Demographic and risk characteristics of healthcare workers infected with SARS-CoV-2 from two tertiary care hospitals in the United Arab Emirates

BACKGROUND Understanding the transmission dynamics of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)infection among healthcare workers(HCWs)and their social contacts is crucial to plan appropriate risk-reduction measures.AIM To analyze the socio-demographic risk factors and transmission of SARS-CoV-2 infection among HCWs in two tertiary care hospitals in Dubai,United Arab Emirates.METHODS The demographic and clinical characteristics were available for all HCWs in both facilities from the human resources department.A cross-sectional survey was conducted from January-April 2022 among HCWs who tested positive through Reverse Transcriptase Polymerase Chain Reaction of the nasopharyngeal swab for SARS-CoV-2 between March 2020 and August 2021 in two tertiary-level hospitals.The survey included questions on demographics,work profile,characteristics of coronavirus disease 2019(COVID-19),and infection among their household or co-workers.The survey also checked the knowledge and perception of participants on the infection prevention measures related to SARS-CoV-2.RESULTS Out of a total of 346 HCWs infected with SARS-CoV-2,286(82.7%)HCWs consented to participate in this study.From the sample population,150(52.5%)of participants were female,and a majority(230,80.4%)were frontline HCWs,including 121 nurses(121,42.4%).Only 48(16.8%)participants were fully vaccinated at the time of infection.Most infected HCWs(85%)were unaware of any unprotected exposure and were symptomatic at the time of testing(225,78.7%).Nearly half of the participants(140,49%)had co-infection among household,and nearly one-third(29.5%)had coinfection among three or more household.Another 108(37.8%)participants reported crossinfection among co-workers.The frontline HCWs were significantly more infected(25.1%vs 8.6%,P<0.001)compared to non-frontline HCWs.Another significant risk factor for a high infection rate was male sex(P<0.001).Among the infected frontline HCWs,a significantly higher proportion were male and shared accommodation with family(P<0.001).COVID-19 vaccination significantly reduced the infection rate(83.2%vs 16.8,P<0.001)among HCWs.Most participants(99.3%)were aware about importance of appropriate use of personal protective equipment.However,only 70%agreed with the efficacy of the COVID-19 vaccination in preventing an infection and severe disease.CONCLUSION The risk profiling of the HCWs infected with SARS-CoV-2 found that working at frontline and being male increase the rate of infection.COVID-19 vaccination can effectively reduce the rate of transmission of SARS-CoV-2 among HCWs.

Assessing effects of reopening policies on COVID-19 pandemic in Texas with a data-driven transmission model

While the Coronavirus Disease 2019(COVID-19)pandemic continues to threaten public health and safety,every state has strategically reopened the business in the United States.It is urgent to evaluate the effect of reopening policies on the COVID-19 pandemic to help with the decision-making on the control measures and medical resource allocations.In this study,a novel SEIR model was developed to evaluate the effect of reopening policies based on the real-world reported COVID-19 data in Texas.The earlier reported data before the reopening were used to develop the SEIR model;data after the reopening were used for evaluation.The simulation results show that if continuing the“stay-at-home order”without reopening the business,the COVID-19 pandemic could end in December 2020 in Texas.On the other hand,the pandemic could be controlled similarly as the case of noreopening only if the contact rate was low and additional high magnitude of control measures could be implemented.If the control measures are only slightly enhanced after reopening,it could flatten the curve of the COVID-19 epidemic with reduced numbers of infections and deaths,but it might make the epidemic last longer.Based on the reported data up to July 2020 in Texas,the real-world epidemic pattern is between the cases of the low and high magnitude of control measures with a medium risk of contact rate after reopening.In this case,the pandemic might last until summer 2021 to February 2022 with a total of 4-10 million infected cases and 20,080e58,604 deaths.

Agent-based Simulation Systems for Emergency Management

Emergencies, which are very difficult to be forecasted, would always bring about huge harm to people. Therefore, to find ways to reduce such devastating effects, researches on emergency management have turned to be paramount. Nowadays, the rapid development of computer technology has supplied a new and effective idea for the researches of emergency management, namely that the researches can be done in computers by performing simulation experiments according to the artificial societies, computational experiments, parallel execution （ACP） approach. Guided by this approach, this paper has proposed one agent-based prototype simulation system to research emergency management. Firstly, structure of the simulation system oriented to emergency management was analyzed and designed. Then a simulation system oriented to public health emergency management was constructed to study the transmission of infectious diseases. Finally, several experiments were carried out based on the system, with several significant conclusions having also been obtained.