Emerging and re-emerging viral diseases

Emerging infectious diseases can be defined as infections that have either newly appeared in a population, or existed, but are rapidly increasing in incidence or geographical range. Even thought there was considerable development regarding prevention, control and elimination of some of the infectious diseases through proper use of hygiene and sanitation practices in addition to development of anti- biotics (bacteria) and vaccination, some infectious diseases remained as the leading causes of morbidity and mortality worldwide. There are many factors involved in the emergence of new infectious diseases or the re-emergence of “old” infectious diseases. Increasing global epidemiological surveillance, improving public health systems, education and research into new antibiotics and new vaccines will allow us to effectively combat the constantly renewed threat of infectious diseases. This review summarizes the work on aspects of virus emergence

Retraction.

This is a retraction of 'Gradual emergence followed by exponential spread of the SARS-CoV-2 Omicron variant in Africa' 10.1126/science.add873

Emergence and spread of the SARS-CoV-2 omicron (BA.1) variant across Africa: an observational study.

BACKGROUND: In mid-November, 2021, the SARS-CoV-2 omicron variant (B.1.1.529; BA.1 sublineage) was detected in southern Africa, prompting international travel restrictions. We aimed to investigate the spread of omicron BA.1 in Africa. METHODS: In this observational study, samples from patients infected with SARS-CoV-2 from 27 laboratories in 24 African countries, collected between June 1, 2021 and April 14, 2022, were tested for omicron BA.1 and delta (B.1.617.2) variants using real-time RT-PCR. Samples that tested positive for BA.1 by RT-PCR and were collected before estimated BA.1 emergence according to epidemiological properties were excluded from downstream analyses. The diagnostic precision of the assays was evaluated by high-throughput sequencing of samples from four countries. The observed spread of BA.1 was compared with mobility-based mathematical simulations and entries for SARS-CoV-2 in the Global Initiative on Sharing All Influenza Data (GISAID) genomic database. We estimated the effective reproduction number (Rt) at the country level considering the BA.1 fraction and the reported numbers of infections. Phylogeographical analyses were done in a Bayesian framework. FINDINGS: Through testing of 13 294 samples from patients infected with SARS-CoV-2, we established that, by November-December, 2021, omicron BA.1 had replaced the delta variant of SARS-CoV-2 in all African subregions, following a south-north gradient, with a median Rt of 2·60 (95% CI 2·46-2·71). This south-north spread, established on the basis of PCR data, was substantiated by phylogeographical reconstructions, ancestral state reconstructions, and GISAID data. PCR-based reconstructions of country-level BA.1 predominance and the availability of BA.1 genomic sequences in GISAID correlated significantly in time (p=0·0002, r=0·78). The first detections of BA.1 in high-income settings beyond Africa were predicted accurately in time by mobility-based mathematical simulations (p<0·0001). Comparing PCR-based reconstructions with mobility-based mathematical simulations suggested that SARS-CoV-2 infections in Africa were under-reported by approximately ten times. Inbound travellers infected with BA.1, departing from five continents, were identified in six African countries by early December, 2021. INTERPRETATION: Omicron BA.1 was widespread in Africa when travel bans were implemented, limiting their effectiveness. Combined with genomic surveillance and mobility-based mathematical modelling, PCR-based strategies can inform Rt and the geographical spread of emerging pathogens in a cost-effective and timely manner, and can guide evidence-based, non-pharmaceutical interventions such as travel restrictions or physical distancing. FUNDING: Bill & Melinda Gates Foundation. TRANSLATIONS: For the French, Portugese and Spanish translations of the abstract see Supplementary Materials section

Gradual emergence followed by exponential spread of the SARS-CoV-2 Omicron variant in Africa.

The geographic and evolutionary origins of the SARS-CoV-2 Omicron variant (BA.1), which was first detected mid-November 2021 in Southern Africa, remain unknown. We tested 13,097 COVID-19 patients sampled between mid-2021 to early 2022 from 22 African countries for BA.1 by real-time RT-PCR. By November-December 2021, BA.1 had replaced the Delta variant in all African sub-regions following a South-North gradient, with a peak Rt of 4.1. Polymerase chain reaction and near-full genome sequencing data revealed genetically diverse Omicron ancestors already existed across Africa by August 2021. Mutations, altering viral tropism, replication and immune escape, gradually accumulated in the spike gene. Omicron ancestors were therefore present in several African countries months before Omicron dominated transmission. These data also indicate that travel bans are ineffective in the face of undetected and widespread infection

Emergence and spread of the SARS-CoV-2 omicron (BA.1) variant across Africa: an observational study.

In mid-November, 2021, the SARS-CoV-2 omicron variant (B.1.1.529; BA.1 sublineage) was detected in southern Africa, prompting international travel restrictions. We aimed to investigate the spread of omicron BA.1 in Africa. In this observational study, samples from patients infected with SARS-CoV-2 from 27 laboratories in 24 African countries, collected between June 1, 2021 and April 14, 2022, were tested for omicron BA.1 and delta (B.1.617.2) variants using real-time RT-PCR. Samples that tested positive for BA.1 by RT-PCR and were collected before estimated BA.1 emergence according to epidemiological properties were excluded from downstream analyses. The diagnostic precision of the assays was evaluated by high-throughput sequencing of samples from four countries. The observed spread of BA.1 was compared with mobility-based mathematical simulations and entries for SARS-CoV-2 in the Global Initiative on Sharing All Influenza Data (GISAID) genomic database. We estimated the effective reproduction number (R ) at the country level considering the BA.1 fraction and the reported numbers of infections. Phylogeographical analyses were done in a Bayesian framework. Through testing of 13 294 samples from patients infected with SARS-CoV-2, we established that, by November-December, 2021, omicron BA.1 had replaced the delta variant of SARS-CoV-2 in all African subregions, following a south-north gradient, with a median R of 2·60 (95% CI 2·46-2·71). This south-north spread, established on the basis of PCR data, was substantiated by phylogeographical reconstructions, ancestral state reconstructions, and GISAID data. PCR-based reconstructions of country-level BA.1 predominance and the availability of BA.1 genomic sequences in GISAID correlated significantly in time (p=0·0002, r=0·78). The first detections of BA.1 in high-income settings beyond Africa were predicted accurately in time by mobility-based mathematical simulations (p<0·0001). Comparing PCR-based reconstructions with mobility-based mathematical simulations suggested that SARS-CoV-2 infections in Africa were under-reported by approximately ten times. Inbound travellers infected with BA.1, departing from five continents, were identified in six African countries by early December, 2021. Omicron BA.1 was widespread in Africa when travel bans were implemented, limiting their effectiveness. Combined with genomic surveillance and mobility-based mathematical modelling, PCR-based strategies can inform R and the geographical spread of emerging pathogens in a cost-effective and timely manner, and can guide evidence-based, non-pharmaceutical interventions such as travel restrictions or physical distancing. Bill & Melinda Gates Foundation. For the French, Portugese and Spanish translations of the abstract see Supplementary Materials section. [Abstract copyright: Copyright © 2025 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance.

Investment in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing in Africa over the past year has led to a major increase in the number of sequences that have been generated and used to track the pandemic on the continent, a number that now exceeds 100,000 genomes. Our results show an increase in the number of African countries that are able to sequence domestically and highlight that local sequencing enables faster turnaround times and more-regular routine surveillance. Despite limitations of low testing proportions, findings from this genomic surveillance study underscore the heterogeneous nature of the pandemic and illuminate the distinct dispersal dynamics of variants of concern-particularly Alpha, Beta, Delta, and Omicron-on the continent. Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve while the continent faces many emerging and reemerging infectious disease threats. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Effect of identified non-synonymous mutations in DPP4 receptor binding residues among highly exposed human population in Morocco to MERS-CoV through computational approach

Dipeptidyl peptidase 4 (DPP4) has been identified as the main receptor of MERS-CoV facilitating its cellular entry and enhancing its viral replication upon the emergence of this novel coronavirus. DPP4 receptor is highly conserved among many species, but the genetic variability among direct binding residues to MERS-CoV restrained its cellular tropism to humans, camels and bats. The occurrence of natural polymorphisms in human DPP4 binding residues is not well characterized. Therefore, we aimed to assess the presence of potential mutations in DPP4 receptor binding domain (RBD) among a population highly exposed to MERS-CoV in Morocco and predict their effect on DPP4 –MERS-CoV binding affinity through a computational approach. DPP4 synonymous and non-synonymous mutations were identified by sanger sequencing, and their effect were modelled by mutation prediction tools, docking and molecular dynamics (MD) simulation to evaluate structural changes in human DPP4 protein bound to MERS-CoV S1 RBD protein. We identified eight mutations, two synonymous mutations (A291 =, R317 =) and six non-synonymous mutations (N229I, K267E, K267N, T288P, L294V, I295L). Through docking and MD simulation techniques, the chimeric DPP4 –MERS-CoV S1 RBD protein complex models carrying one of the identified non-synonymous mutations sustained a stable binding affinity for the complex that might lead to a robust cellular attachment of MERS-CoV except for the DPP4 N229I mutation. The latter is notable for a loss of binding affinity of DPP4 with MERS-CoV S1 RBD that might affect negatively on cellular entry of the virus. It is important to confirm our molecular modelling prediction with in-vitro studies to acquire a broader overview of the effect of these identified mutations.</jats:p

Toscana virus isolated from sandflies, Morocco

Abstract To investigate the transmission of phleboviruses, a total of 7,057 sandflies were collected in well-known foci of cutaneous leishmaniasis and were identified to species level according to morphological characters. Collected sandflies were tested by Nested PCR for the presence of Phleboviruses and subsequently by viral isolation on Vero cells. The corresponding products were sequenced. Toscana virus was isolated, for the first time, from 5 pools of sandflies. Hence, Toscana virus should be considered a potential risk that threatens public health and clinicians should be aware of the role of Toscana virus in cases of meningitis and encephalitis in Morocco