Disaggregated data on age and sex for the first 250 days of the COVID-19 pandemic in Bucharest, Romania

Abstract

Experts worldwide have constantly been calling for high-quality open-access epidemiological data, given the fast-evolving nature of the COVID-19 pandemic. Disaggregated high-level granularity records are still scant despite being essential to corroborate the effectiveness of virus containment measures and even vaccination strategies. We provide a complete dataset containing disaggregated epidemiological information about all the COVID-19 patients officially reported during the first 250 days of the COVID-19 pandemic in Bucharest (Romania). We give the sex, age, and the COVID-19 infection confirmation date for 46,440 individual cases, between March 7th and November 11th, 2020. Additionally, we provide context-wise information such as the stringency levels of the measures taken by the Romanian authorities. We procured the data from the local public health authorities and systemized it to respond to the urgent international need of comparing observational data collected from various populations. Our dataset may help understand COVID-19 transmission in highly dense urban communities, perform virus spreading simulations, ascertain the effects of non-pharmaceutical interventions, and craft better vaccination strategies.

Trends in the morbidity and mortality of coronavirus disease 2019 in different ethnic groups and gender in a large Brazilian city

“…1,[12][13][14][15] Recent reports have suggested a worse prognosis among male patients, 13 and some authors have shown an increased tendency of hospitalization and ICU admission associated with African-Americans/ blacks. 12,16,17 Nonetheless, there is a lack of studies addressing sex differences and race amidst Brazilian cases of COVID-19.…”

Risks and Preventions for Pregnant Women and Their Preterm Infants in a World with COVID-19: A Narrative Review

“…Interestingly, females are slightly more likely to test positive than males [ 4 ]. Data on gender for the first 250 days of the COVID-19 pandemic in Bucharest, Romania showed that 53.2% of COVID-19 cases were females, and gender and age data should influence the prevention measures [ 5 ].…”

Estimating true prevalence through questionnaire data

“…6,7 One recent example of a disease outbreak where estimating prevalence was challenging is COVID-19. [8][9][10][11] This outbreak was characterized by high infection rates, but with frequently asymptomatic cases particularly in vaccinated individuals. Most estimates of population-level prevalence were derived from voluntary testing regimes, using either PCR or antigen test, where the incentives for choosing to be tested varied between individuals (e.g., desire to prevent transmission to clinically vulnerable relatives) and over time (e.g., varying requirements for being tested at workplaces, to enter bars/theatres/restaurants, or before travel).…”

“…One recent example of a disease outbreak where estimating prevalence was challenging is COVID‐19 8–11 . This outbreak was characterized by high infection rates, but with frequently asymptomatic cases particularly in vaccinated individuals.…”