Divergent HIV-1 strains (CRF92_C2U and CRF93_cpx) co-circulating in the Democratic Republic of the Congo: Phylogenetic insights on the early evolutionary history of subtype C.

Molecular epidemiological studies revealed that the epicenter of the HIV pandemic was Kinshasa, the capital city of the Democratic Republic of the Congo (DRC) in Central Africa. All known subtypes and numerous complex recombinant strains co-circulate in the DRC. Moreover, high intra-subtype diversity has been also documented. During two previous surveys on HIV-1 antiretroviral drug resistance in the DRC, we identified two divergent subtype C lineages in the protease and partial reverse transcriptase gene regions. We sequenced eight near full-length genomes and classified them using bootscanning and likelihood-based phylogenetic analyses. Four strains are more closely related to subtype C although within the range of inter sub-subtype distances. However, these strains also have small unclassified fragments and thus were named CRF92_C2U. Another strain is a unique recombinant of CRF92_C2U with an additional small unclassified fragment and a small divergent subtype A fragment. The three remaining strains represent a complex mosaic named CRF93_cpx. CRF93_cpx have two fragments of divergent subtype C sequences, which are not conventional subtype C nor the above described C2, and multiple divergent subtype A-like fragments. We then inferred the time-scaled evolutionary history of subtype C following a Bayesian approach and a partitioned analysis using major genomic regions. CRF92_C2U and CRF93_cpx had the most recent common ancestor with conventional subtype C around 1932 and 1928, respectively. A Bayesian demographic reconstruction corroborated that the subtype C transition to a faster phase of exponential growth occurred during the 1950s. Our analysis showed considerable differences between the newly discovered early-divergent strains and the conventional subtype C and therefore suggested that this virus has been diverging in humans for several decades before the HIV/M diversity boom in the 1950s

Dengue Virus Type 4 Phylogenetics in Brazil 2011: Looking beyond the Veil

Dengue Fever and Dengue Hemorrhagic Fever are diseases affecting approximately 100 million people/year and are a major concern in developing countries. In the present study, the phylogenetic relationship of six strains of the first autochthonous cases of DENV-4 infection occurred in Sao Paulo State, Parana State and Rio Grande do Sul State, Brazil, 2011 were studied. Nucleotide sequences of the envelope gene were determined and compared with sequences representative of the genotypes I, II, III and Sylvatic for DEN4 retrieved from GenBank. We employed a Bayesian phylogenetic approach to reconstruct the phylogenetic relationships of Brazilian DENV-4 and we estimated evolutionary rates and dates of divergence for DENV-4 found in Brazil in 2011. All samples sequenced in this study were located in Genotype II. The studied strains are monophyletic and our data suggest that they have been evolving separately for at least 4 to 6 years. Our data suggest that the virus might have been present in the region for some time, without being noticed by Health Surveillance Services due to a low level of circulation and a higher prevalence of DENV-1 and DENV- 2

Characterising within-hospital SARS-CoV-2 transmission events using epidemiological and viral genomic data across two pandemic waves

Hospital outbreaks of COVID19 result in considerable mortality and disruption to healthcare services and yet little is known about transmission within this setting. We characterise within hospital transmission by combining viral genomic and epidemiological data using Bayesian modelling amongst 2181 patients and healthcare workers from a large UK NHS Trust. Transmission events were compared between Wave 1 (1st March to 25th July 2020) and Wave 2 (30th November 2020 to 24th January 2021). We show that staff-to-staff transmissions reduced from 31.6% to 12.9% of all infections. Patient-to-patient transmissions increased from 27.1% to 52.1%. 40%-50% of hospital-onset patient cases resulted in onward transmission compared to 4% of community-acquired cases. Control measures introduced during the pandemic likely reduced transmissions between healthcare workers but were insufficient to prevent increasing numbers of patient-to-patient transmissions. As hospital-acquired cases drive most onward transmission, earlier identification of nosocomial cases will be required to break hospital transmission chains

Importance of patient bed pathways and length of stay differences in predicting COVID-19 hospital bed occupancy in England.

Background: Predicting bed occupancy for hospitalised patients with COVID-19 requires understanding of length of stay (LoS) in particular bed types. LoS can vary depending on the patient’s “bed pathway” - the sequence of transfers of individual patients between bed types during a hospital stay. In this study, we characterise these pathways, and their impact on predicted hospital bed occupancy. Methods: We obtained data from University College Hospital (UCH) and the ISARIC4C COVID-19 Clinical Information Network (CO-CIN) on hospitalised patients with COVID-19 who required care in general ward or critical care (CC) beds to determine possible bed pathways and LoS. We developed a discrete-time model to examine the implications of using either bed pathways or only average LoS by bed type to forecast bed occupancy. We compared model-predicted bed occupancy to publicly available bed occupancy data on COVID-19 in England between March and August 2020. Results: In both the UCH and CO-CIN datasets, 82% of hospitalised patients with COVID-19 only received care in general ward beds. We identified four other bed pathways, present in both datasets: “Ward, CC, Ward”, “Ward, CC”, “CC” and “CC, Ward”. Mean LoS varied by bed type, pathway, and dataset, between 1.78 and 13.53 days. For UCH, we found that using bed pathways improved the accuracy of bed occupancy predictions, while only using an average LoS for each bed type underestimated true bed occupancy. However, using the CO-CIN LoS dataset we were not able to replicate past data on bed occupancy in England, suggesting regional LoS heterogeneities. Conclusions: We identified five bed pathways, with substantial variation in LoS by bed type, pathway, and geography. This might be caused by local differences in patient characteristics, clinical care strategies, or resource availability, and suggests that national LoS averages may not be appropriate for local forecasts of bed occupancy for COVID-19. Trial registration: The ISARIC WHO CCP-UK study ISRCTN66726260 was retrospectively registered on 21/04/2020 and designated an Urgent Public Health Research Study by NIHR.</p

Genome sequencing reveals Zika virus diversity and spread in the Americas

Although the recent Zika virus (ZIKV) epidemic in the Americas and its link to birth defects have attracted a great deal of attention, much remains unknown about ZIKV disease epidemiology and ZIKV evolution, in part owing to a lack of genomic data. Here we address this gap in knowledge by using multiple sequencing approaches to generate 110 ZIKV genomes from clinical and mosquito samples from 10 countries and territories, greatly expanding the observed viral genetic diversity from this outbreak. We analysed the timing and patterns of introductions into distinct geographic regions; our phylogenetic evidence suggests rapid expansion of the outbreak in Brazil and multiple introductions of outbreak strains into Puerto Rico, Honduras, Colombia, other Caribbean islands, and the continental United States. We find that ZIKV circulated undetected in multiple regions for many months before the first locally transmitted cases were confirmed, highlighting the importance of surveillance of viral infections. We identify mutations with possible functional implications for ZIKV biology and pathogenesis, as well as those that might be relevant to the effectiveness of diagnostic tests

Number of HIV-1 founder variants is determined by the recency of the source partner infection

During sexual transmission, the high genetic diversity of HIV-1 within an individual is frequently reduced to one founder variant that initiates infection. Understanding the drivers of this bottleneck is crucial to developing effective infection control strategies. Little is known about the importance of the source partner during this bottleneck. To test the hypothesis that the source partner affects the number of HIV founder variants, we developed a phylodynamic model calibrated using genetic and epidemiological data on all existing transmission pairs for whom the direction of transmission and the infection stage of the source partner are known. Our results suggest that acquiring infection from someone in the acute (early) stage of infection increases the risk of multiple-founder variant transmission compared with acquiring infection from someone in the chronic (later) stage of infection. This study provides the first direct test of source partner characteristics to explain the low frequency of multiple-founder strain infections

Epidemiological and ecological determinants of Zika virus transmission in an urban setting

The Zika virus has emerged as a global public health concern. Its rapid geographic expansion is attributed to the success of Aedes mosquito vectors, but local epidemiological drivers are still poorly understood. Feira de Santana played a pivotal role in the Chikungunya epidemic in Brazil and was one of the first urban centres to report Zika infections. Using a climate-driven transmission model and notified Zika case data, we show that a low observation rate and high vectorial capacity translated into a significant attack rate during the 2015 outbreak, with a subsequent decline in 2016 and fade-out in 2017 due to herd-immunity. We find a potential Zika-related, low risk for microcephaly per pregnancy, but with significant public health impact given high attack rates. The balance between the loss of herd-immunity and viral re-importation will dictate future transmission potential of Zika in this urban setting