Tracking of Travel Log and Salesforce of Covid-19 Perspective

The purpose of this analysis is to double-check the phrasing in order to make it simpler for experts and scientists to comprehend the impact of the coronavirus on the tourism industry and develop solutions to this problem. This study looks at how and why the pandemic has affected people's freedoms by analyzing the events and worries that have arisen as a result of the virus's spread. By doing so, the study pinpoints personality traits, societal norms, and unproven assumptions that the tourist sector needs to challenge and change. The report also examines the severe difficulties encountered by the travel industry throughout the Coronavirus phases and analyses some issues with the proposed remedy based on Salesforce technology. This document summarizes the nature and scope of the coronavirus, its effects on the tourism sector, and suggestions for analyzing those effects and mitigating some of them through the use of Salesforce's 'Travel Log Analysis.' © 2022 IEEE.

Automated Travel History Extraction From Clinical Notes for Informing the Detection of Emergent Infectious Disease Events: Algorithm Development and Validation.

BACKGROUND: Patient travel history can be crucial in evaluating evolving infectious disease events. Such information can be challenging to acquire in electronic health records, as it is often available only in unstructured text. OBJECTIVE: This study aims to assess the feasibility of annotating and automatically extracting travel history mentions from unstructured clinical documents in the Department of Veterans Affairs across disparate health care facilities and among millions of patients. Information about travel exposure augments existing surveillance applications for increased preparedness in responding quickly to public health threats. METHODS: Clinical documents related to arboviral disease were annotated following selection using a semiautomated bootstrapping process. Using annotated instances as training data, models were developed to extract from unstructured clinical text any mention of affirmed travel locations outside of the continental United States. Automated text processing models were evaluated, involving machine learning and neural language models for extraction accuracy. RESULTS: Among 4584 annotated instances, 2659 (58%) contained an affirmed mention of travel history, while 347 (7.6%) were negated. Interannotator agreement resulted in a document-level Cohen kappa of 0.776. Automated text processing accuracy (F1 85.6, 95% CI 82.5-87.9) and computational burden were acceptable such that the system can provide a rapid screen for public health events. CONCLUSIONS: Automated extraction of patient travel history from clinical documents is feasible for enhanced passive surveillance public health systems. Without such a system, it would usually be necessary to manually review charts to identify recent travel or lack of travel, use an electronic health record that enforces travel history documentation, or ignore this potential source of information altogether. The development of this tool was initially motivated by emergent arboviral diseases. More recently, this system was used in the early phases of response to COVID-19 in the United States, although its utility was limited to a relatively brief window due to the rapid domestic spread of the virus. Such systems may aid future efforts to prevent and contain the spread of infectious diseases.

Travel Log Analysis Tracking System Based On Salesforce For Covid-19

This review aims to examine the writing in order to assist specialists and scientists in better understanding and dealing with the impact of Coronavirus on the tourism sector. The study examines the situations and questions created as a result of the pandemic to see why and how Coronavirus - 19 has impacted people's lives. As a result, the report identifies the qualities, establishments, and preconceptions that the travel industry should question, as well as the activities that should be made to take a step ahead. The study also looks into the considerable loss the travel sector is experiencing throughout the Coronavirus stages and proposes a solution based on the Salesforce platform to address some of the issues. This provides an overview of how the Coronavirus affects the travel business, as well as recommendations for the industry, examining and settling some of them with 'Travel Log Analysis utilizing Salesforce'. © 2022 IEEE.

DETERMINANTS OF TRANSMISSION COVID-19 IN SOUTH SULAWESI

Background: Corona Virus (COVID-19) is a new respiratory viral infectious disease that can cause illnesses ranging from the common cold to severe acute respiratory syndrome. Subsequently, as of May 31, 2022, the government of South Sulawesi reported 143,276 confirmed cases, 2,463 deaths, and 140,395 recovered patients. Purpose: To analyze the impact of behavior, travel history, and comorbidities on the incidence of COVID-19 in South Sulawesi. Methods: This is observational research with a cross-sectional study design and was conducted from January-April 2022 in 7 districts of South Sulawesi Province. A population of 650 respondents with a total sample of 161 patients confirmed positive and 189 suspected of having COVID-19. The Chi-square test and multiple logistic regression were used to analyze the data. Results: There was a relationship between travel history (p0.00;OR 2.19), knowledge (p0.03;OR 1.74), and actions (p0.00;OR 0.18) on the incidence of COVID-19. Additionally, no relationship was reported between comorbidities (p0.85), attitudes (p0.90), and level of knowledge (p0.08>(0.05) on the incidence of COVID-19. The most influential variable in the rapid spread was travel history, with an exp(B) value of 2.19 CI (95%) (LL=1.26;UL=3.80). Conclusion: The results showed that travel history, knowledge, and actions made a major contribution to the spread of COVID-19 in South Sulawesi Province. (English) [ FROM AUTHOR] Latar Belakang: Virus Corona (COVID-19) adalah penyakit infeksi virus pernapasan baru yang dapat menyebabkan penyakit mulai dari flu biasa hingga sindrom pernapasan akut yang parah. Per tanggal 31 Mei 2022, Pemerintah Sulawesi Selatan melaporkan 143.276 kasus terkonfirmasi, 2.463 meninggal, dan 140.395 pasien sembuh. Tujuan: Menganalisis dampak perilaku, riwayat perjalanan, dan penyakit penyerta terhadap kejadian COVID-19 di Sulawesi Selatan. Metode: Penelitian observasional dengan desain cross-sectional yang dilakukan pada bulan Januari-April 2022 di tujuh kabupaten di Provinsi Sulawesi Selatan. Populasi penelitian sebanyak 650 responden dengan total sampel 161 pasien terkonfirmasi positif dan 189 suspek COVID-19. Analisis data menggunakan uji Chi-square dan regresi logistik berganda. Hasil: Terdapat hubungan antara riwayat perjalanan (p0,00;OR 2,19), pengetahuan (p0,03;OR 1,74), dan tindakan (p0,00;OR 0,18) terhadap kejadian COVID-19. Selain itu, tidak ada hubungan yang dilaporkan antara penyakit penyerta (p0.85), sikap (p0.90), dan tingkat pengetahuan (p0.08>(0.05) terhadap kejadian COVID-19. Variabel yang paling berpengaruh terhadap penyebaran cepat adalah riwayat perjalanan dengan nilai exp(B) 2,19 CI (95%) (LL=1,26;UL=3,80). Kesimpulan: Hasil menunjukkan bahwa riwayat perjalanan, pengetahuan, dan tindakan memberikan kontribusi besar terhadap penyebaran COVID-19 di provinsi Sulawesi Selatan. (Indonesian) [ FROM AUTHOR] Copyright of Jurnal Berkala Epidemiologi is the property of Universitas Airlangga 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.)

Transmission dynamics of novel Coronavirus-SARS-CoV-2 in South Sumatera, Indonesia.

SARS-CoV-2 has shaken the world by extremely raising death tolls, illnesses, and economic losses. The virus is transmitted by humans to other humans, spreading to more than 200 countries. This research aims to analyze the transmission dynamics of novel Coronavirus-SARS-CoV-2 in South Sumatera Indonesia. This is epidemiologic research, and the research population is all SARS-CoV-2 patients and those who have close contact with the patients in all districts/cities in South Sumatera. It has been widely known that those that have made contact with patients confirmed positive for SARS-CoV-2 has a risk of getting infected by SARS-CoV-2 by 3.591 higher than those who never have (OR = 3.591, 95% CI: 2.933-4.396). Also, according to the findings, those who have a contact history to patients confirmed positive for SARS-CoV-2 have a risk of getting infected by SARS-CoV-2 by 2.387 higher than those who never have (OR = 2.387, 95% CI: 1.362-4.184). Meanwhile, those who have no idea for having made contact with patients confirmed positive for SARS-CoV-2 has a risk of getting infected by SARS-CoV-2 by 1.082 higher than those who have never a contact history to the SARS-CoV-2 patients (OR = 1.082, 95% CI: 0.622-1.882). To prevent broader transmission, those who have made contact with the SARS-CoV-2 patients need to be quarantined. The findings help us give community health interventions to globally fight this transmittable disease.

Bayesian Phylogeographic Analysis Incorporating Predictors and Individual Travel Histories in BEAST.

Advances in sequencing technologies have tremendously reduced the time and costs associated with sequence generation, making genomic data an important asset for routine public health practices. Within this context, phylogenetic and phylogeographic inference has become a popular method to study disease transmission. In a Bayesian context, these approaches have the benefit of accommodating phylogenetic uncertainty, and popular implementations provide the possibility to parameterize the transition rates between locations as a function of epidemiological and ecological data to reconstruct spatial spread while simultaneously identifying the main factors impacting the spatial spread dynamics. Recent developments enable researchers to make use of travel history data of infected individuals in the reconstruction of pathogen spread, offering increased inference accuracy and mitigating sampling bias. Here, we describe a detailed workflow to reconstruct the spatial spread of a pathogen through Bayesian phylogeographic analysis in discrete space using these novel approaches, implemented in BEAST. The individual protocols focus on how to incorporate molecular data, covariates of spread, and individual travel history data into the analysis. © 2021 Wiley Periodicals LLC. Basic Protocol 1: Creating a SARS-CoV-2 MSA using sequences from GISAID Basic Protocol 2: Setting up a discrete trait phylogeographic reconstruction in BEAUti Basic Protocol 3: Phylogeographic reconstruction incorporating travel history information Basic Protocol 4: Visualizing ancestral spatial trajectories for specific taxa.

Examining geographical disparities in the incubation period of the COVID-19 infected cases in Shenzhen and Hefei, China.

BACKGROUND: Current studies on the COVID-19 depicted a general incubation period distribution and did not examine whether the incubation period distribution varies across patients living in different geographical locations with varying environmental attributes. Profiling the incubation distributions geographically help to determine the appropriate quarantine duration for different regions. METHODS: This retrospective study mainly applied big data analytics and methodology, using the publicly accessible clinical report for patients (n = 543) confirmed as infected in Shenzhen and Hefei, China. Based on 217 patients on whom the incubation period could be identified by the epidemiological method. Statistical and econometric methods were employed to investigate how the incubation distributions varied between infected cases reported in Shenzhen and Hefei. RESULTS: The median incubation period of the COVID-19 for all the 217 infected patients was 8 days (95% CI 7 to 9), while median values were 9 days in Shenzhen and 4 days in Hefei. The incubation period probably has an inverse U-shaped association with the meteorological temperature. The warmer condition in the winter of Shenzhen, average environmental temperature between 10 °C to 15 °C, may decrease viral virulence and result in more extended incubation periods. CONCLUSION: Case studies of the COVID-19 outbreak in Shenzhen and Hefei indicated that the incubation period of COVID-19 had exhibited evident geographical disparities, although the pathological causality between meteorological conditions and incubation period deserves further investigation. Methodologies based on big data released by local public health authorities are applicable for identifying incubation period and relevant epidemiological research.

Epidemiological characteristics and treatment outcomes of hospitalized patients with COVID-19 in Ethiopia.

INTRODUCTION: coronavirus disease (COVID-19) has been identified as the cause of an outbreak of respiratory illness which epidemiologically linked to the seafood and wet animal wholesale market in Wuhan, Hubei Province, China. Since there is paucity of research on characteristics and treatment outcomes of COVID-19, the finding of this study will helps to provide insight for the effectiveness of measures to fight against coronavirus disease in resource-limited countries. METHODS: a retrospective review of released data about cases in daily bases and documents from Ethiopian public health institute website. In this article, we included and analyzed data of cases from 13 March to 13 May 2020 which were available at the time of the review. RESULTS: a total of 263 cases were included (median age, 34 years [range, 0.9-85 years]; 76% male). COVID-19 cases among age group 15-24 years and 25-34 years were 92(35%) and 76(28.9%) respectively. More than half (55.5%) of cases had travel history abroad and African countries are the leading 64(24.3%). About 167(63.5%) cases were identified based on symptom-based surveillance and the finding confirmed an interrupted kind of epidemiological curve. Whereas, one-third (41.1%) were recovered and the overall case fatality rate was 1.9%. Four out of five patients in ICU were deceased after 2-6days spent in critical care. CONCLUSION: an integrated action includes the provision of health education to youths, taking measures to rise up treatment outcomes, enhancing ICU care quality. Moreover, tightening prevention and restriction measures to flattening the curve and also establishment of fast detection and advanced treatment of cases were critically requires through the patriotic efforts of frontline health workers, leaders, and stakeholders.

COVID-19 in children across three Asian cosmopolitan regions.

ABSTRACT As another wave of COVID-19 outbreak has approached in July 2020, a larger scale COVID-19 pediatric Asian cohort summarizing the clinical observations is warranted. Children confirmed with COVID-19 infection from the Republic of Korea, the Hong Kong Special Administrative Region (HKSAR) and Wuhan, China, during their first waves of local outbreaks were included. Their clinical characteristics and the temporal sequences of the first waves of local paediatric outbreaks were compared. Four hundred and twenty three children with COVID-19 were analyzed. Wuhan had the earliest peak, followed by Korea and HKSAR. Compared with Korea and Wuhan, patients in HKSAR were significantly older (mean age: 12.9 vs. 10.8 vs. 6.6 years, p < 0.001, respectively) and had more imported cases (87.5% vs. 16.5% vs. 0%, p < 0.001, respectively). The imported cases were also older (13.4 vs. 7.6 years, p < 0.001). More cases in HKSAR were asymptomatic compared to Korea and Wuhan (45.5% vs. 22.0% vs. 20.9%, p < 0.001, respectively), and significantly more patients from Wuhan developed fever (40.6% vs. 29.7% vs. 21.6%, p=0.003, respectively). There were significantly less imported cases than domestic cases developing fever after adjusting for age and region of origin (p = 0.046). 5.4% to 10.8% of patients reported anosmia and ageusia. None developed pediatric multisystem inflammatory syndrome temporally associated with SARS-CoV-2 (PMIS-TS). In general, adolescents were more likely to be asymptomatic and less likely to develop fever, but required longer hospital stays. In conclusion, majority patients in this pediatric Asian cohort had a mild disease. None developed PIMS-TS. Their clinical characteristics were influenced by travel history and age.

Willingness and beliefs associated with reporting travel history to high-risk coronavirus disease 2019 epidemic regions among the Chinese public: a cross-sectional study.

BACKGROUND: The Coronavirus Disease 2019 (COVID-19) that first occurred in Wuhan, China, is currently spreading throughout China. The majority of infected patients either traveled to Wuhan or came into contact with an infected person from Wuhan. Investigating members of the public with a travel history to Wuhan became the primary focus of the Chinese government's epidemic prevention and control measures, but several instances of withheld histories were uncovered as localized clusters of infections broke out. This study investigated the public's willingness and beliefs associated with reporting travel history to high-risk epidemic regions, to provide effective suggestions and measures for encouraging travel reporting. METHODS: A cross-sectional study was conducted online between February 12 and 19, 2020. Descriptive analysis, chi-squared test, and Fisher's exact test were used to identify socio-demographic factors and beliefs associated with reporting, as well as their impact on the willingness to report on travel history to high-risk epidemic regions. RESULTS: Of the 1344 respondents, 91 (6.77%) expressed an inclination to deliberately withhold travel history. Those who understood the benefits of reporting and the legal consequences for deliberately withholding information, showed greater willingness to report their history (P < 0.05); conversely, those who believed reporting would stigmatize them and feared being quarantined after reporting showed less willingness to report (P < 0.05). CONCLUSIONS: As any incident of withheld history can have unpredictable outcomes, the proportion of people who deliberately withhold information deserves attention. Appropriate public risk communication and public advocacy strategies should be implemented to strengthen the understanding that reporting on travel history facilitates infection screening and prompt treatment, and to decrease the fear of potentially becoming quarantined after reporting. Additionally, social support and policies should be established, and measures should be taken to alleviate stigmatization and discrimination against potential patients and reporters of travel history. Reinforcing the legal accountability of withholding travel history and strengthening systematic community monitoring are the measures that China is currently taking to encourage reporting on travel history to high-risk epidemic regions. These non-pharmaceutical interventions are relevant for countries that are currently facing the spread of the epidemic and those at risk of its potential spread.

Coronavirus Disease 2019 (COVID-19) pandemic, lessons to be learned!

Coronavirus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been reported as a worldwide emergency. Due to the extensiveness of spread and death, it has been declared as a pandemic. This review focused on the current pandemic situation and understanding the prevention and control strategies of COVID-19. Data presented here was by April 3, 2020. A total of 1,016,399 cases of COVID-19 with 53,238 deaths was reported from 204 countries and territories including two international conveyances over the world. After China, most of the new cases were from Europe, particularly Italy acting as the source of importation to many of the other countries around the world. China has obtained success by ascribing control strategies against COVID-19. The implementation of China's strategy, as well as the development of a vaccine, may control the pandemic of COVID-19. Further robust studies are required for a clear understanding of transmission parameters, prevention, and control strategies of SARS-CoV-2. This review paper describes the nature of COVID-19 and the possible ways for the effective controlling of the COVID-19 or similar viral diseases that may come in the future.

Incidence of novel coronavirus (2019-nCoV) infection among people under home quarantine in Shenzhen, China.

BACKGROUND: Since the outbreak of 2019-nCoV in December, Chinese government has implemented various measures including travel bans, centralized treatments, and home quarantines to slowing the transmission across the country. In this study, we aimed to estimate the incidence of 2019-nCoV infection among people under home quarantine in Shenzhen, China. METHODS: We used a stratified multistage random sampling method to recruit participants and collected demographic information and laboratory results of people under home quarantine. We conducted descriptive analysis to estimate the basic characteristics and to calculate the incidence in out study population. RESULTS: A total of 2004 people under home quarantine participated in this study, of which 1637 participants finished the questionnaire with a response rate of 81.7%. Mean age of the participants was 33.7 years, ranging from 0.3 to 80.2 years. Of people who provided clear travel history, 129 people have traveled to Wuhan city and 1,046 people have traveled to other cities in Hubei province within 14 days before the home quarantine. Few (less than 1%) participants reported contact history with confirmed or suspected cases during their trip and most of these arrived at Shenzhen between Jan 24, 2020 to Jan 27, 2020. The incidence of COVID-19 in the sample was 1.5‰ (95% CI: 0.31‰-4.37‰). CONCLUSION: Home quarantine has been effective in preventing the early transmission of COVID-19, but that more needs to be done to improve early detection of COVID-19 infection.