#Global Respiratory #Virus #Activity: Weekly #Update (WHO, August 28 '26)

 

{Excerpt, from Weekly Epidemiological Record}

(...)

    The findings below are based on surveillance conducted through the WHO Global Influenza Surveillance and Response System (GISRS). 

    More details can be found on the Global Influenza Programme's surveillance and monitoring page.

Overview

    ° In week 33 2026, influenza positivity was below 10% and SARS-CoV-2 activity remained low globally. 

    ° During the past few weeks, influenza positivity remained just below 10% overall in the tropical areas and southern hemisphere temperate and subtropical areas. 

    ° RSV positivity also remained low globally.

Influenza

    ° Globally, influenza detections remained low in week 33 with influenza A and B viruses detected in similar proportions.

    ° In the southern hemisphere, influenza percent positivity was elevated (>10%) in one country in Temperate South America. 

    ° Percent positivity was over 30% in one country in Oceania where a medium increase in activity was observed.

    ° In the northern hemisphere, influenza percent positivity was elevated (>10%) in some countries in Central America and the Caribbean, Tropical South America, Western Africa, Western, Southern and South-East Asia and in single countries in Middle Africa, South West and Northern Europe and Eastern Asia. 

    ° Percent positivity was over 30% in single countries in Tropical South America, Western and Eastern Africa and Southern Asia. 

    ° Increases in activity were observed in some countries in Central America and the Caribbean and Southern Asia and in single countries in Tropical South America, Western, Eastern and Middle Africa, South West Europe and Western Asia.

    ° In the zones with elevated positivity, influenza A(H3N2) was predominant in South West Europe, Eastern Africa, Eastern Asia and Oceania; influenza A(H1N1)pdm09 was predominant in Western, Southern and South-East Asia and influenza B was predominant in Tropical and Temperate South America. 

    ° Influenza A and B were codominant in Central America and the Caribbean and Western Africa and influenza A(H1N1)pdm09 and influenza A(H3N2) were codominant in Middle Africa.

SARS-CoV-2

    ° Globally, SARS-CoV-2 positivity remained stable and low across most reporting countries, with elevated positivity (>10%) reported in countries in Central America and the Caribbean and in single countries in Tropical South America, Southern and South-East Asia. 

    ° Small increases in activity were observed in countries in Central America and the Caribbean, Northern Europe and in a single country in Southern Asia.

Respiratory Syncytial Virus (RSV)

    ° RSV positivity was elevated (>10%) in a few countries in Central America and the Caribbean, Tropical and Temperate South America and in a single country in Southern Asia. 

    ° Percent positivity was over 30% in a single country in Temperate South America. 

    ° Small increases in activity were observed in two countries in Central America and the Caribbean. 

    ° RSV and influenza activity were both elevated in single countries in Temperate South America and Southern Asia.

Severity assessment

    ° The severity assessments here are reported from countries, areas and territories. 

    ° Assessments for transmissibility can be reported based on syndromic parameters and/or influenza-specific parameters. 

    ° In the southern hemisphere temperate and subtropical areas, influenza-specific transmissibility was reported as low (1) and moderate (1); transmissibility using syndromic data was reported as moderate (1). 

    ° In the northern hemisphere temperate and subtropical areas, influenza-specific transmissibility was reported as below seasonal threshold (11) and low (2); transmissibility using syndromic data was reported as below seasonal threshold (8). 

    ° Influenza-specific transmissibility was reported as moderate in one country in the tropical areas.

Current update: Global Respiratory Virus Activity: Weekly Update N° 592

All past updates: Global respiratory virus updates

(...)

Source: 

Link: https://www.who.int/publications/journals/weekly-epidemiological-record/wer101-34

____

Modeling the #impact of respiratory disease #outbreaks on the #US #agricultural #workforce

 

Abstract

Background: 

Emerging respiratory disease outbreaks pose a major threat to food production systems. Agricultural workers face health disparities that amplify their susceptibility to respiratory pathogens, yet the consequences for worker health and food production remain poorly understood. 

Methods: 

We developed a household-structured susceptible-infectious-recovered (SIR) transmission model to compare disease dynamics between agricultural workers and the general U.S. population across six regions. We simulated outbreaks across a range of epidemiological scenarios and assessed productivity losses in California for three labor-intensive crops (oranges, iceberg lettuce, strawberries) with different harvest seasonalities. 

Results: 

We show that, for a baseline reproduction number of R0 = 2.0, the peak disease prevalence among agricultural workers is 1.41-1.69 times higher than that of the general population across regions, and final outbreak sizes are 1.29-1.42 times higher. Household structure accounts for 54%-68% of the disease disparity. Peak productivity losses range from 0.50%-0.63% across crops, translating to millions in lost potential revenue. At higher transmissibility and severity (R0 = 3 and assuming all infections are symptomatic), losses are 2.4 times higher. 

Conclusions: 

Household crowding may lead to disproportionate respiratory disease burden among agricultural workers that is exacerbated by vaccination and obesity disparities, highlighting the need for targeted outbreak preparedness and mitigation strategies in the agricultural sector to maintain food system resilience and support public health in these communities.

Competing Interest Statement

The authors have declared no competing interest.

Source: 

Link: https://www.medrxiv.org/content/10.64898/2026.03.31.26349871v2

____

#USA, #Wastewater Data for Avian #Influenza #H5 (US CDC, August 28 '26)

 

{Excerpt}

(...)

A(H5) detections in the past week

Time Period: August 16, 2026 - August 22, 2026

    -- A(H5) Detection: 3 site(s) (0.7%)

    -- No Detection: 437 site(s) (99.3%)

    -- No samples: 72 site(s)

{Click on Image to Enlarge}

___

(...)

Source: 

Link: https://www.cdc.gov/wastewater/emerging-viruses/h5.html?

____

Seasonal #surveillance in #humans in 2026 for #WNV #infection (ECDC, August 28 '26): 877 cases so far, of which 428 in #Italy

 

{Summary}

Week 35, 2026 | Produced on 27 August 2026 at 12:45, based on data submitted up until and including 26 August 2026.

Current situation

    ° Since the beginning of the 2026 transmission season, and as at 26 August, 124 areas affected by West Nile virus (WNV) have been identified in 15 countries across Europe.

    ° These areas are located in: 

        § Italy (55), 

        § Greece (17), 

        § Romania (15), 

        § France (13), 

        § Serbia (six), 

        § Spain (four), 

        § North Macedonia (three), 

        § Croatia (two), 

        § Germany (two), 

        § Albania (one), 

        § Austria (one), 

        § Cyprus (one), 

        § Hungary (one), 

        § Kosovo* (one) and 

        § the Netherlands (one).

    ° This week, 25 areas are reported as affected for the first time this season. (...).

    ° The 15 countries have reported 877 locally acquired human cases of WNV infection: 

        § Italy (428 cases), 

        § Greece (222 cases, of which eight with unknown place of infection), 

        § Spain (79 cases), 

        § North Macedonia (49 cases), 

        § Romania (45 cases), 

        § France (28 cases), 

        § Serbia (11 cases), 

        § Croatia (three cases), 

        § the Netherlands (three cases), 

        § Austria (two cases), 

        § Cyprus (two cases), 

        § Germany (two cases), 

        § Albania (one case), 

        § Hungary (one case) and 

        § Kosovo* (one case)

(...)

Source: 

Link: https://www.ecdc.europa.eu/en/west-nile-fever/surveillance-and-disease-data/disease-data-ecdc

____

Chinese #Taipei - High pathogenicity avian #influenza #H5N1 viruses (Inf. with) (#poultry) - Immediate notification

 

    ° A recurrence of high pathogenicity avian influenza (HPAI) subtype H5N1 (clade 2.3.4.4b) was detected in native chickens at a slaughterhouse in Taipei City, Chinese Taipei. 

    ° On August 8, clinical signs were identified during postmortem inspection by the resident veterinarian, who immediately notified the Local Animal Disease Inspection Authority of Taipei City. 

    ° On the same day, diagnostic samples were collected and sent to the National Reference Laboratory; concurrently, the other 25 native chickens from the same source were depopulated and placed in frozen storage. 

    ° Following official confirmation of the positive case on August 10, the frozen carcasses were destroyed on August 11, with cleaning and disinfection completed thoroughly. 

    ° Trace-back investigation was immediately initiated, and the source poultry farm was placed under movement restriction; subsequent diagnostic testing yielded negative results for avian influenza nucleic acid. 

    ° There are no poultry farms within 3 kilometers of the slaughterhouse.

Source: 

Link: https://wahis.woah.org/#/in-review/7778

____

Operational #epidemiology of the early phase of the 2026 #Bundibugyo virus disease #outbreak in the #DRC and #Uganda

 

Abstract

The 2026 Bundibugyo virus disease outbreak in the Democratic Republic of the Congo (DRC) and Uganda occurred in a fragile cross-border setting marked by delayed recognition, diagnostic uncertainty, insecurity, population mobility, community mistrust, and healthcare-worker exposure. We conducted a retrospective operational epidemiology study using official situation reports, public health declarations, ministry statements, WHO and Africa CDC updates, cross-border communiqués, and selected partner statements. This analysis reflects publicly available data from the early outbreak period, with the primary DRC data lock on 27 May 2026 and Uganda and regional triangulation through 29 May 2026. We reconstructed the early timeline, described epidemiological and geographic progression, quantified response indicators, and applied a transparent health-zone prioritization framework. The earliest documented symptom onset was 24 April 2026. The Institut National de Recherche Biomédicale (INRB) detected non-Zaire ebolavirus in eight of 13 samples on 14 May, giving a 20-day symptom-onset-to-first-laboratory-detection interval; species-level Bundibugyo virus confirmation and official declaration followed on 15 May. By the DRC data lock on 27 May, 125 confirmed cases and 17 confirmed deaths had been reported, giving a confirmed case fatality ratio of 13.6%. DRC also reported 906 suspected cases and 223 suspected deaths, giving a suspected fatality proportion of 24.6%. Confirmed cases expanded from three to 13 health zones across three provinces within 12 days. Ituri province accounted for 110 confirmed cases (88.0%); Bunia, Rwampara, and Mongbwalu health zones together contributed 90 cases (72.0%). Uganda reported nine confirmed cases and one death by 29 May. Operational pressure included 2,635 listed contacts in DRC, 436 contacts under follow-up in Uganda, and 126 of 774 collected samples (16.3%) pending testing in DRC. Healthcare workers represented 16 of 125 DRC confirmed cases (12.8%) and at least three of nine Uganda cases (33.3%). Applying the health-zone prioritization framework, Rwampara, Mongbwalu, and Bunia were classified as higher priority health zones. Excluding confirmed burden did not change any health-zone tier; data classification confidence was high for 10 zones and moderate for three. Within this early operational snapshot, outbreak visibility reflected both transmission and operational factors, particularly detection delay, laboratory backlog, cross-border movement, healthcare-linked exposure, and community trust or security incidents. The framework provides a transparent basis for rapid decision support during an outbreak’s early phase by directing surveillance, laboratory, case-management, infection prevention and control, contact-tracing, and community-engagement resources toward health zones where multiple operational risks converge.

Source: 

Link:https://journals.plos.org/globalpublichealth/article?id=10.1371/journal.pgph.0006680

____

Pre-existing systemic and #nasal #antibodies against avian #H5 #influenza A viruses vary according to childhood #imprinting

 

ABSTRACT

Avian influenza A viruses (IAVs) pose a constant pandemic threat, with the recent 2.3.4.4b clade of the H5 subtype causing high pathogenicity and spreading across animal species and geographic locations. Understanding human pre-existing immunity to avian H5 IAV can inform on population susceptibility, a critical aspect of pandemic preparedness. To that end, we analyzed the IAV HA-specific antibodies across individuals born between 1928 and 1999 with different early life exposures to IAV subtypes. Individuals born prior to 1957 had the highest pre-existing serum antibodies to group 1 HA antigens, including the 2.3.4.4b H5 and a group 1 HA stem antigen. These birth year-specific patterns were not reflected in the limited pre-existing serum neutralizing antibodies detectable against a 2.3.4.4b H5 IAV or in H5-specific memory B cell populations. They were, however, evident in pre-existing nasal IgG and IgA titers to H5, which were greater in individuals born prior to 1957. Our findings demonstrate that the immunological biases afforded by early life exposure extend to antibodies detected in the nasal mucosa, the site of IAV replication.

Source: 

Link: https://journals.asm.org/doi/10.1128/mbio.01892-26

____

West African Clade C #MERS-CoV Strains BF785 and Mor213 Induce More Robust #Interferon and Inflammatory Signaling Compared to Clade A in #Human Respiratory Cells

 

Abstract

Clade A Middle East respiratory syndrome coronavirus (MERS-CoV) spilled over from camels into humans in Saudi Arabia in 2012 and caused pneumonia and severe respiratory disease, with a 37% case fatality rate. While clade A and B viruses are closely related phylogenetically, clade B MERS-CoV strains have since outcompeted clade A strains and continue to circulate in camels and humans in the Middle East and cause outbreaks in humans. Clade C strains circulate in camels across the African continent but have not been reported to cause disease in humans. We have shown that a number of East African clade C isolates are less able to utilize the TMPRSS2-mediated pathway for viral entry in both cell lines and primary nasal epithelial cultures, which may underlie the reduced replication of East African clade C strains in humans. However, the reduced replicative capacity of West African strains in human cells appears to be independent of viral entry, suggesting an alternative basis for their attenuation. Here, we report that West African clade C MERS-CoV isolates with deletions in ORF4b encoding a key accessory protein, NS4b, induced significantly more robust interferon and inflammatory responses than clade A MERS in human respiratory cell lines and primary bronchial air–liquid interface cultures. The replication deficit for the West African strain BF785, which has a complete deletion of ORF4b, was partially rescued when RNASEL was knocked out in A549 cells. These findings demonstrate that complete loss of NS4b results in stronger innate immune activation than partial truncation and suggests that differential selection on NS4b may contribute to the varying phenotypes of clade C MERS-CoV strains circulating in African camels.

Source: 

Link: https://www.mdpi.com/1999-4915/18/9/935

____

#Italy, #WNV & #Usutu Virus #Human Cases Weekly #Surveillance Report (ISS, August 27 '26): 432 cases so far this season, of which 223 #WNND

 

{Excerpt}

(...)

Highlights

    ° Since the beginning of surveillance season and as of August 26 '26, 432  human cases of infection with West Nile Virus have been confirmed in Italy. They were 312 last week. 

    ° Of these: 

        § 223 were WNND (of these, three were imported: 1 from Maldives, 1 from France and 1 from Belgium), 

        § 63 were asymptomatic cases in blood donors, 

        § 144 were West Nile Fever cases, 

    ° Among confirmed cases, 17 were fatal. 

    ° Case Fatality Rate (CFR) is so far at 7.2% (last year it was 13.9%) for severe neuroinvasive cases.

    ° So far this season, 10 human cases of infection with Usutu virus have been confirmed.

(...)

Source:

Link: https://www.epicentro.iss.it/westnile/bollettino/Bollettino_WND_2026_5.pdf

____

A cross-sectional #study of avian #influenza virus in #poultry #markets of #Guangdong #China, 2025

 

Abstract

Background: 

Guangdong, China is a critical epicenter for avian influenza virus (AIV) emergence, where H5N1 and highly pathogenic H7N9 were first identified. Monitoring AIV genotype distribution and genetic diversity in this region is essential for providing early warnings and mitigating the risk of human infections.

Methods: 

In May 2025, a cross-sectional study was conducted across 4 representative cities in Guangdong. We collected 500 environmental swabs and 45 wastewater samples from 23 live poultry markets (LPMs). Samples were screened for influenza A virus (IAV) and subtyped for H5, H7, and H9. Next generation sequencing (NGS) and phylogenetic analyses were employed to characterize viral diversity and zoonotic potential.

Results: 

AIV was detected in 49.2% (246/500) of environmental samples. H9 was the dominant subtype (38.2%), followed by H5 (3.2%) and H7 (0.8%); 2.4% of positive samples showed multi-subtype co-occurrence. “Non-restricted zone” markets (80.0%) and “waste storage areas” (68.4%) were identified as primary contamination hotspots. Phylogenetic analysis revealed that H5 and H9 viruses are accumulating mutations linked to enhanced human-type receptor affinity. Notably, H5 and H6 sequences exhibited long internal branches and clustered with isolates from other Asian countries rather than domestic strains, highlighting a significant gap in current domestic molecular surveillance and a lack of continuous evolutionary data for these genotypes.

Conclusions: 

Widespread AIV contamination persists in Guangdong LPMs, dominated by H9 with low-level circulation of highly pathogenic subtypes. The identified surveillance gaps for H5/H6 and the presence of multi-subtype environments underscore the urgent need for strengthened, integrated molecular monitoring and stricter market regulation to mitigate public health risks.

Source: 

Link: https://www.frontiersin.org/journals/cellular-and-infection-microbiology/articles/10.3389/fcimb.2026.1914072/full

____

#Bundibugyo virus #glycoprotein seroreactivity following recombinant VSV–Zaire #Ebola virus glycoprotein #vaccination in outbreak-affected populations of #DRC: a longitudinal cohort study

 

Summary

Background

There are currently no licensed vaccines for disease caused by Bundibugyo virus (BDBV). The recombinant vesicular stomatitis virus–Zaire Ebola virus glycoprotein (rVSVΔG-ZEBOV-GP) vaccine has been widely deployed during Ebola virus disease outbreaks caused by Ebola virus (EBOV). Human studies have shown cross-reactive BDBV antibody responses following licensed Ebola virus disease vaccine administration, but the durability and longitudinal kinetics of these responses in populations vaccinated during outbreaks remain unknown. We aimed to evaluate BDBV glycoprotein seroreactivity following rVSVΔG-ZEBOV-GP vaccination in two longitudinal cohorts from regions of the Democratic Republic of the Congo affected by Ebola virus disease outbreaks.

Methods

This longitudinal cohort study was done in Mbandaka, Equateur Province, and Beni, North Kivu Province. Individuals aged 1 year and older who received the rVSVΔG-ZEBOV-GP vaccine under the WHO ring-vaccination protocol were eligible for enrolment. These populations were defined as: people with confirmed Ebola virus disease, contacts of people with Ebola virus disease or contacts-of-contacts, and health-care or front-line workers in areas affected by Ebola virus disease. Participants were enrolled from June 2 to July 3, 2018, in Mbandaka and from Aug 15 to 29, 2018, in Beni. Serum samples were collected from vaccine recipients and antibody reactivity was assessed using a multiplex pan-filovirus immunoassay. Both cohorts were followed up over 5 years, with seven data collection periods in each province. We evaluated longitudinal trends in EBOV and BDBV glycoprotein seroreactivity using a pan-filovirus multiplex immunoassay across follow-up visits.

Findings

We analysed 5849 serum samples from 1081 participants. 715 (66%) of 1081 participants were male and 366 (34%) were female. BDBV glycoprotein seroreactivity differed substantially between study sites. At baseline, 16 (3%) of 482 participants in Mbandaka and 62 (10%) of 599 in Beni were seroreactive to BDBV glycoprotein. In Mbandaka, BDBV glycoprotein antibody reactivity remained stable through to 6 months after initial vaccination before increasing from a mean median fluorescent intensity (MFI) of 1238 (SD 1599) at 2·5 years, with 16 (5%) of 355 seroreactive, to 4845 (5881) at 3·5 years and 116 (35%) of 329 seroreactive (p<0·0001), followed by waning at later visits. In Beni, BDBV glycoprotein antibody reactivity increased rapidly after the initial vaccination, with seroreactivity peaking at 21 days to a mean MFI of 6678 (SD 6997) with 283 (52%) of 541 participants seroreactive and at 6 months to an MFI of 6852 (6560) with 270 (54%) of 501 seroreactive. Although antibody levels decreased after 6 months, EBOV glycoprotein and BDBV glycoprotein antibody reactivity remained above baseline through to 5 years after vaccination.

Interpretation

The differing patterns of BDBV glycoprotein seroreactivity observed between Beni and Mbandaka warrant further investigation into the epidemiological and immunological factors associated with this seroreactivity, including the epidemiological significance of baseline seroreactivity observed before vaccination. To our knowledge, these findings provide the first longitudinal human data describing BDBV glycoprotein seroreactivity following licensed Ebola virus disease vaccination in populations living in regions now affected by the current outbreak of disease caused by BDBV. They add to the growing body of human evidence describing cross-reactive antibody responses following licensed Ebola virus disease vaccination and support rigorous clinical evaluation of rVSVΔG-ZEBOV-GP during the ongoing outbreak while BDBV-specific vaccines continue to be developed.

Funding

The US Food and Drug Administration, the Gates Foundation, and the US Defense Advanced Research Projects Agency.

Source: 

Link: https://www.sciencedirect.com/science/article/pii/S0140673626016089?dgcid=rss_sd_all

_____

Highly persistent #antibody levels but limited population #immunity in #gannets after #HPAI #outbreak

 

Abstract

The recent large-scale circulation of High Pathogenicity Avian Influenza (HP AI) viruses H5Nx of clade 2.3.4.4b has been responsible for massive die-offs in wild species, notably in long-lived seabirds, with unknown implications for the immunity of surviving individuals. In the North Atlantic, northern gannet colonies were heavily affected in 2022, with more than 40% mortality observed among breeding adults and some surviving individuals developing dark irises. Using samples collected in 2023 and 2024 on Rouzic colony (France), we report persistent individual anti-AI antibody levels and seroneutralisation titres, with most of the immune individuals showing dark irises. A modelling approach further stressed the importance of long-lasting immunity in such species by showing that the proportion of individuals which kept their immunity between years strongly limited decreases in population size in case of repeated outbreaks. Overall, our results highlight the existence and importance of long-lasting immunity in long-lived species for population persistence.

Competing Interest Statement

The authors have declared no competing interest.

Funder Information Declared

CNRS Ecology Evolution SEE-Life program for long term monitoring

Ceva Wildlife Research Fund, CWR1

Agence Nationale de la Recherche, https://ror.org/00rbzpz17, ECOPATHS (ANR-21-CE35-0016), WILDFLU (ANR-25-CE35-0691)

Ailes Marines

Observatoire de Recherche Montpelliérain de l'Environnement OREME, https://ror.org/00cesps27, SO ECOPOP

Source: 

Link: https://www.biorxiv.org/content/10.64898/2026.08.25.745523v1

____

Person died from a #WNV #infection acquired in the #Netherlands (RIVM, August 26 '26)

 

    In the province of Utrecht, someone has died from West Nile fever. 

    The person contracted the West Nile virus in the Netherlands and died in a hospital. Due to privacy and out of respect for the relatives, RIVM will not make any further statements about this person. 

    So far in 2026, there have been three cases of West Nile virus infections reported that were probably contracted in the Netherlands. 

    It is still very unlikely for people to contract West Nile fever in the Netherlands.

West Nile fever

    The West Nile virus occurs in birds. The common house mosquito can contract the virus when feeding on the blood of an infected bird. An infected mosquito can then pass the virus on to other birds, to mammals such as horses, and to humans. Humans and horses can fall ill with the West Nile virus, but they cannot pass the virus on to others. The disease caused by the West Nile virus is called West Nile fever.

    About 80% of people who contract the West Nile virus do not show any symptoms. Around 19% experience flu-like symptoms, and 1 per cent may develop neurological symptoms. People over 50 and people with weakened immune systems due to illness or medication have a higher risk of becoming very ill from West Nile fever. A small proportion of people who have a severe form of West Nile fever may die.

Alert on West Nile virus

    Experts from various organisations are closely keeping an eye on how often West Nile virus occurs in the Netherlands among humans, horses, birds, and mosquitoes. 

    So far this year, West Nile virus has been found in the provinces of Utrecht, North Brabant, and South Holland. It is possible that the virus is also present in other parts of the Netherlands. That is why RIVM has asked doctors across the country to be alert if they see people with symptoms that match West Nile fever.

What can you do to prevent West Nile fever?

    The West Nile virus is spread by common house mosquitoes that feed on the blood of an infected bird. Mosquitoes are mostly active at dusk. 

    To avoid mosquito bites as much as possible, you can, for example:

        ° wear clothing that covers the skin (long sleeves, long trousers)

        ° keep mosquitoes out (insect screens for windows/doors)

        ° use mosquito repellents on exposed skin

        ° sleep under a mosquito net

Source: 

Link: https://www.rivm.nl/en/news/person-died-from-west-nile-virus-infection-acquired-in-netherlands

____

Evaluating the #impact of #antiviral post-exposure #prophylaxis for health-care workers during #orthoebolavirus outbreaks: a modelling study

 

Summary

Background

Orthoebolavirus outbreaks place health-care workers (HCWs) at substantial risk, and HCW illness or death can weaken response capacity. The 2026 Bundibugyo virus outbreak in DR Congo highlights the need for deployable countermeasures when species-specific vaccines are unavailable. With candidate antivirals under evaluation, we aimed to estimate the impact of HCW-targeted antiviral post-exposure prophylaxis (PEP) across different readiness, disruption, and allocation scenarios.

Methods

We adapted a previously published stochastic branching-process model of orthoebolavirus transmission, representing health care, community, and funeral transmission; time-varying non-pharmaceutical interventions; and HCW-targeted PEP. The model was calibrated to two historical outbreaks using sequential approximate Bayesian computation: the 2013–16 west Africa epidemic, to define a high-burden, reasonable worst-case scenario archetype (west Africa-like archetype); and the 2018–20 North Kivu and Ituri outbreak in eastern DR Congo, to define an archetype with longer transmission under conflict-related response disruption (DR Congo-like archetype). The primary outcome was HCW deaths averted. For both archetypes, we simulated three antiviral deployment readiness scenarios (scenario 1: 100% coverage on day 0; scenario 2: scaled up to 80% coverage over 180 days; and scenario 3: scaled up to 50% coverage over 1 year) and compared their impact on HCW deaths with a scenario of no antiviral. For the DR Congo-like archetype only, we simulated four disruption scenarios: no antiviral PEP, ideal delivery (100% coverage and no dosing delay), delayed dosing with coverage preserved, and delayed dosing with delayed coverage. As a secondary outcome, we assessed number of PEP doses required per HCW death averted under different allocation scenarios.

Findings

At baseline (no antiviral PEP), cumulative HCW deaths reached a median of 553 (IQR 208–983) in the west Africa-like archetype by week 60, compared with 61 (19–125) in the DR Congo-like archetype by week 80. Assuming 80% efficacy and 80% coverage with antiviral PEP in the same timeframe in a central analysis, cumulative HCW deaths fell to 200 (68–349; equivalent reduction of 64% [63–66] relative to baseline) in the west Africa-like archetype and 22 (10–44; equivalent reduction of 64% [60–68]) in the DR Congo-like archetype. Under different scenarios of deployment readiness at 80% antiviral efficacy, the median reduction in HCW deaths compared with no PEP was 80% (95% CrI 79–81) in the west Africa-like archetype and 80% (76–84) in the DR Congo-like archetype for scenario 1; 60% (57–62) and 52% (41–58), respectively, for scenario 2; and 19% (16–22) and 22% (7–29), respectively, for scenario 3. In the DR Congo-like operational disruption analyses, an ideal scenario (PEP delivered at 100% coverage without a delay after exposure) averted 83% (79–87) of HCW deaths compared with no antiviral; maintaining 100% coverage but introducing delayed dosing (1–5 days post-exposure) reduced this finding to 50% (40–55) compared with no antiviral. Delayed coverage and dosing resulted in only 35% (25–47) of the ideal scenario impact. At 80% antiviral efficacy with same-day dosing, targeted allocation of recognised high-risk exposures (such as personal protective equipment breaches or direct body-fluid contact) required 44 doses (95% Crl 43–44) per HCW death averted versus 109 doses (85–161) with broad allocation.

Interpretation

HCW-targeted antiviral PEP could substantially reduce HCW deaths during orthoebolavirus outbreaks if efficacious antivirals can be delivered rapidly and high operational coverage is maintained. Comparisons of antiviral use cases and alternative response investments are needed to determine how resources can best support outbreak response.

Funding

Gilead Sciences, UK National Institute for Health and Care Research, Oxford Martin School, Miller Institute, EU Global Health EDCTP3, and Coalition for Epidemic Preparedness Innovations.

Translations

For the French and Swahili translations of the abstract see Supplementary Materials section.

Source: 

Link: https://www.thelancet.com/journals/laninf/article/PIIS1473-3099(26)00437-8/fulltext?rss=yes

____

Predicting the #Risk of Avian #Influenza #Zoonosis using Viral #Genome Sequencing Data

 

Abstract

Avian Influenza viruses (AIVs) infect a broad host range despite having a natural reservoir in wild aquatic birds. Whilst most strains stay within their host species, some break the species barrier through genetic adaptations. We are most concerned about zoonotic cases, where a human becomes infected. Despite these events being rare, they are associated with high mortality and introduce the risk of onward human-to-human transmission of AIV. As a novel pathogen within the human population, this could have pandemic potential. Using genetic composition features for 8 AIV proteins drawn from viral sequence data, we employ machine-learning algorithms to classify AIV cases as zoonotic or not. These genetic features encode host 'signatures' which can indicate zoonosis and include frequency measures such as dipeptide composition and amino acid physiochemical properties. We consistently find XGBoost to outperform all other algorithms. We optimise parameters for ten classification models: one for each of the 8 proteins and two combined models. Following this, we show that a multi-model approach gives the best performing prediction for AIV zoonosis. We have identified all 8 proteins as having a role in predicting zoonotic transmission. Of particular importance is the PB2 and HA proteins, with specific amino acid physiochemical properties such as charge, secondary structure and hydrophobicity amongst the most indicative features in our combined models. Our alignment-free computational study can identify AIV cases still within avian hosts which are genetically closest to zoonotic AIV cases, thereby identifying the cases most likely to cross the species barrier. In a resource limited environment, our model could be used to quickly identify high priority cases for further investigation.

Competing Interest Statement

The authors have declared no competing interest.

Source: 

Link: https://www.biorxiv.org/content/10.64898/2026.08.21.746166v1

____

#Bundibugyo Virus Disease #Outbreak, #DRC - Situation #Report No. 15, Data as of 23 August '26 (WHO, summary): 5,584 cases & 2,680 deaths in DRC

 

{Summary}

{Click on Image to Enlarge}

___

Event description

Democratic Republic of the Congo

    More than three months into the response, the Bundibugyo virus disease  (BVD) outbreak in the Democratic Republic of the Congo remains characterized by  sustained transmission, high mortality and continued geographic expansion. 

    The epidemiological picture is increasingly heterogeneous, with  persistent transmission in established hotspots in Ituri, intensifying transmission  in parts of Nord-Kivu and Haut-Uélé, and continued geographic expansion  through the emergence of cases in previously unaffected health zones. 

    Since External Situation Report #14, a total of 563 new confirmed cases and 302 confirmed deaths have been reported, bringing the cumulative total to  5 584 confirmed cases, including 2 680 deaths. 

    The number of affected health zones has increased from 55 to 57 across  six provinces, with Viadana in Bas-Uélé and Mutwanga in Nord-Kivu being  the most recently affected health zones.

Figure 1. Daily growth trend in confirmed Bundibugyo virus disease cases in the  Democratic Republic of the Congo, by date of report, data as of 23 August 2026

{Click on Image to Enlarge}

___

(...)

    During the most recent 21 days (3 – 23 August 2026), 1 782 confirmed  cases were reported nationally. Compared with the preceding 21-day period (13  July – 2 August 2026), reported cases declined slightly by 57 (−3.1%). Given  the small magnitude of this decline and the potential influence of reporting  delays and retrospective data reconciliation, this should be interpreted cautiously  because it does not yet provide clear evidence of declining transmission. 

    The national trend also masks a continued redistribution of reported incidence, with cases declining by 13.4% in Ituri but increasing by 32.5% in  Nord-Kivu and 122.2% in Haut-Uélé. Consequently, Ituri’s contribution to newly  reported cases declined from 84.0% to 75.1%, while the contribution of Nord-Kivu  increased from 12.9% to 17.6% and that of Haut-Uélé more than doubled  from 2.9% to 6.7%.

    During the same period, 973 confirmed deaths were reported nationally, a  slight decrease of 16 deaths (−1.6%) compared with the preceding 21 days. A  marked geographic redistribution of mortality was nevertheless observed. While  deaths declined by 8.8% in Ituri, they increased by 15.1% in Nord-Kivu and  85.2% in Haut-Uélé. Consequently, Ituri’s contribution to newly reported deaths  declined from approximately 78.3% to 72.6%, while Nord-Kivu’s contribution  increased from 18.7% to 21.9% and Haut-Uélé’s nearly doubled from 2.7% to  5.1%. Transmission therefore remains dominated by Ituri but is increasingly  distributed across other active foci, indicating that the outbreak is becoming progressively less concentrated in its original epicentre.

(...)

    At health-zone level, the changing geographic pattern is more pronounced, with substantial variation in reported incidence across established  and emerging transmission foci. In Ituri, reported cases declined markedly in  Mongbwalu from 223 to 50 (−173; −77.6%), Lita from 96 to 56 (−40; −41.7%),  and Nizi from 292 to 210 (−82; −28.1%), while Bunia declined slightly from 411  to 384 (−27; −6.6%) and Rwampara from 271 to 258 (−13; −4.8%). In contrast,  cases increased in Bambu from 33 to 63 (+30; +90.9%), Mangala from  55 to 92 (+37; +67.3%), and Nia-Nia from 69 to 89 (+20; +29.0%).

    Outside Ituri, reported cases increased substantially in Katwa from 115  to 162 (+47; +40.9%) and Beni from 34 to 53 (+19; +55.9%) in Nord-Kivu, and  in Isiro from 19 to 49 (+30; +157.9%) and Wamba from 9 to 47 (+38; +422.2%)  in HautUélé. These patterns indicate that the declining contribution of  Ituri is being driven primarily by substantial reductions in several established  hotspots, particularly Mongbwalu and Nizi, rather than by a uniform decline across  the province.

    At the same time, increasing incidence in selected health zones within  Ituri and the continued growth of foci in NordKivu and Haut-Uélé indicate an  increasingly heterogeneous and geographically dispersed transmission pattern. 

    Reported deaths at health-zone level show a broadly similar geographic redistribution  but also highlight important discordance with trends  in reported cases. In Nord-Kivu, deaths in Katwa increased from 71 to 112 (+41;  +57.7%), alongside the increase in reported cases, while deaths in Beni increased  from 29 to 35 (+6; +20.7%). In Haut-Uélé, deaths increased in Isiro  from 11 to 18 (+7; +63.6%) and Wamba from two to 17 (+15; +750.0%),  consistent with increasing reported incidence in both health zones. In Ituri, deaths  declined substantially alongside cases in several established hotspots,  including Mongbwalu from 82 to 20 (−62; −75.6%), Nizi from 146 to 58 (−88;  −60.3%), Lita from 62 to 25 (−37; −59.7%), and Rwampara from 173 to 72  (−101; −58.4%).

    However, the pattern was not consistent across all health zones. Most  notably, Bunia recorded a 29.8% increase in deaths, from 104 to 135 (+31),  despite a 6.6% decline in reported cases. Deaths also increased in Bambu from 5  to 13 (+8; +160.0%), alongside the increase in cases, while Mangala showed  little change in deaths, from 37 to 40 (+3; +8.1%), despite a 67.3% increase in  reported cases. These discordant trends warrant cautious interpretation of  apparent declines in reported incidence. Where fatal infections are more  consistently ascertained than non-fatal cases, a reduction in reported cases  without a corresponding reduction in deaths may reflect differences in case  ascertainment,  reporting delays, or the lag between case detection and death  rather than a true decline in transmission. Interpretation of recent health-zone  mortality patterns in Ituri is further limited by 250 cumulative deaths that had not  yet been assigned to a health zone as of 23 August 2026.

    Ten previously affected health zones reported no confirmed cases  during the most recent 21 days (3 – 23 August 2026): Adja, Boga,  Kambala and Mahagi in Ituri; Goma and Lubero in Nord-Kivu; Rungu in Haut-Uélé;  Lubunga and WanieRukula in Tshopo; and Miti-Murhesa in Sud-Kivu. During  the same period, six health zones were reported as affected for the first  time: Mutwanga in Nord-Kivu; Gombari in Haut-Uélé; Bafwasende and Tshopo in  Tshopo; and Buta and Viadana in Bas-Uélé.

(...)

    Mortality remains high, with 302 confirmed deaths reported during the last seven days, including 171 (56.6%) in the community and 131 (43.4%) in  BVD treatment facilities. The persistently high proportion of community deaths  (defined as both deaths at home and at non-BVD health facilities) highlights  continued challenges with early detection, referral and timely access to treatment,  while mortality in BVD treatment facilities may reflect late  presentation, quality of care and patient vulnerabilities, including age, malnutrition  and comorbidities; further analysis to understand the risk factors 

is underway.

    Among 4807 confirmed cases and 1820 deaths with available age and  sex information, adults aged 20 – 59 years continue to account for the majority of confirmed cases, representing about two-thirds of cases overall and  58% in the most recent epidemiological week. However, mortality remains disproportionately concentrated among young children.

    In week 34, children aged <5 years accounted for 17% of reported cases but 29% of deaths, continuing the increased contribution of this age group to  mortality observed in recent weeks. Overall, the sex distribution of cases is  relatively balanced, although females account for slightly more cases, while  deaths are broadly similar between males and females. These findings continue to  indicate a high burden of transmission among working-age adults alongside  

disproportionate mortality among young children.

(...)

    The current BVD outbreak continues to follow a markedly different  trajectory from previous major Ebola disease outbreaks. 

    

    During the first 102 days of reporting, the 7-day moving average of  daily cases remained substantially higher than levels observed during  comparable periods of the 2014 – 2016 West Africa and 2018 – 2020 Democratic  Republic of the Congo outbreaks, reaching more than 90 confirmed cases per day  at its recent peak. With 5514 confirmed cases, including 2642 deaths, reported as  of 22 August 2026, this is the largest BVD outbreak ever recorded and the  secondlargest Ebola disease outbreak on record. Notably, the number of deaths  has already surpassed the 2287 deaths reported during the entire 2018–2020  outbreak in eastern Democratic Republic of the Congo.

Figure 7. Comparison of three major Ebola disease outbreak trajectories during  the first 102 days of reporting using seven-day moving averages of the daily number of confirmed cases reported.

{Click on Image to Enlarge}

___

    The security situation in eastern Democratic Republic of the Congo  remains volatile and continues to present operational challenges for the  outbreak response. Recent insecurity has included armed clashes, attacks  affecting civilians and health services, population displacement and constraints on  humanitarian access in parts of the affected area. In addition, the AFC/M23 group  recently announced restrictions on movement to and from Ebola-affected government-controlled areas as a measure to reduce the risk of disease  importation into areas under their control.

    While the operational implications of these measures are still being assessed, continued insecurity, displacement and  restrictions on population  movement underscore the complexity of maintaining coordinated outbreak  response activities across areas with different security and administrative  contexts.

Uganda and France

    Uganda has now recorded 38 consecutive days without a new confirmed BVD case  since the last patient was discharged on 16 July 2026. All  identified contacts completed follow-up, with no further cases detected. The  continued high level of transmission in neighbouring eastern Democratic Republic  of the Congo, however, means that the risk of cross-border reintroduction  remains. France has reported no new confirmed BVD cases for 50 consecutive  days since the imported case was discharged on 4 July 2026. The outbreak is thus  considered over by WHO’s norm of 42 days without any cases. 

Risk Assessment

    According to WHO’s latest Rapid Risk Assessment as of 20 August 2026, the risk of further spread remains very high within the Democratic  Republic of the Congo and high for neighbouring countries sharing land  borders with the country. 

    The assessment reflects sustained transmission, continued geographic expansion, high mortality, population mobility, insecurity and persistent  response challenges. The risk is considered low elsewhere in Africa and globally.  The second IHR Emergency Committee, convened on 18 August 2026, also  reviewed the evolving situation and emphasized that the outbreak remains far  from controlled, and continues to constitute a Public Health Emergency of  International Concern.

(...)

Situation interpretation

    The BVD outbreak continues to evolve into a more complex and geographically dispersed phase , in which modest reductions in some  established hotspots are being offset by intensification and emergence of  transmission elsewhere. 

    The simultaneous persistence of high mortality, community deaths, health-worker infections, uneven contact followup, localized treatment  constraints and community resistance indicates that expansion of response  capacity alone is not yet translating consistently into transmission control. The  priority must remain faster, locally differentiated and community-centred  operations, concentrating resources on active and emerging transmission foci,  closing critical surveillance, IPC and treatment gaps, and ensuring rapid access to  affected communities. At the same time, sustained regional preparedness and  cross-border coordination are essential to contain further geographic spread.

Source: 

Link: https://www.afro.who.int/health-topics/ebola-disease

____