 asymptomatic cases and 118 mild cases. The cohort included 113 men and 67 women, with an average age of 45.73 years. The median time between recovery from the virus and re-positivity was 13 days. Our results showed that the proportion of re-positive patients with symptoms was lower, and the nucleic acid test-positive duration was shorter during the re-positive period. Furthermore, in patients with underlying disease, the proportion of patients with symptoms was higher, anti-CoV IgG levels were lower, and the total disease duration was longer. In conclusion, during the re-positive period, the symptoms were milder, and the CoV nucleic acid test-positive course was shorter. The concomitant underlying disease is an important factor associated with clinical symptoms, and the overall course of COVID-19 re-positive patients may be associated with lower anti-CoV IgG levels. Large-scale and multicenter studies are recommended to better understand the pathophysiology of recurrence in patients with COVID-19.

FusIon Data Tracking System (FITS)

The field of generating movement profiles of individuals is valuable in many real-world applications (e.g., controlling disease spread or evaluating marketing engagement). Existing solutions often rely on global positioning systems (GPS) or similar systems, primarily targeted at outdoor use cases. However, the indoor tracking capabilities of current solutions either lack precision or are available in closed buildings only. The literature proposes sensor fusion approaches, but many of those are based on specific sensors. These approaches do not reveal implementation details or data to allow for their independent evaluation. Therefore, this article presents FusIon Data Tracking System ( <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FITS</monospace> ) as an approach and proof-of-concept to facilitate the correlation of data from different indoor sensors to movement profiles of different individuals. Functionally, <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FITS</monospace> does this by generating synthetic sensor measurement data based on real-world movement data and correlating objects tracked from distinct sensors by effectively solving clustering and position prediction tasks. This correlation is evaluated based on different metrics [multiple object tracker accuracy/precision (MOTA/MOTP)] in four different scenarios, for example, sparse data, high density of sensors, low density of sensors, and a base case. Finally, <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FITS</monospace> ’s performance was evaluated by increasing the load test (dataset up to 100000 measurements and 1000 visitors) to assess whether near real-time processing is feasible under a high workload.