State fragility and the coronavirus disease 2019 (COVID-19) pandemic: an ecologic analysis of data from 146 countries

SARS-CoV-2 chronological genomic evolution and epidemiology in the Middle East and North Africa (MENA) region as affected by vaccination, conflict and socioeconomical disparities: a population-based cohort study

OBJECTIVE

To describe the chronological genomic evolution of SARS-CoV-2 and its impact on public health in the Middle East and North Africa (MENA) region.

METHODS

This study analysed all available SARS-CoV-2 genomic sequences, metadata and rates of COVID-19 infection from the MENA region retrieved from the Global Initiative on Sharing All Influenza Data database from January 2020 to August 2021. Inferential and ‎descriptive statistics were conducted to describe the epidemiology of SARS-CoV-2.

RESULTS

Genomic surveillance of SARS-CoV-2 in the MENA region indicated that the variants in January 2020 predominately belonged to the G, GR, GH or O clades and that the most common variant of concern was Alpha. By August 2021, however, the GK clade dominated (57.4% of all sequenced genomes), followed by the G clade (18.7%) and the GR clade (11.6%). In August, the most commonly sequenced variants of concern were Delta in the Middle East region (91%); Alpha (44.3%) followed by Delta (29.7%) and Beta (25.3%) in the North Africa region; and Alpha (88.9%), followed by Delta (10%) in the fragile and conflict-affected regions of MENA. The mean proportion of the variants of concern among the total sequenced samples differed significantly by country (F=1.93, P=0.0112) but not by major MENA region (F=0.14, P=0.27) or by vaccination coverage (F=1.84, P=0.176).

CONCLUSION

This analysis of the genomic surveillance of SARS-CoV-2 provides an essential description the virus evolution and its impact on public health safety in the MENA region. As of August 2021, the Delta variant showed a genomic advantage in the MENA region. The MENA region includes several fragile and conflict-affected countries with extremely low levels of vaccination coverage and little genomic surveillance, which may soon exacerbate the existing health crisis within those countries and globally.

Exploring the effects of PM2.5 and temperature on COVID-19 transmission in Seoul, South Korea

With a recent surge of the new severe acute respiratory syndrome-coronavirus 2 (SARS-Cov-2, COVID-19) in South Korea, this study attempts to investigate the effects of environmental conditions such as air pollutants (PM_2.5) and meteorological covariate (Temperature) on COVID-19 transmission in Seoul. To account for unobserved heterogeneity in the daily confirmed cases of COVID-19 across 25 contiguous districts within Seoul, we adopt a full Bayesian hierarchical approach for the generalized linear mixed models. A formal statistical analysis suggests that there exists a positive correlation between a 7-day lagged effect of PM_2.5 concentration and the number of confirmed COVID-19 cases, which implies an elevated risk of the infectious disease. Conversely, temperature has shown a negative correlation with the number of COVID-19 cases, leading to reduction in relative risks. In addition, we clarify that the random fluctuation in the relative risks of COVID-19 mainly originates from temporal aspects, whereas no significant evidence of variability in relative risks is observed in terms of spatial alignment of the 25 districts. Nevertheless, this study provides empirical evidence using model-based formal assessments regarding COVID-19 infection risks in 25 districts of Seoul from a different perspective.