This dataset is a dump made on 14 December 2020 of the metadata of the submissions to the Corona in the City platform, including URLs that link to the submission content, which has been processed by the listed authors. Corona in the City is a project by the Amsterdam Museum, the museum that documents the story of the Dutch capital as it evolved in the past millennium. The museum developed an online, bilingual (Dutch-English) platform that was launched on 30 April 2020 for the collection of contributions from “all inhabitants, visitors and lovers of Amsterdam” that document their experiences with the Covid-19 pandemic. The explicit aim was to present these contributions in an online exhibition that opened on 15 May 2020. In order to ensure a wide variety of contributions, the museum collaborated with 45 local partner institutions, some of which curated their contributions in dedicated virtual exhibition rooms. By December 2020 the exhibition counted just over 3.000 submissions and had drawn 100.000 visitors; it is presently still open for contributions and new exhibition rooms are added occasionally.In line with the Privacy Policy of our Archiving COVID-19 Communities project (https://covid19communities.humanities.uva.nl/privacy-policy), for which we analyzed this dataset, we anonymized the original datadump by removing names of submitters, phone numbers and IP addresses. Email addresses of submitters have been anonymized by mapping them to unique identifyers. Although both the title of the submissions and summary description columns in many cases also reference person names, we considered that, since all submitters have consented to being mentioned on the Corona in the City website and having their submissions analyzed by the University of Amsterdam for research purposes (see https://www.coronaindestad.nl/en/terms-and-conditions/), these data could remain as received.

There are few data regarding clinical outcomes from COVD-19 from low-income countries (LICs) including Rwanda. Accordingly, we aimed to determine 1) outcomes of patients admitted to hospital with COVID-19 in Rwanda, and 2) the ability of the Universal Vital Assessment (UVA) score to predict mortality in patients with COVID-19 compared to sequential organ failure assessment (SOFA) and quick (qSOFA) scores. We conducted a retrospective study of patients aged ≥18 years hospitalized with laboratory-confirmed COVID-19 at the University Teaching Hospital of Butare (CHUB), Rwanda, April 2021-January 2022. For each participant, we calculated UVA, SOFA, and qSOFA risk scores and determined their area under the receive operating characteristic curve (AUC). We used logistic regression to determine predictors of mortality. Of the 150 patients included, 83 (55%) were female and the median (IQR) age was 61 (43–73) years. The median (IQR) length of hospital stay was 6 (3–10) days. Respiratory failure occurred in 69 (46%) including 34 (23%) who had ARDS. The case fatality rate was 44%. Factors independently associated with mortality included acute kidney injury (adjusted odds ratio [aOR] 7.99, 95% confidence interval [CI] 1.47–43.22, p = 0.016), severe COVID-19 (aOR 3.42, 95% CI 1.06–11.01, p = 0.039), and a UVA score >4 (aOR 7.15, 95% CI 1.56–32.79, p = 0.011). The AUCs for UVA, qSOFA, and SOFA scores were 0.86 (95% CI 0.79–0.92), 0.81 (95% CI 0.74–0.88), and 0.84 (95% CI 0.78–0.91), respectively, which were not statistically significantly different from each other. At a UVA score cut-off of 4, the sensitivity, specificity, positive predictive value, and negative predictive value for mortality were 0.58, 0.93, 0.86, and 0.74, respectively. Patients hospitalized with COVID-19 in CHUB had high mortality, which was accurately predicted by the UVA score. Calculation of the UVA score in patients with COVID-19 in LICs may assist clinicians with triage and other management decisions.

Association of clinical and socio-demographic characteristics with mortality among patients with COVID-19 admitted to hospital at CHUB, May through October, 2021.