MHC polymorphism is explained by natural selection driven by the MHC-dependent impact of certain infections, inflammatory conditions, autoimmune diseases, and cancers. However, examples of human disease driving this process are rare. We evaluated the impact of HIV-1 in altering HLA-I frequencies in KwaZulu-Natal, South Africa, and the influence of antiretroviral therapy (ART) on this process. In a historical mother-child cohort in the pre-ART era (1998-2005), HIV-1 survival and vertical transmission were both strongly HLA-B dependent: "disease-susceptible" HLA-B alleles (HLA-B*18/B*45:01/B*58:02) increased adult AIDS progression and vertical transmission (OR 1.6, P = 0.01), whereas "protective" HLA-B alleles (HLA-B*57/B*58:01/B*81:01) slowed AIDS progression, and decreased vertical transmission (OR 0.57, P = 0.002). By contrast, in contemporary antenatal KwaZulu-Natal cohorts in the ART era (2015-2025) the impact of HLA-B on HIV-1 disease outcome and vertical transmission is dramatically reduced. Using these and reported data, we constructed a model to estimate the impact of HIV-1 on HLA-B frequencies in KwaZulu-Natal, both in the prevailing setting of ART and in a hypothetical counterfactual scenario where ART was never rolled out. Over the 45-y period 1990-2035, in the absence of ART, the proportion of the population possessing any "protective" HLA-B allele was projected to increase from 23 to 42% (allele frequencies increasing from 0.12 to 0.24), and the proportion of the population possessing any "disease-susceptible" HLA-B allele was projected to decrease from 28 to 18% (allele frequencies declining from 0.15 to 0.092). The introduction of ART radically slows HLA-B frequency change. These data therefore demonstrate the potential for natural selection from an infectious disease to alter human population genetics within decades, and for the successful roll-out of therapy to halt this process.

H9N2 avian influenza viruses (AIVs) are a major concern for the poultry sector and human health in countries where this subtype is endemic. By fitting a model simulating H9N2 AIV transmission to data from a field experiment, we characterise the epidemiology of the virus in a live bird market in Bangladesh. Many supplied birds arrive already exposed to H9N2 AIVs, resulting in many broiler chickens entering the market as infected, and many indigenous backyard chickens entering with pre-existing immunity. Most susceptible chickens become infected within one day spent at the market, owing to high levels of viral transmission within market and short latent periods, as brief as 5.3 hours. Although H9N2 AIV transmission can be substantially reduced under moderate levels of cleaning and disinfection, effective risk mitigation also requires a range of additional interventions targeting markets and other nodes along the poultry production and distribution network.

The rapid intensification of poultry production raises important concerns about the associated risks of zoonotic infections. Here, we introduce EPINEST (EPIdemic NEtwork Simulation in poultry Transportation systems): an agent-based modelling framework designed to simulate pathogen transmission within realistic poultry production and distribution networks. We provide example applications to broiler production in Bangladesh, but the modular structure of the model allows for easy parameterization to suit specific countries and system configurations. Moreover, the framework enables the replication of a wide range of eco-epidemiological scenarios by incorporating diverse pathogen life-history traits, modes of transmission and interactions between multiple strains and/or pathogens. EPINEST was developed in the context of an interdisciplinary multi-centre study conducted in Bangladesh, India, Vietnam and Sri Lanka, and will facilitate the investigation of the spreading patterns of various health hazards such as avian influenza, Campylobacter, Salmonella and antimicrobial resistance in these countries. Furthermore, this modelling framework holds potential for broader application in veterinary epidemiology and One Health research, extending its relevance beyond poultry to encompass other livestock species and disease systems.

By definition, all pathogens cause some level of harm to their hosts. If this harm occurs while the pathogen is transmitting, it can negatively affect the pathogen's fitness by shortening the duration over which transmission can occur. However, many of the factors that increase virulence (i.e. harm to host) also promote transmission, driving the pathogen population towards an optimal state of intermediate virulence. A wider spectrum of virulence may be maintained among pathogen populations which are structured into multiple discrete strains though direct resource and immune-mediated competition. These various evolutionary outcomes, and the effects of medical and public health interventions, are best understood within a framework that recognizes the complex relationship between transmission and virulence in the context of the antigenic diversity of the pathogen population.

In 2015, the Zika virus (ZIKV) emerged in Brazil, leading to widespread outbreaks in Latin America. Following this, many countries in these regions reported a significant drop in the circulation of dengue virus (DENV), which resurged in 2018-2019. We examine age-specific incidence data to investigate changes in DENV epidemiology before and after the emergence of ZIKV. We observe that incidence of DENV was concentrated in younger individuals during resurgence compared to 2013-2015. This trend was more pronounced in Brazilian states that had experienced larger ZIKV outbreaks. Using a mathematical model, we show that ZIKV-induced cross-protection alone, often invoked to explain DENV decline across Latin America, cannot explain the observed age-shift without also assuming some form of disease enhancement. Our results suggest that a sudden accumulation of population-level immunity to ZIKV could suppress DENV and reduce the mean age of DENV incidence via both protective and disease-enhancing interactions.

It is commonly assumed that all naturally protective targets of immunity in influenza are highly variable. Our theoretical work suggests, by contrast, that influenza evolution is primarily driven by naturally protective immune responses against epitopes of limited variability (ELV). We have identified and characterised at least one such ELV on the head region of the major influenza antigen, haemagglutinin (HA), of H1 influenza, opening up the possibility of a novel method of producing a universal influenza vaccine. Here we demonstrate that the head region of H1 haemagglutinin can be decomposed into a number of discrete variable regions (VRs): ELVs tend to include a limited number of VRs compared to other epitopes either because of the smaller footprint of the associated antibody or because they are centred on VRs that are relatively isolated from the others. We conclude that the variability of an antibody binding site is determined by the number of variable residues included in its footprint rather than the intrinsic entropy of any particular region. ### Competing Interest Statement The authors received financial support from Blue Water Vaccines.

The Zika virus (ZIKV) emerged in Brazil in 2015, causing large outbreaks across South America and the Caribbean. In the years that followed, many countries in these areas reported exceptionally low circulation of Dengue virus (DENV), which later resurged in 2018-2019. Several hypotheses have been proposed to explain low DENV transmission, yet no consensus has been reached so far. We show that while short-term cross-protection induced by ZIKV can explain the temporary disappearance of DENV, it also predicts, in contrast with observations, a rising mean age of DENV incidence in the post-ZIKV era. We further demonstrate that disease enhancement of DENV, especially in primary infections in ZIKV-positive hosts, is required to remedy these shortfalls. Our results suggest that both population-level immunity to DENV and ZIKV contributed positively to the reduction in mean age of DENV incidence.

Streptococcus pneumoniae causes substantial mortality among children under 5-years-old worldwide. Polysaccharide conjugate vaccines (PCVs) are highly effective at reducing vaccine serotype disease, but emergence of non-vaccine serotypes and persistent nasopharyngeal carriage threaten this success. We investigated the hypothesis that following vaccine, adapted pneumococcal genotypes emerge with the potential for vaccine escape. We genome sequenced 2804 penumococcal isolates, collected 4-8 years after introduction of PCV13 in Blantyre, Malawi. We developed a pipeline to cluster the pneumococcal population based on metabolic core genes into “Metabolic genotypes” (MTs). We show that S. pneumoniae population genetics are characterised by emergence of MTs with distinct virulence and antimicrobial resistance (AMR) profiles. Preliminary in vitro and murine experiments revealed that representative isolates from emerging MTs differed in growth, haemolytic, epithelial infection, and murine colonisation characteristics. Our results suggest that in the context of PCV13 introduction, pneumococcal population dynamics had shifted, a phenomenon that could further undermine vaccine control and promote spread of AMR.

Navigating the intricate interplay of competitive and co‐operative interactions and the complex relationship between virulence and transmission pose challenges for our understanding of how pathogens evolve and spread.

Navigating the intricate interplay of competitive and co-operative interactions and the complex relationship between virulence and transmission pose challenges for our understanding of how pathogens evolve and spread.

Background Understanding the age patterns of disease is necessary to target interventions to maximise cost-effective impact. New malaria chemoprevention and vaccine initiatives target young children attending routine immunisation services. Here we explore the relationships between age and severity of malaria hospitalisation versus malaria transmission intensity. Methods Clinical data from 21 surveillance hospitals in East Africa were reviewed. Malaria admissions aged 1 month to 14 years from discrete administrative areas since 2006 were identified. Each site-time period was matched to a model estimated community-based age-corrected parasite prevalence to provide predictions of prevalence in childhood ( Pf PR 2–10 ). Admission with all-cause malaria, severe malaria anaemia (SMA), respiratory distress (RD) and cerebral malaria (CM) were analysed as means and predicted probabilities from Bayesian generalised mixed models. Results 52,684 malaria admissions aged 1 month to 14 years were described at 21 hospitals from 49 site-time locations where Pf PR 2–10 varied from < 1 to 48.7%. Twelve site-time periods were described as low transmission ( Pf PR 2–10 < 5%), five low-moderate transmission ( Pf PR 2–10 5–9%), 20 moderate transmission ( Pf PR 2–10 10–29%) and 12 high transmission ( Pf PR 2–10 ≥ 30%). The majority of malaria admissions were below 5 years of age (69–85%) and rare among children aged 10–14 years (0.7–5.4%) across all transmission settings. The mean age of all-cause malaria hospitalisation was 49.5 months (95% CI 45.1, 55.4) under low transmission compared with 34.1 months (95% CI 30.4, 38.3) at high transmission, with similar trends for each severe malaria phenotype. CM presented among older children at a mean of 48.7 months compared with 39.0 months and 33.7 months for SMA and RD, respectively. In moderate and high transmission settings, 34% and 42% of the children were aged between 2 and 23 months and so within the age range targeted by chemoprevention or vaccines. Conclusions Targeting chemoprevention or vaccination programmes to areas where community-based parasite prevalence is ≥10% is likely to match the age ranges covered by interventions (e.g. intermittent presumptive treatment in infancy to children aged 2–23 months and current vaccine age eligibility and duration of efficacy) and the age ranges of highest disease burden.

The role of immune responses to previously seen endemic coronavirus epitopes in severe acute respiratory coronavirus 2 (SARS-CoV-2) infection and disease progression has not yet been determined. Here, we show that a key characteristic of fatal outcomes with coronavirus disease 2019 (COVID-19) is that the immune response to the SARS-CoV-2 spike protein is enriched for antibodies directed against epitopes shared with endemic beta-coronaviruses and has a lower proportion of antibodies targeting the more protective variable regions of the spike. The magnitude of antibody responses to the SARS-CoV-2 full-length spike protein, its domains and subunits, and the SARS-CoV-2 nucleocapsid also correlated strongly with responses to the endemic beta-coronavirus spike proteins in individuals admitted to an intensive care unit (ICU) with fatal COVID-19 outcomes, but not in individuals with nonfatal outcomes. This correlation was found to be due to the antibody response directed at the S2 subunit of the SARS-CoV-2 spike protein, which has the highest degree of conservation between the beta-coronavirus spike proteins. Intriguingly, antibody responses to the less cross-reactive SARS-CoV-2 nucleocapsid were not significantly different in individuals who were admitted to an ICU with fatal and nonfatal outcomes, suggesting an antibody profile in individuals with fatal outcomes consistent with an "original antigenic sin" type response.

Streptococcus pneumoniae is a major cause of pneumonia, meningitis, and septicaemia worldwide. Pneumococcal antimicrobial resistance (AMR) has been highlighted by the WHO as an important public health concern, with emerging serotypes showing resistance to multiple antibiotics. Indeed, although the introduction of pneumococcal conjugate vaccines (PCVs) has been associated with an overall decline in pneumococcal AMR, there have been increases in prevalence of potentially disease-causing AMR serotypes not targeted by vaccination. Here, we discuss a variety of evolutionary mechanisms at the host, pathogen, and environmental levels that may contribute to changes in the prevalence of pneumococcal AMR in the post-vaccination era. The relative importance of these factors may vary by population, pneumococcal lineage, geography, and time, leading to the complex relationship between vaccination, antibiotic use, and AMR.

ABSTRACT Hepatitis B viruses (HBV) are compact viruses with circular genomes of ∼3.2kb in length. Four genes (HBx, Core, Surface and Polymerase) generating seven products are encoded on overlapping reading frames. Ten HBV genotypes have been characterised (A-J), which may account for differences in transmission, outcomes of infection, and treatment response. However, HBV genotyping is rarely undertaken, and sequencing remains inaccessible in many settings. We used a machine learning approach based on random forest algorithms (RFA) to assess which amino acid (aa) sites in the genome are most informative for determining genotype. We downloaded 5496 genome-length HBV sequences from a public database, excluding recombinant sequences, regions with conserved indels, and genotypes I/J. Each gene was separately translated into aa, and the proteins concatenated into a single sequence (length 1614aa). Using RFA, we searched for aa sites predictive of genotype, and assessed co-variation among the sites with a Mutual Information (MI)-based method. We were able to discriminate confidently between genotypes A-H using 10 aa sites. 5/10 sites were identified in Polymerase (Pol), of which 4/5 were in the spacer domain, and a single site in reverse transcriptase. A further 4/10 sites were located in Surface protein, and a single site in HBx. There were no informative sites in Core. Properties of the aa were generally not conserved between genotypes at informative sites. Co-variation analysis identified 55 pairs of highly-linked sites. Three RFA-identified sites were represented across all pairs (two sites in spacer, and one in HBx). Residues that co-vary with these sites are concentrated in the small HBV surface gene. We also observe a cluster of sites adjacent to the Surface promoter region that co-vary with a spacer residue. Overall, we have shown that RFA analysis is a powerful tool for identifying aa sites that predict HBV lineage, with an unexpectedly high number of such sites in the spacer domain, which has conventionally been viewed as unimportant for structure or function. Our results improve ease of genotype prediction from limited regions of HBV sequence, and may have implications for understanding HBV evolution and the role of the spacer domain.

The COVID-19 pandemic has caused more than 448 million cases and 6 million deaths worldwide to date. Omicron is now the dominant SARS-CoV-2 variant, making up more than 90% of cases in countries reporting sequencing data. As the pandemic continues into its third year, continued testing is a strategic and necessary tool for transitioning to an endemic state of COVID-19. Here, we address three critical topics pertaining to the transition from pandemic to endemic: defining the endemic state for COVID-19, highlighting the role of SARS-CoV-2 testing as endemicity is approached, and recommending parameters for SARS-CoV-2 testing once endemicity is reached. We argue for an approach that capitalizes on the current public health momentum to increase capacity for PCR-based testing and whole genome sequencing to monitor emerging infectious diseases. Strategic development and utilization of testing, including viral panels in addition to vaccination, can keep SARS-CoV-2 in a manageable endemic state and build a framework of preparedness for the next pandemic.

Serological assays for detection of IgG, IgM or IgA against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) play an important role in surveillance, antibody persistence, vaccine coverage and infection rate. Serological assays, including both ELISA and rapid lateral flow assays, are available commercially but the cost limits their accessibility for low resource countries. Although serological assays based on mammalian-expressed SARS-CoV-2 spike protein have been previously described these assays need to be validated using samples from local populations within the continent, or country, in which they will be used. Interpretation of results could be influenced by differences in specificity and potential for pre-existing cross-reactive antibodies. In this study, we investigated two laboratory developed serological assays, an enzyme linked immunosorbent assay (ELISA) and an immunofluorescent assay (IFA), developed using recombinant SARS-CoV-2 spike protein, for use in South African populations. The tests were compared with commercially available and South Africa Health Products Regulatory Authority (SAPHRA) approved assays. A panel of 100 residual diagnostic serum samples, collected prior to the pandemic, were tested on three separate occasions to determine a suitable cut-off value for differ-entiation of positive from negative samples. Specificity of 96 % and 100 % for ELISA and IFA respectively was demonstrated. A total of 82/89 serum samples collected between days 2-94 after onset of illness from patients with a positive molecular result were positive for IgG antibody. The sensitivity of the laboratory developed assays on samples collected > one week after onset of illness was shown to be 100 % and 98.8 % for ELISA and IFA respectively. Positive predictive values were 92.1 % for ELISA and 91.0 % for IFA using characterization of samples as positive based on confirmation of infection using RT-PCR. Serum samples (n = 62) collected from RT-PCR positive patients infected with either ancestral, or emerging variants such as Beta or Delta, tested positive for IgG antibody (62/62) using the laboratory developed assays confirming application of the assays regardless of currently circulating variant during the time of evaluation. High concordance was demonstrated between the laboratory developed assays and the commercial immunoassay among samples collected from South African populations, although the small sample size, especially for the comparison with commercial assays, must be noted. If all quality assurance controls are in place, the use of local laboratory developed assays for high -throughput screening in resource-constrained environments is a realistic alternative option.

MEMBERS TRANSITION IN THE GLEN TORRIDON REGION (GALE CRATER, MARS). G. Caravaca, N. Mangold, E. Dehouck, J. Schieber, A.B. Bryk, C.M. Fedo, S. Le Mouélic, S.G. Banham, S. Gupta, A. Cousin, W. Rapin, O. Gasnault, R.C. Wiens. UMR CNRS 6112 LPG, Univ. Nantes, France, LGL-TPE, Univ. Lyon, France, Indiana University, IN, University of California, Berkeley, CA, Dept Earth & Planetary Sciences, University of Tennessee, Knoxville, TN, Imperial College London, UK, IRAP, Toulouse, France, LANL, Los Alamos, NM. *gwenael.caravaca@univ-nantes.fr.

Antibodies are crucial to immune protection against SARS-CoV-2, with some in emergency use as therapeutics. Here, we identify 377 human monoclonal antibodies (mAbs) recognizing the virus spike and focus mainly on 80 that bind the receptor binding domain (RBD). We devise a competition data-driven method to map RBD binding sites. We find that although antibody binding sites are widely dispersed, neutralizing antibody binding is focused, with nearly all highly inhibitory mAbs (IC50 < 0.1 μg/mL) blocking receptor interaction, except for one that binds a unique epitope in the N-terminal domain. Many of these neutralizing mAbs use public V-genes and are close to germline. We dissect the structural basis of recognition for this large panel of antibodies through X-ray crystallography and cryoelectron microscopy of 19 Fab-antigen structures. We find novel binding modes for some potently inhibitory antibodies and demonstrate that strongly neutralizing mAbs protect, prophylactically or therapeutically, in animal models.