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At present time, a variety of infectious and lifestyle diseases are becoming lifethreatening day by day. Development in technology and immergence of nanoscience helped to provide a better health care system. Based on the working mechanism nano-biosensors are of majorly two types: electrochemical nanobiosensor and optical nano-biosensor. Nanomaterials used in the nano-biosensor increased their efficacy, sensitivity, and selectivity of the device. Different diseases have different biomarkers to get detected such as, absorption of cholesterol oxidase detect cholesterol, glaucoma in a diabetes patient is detected by cytokine Interleukin 12 in tear, C-reactive protein is detected for liver inflammation, the SARS virus is detected by N-protein and miRNA is a potential biomarker of cancers, especially colorectal cancer. Hitherto, identification of a biomarker for a specific disease is the major work. The accuracy of nanobiosensor in diagnosing diseases put them in demand in the biomedical field. But the major drawback comes with the cost-effectiveness and use of nanomaterial in health sectors focussing on any toxicological impact of the nano-biosensor on health in long run. In this chapter, we present an overview of the working mechanism of different nano-biosensors in diagnosing different infectious and lifestyle diseases. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.
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Objective: To analyze the vaccination status of SARS-CoV-2 in children, and explore the relationship between SARS-CoV-2 vaccination and COVID-19 in children. Methods: A retrospective study was conducted to analyze the clinical data of 335 cases of SARS-CoV-2 Omicron variant infection from February 15, 2022 to March 18, 2022 in Shenzhen Third People's Hospital. Results: Among 335 children with SARS-CoV-2 infection, 174(51.9%) cases were vaccinated with the SARS-CoV-2 vaccine;33(31.4%) cases were vaccinated in the 3-<6 years old group;141(61.3%) cases were vaccinated in the 6-<14 years old group. There was a statistically significant difference in the proportion of SARS-CoV-2 vaccination between the 6-<14 years old group and the 3-<6 years old group (X2=26.1, P < 0.05). In the study cohort, 3-<6 years old group and 6-<14 years old group, there was no significant difference in the incidence of COVID-19 in the vaccinated group compared with the unvaccinated group (P > 0.05). In the study cohort, the proportion of confirmed cases of 1 dose of SARS-CoV-2 vaccine and 2 doses or more of SARS-CoV-2 vaccine was 89.5% (68 cases) and 77.6% (76 cases), respectively;in the 6~<14 years old group, the proportion of confirmed cases of 1 dose of SARS-CoV-2 vaccine and 2 doses or more of SARS-CoV-2 vaccine was 90.0% (54 cases) and 76.5% (62 cases), respectively;the differences were statistically significant (X2=4.264, P < 0.05;X2=4.279, P < 0.05). The IgG levels of 18.28 (6.61, 55.2) AU/mL and 58.3 (25.85, 131.41) AU/mL in the study cohort who were vaccinated for 1 dose, 2 doses and more, respectively;the IgG levels of 20.13 (8.33, 44.33) AU/mL and 56.57 (25.85, 150.07) AU/mL in the 6~<14 years old group who were vaccinated for 1 dose, 2 doses and more, respectively;and the differences were statistically significant (Z=-4.37, P < 0.05;Z=-3.96, P < 0.05). Conclusions: Children who received 2 doses of SARS-CoV-2 vaccine have a lower incidence of COVID-19 and higher levels of SARS-CoV-2 antibodies compared with who received 1 dose. It is recommended that children are advised to be vaccinated against the COVID-19.
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Objective. Most respiratory infections have similar symptoms, so it is clinically difficult to determine their etiology. This study aimed to show the importance of molecular diagnostics in identifying the etiological agent of respiratory infections, especially during the coronavirus disease 2019 (COVID-19) pandemic. Methods. A total of 849 samples from patients hospitalized at the University Clinical Center Kragujevac (from January 1 to August 1, 2022) were examined using automated multiplex-polymerase chain reaction (PCR) tests. The BioFire-FilmArray-Respiratory Panel 2.1 test was used for 742 nasopharyngeal swabs [identification of 19 viruses (including SARS-CoV-2) and four bacteria], while the BioFire-FilmArray-Pneumonia Panel was used [identification of 18 bacteria and nine viruses] (BioMerieux, Marcy l'Etoile, France) for 107 tracheal aspirates. The tests were performed according to the manufacturer's instructions, and the results were available within an hour. Results. In 582 (78.4%) samples, the BioFire-FilmArray-Respiratory Panel 2.1 plus test identified at least one pathogen. The rhinovirus (20.6%), SARS-CoV-2 (17.7%), influenza A (17.5%), respiratory syncytial virus (12.4%), and parainfluenza 3 (10.1%) were the most common. Other viruses were found less frequently, and Bordetella parapertussis was detected in one sample. In 85 (79.4%) samples, the BioFire-FilmArray-Pneumonia Panel test identified at least one bacterium or virus. The most prevalent bacteria were Staphylococcus aureus (42.4%), Haemophilus influenzae (41.2%), Streptococcus pneumoniae (36.5%), Moraxella catarrhalis (22.3%), and Legionella pneumophila (2.4%). Among viruses, rhinovirus (36.5%), adenovirus (23.5%), influenza A (11.8%), and the genus Coronavirus (4.7%), were detected. Conclusion. Multiplex-PCR tests improved the implementation of therapeutic and epidemiological measures, preventing the spread of the COVID-19 infection and Legionnaires' disease.Copyright © 2022, Serbian Medical Society. All rights reserved.
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The COVID-19 pandemic that started in 2019-2020 has led to a gigantic increase in modeling and simulation of infectious diseases. There are numerous topics associated with this epoch-changing event, such as (a) disease propagation, (b) transmission, (c) decontamination, and (d) vaccines. This is an evolving field. The targeted objective of this book is to expose researchers to key topics in this area, in a very concise manner. The topics selected for discussion have evolved with the progression of the pandemic. Beyond the introductory chapter on basic mathematics, optimization, and machine learning, the book covers four themes in modeling and simulation infectious diseases, specifically: Part 1: Macroscale disease propagation, Part 2: Microscale disease transmission and ventilation system design, Part 3: Ultraviolet viral decontamination, and Part 4: Vaccine design and immune response. It is important to emphasize that the rapid speed at which the simulations operate makes the presented computational tools easily deployable as digital twins, i.e., digital replicas of complex systems that can be inexpensively and safely optimized in a virtual setting and then used in the physical world afterward, thus reducing the costs of experiments and also accelerating development of new technologies. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.
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Based on the SEIR model, two compartments for self-protection and isolation are introduced, and a more general infectious disease transmission model is proposed.Through qualitative analysis of the model, the basic reproduction number of the model is calculated, and the local asymptotic stability of the disease-free equilibrium point and the endemic equilibrium point of the model is analyzed through eigenvalue theory and Routh-Hurwitz criterion.The numerical simulation and fitting results of COVID-19 virus show that the proposed SEIQRP model can effectively describe the dynamic transmission process of the infectious disease.In the model, the three parameters, i.e.protection rate, incubation period isolation rate, and infected person isolation rate play a very critical role in the spread of the disease.Raising people's awareness of self-protection, focusing on screening for patients in the incubation period, and isolating and treating infected people can effectively reduce the spread of infectious diseases. © 2023 Northeastern University.All rights reserved.
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Non-Drug Intervention (NDI) is one of the important means to prevent and control the outbreak of coronavirus disease 2019 (COVID-19), and the implementation of this series of measures plays a key role in the development of the epidemic. The purpose of this paper is to study the impact of different mitigation measures on the situation of the COVID 19, and effectively respond to the prevention and control situation in the "post-epidemic era". The present work is based on the Susceptible-Exposed-Infectious-Remove-Susceptible (SEIRS) Model, and adapted the agent-based model (ABM) to construct the epidemic prevention and control model framework to simulate the COVID-19 epidemic from three aspects: social distance, personal protection, and bed resources. The experiment results show that the above NDI are effective mitigation measures for epidemic prevention and control, and can play a positive role in the recurrence of COVID-19, but a single measure cannot prevent the recurrence of infection peaks and curb the spread of the epidemic;When social distance and personal protection rules are out of control, bed resources will become an important guarantee for epidemic prevention and control. Although the spread of the epidemic cannot be curbed, it can slow down the recurrence of the peak of the epidemic;When people abide by social distance and personal protection rules, the pressure on bed resources will be eased. At the same time, under the interaction of the three measures, not only the death toll can be reduced, but the spread of the epidemic can also be effectively curbed. © 2022 ACM.
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Many zoonotic diseases are found in wild animals and present a serious risk to human health, in particularly the virus carried by birds flying freely around the world is hard to control. There are three main bird migration routes which cover the most areas of China. It is important to investigate and fully understand the types of avian transmitted diseases in key areas on the bird migration routines and its impacts on both birds and human health. However, no literature is available in how about the risk of virus carried by migrating birds, and how to predict and reduce this risk of virus spreading to human being so far. In this paper, we first reviewed the main pathogen types carried by birds, including coronaviruses, influenza viruses, parasites, Newcastle disease virus (NDV), etc., and then discussed the spread risk of avian viruses to human being and animals in key areas of biosafety prevention. We also analyzed and discussed the risk of cross-spread of diseases among different bird species in nature reserves located on bird migration routes which provide sufficient food sources for migratory birds and attract numerous birds. Diseases transmitted by wild birds pose a serious threat to poultry farms, where high density of poultry may become avian influenza virus (AIV) reservoirs, cause a risk of avian influenza outbreaks. Airports are mostly built in suburban areas or remote areas with good ecological environment. There are important transit places for bird migration and densely populated areas, which have serious risk of disease transmission. Finally, this paper puts forward the following prevention suggestions from three aspects. First, establish and improve the monitoring and prediction mechanism of migratory birds, and use laser technology to prevent contact between wild birds and poultry. Second, examine and identify virus types carried by birds in their habitats and carry out vaccination. Third, protect the ecological environment of bird habitat, and keep wild birds in their natural habitat, so as to reduce the contact between wild birds and human and poultry, and thus reduce the risk of virus transmission.
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Urban scaling law quantifies the disproportional growth of urban indicators with urban population size, which is one of the simple rules behind the complex urban system. Infectious diseases are closely related to social interactions that intensify in large cities, resulting in a faster speed of transmission in large cities. However, how this scaling relationship varies in an evolving pandemic is rarely investigated and remains unclear. Here, taking the COVID- 19 epidemic in the United States as an example, we collected daily added cases and deaths from January 2020 to June 2022 in more than three thousand counties to explore the scaling law of COVID- 19 cases and city size and its evolution over time. Results show that COVID- 19 cases super- linearly scaled with population size, which means cases increased faster than population size from a small city to a large city, resulting in a higher morbidity rate of COVID- 19 in large cities. Temporally, the scaling exponent that reflects the scaling relationship stabilized at around 1.25 after a fast increase from less than one. The scaling exponent gradually decreased until it was close to one. In comparison, deaths caused by the epidemic did not show a super-linear scaling relationship with population size, which revealed that the fatality rate of COVID-19 in large cities was not higher than that in small or medium-sized cities. The scaling exponent of COVID- 19 deaths shared a similar trend with that of COVID- 19 cases but with a lag in time. We further estimated scaling exponents in each wave of the epidemic, respectively, which experienced the common evolution process of first rising, then stabilizing, and then decreasing. We also analyzed the evolution of scaling exponents over time from regional and provincial perspectives. The northeast, where New York State is located, had the highest scaling exponent, and the scaling exponent of COVID- 19 deaths was higher than that of COVID-19 cases, which indicates that large cities in this region were more prominently affected by the epidemic. This study reveals the size effect of infectious diseases based on the urban scaling law, and the evolution process of scaling exponents over time also promotes the understanding of the urban scaling law. The mechanism behind temporal variations of scaling exponents is worthy of further exploration. © 2023 Science Press. All rights reserved.
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Severe Acute Respiratory Syndrome Coronavirus 2 Related Diseases (COVID-19) is now one of the most challenging and concerning epidemics, which has been affecting the world so much. After that, countries around the world have been actively developing vaccines to deal with the sudden disease. How to carry out more efficient epidemic prevention has also become a problem of our concern. Unlike traditional SIR disease transmission models, network percolation has unique advantages in disease immune modelling, which makes it closer to reality in the simulation. This article introduces the study of SIR percolation network on infection probabilities of COVID-19, and proposes a method to preventing the spread of disease. © 2022 IEEE.
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Objective: To analyze the clinical manifestations, diagnostic methods and treatment process of the patients with non-Hodgkin's lymphoma complicated with human coronavirus(HCoV)-HKU1 pneumonia and improve the clinical medical staff's awareness of the disease, and to reduce the occurrence of clinical adverse events. Method(s): The clinical data of a patient with non-Hodgkin's lymphoma complicated with HCoV-HKU1 pneumonia with hot flashes and night sweats, dry cough and dry throat as the main clinical features who were hospitalized in the hospital in January 2021 were analyzed, and the relevant literatures were reviewed and the clinical manifestations and diagnosis of HCoV-HKU1 were analyzed. Result(s): The female patient was admitted to the hospital due to diagnosed non-Hodgkin's lymphoma for more than 2 months. The physical examination results showed Karnofsky score was 90 points;there was no palpable enlargement of systemic superfical lymph nodes;mild tenderness in the right lower abdomen, no rebound tenderness, and slightly thicker breath sounds in both lungs were found, and a few moist rales were heard in both lower lungs. The chest CT results showed diffuse exudative foci in both lungs, and the number of white blood cells in the urine analysis was 158 muL-1;next generation sequencing technique(NGS) was used the detect the bronchoalveolar lavage fluid, and HCoV-HKU1 pneumonia was diagnosed. At admission, the patient had symptoms such as dull pain in the right lower abdomen, nighttime cough, and night sweats;antiviral treatment with oseltamivir was ineffective. After treatment with Compound Sulfamethoxazole Tablets and Lianhua Qingwen Granules, the respiratory symptoms of the patient disappeared. The re-examination chest CT results showed the exudation was absorbed. Conclusion(s): The clinical symptoms of the patients with non-Hodgkin's lymphoma complicated with HCoV-HKU1 pneumonia are non-specific. When the diffuse shadow changes in the lungs are found in clinic, and the new coronavirus nucleic acid test is negative, attention should still be paid to the possibility of other HCoV infections. The NGS can efficiently screen the infectious pathogens, which is beneficial to guide the diagnosis and treatment of pulmonary infectious diseases more accurately.Copyright © 2023 Jilin University Press. All rights reserved.
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Global infections are very frequent cause of AKI. Often this is due to the non-specific systemic effects of sepsis and volume depletion and therefore can occur with many infectious agents perhaps most searingly brought to our attention with the SARS-CoV-2 pandemic. The kidney can also be damaged by infections directly involving the renal parenchyma, because of persistent infection elsewhere in the body, as a post-infectious response and secondary diseases causing obstruction. Identifying, first, that kidney injury is due to infection and the particular infection causing the patient's presentation is critical to management. Some infections discussed in this chapter are confined to specific areas of the world, but with increasing global travel and migration, patients may present to healthcare facilities anywhere;thus, a thorough travel history is invaluable. © Springer Nature Switzerland AG 2014, 2022.
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After the outbreak of COVID-19, it is of great significance to find an appropriate dynamic model of COVID-19 epidemic in order to master its transmission law, predict its development trend, and provide corresponding prevention and control basis. In this paper, the SEIRV chamber model is adopted, and the dynamics model of infectious disease is established by combining the fractional derivative of Conformable. The fractional derivative differential equation of Conformable is discretized by numerical method and its numerical solution is obtained. In addition, numerical simulation was carried out on the confirmed data of Wuhan city from January 23, 2020 to February 11, 2020. At the same time, consider that the Wuhan municipal government revised the epidemic data on February 12, 2020, adding nearly 14,000 people. The order α value of SEIRV model is modified, and then the revised data is simulated. The simulation results are in good agreement with the published data. The results show that compared with the traditional integer order model, the fractional order model can simulate the modified data. This reflects the advantages of fractional infectious disease dynamics model, and can provide certain reference value for the prediction of COVID-19 model. © 2022 Editorial Borad of Complex Systems and Complexity Science. All rights reserved.
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As cruise ships call at many ports and passengers come from all over the world, it is very easy to carry viruses on cruise ships. Under the control of the epidemic situation on board, the solid waste generated by them should be scientifically treated to prevent the spread of infectious diseases such as COVID-19 pneumonia. Therefore, Reasonable selection of waste disposal ports and formulation of unloading plans are directly related to the resumption of cruise operations. This study considers the cost and risk of waste disposal, uses robust optimization to deal with waste volume, increases the scenarios of port service interruption due to epidemics and other reasons, and proposes a variety of emergency strategies. Finally, the relevant strategies are selected according to the decision-maker's preference for cost and risk;By solving the relevant examples, the optimal choice of the cruise ship waste disposal port under the epidemic situation is given, which verifies the validity and feasibility of the model. The research helps to improve the management of cruise waste during the post-epidemic period, and has practical value and guiding significance for the normal operation and development of the global cruise market. © 2023 SPIE.
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Given the time criticality of finding treatments for the novel COVID-19 pandemic disease, drug repurposing has proved to be a vital strategy as the first response while de novo drug and vaccine developments are underway. Furthermore, Artificial Intelligence (AI) has also accelerated drug development in general. Key desirable features of AI that support a rapid and sustained response along the pandemic timeline include technical flexibility and efficiency (i.e. speed, resource-efficiency, algorithm adaptability), and clinical applicability and acceptability (i.e. scientific rigor, physiological applicability and practical implementation of proposed drugs). This chapter reviews a selection of AI-based applications used in drug development targeting COVID-19, including IDentif.AI-a small data platform for a rapid identification of optimal drug combinations, to illustrate the potential of AI in drug repurposing. The benefits and limitations of using Real-World Data are also discussed. The response to the COVID-19 pandemic has offered multiple learnings which highlight the need to strengthen both short- and long-term strategies in developing AI technologies, scientific and regulatory frameworks as well as worldwide collaborations to enable effective preparedness for future epidemic and pandemic risks. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.
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For many science teachers and science teacher educators, COVID-19 made clear a need to focus on the socioscientific issues. [...]it subverts and undercuts the goals of having inquiry in the standards as it was intended. [...]the lack of ability to address things outside the standards leads to a lesser engagement with inquiry as it becomes more a poorly implemented default than a carefully crafted learning objective. [...]it is one with no explicit link to the NGSS. [...]teachers have made a choice either to teach about IDE outside the content mandated by the NGSS-perhaps under the cover of inquiry-or to avoid instruction on the most relevant and immediate socioscientific issue in students' lives. [...]current events have prompted a resurgence of this discussion (Zucker and Noyce 2020). [...]examination and discussion of how the NGSS might be understood or implemented in more adaptive ways is both timely and productive for scholars and policy makers who have a vested interest in the sufficiency or potential shortcomings of the dominant set of science education standards.
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According to recent market research, the vaccines market is expected to grow at a compound annual rate of 14.7% for the forecast period of 2020-2026 (1), the growth of which has been accelerated by the recent COVID-19 pandemic. Durability of glass vials at very low temperatures and permeability of plastic vials has complicated the packaging decisions as well." Since the beginning of the pandemic, the bio/pharma industry has been under pressure to produce stable formulations for effective vaccines in accelerated timescales, Blouet asserts. [...]the drive for a COVID-19 vaccine has occurred during a period of increased basic scientific understanding, such as in genomics and structural biology, supporting a new wave of vaccine development and production, she says. According to Phadnis, in addition to single-use technologies, automation for high throughput and robust analytical assays are necessary for rapid turnover during development and manufacturing of vaccines.
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Background and Aim: QX-like infectious bronchitis virus (IBV) is a highly infectious avian coronavirus that causes respiratory and kidney disease. It is linked to increased mortality and loss of performance in infected chickens worldwide, including Thailand. Thus, a simple and rapid diagnostic method for the diagnosis of QX-like IBV is needed. This study aimed to develop a single-step multiplex reverse transcription-polymerase chain reaction (mRT-PCR) assay to detect and differentiate QX-like IBV from Thai IBV and vaccine strains used in the poultry industry (H120, Ma5, and 4/91). Materials and Methods: Primer sets specific for QX-like and Thai IBV were designed to target the S1 gene. The specificity of the technique was verified using nine isolates of QX-like IBV, four isolates of Thai IBV, and other avian viral respiratory pathogens. The detection limit was evaluated using a serial ten-fold dilution of QX-like and Thai IBV. Results: The results showed that single-step mRT-PCR could detect QX-like IBV and differentiate it from Thai IBV and the vaccine strains H120, Ma5, and 4/91. The limit of detection of the developed assay was 102.2 embryo infectious dose (EID)50/mL for QX-like IBV and 101.8 EID50/mL for Thai IBV. Interestingly, the developed assay could identify mixed infection by both IBVs in a single sample. Conclusion: The single-step mRT-PCR assay developed in this study can potentially discriminate QX-like IBV from Thai IBV and the vaccine strains H120, Ma5, and 4/91 in a single reaction. It is also suitable for use in all laboratories with access to conventional PCR equipment. [ FROM AUTHOR] Copyright of Veterinary World is the property of Veterinary World and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
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Most countries in the world closed their educational centers and maintained classes online to prevent the spread of the virus SARSV-Cov-2. Latin America is not an exception. Estimates of the transmission dynamics of the pandemic indicate the application of actions that will affect educational contexts for years. This piece reflects on necessary changes in educational policies to take account of the current setting of COVID-19. We focus this reflection from a Latino American perspective, but it is not exclusive. The discussion can be useful to other countries with similar characteristics. [ FROM AUTHOR] Copyright of Journal of Latinos & Education is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
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This study explores the association between experiencing food insecurity and COVID-19 diagnosis in the United States, and what sociodemographic characteristics moderate this relationship. We analyzed a national sample of adults in the United States (n = 6,475). Multiple logistic regression results revealed respondents experiencing food insecurity had an approximately 3.0 times significantly higher odds of a positive COVID-19 diagnosis (odds ratio [OR] = 2.95, 95% confidence interval [CI] = 1.38-6.32, p < 0.01), which remained significant after adjusting for sociodemographics and COVID-19 mitigation behaviors (OR = 2.59, 95% CI = 1.09-6.18, p < 0.05). Age group had a significant moderating effect (OR = 42.55, 95% CI = 3.13-579.15, p < 0.01). Results indicate experiencing food insecurity is associated with contracting COVID-19.Copyright © 2022 Taylor & Francis Group, LLC.