Molecular testing and analysis of disease spreading during the emergence of COVID-19 in Macaé, the Brazilian National Capital of Oil

Exploring the Spatial Relative Risk of COVID-19 in Berlin-Neukölln

Identifying areas with high and low infection rates can provide important etiological clues. Usually, areas with high and low infection rates are identified by aggregating epidemiological data into geographical units, such as administrative areas. This assumes that the distribution of population numbers, infection rates, and resulting risks is constant across space. This assumption is, however, often false and is commonly known as the modifiable area unit problem. This article develops a spatial relative risk surface by using kernel density estimation to identify statistically significant areas of high risk by comparing the spatial distribution of address-level COVID-19 cases and the underlying population at risk in Berlin-Neukölln. Our findings show that there are varying areas of statistically significant high and low risk that straddle administrative boundaries. The findings of this exploratory analysis further highlight topics such as, e.g., Why were mostly affluent areas affected during the first wave? What lessons can be learned from areas with low infection rates? How important are built structures as drivers of COVID-19? How large is the effect of the socio-economic situation on COVID-19 infections? We conclude that it is of great importance to provide access to and analyse fine-resolution data to be able to understand the spread of the disease and address tailored health measures in urban settings.

The long-term dynamics of serum antibodies against SARS-CoV-2

Objective

To analyze the long-term dynamics of antibodies against SARS-CoV-2 and understand the impact of age, gender, and viral load on patients' immunological response.

Methods

Serum samples were obtained from 231 COVID-19 positive patients from Macaé, in Rio de Janeiro state, in Brazil, from June 2020 until January 2021. The production of IgA, IgM, IgG, and IgE against S glycoprotein was analyzed using the S-UFRJ assay, taking into account the age, gender, and viral load.

Results

Analysis of antibody production over 7 months revealed that IgA positivity gradually decreased after the first month. Additionally, the highest percentage of IgM positivity occurred in the first month (97% of patients), and declined after this period, while IgG positivity remained homogeneous for all 7 months. The same analysis for IgE revealed that almost all samples were negative. The comparison of antibody production between genders showed no significant difference. Regarding the age factor and antibody production, patients aged ≥60 years produced almost twice more IgA than younger ones (17-39 years old). Finally, a relationship between viral load and antibody production was observed only for older patients.

Conclusions

Our work provides an overview of long-term production of antibodies against SARS-CoV-2, suggesting prolonged production of IgA and IgM antibodies for 3 months and continued IgG production for over 7 months. In addition, it identified a correlation between viral load and IgM titers in the older group and, finally, different IgA production between the age groups.

SARS-CoV-2 Spatiotemporal Genomic and Molecular Analysis of the First Wave of the COVID-19 Pandemic in Macaé, the Brazilian Capital of Oil

The SARS-CoV-2 virus infection led to millions of deaths during the COVID-19 pandemic. Hundreds of workers from several other Brazilian cities, as well as from other countries, arrive daily in Macaé to work in the oil supply chain, making this city a putative hotspot for the introduction of new viral lineages. In this study, we performed a genomic survey of SARS-CoV-2 samples from Macaé during the first outbreak of COVID-19, combined with clinical data and a molecular integrative analysis. First, phylogenomic analyses showed a high occurrence of viral introduction events and the establishment of local transmissions in Macaé, including the ingression and spread of the B.1.1.28 lineage in the municipality from June to August 2020. Second, SARS-CoV-2 mutations were identified in patients with distinct levels of COVID-19 severity. Third, molecular interactions of the mutated spike protein from three B.1.1.33 local samples and human ACE2 showed higher interactions than that of the wild-type spike protein from the ancestral virus. Altogether, these results elucidate the SARS-CoV-2 genomic profile in a strategic Brazilian city and further explore the functional aspects of SARS-CoV-2 with a characterization of emerging viral mutations associated with clinical data and the potential targets for drug development against SARS-CoV-2.

da Paixão Melo M, Ferreira da Silva M, de Jesus Gonçalves dos Santos N, de Souza Pessoa N, Silva de Araujo R, de Macedo Godim T, Fraga de Oliveira Tosta S, Brandão Nardy V, Cristina Faria E, Frederico de Carvalho Dominguez Souza B, Laís Almeida dos Santos J, Wikramaratna P, Giovanetti M, Alcântara LCJ, Lourenço J, Leal e Silva de Mello A. Dynamics and Determinants of SARS-CoV-2 RT-PCR Testing on Symptomatic Individuals Attending Healthcare Centers during 2020 in Bahia, Brazil

RT-PCR testing data provides opportunities to explore regional and individual determinants of test positivity and surveillance infrastructure. Using Generalized Additive Models, we explored 222,515 tests of a random sample of individuals with COVID-19 compatible symptoms in the Brazilian state of Bahia during 2020. We found that age and male gender were the most significant determinants of test positivity. There was evidence of an unequal impact among socio-demographic strata, with higher positivity among those living in areas with low education levels during the first epidemic wave, followed by those living in areas with higher education levels in the second wave. Our estimated probability of testing positive after symptom onset corroborates previous reports that the probability decreases with time, more than halving by about two weeks and converging to zero by three weeks. Test positivity rates generally followed state-level reported cases, and while a single laboratory performed ~90% of tests covering ~99% of the state's area, test turn-around time generally remained below four days. This testing effort is a testimony to the Bahian surveillance capacity during public health emergencies, as previously witnessed during the recent Zika and Yellow Fever outbreaks.