Prolonged shedding of infectious viruses with haplotype switches of SARS-CoV-2 in an immunocompromised patient.

A concern has been raised that the persistent COVID-19 infection in an immunocompromised host can be the source of the SARS-CoV-2 variants. This is the case of a 61-year-old man in complete remission of a follicular lymphoma after six cycles of rituximab and bendamustine with additional two cycles of rituximab completed eight months prior to the episode of COVID-19 pneumonia. The patient's respiratory failure was long-lasting, and required mechanical ventilation until day 75. Acquired immunity tested negative throughout the observational period. The viral RNA was detectable until day 100 while the infectious virus was isolated until day 79. Seven haplotypes were identified and the non-synonymous mutations accumulated in the spike gene which included E484Q and S494P. In the management of COVID-19 cases with suppressed immune statuses, initial evaluation of existing immunity and monitoring for infectiousness throughout the clinical course including the convalescent stage may be necessary.

Quantitative evaluation of water, sanitation, and hygiene measures on COVID-19 pandemic peak reduction in the Philippines.

New cases of coronavirus disease 2019 (COVID-19) are continually being recorded worldwide, despite global efforts in implementing non-pharmaceutical interventions and establishing vaccination programs. This trend highlights the need to identify the factors associated with the continued spread of COVID-19. The World Health Organization recommends hand washing as a cost-effective intervention for preventing COVID-19, indicating that water, sanitation, and hygiene (WaSH) are central to the prevention of the disease. However, low- and middle-income countries lack adequate access to WaSH, which increases the risk of contracting COVID-19. The aim of this study was to identify the WaSH factors associated with the incidence of COVID-19 and quantitatively estimate the effects of improvements in WaSH on reducing the incidence of COVID-19 during the peak of the pandemic. Lasso regression and extreme gradient boosting models were used to identify the WaSH factors. Distinct estimation models were developed to assess the effect of WaSH in rural regions under two assumptions: increasing regional basic sanitation coverage up to 25 % and 50%. The reduction in the incidence of COVID-19 during the peak of the pandemic was calculated for each rural region. The results of the analyses indicated that basic sanitation is important for reducing the incidence of COVID-19 in rural regions compared to urban regions in the Philippines. In addition, the results suggested that increasing basic sanitation coverage could reduce the incidence of COVID-19 by 2-66 %, alleviating the burden on healthcare facilities. This study indicates that improved basic sanitation infrastructure are needed in rural Philippines. The results of this study emphasise the significance of WaSH as an indicator of COVID-19 incidence, highlighting the need for its enhancement to enable the achievement of sustainable disease prevention and pandemic preparedness goals.

Identification of environmental, socioeconomic, water, sanitation, and hygiene (WaSH) factors associated with COVID-19 incidence in the Philippines: A nationwide modelling study.

Despite the implementation of non-pharmaceutical interventions, the threat of coronavirus disease 2019 (COVID-19) remains significant on a global scale. Identifying external factors contributing to its spread is crucial, especially given the World Health Organization's recommendation emphasizing access to water, sanitation, and hygiene as essential in curbing COVID-19. There is a notable discrepancy in access to sanitation facilities, particularly evident in low- and middle-income countries. However, there is a lack of quantitative assessments regarding these factors. This study examines various environmental, socioeconomic, water, sanitation, and hygiene factors and their associations with COVID-19 incidence. All regions in the Philippines were categorized into clusters based on socioeconomic factors. A conceptual structural equation model (SEM) was developed using domain knowledge. The best-fitting SEM for each cluster was determined, and associations between factors and COVID-19 incidence were estimated. The correlation analysis revealed that rainfall, minimum temperature, and relative humidity were positively correlated with weekly COVID-19 incidence in urban regions. Maximum temperature, mean temperature, wind speed, and wind direction were negatively correlated with weekly COVID-19 incidence in rural regions, with time lags of 0, 3, and 7 weeks. In urban regions (Cluster 1), factors such as urbanization rate (1.00), area (-0.93), and population (0.54) were found to be associated with weekly COVID-19 incidence. Conversely, in rural regions (Cluster 2), factors including area (0.17), basic sanitation (0.84), and wind direction (0.83) showed associations with weekly COVID-19 incidence. These factors were causally associated with a latent variable reflecting the hidden confounders associated with COVID-19 incidence. It is important to note that sanitation factors were associated only in rural regions. Improving access to sanitation facilities in rural regions of the Philippines is imperative to effectively mitigate disease transmission in future pandemics. Identification of the causal effect of unobserved confounders with COVID-19 incidence is recommended for future research.

Rapid Detection of SARS-CoV-2 RNA Using Reverse Transcription Recombinase Polymerase Amplification (RT-RPA) with Lateral Flow for N-Protein Gene and Variant-Specific Deletion-Insertion Mutation in S-Protein Gene.

Rapid molecular testing for severe acute respiratory coronavirus 2 (SARS-CoV-2) variants may contribute to the development of public health measures, particularly in resource-limited areas. Reverse transcription recombinase polymerase amplification using a lateral flow assay (RT-RPA-LF) allows rapid RNA detection without thermal cyclers. In this study, we developed two assays to detect SARS-CoV-2 nucleocapsid (N) gene and Omicron BA.1 spike (S) gene-specific deletion-insertion mutations (del211/ins214). Both tests had a detection limit of 10 copies/µL in vitro and the detection time was approximately 35 min from incubation to detection. The sensitivities of SARS-CoV-2 (N) RT-RPA-LF by viral load categories were 100% for clinical samples with high (>9015.7 copies/µL, cycle quantification (Cq): < 25) and moderate (385.5-9015.7 copies/µL, Cq: 25-29.9) viral load, 83.3% for low (16.5-385.5 copies/µL, Cq: 30-34.9), and 14.3% for very low (<16.5 copies/µL, Cq: 35-40). The sensitivities of the Omicron BA.1 (S) RT-RPA-LF were 94.9%, 78%, 23.8%, and 0%, respectively, and the specificity against non-BA.1 SARS-CoV-2-positive samples was 96%. The assays seemed more sensitive than rapid antigen detection in moderate viral load samples. Although implementation in resource-limited settings requires additional improvements, deletion-insertion mutations were successfully detected by the RT-RPA-LF technique.

Recent updates on the possible reasons for the low incidence and morbidity of COVID-19 cases in Africa.

BACKGROUND: The COVID-19 respiratory illness caused by the SARS-CoV-2 has been a major cause of morbidity and mortality worldwide since the first reported case in Wuhan, China. A year has passed since pandemic began, and the reasons for different COVID-19 burden variation across continents keep puzzling the general public. MAIN BODY OF THE ABSTRACT: Since the COVID-19 pandemic started, published research articles have addressed the epidemiological risk factors, host factors, susceptibility and immunity. To ascertain possible reasons for the different rates of COVID-19 infections between Africa and other continents, we summarized the up-to-date scientific literature to identify possible arguments in this regard. Available literature suggests that demographic, epidemiological, sociological, genetic and immunological factors contribute in the COVID-19 severity and the susceptibly to SARS-CoV-2. SHORT CONCLUSION: This review summarizes existing data and discusses reasons for differential COVID-19 burden across continents. The arguments mentioned herein will be helpful to guide future experimental studies to test different hypotheses.

COVID-19 Pandemic Related Research in Africa: Bibliometric Analysis of Scholarly Output, Collaborations and Scientific Leadership.

Scientometrics enables scholars to assess and visualize emerging research trends and hot-spots in the scientific literature from a quantitative standpoint. In the last decades, Africa has nearly doubled its absolute count of scholarly output, even though its share in global knowledge production has dramatically decreased. The still-ongoing COVID-19 pandemic has profoundly impacted the way scholarly research is conducted, published, and disseminated. However, the COVID-19-related research focus, the scientific productivity, and the research collaborative network of African researchers during the ongoing COVID-19 pandemic remain to be elucidated. This study aimed to clarify the COVID-19 research patterns among African researchers and estimate the strength of collaborations and partnerships between African researchers and scholars from the rest of the world during the COVID-19 pandemic, collecting data from electronic scholarly databases such as Web of Science (WoS), PubMed/MEDLINE and African Journals OnLine (AJOL), the largest and prominent platform of African-published scholarly journals. We found that COVID-19-related collaboration patterns varied among African regions. For instance, most of the scholarly partnerships occurred with formerly colonial countries (such as European or North-American countries). In other cases, scholarly ties of North African countries were above all with the Kingdom of Saudi Arabia. In terms of number of publications, South Africa and Egypt were among the most productive countries. Bibliometrics and, in particular, scientometrics can help scholars identify research areas of particular interest, as well as emerging topics, such as the COVID-19 pandemic. With a specific focus on the still-ongoing viral outbreak, they can assist decision- and policy-makers in allocating funding and economic-financial, logistic, organizational, and human resources, based on the specific gaps and needs of a given country or research area.

The Determinants of the Low COVID-19 Transmission and Mortality Rates in Africa: A Cross-Country Analysis.

Background: More than 1 year after the beginning of the international spread of coronavirus 2019 (COVID-19), the reasons explaining its apparently lower reported burden in Africa are still to be fully elucidated. Few studies previously investigated the potential reasons explaining this epidemiological observation using data at the level of a few African countries. However, an updated analysis considering the various epidemiological waves and variables across an array of categories, with a focus on African countries might help to better understand the COVID-19 pandemic on the continent. Thus, we investigated the potential reasons for the persistently lower transmission and mortality rates of COVID-19 in Africa. Methods: Data were collected from publicly available and well-known online sources. The cumulative numbers of COVID-19 cases and deaths per 1 million population reported by the African countries up to February 2021 were used to estimate the transmission and mortality rates of COVID-19, respectively. The covariates were collected across several data sources: clinical/diseases data, health system performance, demographic parameters, economic indicators, climatic, pollution, and radiation variables, and use of social media. The collinearities were corrected using variance inflation factor (VIF) and selected variables were fitted to a multiple regression model using the R statistical package. Results: Our model (adjusted R-squared: 0.7) found that the number of COVID-19 tests per 1 million population, GINI index, global health security (GHS) index, and mean body mass index (BMI) were significantly associated (P < 0.05) with COVID-19 cases per 1 million population. No association was found between the median life expectancy, the proportion of the rural population, and Bacillus Calmette-Guérin (BCG) coverage rate. On the other hand, diabetes prevalence, number of nurses, and GHS index were found to be significantly associated with COVID-19 deaths per 1 million population (adjusted R-squared of 0.5). Moreover, the median life expectancy and lower respiratory infections rate showed a trend towards significance. No association was found with the BCG coverage or communicable disease burden. Conclusions: Low health system capacity, together with some clinical and socio-economic factors were the predictors of the reported burden of COVID-19 in Africa. Our results emphasize the need for Africa to strengthen its overall health system capacity to efficiently detect and respond to public health crises.