Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 20 de 331
Filter
1.
JMIR Public Health Surveill ; 7(4): e24288, 2021 04 06.
Article in English | MEDLINE | ID: covidwho-2141291

ABSTRACT

BACKGROUND: There is an urgent need for consistent collection of demographic data on COVID-19 morbidity and mortality and sharing it with the public in open and accessible ways. Due to the lack of consistency in data reporting during the initial spread of COVID-19, the Equitable Data Collection and Disclosure on COVID-19 Act was introduced into the Congress that mandates collection and reporting of demographic COVID-19 data on testing, treatments, and deaths by age, sex, race and ethnicity, primary language, socioeconomic status, disability, and county. To our knowledge, no studies have evaluated how COVID-19 demographic data have been collected before and after the introduction of this legislation. OBJECTIVE: This study aimed to evaluate differences in reporting and public availability of COVID-19 demographic data by US state health departments and Washington, District of Columbia (DC) before (pre-Act), immediately after (post-Act), and 6 months after (6-month follow-up) the introduction of the Equitable Data Collection and Disclosure on COVID-19 Act in the Congress on April 21, 2020. METHODS: We reviewed health department websites of all 50 US states and Washington, DC (N=51). We evaluated how each state reported age, sex, and race and ethnicity data for all confirmed COVID-19 cases and deaths and how they made this data available (ie, charts and tables only or combined with dashboards and machine-actionable downloadable formats) at the three timepoints. RESULTS: We found statistically significant increases in the number of health departments reporting age-specific data for COVID-19 cases (P=.045) and resulting deaths (P=.002), sex-specific data for COVID-19 deaths (P=.003), and race- and ethnicity-specific data for confirmed cases (P=.003) and deaths (P=.005) post-Act and at the 6-month follow-up (P<.05 for all). The largest increases were race and ethnicity state data for confirmed cases (pre-Act: 18/51, 35%; post-Act: 31/51, 61%; 6-month follow-up: 46/51, 90%) and deaths due to COVID-19 (pre-Act: 13/51, 25%; post-Act: 25/51, 49%; and 6-month follow-up: 39/51, 76%). Although more health departments reported race and ethnicity data based on federal requirements (P<.001), over half (29/51, 56.9%) still did not report all racial and ethnic groups as per the Office of Management and Budget guidelines (pre-Act: 5/51, 10%; post-Act: 21/51, 41%; and 6-month follow-up: 27/51, 53%). The number of health departments that made COVID-19 data available for download significantly increased from 7 to 23 (P<.001) from our initial data collection (April 2020) to the 6-month follow-up, (October 2020). CONCLUSIONS: Although the increased demand for disaggregation has improved public reporting of demographics across health departments, an urgent need persists for the introduced legislation to be passed by the Congress for the US states to consistently collect and make characteristics of COVID-19 cases, deaths, and vaccinations available in order to allocate resources to mitigate disease spread.


Subject(s)
COVID-19 , Coronavirus Infections , Data Collection , Public Health Surveillance , Adolescent , Adult , Aged , Aged, 80 and over , Child , Child, Preschool , Coronavirus Infections/epidemiology , Coronavirus Infections/ethnology , Data Interpretation, Statistical , District of Columbia , Female , Humans , Infant , Infant, Newborn , Male , Middle Aged , Time Factors , United States/epidemiology , Young Adult
2.
Rev Bras Enferm ; 75(5): e750501, 2022 08 01.
Article in English, Portuguese, Spanish | MEDLINE | ID: covidwho-2118354
3.
Aust J Gen Pract ; 51(11): 879-883, 2022 11.
Article in English | MEDLINE | ID: covidwho-2100931

ABSTRACT

BACKGROUND: International travel is resuming, but the COVID-19 pandemic has radically changed the context in terms of regulation, risks and models of travel. OBJECTIVE: Providing travel health advice is an important role for general practice. The aim of this article is to cover the changed context and wide-ranging implications of the COVID­19 pandemic for travel health advice. DISCUSSION: Travel in the COVID-19 era requires travellers to be well informed and prepared to comply with complex and evolving public health measures. There are changing patterns of infectious disease risk related to the impacts of the pandemic, increasing antimicrobial resistance and climate change. New models of travel include a shift towards greater environmental sustainability.


Subject(s)
COVID-19 , Pandemics , Humans , Pandemics/prevention & control , COVID-19/epidemiology , COVID-19/prevention & control , Travel , Family Practice , Data Collection
4.
BMC Public Health ; 22(1): 1921, 2022 10 15.
Article in English | MEDLINE | ID: covidwho-2079404

ABSTRACT

BACKGROUND: The age-specific distribution of SARS-CoV-2 cases in schools is not well described. Reported statistics reflect the intensity of community transmission while being shaped by biases from age-dependent testing regimes, as well as effective age-specific interventions. A case surveillance system was introduced within the Flemish school and health-prevention network during the 2020-2021 school year. We present epidemiological data of in-school reported cases in pre-, primary and secondary schools identified by the case surveillance system, in conjunction with test data and community cases from October 2020 to June 2021. METHODS: We describe the development of the surveillance system and provide the number of reported cases and standardized rates per grade over time. We calculated absolute and relative differences in case incidence according to school grade (primary: grades 1-6, and secondary: grades 7-12) using grades 7-8 as a comparator, relating them to non-pharmaceutical infection prevention interventions. Cumulative population incidences (IP) stratified by age, province and socioeconomic status (SES) of the school population are presented with their 95% confidence intervals (CI). RESULTS: A total of 59,996 COVID-19 cases were reported in the school surveillance system, with the highest population adjusted IP in grade 11-12 of 7.39% (95%CI 7.24-7.53) and ranging from 2.23% to 6.25% from pre-school through grade 10. Age-specific reductions in mask introduction and in-person teaching were temporally associated with decreased case incidence, while lower pupil SES was associated with an increase in cumulative cases (excess 2,739/100,000 pupils compared to highest SES tertile). Community testing volumes varied more for children compared to adults, with overall higher child test-positivity. Holidays influence capturing of cases by the system, however efficiency increased to above 75% after further automation and integration in existing structures. CONCLUSION: We demonstrate that effective integration of case surveillance within an electronic school health system is feasible, provides valuable data regarding the evolution of an epidemic among schoolchildren, and is an integral component of public health surveillance and pandemic preparedness. The relationship towards community transmission needs careful evaluation because of age-different testing regimens. In the Flemish region, case incidence within schools exhibited an age gradient that was mitigated through grade-specific interventions, though differences by SES remain.


Subject(s)
COVID-19 , Adult , COVID-19/epidemiology , Child , Child, Preschool , Data Collection , Humans , SARS-CoV-2 , Schools , Schools, Public Health
5.
Clin J Sport Med ; 32(5): e444-e450, 2022 09 01.
Article in English | MEDLINE | ID: covidwho-2063065

ABSTRACT

ABSTRACT: Previous studies involving injury surveillance in badminton players have used nonstandardized injury definitions and data collection methodologies. The purpose of this study was to apply a Delphi method to (1) reach a consensus on an injury definition in badminton and (2) develop a standardized badminton injury report form. An Injury Consensus Group was established under the auspices of the Badminton World Federation, and initial injury definitions and injury report form were developed. An internal panel was formed from the Injury Consensus Group, and an external panel was selected based on a combination of profession, experience in the field, sport-specific knowledge/expertise, and geographical location to obtain a widely representative sample. Through 2 rounds of voting by the external panel, consensus was reached on both the definition of an injury in badminton and a standardized injury report form. The agreed injury definition was "Any physical injury sustained by a player during a match or training regardless if further diagnostic tests were done or if playing time was lost" and the injury report form contained the following 7 sections: Injury record, Diagnosis, Injury mechanism, Regarding pain, Pain and return to play/training after injury, Grade of severity, and Recurrence. We recommend the use of the definitions and methods presented in this consensus statement for the reporting of injury in all international and domestic badminton players. This should make future injury surveillance reports directly comparable and hence more informative in recognizing trends over time and differences between countries.


Subject(s)
Athletic Injuries , Racquet Sports , Athletic Injuries/diagnosis , Athletic Injuries/epidemiology , Consensus , Data Collection , Delphi Technique , Humans , Pain
6.
BMJ Open Qual ; 11(3)2022 09.
Article in English | MEDLINE | ID: covidwho-2053229

ABSTRACT

NEPHwork was established in 2020 as a renal specialty trainee-driven national quality improvement and research network with the aim of coupling the benefits of trainee-led collaboration with the rich data collection infrastructure established by the UK renal registry. NEPHwork was established to support the development, coordination and delivery of audit and research projects by renal trainees on a national scale. The first collaborative project centred on the compliance with care quality standards in managing acute kidney injury. The project enabled a large amount of data to be collected over a relatively short period of time and allowed comparison between renal units involved in contributing to the data. The initiation of the NEPHwork collaboration had to overcome delays and service pressure related to the COVID-19 pandemic. Furthermore, the method of linkage analysis used in the data collection and lack of cohesion with regional information technology (IT) services prevented trainees from certain regions from contributing to the project and this is a key priority for the next NEPHwork collaboration.


Subject(s)
COVID-19 , Quality Improvement , Data Collection , Humans , Pandemics , United Kingdom
8.
Vaccine ; 40(44): 6431-6444, 2022 Oct 19.
Article in English | MEDLINE | ID: covidwho-2042184

ABSTRACT

This is a Brighton Collaboration case definition of thrombosis and thromboembolism to be used in the evaluation of adverse events following immunization, and for epidemiologic studies for the assessment of background incidence or hypothesis testing. The case definition was developed by a group of experts convened by the Coalition for Epidemic Preparedness Innovations (CEPI) in the context of active development of SARS-CoV-2 vaccines. The case definition format of the Brighton Collaboration was followed to develop a consensus definition and defined levels of certainty, after an exhaustive review of the literature and expert consultation. The document underwent peer review by the Brighton Collaboration Network and by selected expert reviewers prior to submission.


Subject(s)
COVID-19 , Thromboembolism , Thrombosis , Humans , COVID-19 Vaccines , SARS-CoV-2 , COVID-19/epidemiology , COVID-19/prevention & control , Immunization/adverse effects , Data Collection , Thrombosis/etiology , Thromboembolism/etiology
9.
Zhonghua Liu Xing Bing Xue Za Zhi ; 43(9): 1376-1380, 2022 Sep 10.
Article in Chinese | MEDLINE | ID: covidwho-2040004

ABSTRACT

Objective: To understand the epidemiological characteristics of a local clustered epidemic caused by 2019-nCoV Delta variant in Ningbo and provide reference for the improvement of COVID-19 epidemic prevention and control. Methods: Case finding was conducted based on case definitions, and field epidemiological investigation of COVID-19 cases was carried out. In which Nasal and oropharyngeal swabs of the cases were collected for pathogen testing, and the results were analyzed with descriptive epidemiological methods. Results: A total of 74 COVID-19 cases were reported in this epidemic, and the cases were mainly mild ones, accounting for 87.84% (65/74), and there were no severe or critical cases. The epidemic curve showed a human-to-human transmission mode, indicating that a transmission for at least six generations had occurred. The age of the COVID-19 patients ranged from 2 years to 80 years, and 27.03% (20/74) of the cases were older than 60 years. The cases were mainly workers (55.41%, 41/74) and housework/the unemployed (27.03%, 20/74). The COVID-19 epidemic was limited, and no further spread to other areas occurred. The transmission chain among the cases was clear, and the gene sequencing results confirmed that the current epidemic was caused by 2019-nCoV Delta variant, which was highly homologous to the strains from other province. Conclusion: The local COVID-19 epidemic in Ningbo was caused by imported cases of COVID-19 from other province, and local community spread occurred through daily contacts between cases and contacts.


Subject(s)
COVID-19 , Epidemics , COVID-19/epidemiology , Child, Preschool , Data Collection , Humans , SARS-CoV-2
10.
BMJ Open ; 12(9): e064096, 2022 09 17.
Article in English | MEDLINE | ID: covidwho-2038315

ABSTRACT

OBJECTIVES: This study aims to determine the COVID-19 vaccination coverage and the factors associated with vaccine acceptance and hesitancy in the general population of Pakistan. SETTING: This population-based study covers all major areas of Pakistan, including Sindh, Punjab, Khyber Pakhtunkhwa and Baluchistan provinces and the capital Islamabad. PARTICIPANTS: A total of 541 male and female Pakistani adults above 18 years were interviewed to determine the COVID-19 vaccination coverage and understand the factors associated with vaccine acceptance and hesitancy. OUTCOME: The outcome was COVID-19 vaccination status (not vaccinated or vaccinated). RESULTS: Of 541 participants, 227 (41.96%) were non-vaccinated and 314 (58.04%) were vaccinated. Two-thirds of the participants from both the non-vaccinated and vaccinated groups (185 (81.50%) vs 236 (75.16%), p=0.008) reside in Sindh. Nearly one-third of participants from both groups were ever infected with COVID-19 (77 (33.92%) and 90 (28.66%)). The odds of COVID-19 vaccination among the age group 34-42 years were 1.75 times higher (95% CI 1.35 to 2.09, p=0.008) than the other age groups. The odds of COVID-19 vaccination among those with COVID-19 ever-infected family members were 1.87 times higher (95% CI 1.56 to 2.34, p=0.032) than those with uninfected family members. CONCLUSIONS: Targeted interventions for subsets of populations reluctant to vaccination can improve vaccine coverage. Moreover, advocacy and explaining the public health benefits of vaccination can enhance the coverage in Pakistan.


Subject(s)
COVID-19 Vaccines , COVID-19 , Adult , COVID-19/epidemiology , COVID-19/prevention & control , Data Collection , Female , Humans , Male , Pakistan/epidemiology , Vaccination
11.
J Med Internet Res ; 24(9): e37752, 2022 09 06.
Article in English | MEDLINE | ID: covidwho-2022379

ABSTRACT

BACKGROUND: Physicians are increasingly using Twitter as a channel for communicating with colleagues and the public. Identifying physicians on Twitter is difficult due to the varied and imprecise ways that people self-identify themselves on the social media platform. This is the first study to describe a reliable, repeatable methodology for identifying physicians on Twitter. By using this approach, we characterized the longitudinal activity of US physicians on Twitter. OBJECTIVE: We aimed to develop a reliable and repeatable methodology for identifying US physicians on Twitter and to characterize their activity on Twitter over 5 years by activity, tweeted topic, and account type. METHODS: In this study, 5 years of Twitter data (2016-2020) were mined for physician accounts. US physicians on Twitter were identified by using a custom-built algorithm to screen for physician identifiers in the Twitter handles, user profiles, and tweeted content. The number of tweets by physician accounts from the 5-year period were counted and analyzed. The top 100 hashtags were identified, categorized into topics, and analyzed. RESULTS: Approximately 1 trillion tweets were mined to identify 6,399,146 (<0.001%) tweets originating from 39,084 US physician accounts. Over the 5-year period, the number of US physicians tweeting more than doubled (ie, increased by 112%). Across all 5 years, the most popular themes were general health, medical education, and mental health, and in specific years, the number of tweets related to elections (2016 and 2020), Black Lives Matter (2020), and COVID-19 (2020) increased. CONCLUSIONS: Twitter has become an increasingly popular social media platform for US physicians over the past 5 years, and their use of Twitter has evolved to cover a broad range of topics, including science, politics, social activism, and COVID-19. We have developed an accurate, repeatable methodology for identifying US physicians on Twitter and have characterized their activity.


Subject(s)
COVID-19 , Physicians , Social Media , Algorithms , Data Collection , Humans
12.
J Med Internet Res ; 24(8): e29186, 2022 08 02.
Article in English | MEDLINE | ID: covidwho-2022318

ABSTRACT

BACKGROUND: Patients use social media as an alternative information source, where they share information and provide social support. Although large amounts of health-related data are posted on Twitter and other social networking platforms each day, research using social media data to understand chronic conditions and patients' lifestyles is limited. OBJECTIVE: In this study, we contributed to closing this gap by providing a framework for identifying patients with inflammatory bowel disease (IBD) on Twitter and learning from their personal experiences. We enabled the analysis of patients' tweets by building a classifier of Twitter users that distinguishes patients from other entities. This study aimed to uncover the potential of using Twitter data to promote the well-being of patients with IBD by relying on the wisdom of the crowd to identify healthy lifestyles. We sought to leverage posts describing patients' daily activities and their influence on their well-being to characterize lifestyle-related treatments. METHODS: In the first stage of the study, a machine learning method combining social network analysis and natural language processing was used to automatically classify users as patients or not. We considered 3 types of features: the user's behavior on Twitter, the content of the user's tweets, and the social structure of the user's network. We compared the performances of several classification algorithms within 2 classification approaches. One classified each tweet and deduced the user's class from their tweet-level classification. The other aggregated tweet-level features to user-level features and classified the users themselves. Different classification algorithms were examined and compared using 4 measures: precision, recall, F1 score, and the area under the receiver operating characteristic curve. In the second stage, a classifier from the first stage was used to collect patients' tweets describing the different lifestyles patients adopt to deal with their disease. Using IBM Watson Service for entity sentiment analysis, we calculated the average sentiment of 420 lifestyle-related words that patients with IBD use when describing their daily routine. RESULTS: Both classification approaches showed promising results. Although the precision rates were slightly higher for the tweet-level approach, the recall and area under the receiver operating characteristic curve of the user-level approach were significantly better. Sentiment analysis of tweets written by patients with IBD identified frequently mentioned lifestyles and their influence on patients' well-being. The findings reinforced what is known about suitable nutrition for IBD as several foods known to cause inflammation were pointed out in negative sentiment, whereas relaxing activities and anti-inflammatory foods surfaced in a positive context. CONCLUSIONS: This study suggests a pipeline for identifying patients with IBD on Twitter and collecting their tweets to analyze the experimental knowledge they share. These methods can be adapted to other diseases and enhance medical research on chronic conditions.


Subject(s)
Inflammatory Bowel Diseases , Social Media , Chronic Disease , Data Collection/methods , Humans , Inflammatory Bowel Diseases/diagnosis , Retrospective Studies
13.
J Transcult Nurs ; 33(6): 742-751, 2022 11.
Article in English | MEDLINE | ID: covidwho-2020944

ABSTRACT

INTRODUCTION: Even under normal circumstances, anxiety is quite common among nursing students. Therefore, this study compared nursing students' health and coronavirus anxiety in two European countries. METHOD: The sample of the descriptive, cross-sectional study consisted of 685 undergraduate students studying at two different nursing schools in Turkey and Portugal. The study data were collected with the Personnel Data Collection Form, Coronavirus Anxiety Scale, and Short Health Anxiety Inventory. RESULTS: While there was no difference between the Coronavirus Anxiety Scale scores of Turkish and Portuguese nursing students (p > .05), a statistically significant difference was found between the Short Health Anxiety Inventory total scores and negative consequences scores (p < .05). DISCUSSION: Against the pandemic that the whole world is experiencing, it is recommended to compare nursing students in a cultural context and take precautions.


Subject(s)
Coronavirus , Students, Nursing , Anxiety/epidemiology , Anxiety/etiology , Cross-Sectional Studies , Data Collection , Humans , Turkey/epidemiology
14.
Comput Intell Neurosci ; 2022: 4383245, 2022.
Article in English | MEDLINE | ID: covidwho-2020503

ABSTRACT

This study aims to establish the model of the cryptocurrency price trend based on a financial theory using the Long Short-Term Memory (LSTM) networks model with multiple combinations between the window length and the predicting horizons. The Random Walk model is also applied with different parameter settings. The object of this study is the cryptocurrency and medical issues, primarily the Bitcoin and Ethereum and the COVID-19. Quantitative analysis is adopted as the method of this dissertation. The research tool is Python programming language, and the TensorFlow package is employed to model and analyze research topics. The results of this study show the limitations of the LSTM and Random Walk model for price prediction while demonstrating the different characteristics of both models with different parameter settings, providing a balance between the model's accuracy and the model's practicality.


Subject(s)
COVID-19 , Deep Learning , Data Collection , Humans , Memory, Long-Term
15.
BMJ Open ; 12(8): e063236, 2022 08 29.
Article in English | MEDLINE | ID: covidwho-2020064

ABSTRACT

OBJECTIVES: Decentralised clinical trial activities-such as participant recruitment via social media, data collection through wearables and direct-to-participant investigational medicinal product (IMP) supply-have the potential to change the way clinical trials (CTs) are conducted and with that to reduce the participation burden and improve generalisability. In this study, we investigated the decentralised and on-site conduct of trial activities as reported in CT protocols with a trial start date in 2019 or 2020. DESIGN: We ascertained the decentralised and on-site conduct for the following operational trial activities: participant outreach, prescreening, screening, obtaining informed consent, asynchronous communication, participant training, IMP supply, IMP adherence monitoring, CT monitoring, staff training and data collection. Results were compared for the public versus private sponsors, regions involved, trial phases and four time periods (the first and second half of 2019 and 2020, respectively). SETTING: Phases 2, 3 and 4 clinical drug trial protocols with a trial start date in 2019 or 2020 available from ClinicalTrials.gov. OUTCOME MEASURES: The occurrence of decentralised and on-site conduct of the predefined trial activities reported in CT protocols. RESULTS: For all trial activities, on-site conduct was more frequently reported than decentralised conduct. Decentralised conduct of the individual trial activities was reported in less than 25.6% of the 254 included protocols, except for decentralised data collection, which was reported in 68.9% of the protocols. More specifically, 81.9% of the phase 3 protocols reported decentralised data collection, compared with 73.3% and 47.0% of the phase 2 and 4 protocols, respectively. For several activities, including prescreening, screening and consenting, upward trends in reporting decentralised conduct were visible over time. CONCLUSIONS: Decentralised methods are used in CTs, mainly for data collection, but less frequently for other activities. Sharing best practices and a detailed description in protocols can drive the adoption of decentralised methods.


Subject(s)
Informed Consent , Inosine Monophosphate , Cross-Sectional Studies , Data Collection , Humans , Time Factors
16.
JAMA Netw Open ; 5(8): e2228885, 2022 08 01.
Article in English | MEDLINE | ID: covidwho-2013234

ABSTRACT

Importance: Widespread distribution of rapid antigen tests is integral to the US strategy to address COVID-19; however, it is estimated that few rapid antigen test results are reported to local departments of health. Objective: To characterize how often individuals in 6 communities throughout the United States used a digital assistant to log rapid antigen test results and report them to their local departments of health. Design, Setting, and Participants: This prospective cohort study is based on anonymously collected data from the beneficiaries of the Say Yes! Covid Test program, which distributed more than 3 000 000 rapid antigen tests at no cost to residents of 6 communities (Louisville, Kentucky; Indianapolis, Indiana; Fulton County, Georgia; O'ahu, Hawaii; Ann Arbor and Ypsilanti, Michigan; and Chattanooga, Tennessee) between April and October 2021. A descriptive evaluation of beneficiary use of a digital assistant for logging and reporting their rapid antigen test results was performed. Interventions: Widespread community distribution of rapid antigen tests. Main Outcomes and Measures: Number and proportion of tests logged and reported to the local department of health through the digital assistant. Results: A total of 313 000 test kits were distributed, including 178 785 test kits that were ordered using the digital assistant. Among all distributed kits, 14 398 households (4.6%) used the digital assistant, but beneficiaries reported three-quarters of their rapid antigen test results to their state public health departments (30 965 tests reported of 41 465 total test results [75.0%]). The reporting behavior varied by community and was significantly higher among communities that were incentivized for reporting test results vs those that were not incentivized or partially incentivized (90.5% [95% CI, 89.9%-91.2%] vs 70.5%; [95% CI, 70.0%-71.0%]). In all communities, positive tests were less frequently reported than negative tests (60.4% [95% CI, 58.1%-62.8%] vs 75.5% [95% CI, 75.1%-76.0%]). Conclusions and Relevance: These results suggest that application-based reporting with incentives may be associated with increased reporting of rapid tests for COVID-19. However, increasing the adoption of the digital assistant may be a critical first step.


Subject(s)
COVID-19 , Data Collection , Georgia , Humans , Prospective Studies , Self-Testing , United States
17.
Lancet Infect Dis ; 22(12): e370-e376, 2022 Dec.
Article in English | MEDLINE | ID: covidwho-2004660

ABSTRACT

On Jan 22, 2020, a day after the USA reported its first COVID-19 case, the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE) launched the first global real-time coronavirus surveillance system: the JHU CSSE COVID-19 Dashboard. As of June 1, 2022, the dashboard has served the global audience for more than 30 consecutive months, totalling over 226 billion feature layer requests and 3·6 billion page views. The highest daily record was set on March 29, 2020, with more than 4·6 billion requests and over 69 million views. This Personal View reveals the fundamental technical details of the entire data system underlying the dashboard, including data collection, data fusion logic, data curation and sharing, anomaly detection, data corrections, and the human resources required to support such an effort. The Personal View also covers the challenges, ranging from data visualisation to reporting standardisation. The details presented here help develop a framework for future, large-scale public health-related data collection and reporting.


Subject(s)
COVID-19 , Humans , Universities , Data Collection , Public Health
19.
Nat Med ; 28(8): 1554-1555, 2022 08.
Article in English | MEDLINE | ID: covidwho-1991645
20.
Lancet ; 400(10351): 490, 2022 08 13.
Article in English | MEDLINE | ID: covidwho-1991368
SELECTION OF CITATIONS
SEARCH DETAIL