Geographical Distribution and Social Justice of the COVID-19 Pandemic: The Case of Palma (Balearic Islands).

The spatial distribution of the COVID-19 infection rate in the city of Palma (Balearic Islands) is analyzed from the geolocation of positive cases by census tract and its relationship with socioeconomic variables is evaluated. Data on infections have been provided by the Health Service of the Ministry of Health and Consumption of the Government of the Balearic Islands. The study combines several methods of analysis: spatial autocorrelation, calculation of the Gini index and least squares regression, and weighted geographical regression. The results show that the pandemic comprised five waves in the March 2020-March 2022 period, corresponding to the months of April 2020, August 2020, December 2020, July 2021, and January 2022. Each wave shows a particular geographical distribution pattern, however, the second and third waves show higher levels of spatial concentration. In this sense, the second wave, affecting the peripheral neighborhoods of the eastern part of the city. The Gini index confirms geographical imbalances in the distribution of infections in the first waves of the pandemic. In addition, the regression models indicate that the most significant socioeconomic variables in the prediction of COVID-19 infection are average income, percentage of children under 18 years of age, average size of the household, and percentage of single-person households. The study shows that economic imbalances in the city have had a clear influence on the spatial pattern of pandemic distribution. It shows the need to implement spatial justice policies in income distribution to balance the effects of the pandemic.

SARS-CoV-2 detection in bioaerosols using a liquid impinger collector and ddPCR.

The airborne route is the dominant form of COVID-19 transmission, and therefore, the development of methodologies to quantify SARS-CoV-2 in bioaerosols is needed. We aimed to identify SARS-CoV-2 in bioaerosols by using a highly efficient sampler for the collection of 1-3 µm particles, followed by a highly sensitive detection method. 65 bioaerosol samples were collected in hospital rooms in the presence of a COVID-19 patient using a liquid impinger sampler. The SARS-CoV-2 genome was detected by ddPCR using different primer/probe sets. 44.6% of the samples resulted positive for SARS-CoV-2 following this protocol. By increasing the sampled air volume from 339 to 650 L, the percentage of positive samples went from 41% to 50%. We detected five times less positives with a commercial one-step RT-PCR assay. However, the selection of primer/probe sets might be one of the most determining factor for bioaerosol SARS-CoV-2 detection since with the ORF1ab set more than 40% of the samples were positive, compared to <10% with other sets. In conclusion, the use of a liquid impinger collector and ddPCR is an adequate strategy to detect SARS-CoV-2 in bioaerosols. However, there are still some methodological aspects that must be adjusted to optimize and standardize a definitive protocol.

Hospital Epidemics Tracker (HEpiTracker): Description and pilot study of a mobile app to track COVID-19 in hospital workers.

BACKGROUND: Hospital workers have been the most frequently and severely affected professional group during the COVID-19 pandemic, and have a big impact on transmission. In this context, innovative tools are required to measure the symptoms compatible with COVID-19, the spread of infection, and testing capabilities within hospitals in real time. OBJECTIVE: We aimed to develop and test an effective and user-friendly tool to identify and track symptoms compatible with COVID-19 in hospital workers. METHODS: We developed and pilot tested Hospital Epidemics Tracker (HEpiTracker), a newly designed app to track the spread of COVID-19 among hospital workers. Hospital staff in 9 hospital centers across 5 Spanish regions (Andalusia, Balearics, Catalonia, Galicia, and Madrid) were invited to download the app on their phones and to register their daily body temperature, COVID-19-compatible symptoms, and general health score, as well as any polymerase chain reaction and serological test results. RESULTS: A total of 477 hospital staff participated in the study between April 8 and June 2, 2020. Of note, both health-related (n=329) and non-health-related (n=148) professionals participated in the study; over two-thirds of participants (68.8%) were health workers (43.4% physicians and 25.4% nurses), while the proportion of non-health-related workers by center ranged from 40% to 85%. Most participants were female (n=323, 67.5%), with a mean age of 45.4 years (SD 10.6). Regarding smoking habits, 13.0% and 34.2% of participants were current or former smokers, respectively. The daily reporting of symptoms was highly variable across participating hospitals; although we observed a decline in adherence after an initial participation peak in some hospitals, other sites were characterized by low participation rates throughout the study period. CONCLUSIONS: HEpiTracker is an already available tool to monitor COVID-19 and other infectious diseases in hospital workers. This tool has already been tested in real conditions. HEpiTracker is available in Spanish, Portuguese, and English. It has the potential to become a customized asset to be used in future COVID-19 pandemic waves and other environments. TRIAL REGISTRATION: ClinicalTrials.gov NCT04326400; https://clinicaltrials.gov/ct2/show/NCT04326400.